Shigella and Salmonella have been implicated in neonatal sepsis, food poisoning, and bacteremia. Their increasing resistance to antibiotics has undermined treatment options, constituting a public health crisis. Also, the scarcity of new antibiotics in the development pipeline compounds multidrug-resistance (MDR). Hence, there is a need to potentiate antibiotics to mitigate resistance. This study leveraged riboflavin to re-sensitize fluoroquinolones and carbapenems against MDR Shigella and Salmonella spp. Disk diffusion, microbroth-dilution, chequerboard, and time-kill assays were used to determine resistance profiles and riboflavin-antibiotic activity. Biofilm-formation and bacterial viability (after riboflavin-antibiotic challenge) was determined with crystal-violet and Macrophage infection assays, respectively. Strains exhibited >80% resistance to fluoroquinolones and carbapenems, with 160–320 µg MIC ranges and 0.5–2 FIC, indicating no synergy. At 40–80 µg riboflavin, there was two-fold reduction in bacterial survival, with meropenem-riboflavin exhibiting significant reduction and FIC of 0.075 indicating high synergistic activity. Biofilm-formation was altered (from strong to weak phenotype) with 40 µg riboflavin-antibiotic treatment. There was a 40–70% reduction in bacterial survival in THP-1 cells treated with meropenem-riboflavin after 3 hours, and complete clearance between 24-48 hpi. Riboflavin potentiated fluoroquinolones and meropenem, leading to modulation of the host immune response for the clearance of the strains.

This study evaluated the use of filtration and UV-A photocatalysis for the reduction of particulate matter (PM) and airborne bacterial pathogens in swine barns. Two MERV filters (8 and 15) were used to mitigate PM concentrations measured at the PM 1, PM 2.5, respirable PM, and PM 10 ranges. Filtration was also used to generate different levels of airborne pathogens to be treated by UV-A. Results show that MERV 8 and 15 filters effectively reduced PM concentrations (96-98%) in air exhausted from a swine barn (p ranged from < 0.01 to 0.04). UV-A photocatalysis did not mitigate PM concentrations. UV-A photocatalysis treatment reduced measured colony-forming units (CFUs) by 15-95%. The CFU percent reduction was higher when airborne PM concentration was low. The numeric results suggested a real mitigation effect despite p-values that did not meet the usual statistical cut-off of <0.05 for significance due to the large variability of the CFU control samples. Normalization of measured airborne pathogen concentrations by smaller PM size range concentrations led to emerging significant treatment differences for CFUs. A significant decrease (~60% reduction; p < 0.03) in the concentration of viable airborne bacteria was shown for all PM below the 10-micron range.

In this work, we introduce the first pipeline that combines a refraction-aware Structure-from-Motion (SfM) method with a deep learning model specifically designed for airborne bathymetry. We accurately estimate the 3D positions of the submerged points by integrating refraction geometry within the SfM optimization problem. This way, no refraction correction as post-processing is required. Experiments with simulated data that approach the real-world capturing conditions demonstrate that SfM with refraction correction is extremely accurate, with submillimeter errors. We integrate our refraction-aware SfM within a deep learning framework that also takes into account radiometrical information, developing a combined spectral and geometry-based approach, with further improvements on accuracy and robustness to different seafloor types, both textured and textureless. We conducted experiments with real-world data at 2 locations in the southern Mediterranean Sea, with varying seafloor types which demonstrate the benefits of refraction correction for the deep learning framework. We open-source our refraction-aware SfM, providing researchers in airborne bathymetry with a practical tool to apply SfM in shallow water areas.

Unlike fowl pox, pigeon pox virus (PPV) has not been described in Ghana. This is the first report of the disease and virus in Ghana based on gross necropsy, histopathological analysis and molecular techniques. This index case was presented as the occurrence of both cutaneous (dry) and diphtheritic (wet) forms of the pigeon pox disease in a 5-month-old female pigeon. Although the observation of Bollinger bodies during histology is confirmatory of pox viruses, the amplification of the p4b gene using polymerase chain reaction and its visualisation by gel electrophoresis confirmed the presence of an avian pox virus. Sequencing and phylogenetic analysis of the isolates from this case showed 100% relatedness to the reference PPV isolate FeP2. Thus, confirming the presence of PPV. The discovery of this virus in the Ghana raises the need for surveillance of both wild and domestic avian populations in preparation for any future outbreak, protection of the production birds and decision on the need for other pox viruses in the country.

Air pollution has created a lot of problems in the developed and developing countries. To avoid or reduce these problems, constant monitoring of the air should be ensured. The conventional techniques is costly because it requires a lot of money and time consuming. Biomonitoring has been the alternative method. Moss, lichens and plants are biomonitors available to entrap air pollutants. The aim of this paper is to discuss one of the ways of monitoring air pollution – Moss bag technique. To do this, types, choice, preparation, handling of bags after preparation of moss were discussed. From the literatures consulted, it was discovered that there were differences in the techniques used by the researchers. In all, the use of mosses with emphasis on the employment of moss bag have proved to be a powerful tool in airborne particulate and toxic elements. To conclude, developing countries should focus more on this technique because it will reduce cost of air monitoring.

Asthma is a heterogeneous and very complex group of diseases, which includes different clinical phenotypes depending on symptoms, progression, exacerbation pattern or response to treatment among other characteristics. The allergic phenotype is the most frequent, especially in pediatric asthma. It is characterized by sensitization (production of specific IgE) to allergens, and frequent comorbidity with rhinitis and atopic dermatitis. An allergen is a substance that triggers the production of specific IgE antibodies in susceptible individuals, who present symptoms that will depend on the type and intensity of the allergenic load and the tissue where the interaction occurs. Airborne allergens cause their effects in the respiratory tract and eyes, and can be indoor or outdoor, perennial or seasonal. Although allergens such as mites, pollens or animal dander are generally considered as a single particle, it is important to note that they contain different molecules which could trigger distinct specific IgE molecules on different patients.The key points that a physician who treats asthma should be aware of are:

The study investigated farmers’ perception on pests and diseases management strategies, agricultural practices, production constraints and selection criteria of elite varieties using a survey research design. A total of 700 questionnaires were administered to smallholder farmers who were farming for household consumption, those producing for sale and household consumption and those who were mainly producing for sale because their primary goal was to produce for the market. Findings revealed that the most prevalent pests identified were whiteflies (Bemisia tabaci), grasshoppers (Zonocerus variegatus), aphids (Aphis gossypii), mealybugs (Phenacoccus manihoti), termites (Isoptera), and grasscutters (Thryonomys swinderianus). The three most common diseases of cassava limiting growth and yield with mixed infection include viral, bacterial, and fungal. The study also revealed that only 12.5% of farmers cultivated improved cassava varieties. The management practices implemented encompassed field sanitation and the application of pesticides. Lack of capital and no availability of market were the most important production and marketing constraints faced by farmers in the study area, whereas poundability and high storage root yield are the most preferred traits farmers consider in selecting a new variety. Results suggest that smallholder farmers should endeavor to undergo various developmental programs to develop themselves to increase their competitive advantage in their locality and in the local and global agricultural sectors. In addition, governments and other policy makers should strategize plans and programs that would contribute to smallholder farmers’ agriculture, community and national development.

Based on the Flashing Ratchet Potential (FRP) and Electro-Spectroscopy detection techniques, a new detection method was experimentally examined. This method allows the detection of sub-micro particles in the human exhaled air such as viral particles and other biological agents. The detection signal created by this method is carried out by electron current buildup forming an Electric Current-Spectrum (ECS) distinguishing the contents of the exhaled air samples. The detection method was developed based on FRP and a beam of free charges passing through the electrodes of the FRP. The ECS is characterized by low-energy free charges interacting with the medium through which they pass, where numerous free charges are scattered (delayed) as a result of these interactions. The resulting ECS is characterized by FRP's capacity to drift back the delayed free charges to their original starting positions. By comparing the ECS of two exhale air samples, this new technology can be utilized to identify the presence of viral and microorganisms’ particles. The time-escalating ECS difference quickly indicates the presence of such particles. Moreover, the FRP's optimal operating settings was experimentally defined, in addition to the experimental evaluation of its functionality to confirm the FRP's promising sensing capabilities, which were statistically examined several times to ensure the reproducibility of the results.

Fungal spores are universal atmospheric components associated to allergic reactions. Alternaria (Ascomycota) is considered the most allergenic spore taxa. Alt a 1 is the major allergen of Alternaria and is present also in other Pleosporales. In this study, standard Hirst-based sampling and analyzing methods for measuring spore daily concentrations of Alternaria, Curvularia, Drechslera-Helminthosporium, Epicoccum, Leptosphaeria, Pithomyces, Pleospora and Stemphyllium (all included in the taxon Pleosporales) have been used besides two high-volume samplers, Burkard Cyclone (2017) and MCV CAV-A/mb (2019-2020), and ELISA Kits for measuring the allergen. The detection and quantification of Alt a 1 was only possible in the samples from the MCV sampler. Although Alt a 1 was better correlated with Alternaria spores than with Pleosporales spores, the three of them showed high correlations. It is shown, for the first time, a high and significant correlation of Alt a 1 with temperature, a negative one with relative humidity and no correlation with precipitation. The aerobiological monitoring of these three elements ensures the best information for understanding the affectation to allergy sufferers but, if not possible, as a minimum public health service aiming at the detection, treatment and prevention of allergy, the study of the airborne Alternaria spores should be ensured.

In Germany, the phloem sucking planthopper Pentastiridius leporinus (Hemiptera: Cixiidae) currently represents the epidemiological driver for the spread of the syndrome “Basses Richesses” in sugar beet, which results in a reduced sugar content and an economic loss for the farmers. This disease is associated with the γ-proteobacterium ‘Candidatus Arsenophonus phytopathogenicus’ and the Stolbur phytoplasma ‘Candidatus Phytoplasma solani’. Recently, P. leporinus was found in potato fields in Germany associated with Stolbur-like symptoms in this crop. In this study, we confirmed that the vector completes its lifecycle on sugar beet as well as on potato when reared under controlled conditions. Transmission experiments with adults of this vector combined with molecular analyses showed for the first time that both pathogens are transmitted by this vector to potato. For an accurate assessment of the Ca. P. solani and Ca. A. phytopathogenicus titers in the vector and host plants, gBlocks derived from the hsp20- and 16S rRNA gene were employed, respectively. For Ca. P. solani the limit of detection was determined in potato and sugar beet material. The results of this study will further research on the epidemiology of the syndrome “Basses Richesses” and “Stolbur” diseases and the response of host plants and vector insects to both pathogens.

Zucchini (Cucurbita pepo L.) is an important crash crop for producing seeds in Inner Mongolia, China. In August 2021, the harvest season of seed-producing zucchini, fruit rot symptom (cv. Jindi No.1) was found in the Wuyuan region. The incidence of infected fruits of zucchini ranged from 10% to 30% and symptom consisted in 4 to 5 cm diameter lesions where the fruit was in contact with the soil. Ten isolations from six symptomatic fruits were preliminary classified as Fusarium species based on its morphological characters in potato dextrose agar. Phylogenetic tree was constructed by concatenating TEF-1α and RPB2 gene and exhibited the isolates clustered together with the Fusarium solani f. sp. cucurbitae sequences. Pathogenicity tests revealed that two isolates caused over 3 cm diameter lesions on the fruits while negative-controls remained asymptomatic. The colonies reisolated from the leasions were morphologically identical to the original isolates, thus fulfilling Koch’s postulates. Results demonstrated that F. solani f. sp. cucurbitae was the causal agent of fruit rot observed in the field. To our knowledge, this is the first report of fruit rot of seed-producing zucchini caused by F. solani f. sp. cucurbitae in Inner Mongolia, China.

Chronic granulomatous disease (CGD) is a primary immunodeficiency caused by a defect in the phagocytic function of the innate immune system owing to mutations in genes encoding the five subunits of the nicotinamide adenine dinucleotide (NADPH) oxidase enzyme complex. This review aimed to provide a comprehensive approach to the pathogens associated with chronic granulomatous disease (CGD) and its management. The topics covered included common pathogens infecting CGD patients, granulomas, and CGD-related infectious diseases, including invasive aspergillosis, Mulch pneumonitis, and liver abscesses. In addition, we also covered the differential diagnosis of CGD and its management. Patients with CGD, often children, have recurrent life-threatening infections and may develop infectious or inflammatory complications. The most common microorganisms observed in the patients with CGD are Staphylococcus aureus, Aspergillus spp, Candida spp, Nocardia spp, Burkholderia spp, Serratia spp, and Salmonella spp. Triple-dose antimicrobial prophylaxis with empiric regimens is recommended. Therefore, therapeutics against this disease must be optimised, considering the lack of curative therapies and the long-term side effects of prophylactic regimens. Consequently, allogeneic haematopoietic stem cell transplantation from a human leukocyte antigen-identical donor has been proven to cure CGD.

Chronic granulomatous disease (CGD) is a primary immunodeficiency caused by a defect in the phagocytic function of the innate immune system owing to mutations in genes encoding the five subunits of the nicotinamide adenine dinucleotide (NADPH) oxidase enzyme complex. This review aimed to provide a comprehensive approach to the pathogens associated with chronic granulomatous disease (CGD) and its management. The topics covered included common pathogens infecting CGD patients, granulomas, and CGD-related infectious diseases, including invasive aspergillosis, Mulch pneumonitis, and liver abscesses. In addition, we also covered the differential diagnosis of CGD and its management. Patients with CGD, often children, have recurrent life-threatening infections and may develop infectious or inflammatory complications. The most common microorganisms observed in the patients with CGD are Staphylococcus aureus, Aspergillus spp, Candida spp, Nocardia spp, Burkholderia spp, Serratia spp, and Salmonella spp. Triple-dose antimicrobial prophylaxis with empiric regimens is recommended. Therefore, therapeutics against this disease must be optimised, considering the lack of curative therapies and the long-term side effects of prophylactic regimens. Consequently, allogeneic haematopoietic stem cell transplantation from a human leukocyte antigen-identical donor has been proven to cure CGD.

COVID-19, caused by SARS-CoV-2, was first identified in China in 2019. The exact origin of the disease remains uncertain, with theories suggesting it may have emerged from animals or accidentally leaked from a research laboratory. If the hypothesis that COVID-19 originated from a research laboratory is accurate, it is crucial to investigate potential pathways for pathogens to escape from biocontainment research animal facilities (BRAFs). We examine key biosafety issues associated with BRAFs, including inadequate decontamination procedures for water and experimental samples, handling high biosafety level pathogens in lower level laboratories, risks of animal bites and sharps injuries, contamination of bedding and enrichment materials, and improper management and transportation of biohazard samples. Additionally, we discuss the role of veterinarians in African research animal facilities and the challenges they encounter in maintaining biocontainment standards. We emphasize the importance of routine monitoring of effluent water to detect possible disease outbreaks. We recommend a thorough investigation of the COVID-19 pandemic to identify potential sources of pathogen release from BRAFs, which could serve as hotspots for future disease outbreaks. Findings from such investigations will inform the development of policies aimed at safeguarding human populations from future pandemics and preventing BRAFs from becoming sources of infectious disease outbreaks.

Since there is not a clear consensus about the possibility for COVID-19 to be an airborne disease, exists a controversy regarding the need to use surgical masks to prevent its spread. Here, using the Kepler conjecture for ideal packaging, the number of virions of different sizes that can be accommodated inside droplets was calculated and are proportional to the 3^rd potency of the droplet/virion diameter. The differences between particles of 5 um and 100 μm are around four orders of magnitude, explaining why the airborne spread is much more difficult but still possible. There is no solid evidence yet that the airborne coronaviruses may reach enough concentration to infect, but this may be the case under certain circumstances. The WHO partially recognizes now this fact in a warning to health workers (from my point of view too late, as it was the declaration of a pandemic). Another issue is whether the virus stays infective in aerosols generated from patients. This has not been directly proved yet except with artificial aerosols, but there are no reasons why the virus cannot remain in the air and be infective if the viral charge and time of exposure are enough. We must also consider whether the virus can infect the intestine; there are some signs in this sense. Finally, and most importantly, we need to reduce interactions by using surgical masks to flatten the curve, leave the quarantine and avoid a rebound. For cultural reasons, a social distance of 2 meters (2M) is extremely hard to manage. Surgical masks do reduce the interactions in conditions of proximity and, therefore, help to “flatten the curve”. The WHO and CDC “laissez-faire” on this matter do not help and we are running out of time. Anticipated actions, such as the use of surgical masks for the general population, are critical.

Because of the near-term risk of extreme weather events and other adverse consequences from climate change, and, at least in the longer term, global fossil fuel depletion, there is world-wide interest in shifting to noncarbon energy sources, especially renewable energy (RE). Because of possible limitations on conventional renewable energy sources, researchers have looked for ways of overcoming these shortcomings by introducing radically new energy technologies. The largest RE source today is bioenergy, while solar energy and wind energy are regarded as having the largest technical potential. This paper reviews the literature on proposed new technologies for each of these three RE sources: microalgae for bioenergy, photolysis and airborne wind turbines. The main finding is that their proponents have underestimated the difficulties facing their introduction on a very large scale.

Microbial foodborne pathogens can cause major risks to public health and the food industry. Rapid and accurate detection of these pathogens is crucial to prevent outbreaks and ensure food safety. Traditional single-mode biosensing approaches have their limitations in terms of specificity, sensitivity, and speed. Over the years, there has been an increasing research interest in developing multimodal biosensing strategies that integrate multiple sensing techniques to achieve enhanced accuracy, efficacy, and precision in foodborne pathogen detection. This article review paper explores the current state of multimodal biosensing technologies and their promising applications in the food industry. We discuss various integrated biosensing platforms, including optical, electrochemical, and nanomaterial-based systems, among others. The advantages, challenges, and future prospects of multimodal biosensing for foodborne pathogens are thoroughly examined, highlighting the potential impact of these advanced technologies on food safety and public health.

Airborne virus, such as COVID-19, caused pandemics all over the world. Virus-containing particles produced by infected individuals are suspended in the air for extended periods of time, actually results in viral aerosols and the spread of infectious diseases. Aerosol collection and detection devices are essential for limiting the spread of airborne virus diseases. This review provides an overview of the primary mechanisms and enhancement techniques for collecting and detecting airborne viruses. Indoor virus detection strategies for scenarios with varying ventilations are also summarized based on the excellent performance of existing advanced comprehensive devices. This review provides guidance for the development of future aerosol detection devices and aids in the control of airborne transmission diseases, such as COVID-19, monkeypox, and other airborne transmission viruses.

This study investigates the application of frequency augmentation techniques to improve condition-based maintenance (CBM+) systems for airborne weapon systems, focusing on the predictive accuracy of velocity and acceleration parameters. Utilizing MIL-STD-1553B MUX data from 138 sorties of fixed-wing aircraft, we explored six augmentation methods, including traditional interpolations (linear, quadratic, cubic spline) and advanced machine learning models (K-Nearest Neighbor, LSTM, and Bi-LSTM). Our findings indicate that while traditional methods like linear interpolation are more effective for velocity parameters, advanced ML techniques, particularly Bi-LSTM, provide better results for acceleration parameters, which exhibit more complex and rapid variability. The study underscores the necessity of tailoring augmentation approaches to specific parameter characteristics and highlights the potential of ML models in capturing intricate patterns within time-series data. These insights are critical for advancing CBM+ systems in military avionics, enhancing reliability and operational efficiency through improved data processing strategies. Future work should explore more performant augmentation techniques, such as by integrating multi-dimensional datasets, and explore ways to develop automated tools for a more powerful predictive maintenance framework.

This overview initially describes insect immune reactions and then brings together present knowledge of the interactions of vector insects with their invading parasites and pathogens. It is a way of introducing this special issue with subsequent papers presenting the latest details of these interactions in each particular group of vectors. Hopefully, this paper will fill a void in the literature since brief descriptions of vector immunity have now been brought together in one publication and could form a starting point for those interested and new to this important area. Descriptions are given on the immune reactions of mosquitoes, blackflies, sandflies, tsetse flies, lice, fleas and triatomine bugs. Cellular and humoral defences are described separately but emphasis is made on the co-operation of these processes in the completed immune response. The paper also emphasises the need of great care in extracting haemocytes for subsequent study as appreciation of their fragile nature is sometimes overlooked with non-sterile media, smearing techniques and excessive centrifugation sometimes used. The potential vital role of eicosanoids in the instigation of many of the immune reactions described is also discussed. Finally, the priming of the immune system, mainly in mosquitoes, is considered and one possible mechanism is presented

Globally, zoonotic diseases have been on the rise in recent years. Predictive modelling approaches have been successfully used in the literature to identify the underlying causes of these zoonotic diseases. We examine the latest research in the field of predictive modeling that verifies the growth of zoonotic pathogens and assesses the factors associated with their spread. The results of our survey indicate that popular mathematical models can successfully be used in modeling the growth rate of these pathogens under varying storage temperatures. Additionally, some of them are used for the assessment of the inactivation of these pathogens based on various conditions. Based on the results of our study, machine learning models and deep learning are commonly used to detect pathogens within food items and to predict the factors associated with the presence of the pathogens.

A recent study has suggested that the age profiles for deaths due to COVID-19 variants differs between variants and shows male/female specificity. This study demonstrates the age and sex dependency is common among human pathogens. The often-reported higher susceptibility to infections among the young and elderly is true in general but does not apply to individual pathogens. Even among different types of pneumonia there are subtle differences in the age profile. The gender ratio between pathogens likewise shows wide variation from as low as 10% female admissions for leptospirosis to around 90% for gonococcal admissions. The observed age/sex variation observed for mortality due to COVID-19 variants is an expression of a far wider phenomenon with implications to the age/sex response to vaccines. We propose that such differences are likely to be controlled by small noncoding RNAs which act as potent regulators of gene expression leading to altered cell morphology, metabolism, immune function, and response to vaccines.

Food security has become a major concern worldwide in recent years due to ever increasing population. Providing food for the growing billions without disturbing environmental balance is incessantly required in the current scenario. In view of this, sustainable modes of agricultural practices offer better promise and hence are gaining prominence recently. Moreover, these methods have taken precedence currently over chemical-based methods of pest restriction and pathogen control. Adoption of Biological Control is one such crucial technique that is currently in the forefront. Over a period of time, various biocontrol strategies have been experimented with and some have exhibited great success and promise. This review highlights the different methods of plant-pathogen control, types of plant pathogens, their modus operandi and various biocontrol approaches employing a range of microorganisms and their byproducts. The study lays emphasis on the use of upcoming methodologies like microbiome management and engineering, phage cocktails, genetically modified biocontrol agents and microbial volatilome as available strategies to sustainable agricultural practices. More importantly, a critical analysis of the various methods enumerated in the paper indicates the need to amalgamate these techniques in order to improve the degree of biocontrol offered by them.

Natural and sustainable plant-based antioxidants and antimicrobials are highly desirable for improving food quality and safety. The present investigation assessed the antimicrobial and antioxidant properties of active components from Alkanna tinctoria (herb) roots, also known as Ratanjot root. Two methods were used to extract active components: microwave-assisted hot water (MAHW) and ethanol and air-dried. MAHW extract yielded 6.29% while the ethanol yielded 18.27%, suggesting superior Ratanjot root extract powder (RRP) solubility in ethanol over water. The ethanol extract showed significantly higher antioxidant activity than the MAHW extract. Gas chromatography and mass-spec analysis revealed three major phenolic compounds: Butanoic acid, 3-hydroxy-3-methyl-; Arnebin 7, and Diisooctylpthalate. The color attributes (L*, a*, b*, hab, C*ab) for the ethanolic and MAHW extracts revealed significant differences (P < 0.05) in all the above parameters for both types of extracts, except for yellowness (b*) and chroma (C*ab) values. The ethanol extract exhibited antimicrobial activity against 14 bacterial species, with a signifi-cantly higher inhibitory effect against Gram-positive bacteria (Listeria monocytogenes and Staphylococcus aureus) than the Gram-negative bacteria (Salmonella enterica serovar Typhimurium and Escherichia coli). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were both 25 mg/ml for the Gram-negative bacteria, while the MIC and MBC concentrations varied for Gram-positive bacteria (0.049 - 0.098 mg/ml and 0.098 - 0.195 mg/ml) and the antimicrobial effect was bactericidal. The antimicrobial activities of RRP extract remained stable under broad temperature (37-100°C) and pH (2-6) conditions, as well as during refrigerated storage for 30 days. Application of RRP at 1% (10 mg/g) and 2.5% (25 mg/g) levels in a cooked chicken meatball model system prevented lipid oxidation and improved sensory attributes and retarded microbial growth during refrigerated (4°C) storage for 20 days. Furthermore, the RRP extract was non-toxic when tested with sheep erythrocytes and did not inhibit the growth of probiotics, Lacticaseibacillus casei, and Lactiplantibacillus plantarum. In conclusion, the study suggests that RRP possesses excellent antimicrobial and antioxidant activities, thus making it suitable for food preservation.

Carbapenem antibiotics are the drug of choice for treating multidrug-resistant bacterial infections. Metallo-beta-lactamases (MBLs) are carbapenemase capable of hydrolyzing nearly all therapeutically available beta-lactam antibiotics. Consequently, a need to assess the frequency and phenotypic resistance phenomena of two MBL genes in diarrheal and urinary tract infections (UTIs). Samples were collected through a cross-sectional study, with MBLs genes detected via PCR. Two hundred twenty eight diarrheal bacteria were isolated from 240 samples. The most predominant pathogens were Escherichia coli (32%) and Klebsiella spp. (7%). Phenotypic resistance to amoxicillin-clavulanic acid, aztreonam, cefuroxime, cefixime, cefepime, imipenem, meropenem, gentamicin, netilmicin, and amikacin was 50.4%, 65.6%, 66.8%, 80.5%, 54.4%, 41.6%, 25.7%, 41.2%, 37.2%, and 42.9%, respectively.  Total 142 UTI pathogens were obtained from 150 urine samples, with Klebsiella spp. (39%) and Escherichia coli (24%) are the major pathogens. Phenotypic resistance to amoxycillin-clavulanic acid, aztreonam, cefuroxime, cefixime, cefepime, imipenem, meropenem, gentamicin, netilmicin, and amikacin was 93.7%, 75.0%, 91.5%, 93.7%, 88.0%, 72.5%, 13.6%, 44.4%, 71.1%, and 43%, respectively.  Twenty four diarrheal isolates carried either blaNDM-1 or blaVIM genes; the overall MBL gene prevalence was 10.5%. Thirty six UTI pathogens carried either blaNDM-1 or blaVIM genes (25.4%). Seven isolates carried both blaNDM-1 and blaVIM genes.  MBL genes exhibited a strong association with phenotypic carbapenem and other beta-lactam antibiotic resistance. Resistance to carbapenems requires active surveillance and stewardship.

Multidrug resistant organisms (MDROs) outbreaks have been steadilyincreasing in Intensive care units (ICUs). Still, healthcare institutions and workers (HCW) reached no unanimity on how and when implementing infection prevention and control (IPC) strategies. We aimed to provide a pragmatic, physician practice-oriented, resume of strategies towards different MRDOs outbreaks in ICU. We performed a narrative review on IPC in ICUs, investigating patient-to-staff ratios, education, isolation, decolonization, screening and hygiene practices, outbreak reporting, cost-effectiveness, reproduction-number(R0), and future perspectives. The most effective IPC strategy remains unknown. Most studies focus on a specific pathogen or disease, making the clinician losing the big picture. IPC strategies proved their cost-effectiveness regardless typology, country, or pathogen. A standardized, universal, pragmatic protocol for HCW education should be elaborated. Likewise, a rapid outbreak recognition tool elaboration (i.e., an easy-to-use mathematical model) would improve early diagnosis and spreading prevention. Further studies are needed to express in favor or against MDROs decolonization. New promising strategies are emerging and need to be tested in the field. The lack of IPC strategies application has made, and still makes ICUs a major MDROs reservoir into the community. In a not-too-distant future genetic engineering and phage therapies could represent a plot-twist in MDROs IPC strategies.

Abstract: Colistin is a last-resort antimicrobial for treating multidrug-resistant Gram-negative bacteria. Phe-notypic colistin resistance is highly associated with plasmid-mediated mobile colistin resistance (mcr) genes. mcr-bearing Enterobacteriaceae have been detected in many countries, with the emergence of colistin-resistant pathogens a global concern. This study assessed the distribution of mcr-1, mcr-2, mcr-3, mcr-4, and mcr-5 genes with the phenotypic colistin resistance in isolates from diarrheal infants and children in Bangladesh. Bacteria were identified using the API-20E biochemical panel and 16s rDNA gene sequencing. Polymerase chain reac-tions detected mcr gene variants in the isolates. Their susceptibilities to colistin were determined by agar dilu-tion and E-test by minimal inhibitory concentration (MIC) measurements. Over 30.0% (69/225) of isolates showed colistin resistance by agar dilution assessment (MIC> 2.0 μg/mL). Overall, 15.5% of isolates carried mcr genes (7, mcr-1; 17, mcr-2; 13, mcr-3; and co-occurrence occurred in 2 isolates). Clinical breakout MIC val-ues (≥ 4 μg/mL) were associated with 91.3% of mcr-positive isolates. The mcr-positive pathogens include twenty Escherichia spp., five Shigella flexneri, five Citrobacter spp., two Klebsiella pneumoniae, and three Pseudo-monas parafulva. mcr-genes appeared to be significantly associated with phenotypic colistin resistance phe-nomena (p=0.000), with 100% colistin-resistant isolates showing MDR phenomena. Age and sex of patients showed no significant association with detected mcr variants. Overall, mcr-associated colistin-resistant bacte-ria have emerged in Bangladesh, which warrants further research to determine their spread and instigate ac-tivities to reduce resistance.

Candida albicans is an opportunistic fungus that becomes pathogenic and problematic under certain biological conditions. C.albicans may cause painful and uncomfortable symptoms, as well as deaths in immunocompromised patients. Therefore, early detection of c.albicans is essential. However, conventional detection methods are costly, slow and inaccessible to women in remote or developing areas. To address these concerns, we have developed a wearable and discrete naked-eye detectable, colorimetric platform for c.albicans detection. With some modification, this platform is designed to be directly adhered to existing feminine hygiene pads. Our platform is rapid, inexpensive, user-friendly, disposable and only requires three steps: i) addition of vaginal fluid onto sample pads; ii) addition of gold nanoparticle gel and running buffer, and iii) naked eye detection. Our platform is underpinned by selective thiolated aptamer-based recognition of 1,3-β-D glucan molecules- a hallmark of c.albicans cell walls. In the absence of c.albicans, wearable sample pads turn bright pink. In the presence of c. albicans, the wearable pads turn dark blue due to significant nanoparticle target-induced aggregation. We demonstrate naked eye colorimetric detection of 4.4 ×106 c.albicans cells per ml. We believe that this proof-of-concept platform has the potential to have a significant impact on women’s health, globally.

The rapid development of LiDAR technology has promoted great changes in forest resource surveys. The airborne LiDAR point cloud can provide precise tree height and detailed vertical structure of the tree stands. Coordinating some representative ground sample plots, LiDAR can be used to estimate key forest resource indicators such as forest stock volume, diameter at breast height, and forest biomass at a large scale. By establishing relationship models between the forest parameters of sample plots and the calculated parameters of LiDAR, these developments may eventually expand the models to large-scale forest resource surveys of entire areas. In this study, eight sample plots in northeast China are used to verify and update the information using point cloud obtained by the LiDAR scanner riegl-vq-1560i. Firstly, the tree crowns are segmented using the profile-rotating algorithm, and dominant trees height are used to check and rectify the tree locations. Secondly, considering the correlation between forestry parameters and tree species, we establish models to distinguish between species using geometric characteristics of tree crowns. Thirdly, when the tree species is known, parameters such as height, crown width, diameter at breast height, biomass and stock volume can be extracted from trees. The prediction models of forestry parameters can also be verified, which can be extended to accurate large-scale forestry surveys based on LiDAR data. Finally, experiment results demonstrate that the F-score of the eight plots in the tree segmentation exceed 0.95, the accuracy of tree species correction exceeds 90%, and the R2 of tree height, east-west canopy width, north-south canopy width, diameter at breast height, above-ground biomass and stock volume are 0.893, 0.757, 0.694, 0.840, 0.896 and 0.891, respectively. The above results indicate that the LiDAR-based estimation of forestry parameters is practical and that these forestry parameter prediction models can be widely applied in forest resource monitoring.

Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 km² agricultural plain investigated through a dedicated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gamma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.

Rodents are known to be reservoir hosts for at least 60 zoonotic diseases and are known to play an important role in their transmission and spreading in different ways. We sampled different rodent communities within and around human settlements in Northern Senegal, an area subjected to major environmental transformations associated with global changes. Herein, we conducted an epidemiological study on their bacterial communities.One hundred and seventy-one (171) invasive and native rodents were captured, 50 from outdoors trapping sites and 121 rodents from indoors habitats, consisting on 5 species. DNA of thirteen pathogens have been successfully screened on the rodent’s spleens. We found: 2.3% of positive spleens to Piroplasmida and amplified one which gives a potentially new species Candidatus “Theileria senegalensis”; 9.35% of Bartonella spp. and amplified 10, giving three genotypes. 3.5% of filariasis species; 18.12% of Anaplasmataceae species and amplified only 5, giving a new potential species Candidatus “Ehrlichia senegalensis”; 2.33 % of Hepatozoon spp.; 3.5% of Kinetoplastidae spp; and 15.2% of Borrelia spp. and amplified 8 belonging all to Borrelia crocidurae.Some of the species of pathogens carried by the rodents of our studied area may be unknown because most of those we have identified are new species. In one bacterial taxon, Anaplasma, a positive correlation between host body mass and infection was found. Overall, male and invasive rodents appeared less infected than female and native ones, respectively.

Microorganisms belonging to the Lactobacillus genus are naturally associated or deliberately added to fermented food products and are widely used in probiotic food additives and supplements. Moreover these bacteria normally colonize mouth, gastrointestinal (GI) tract and female genitourinary tract of humans. They exert multiple beneficial effects and are regarded as safe microorganisms. However, infections caused by lactobacilli, mainly endocarditis, bacteremia and pleuropneumonia occasionally occur. The relevance of Lactobacillus spp. as opportunistic pathogens in humans and related risk factors and predisposing conditions are illustrated in this review article with more emphasis on the species L. rhamnosus, that has been more often involved in infection cases. The methods used to identify this species in clinical samples, to distinguish strains and to evaluate traits that can be associated to pathogenicity, as well as future perspectives for improving the identification of potentially pathogenic strains are outlined.

Covid-19 is an airborne disease, with the vast majority of infections occurring indoors. By comparison, little transmission occurs outdoors. Here, we investigate the airborne transmission pathways that differentiate the indoors from outdoors, and conclude that profound differences exist, which help to explain why SARS-CoV-2 transmission is much more prevalent indoors. Near and far-field transmission pathways are discussed along with factors that affect infection risk, with aerosol concentration, air entrainment, thermal plumes, and occupancy duration all identified as being influential. In particular, we present the fundamental equations that underpin the Wells-Riley model, and show the mathematical relationship between inhaled virus particles and quanta of infection. A simple model is also presented for assessing infection risk in spaces with incomplete air mixing. Transmission risk is assessed in terms of aerosol concentration using simple 1D equations, followed by a description of thermal plume-ceiling interactions. With respect to this, we present new experimental results using Schlieren-visualisation and Computational Fluid Dynamics (CFD) based on the Eulerian-Lagrangian approach. Pathways of airborne infection are discussed, with the key differences identified between indoors and outdoors. In particular, the contribution of thermal and exhalation plumes is evaluated, and the presence of near-field/far-field feedback loop postulated, which is absent outdoors.

Invasive species are significant threats to global agriculture and food security being the major causes of crop loss. An operative biosecurity policy requires full automation of detection and habitat identification of the potential pests and pathogens. Unmanned Aerial Vehicles (UAVs) mounted thermal imaging cameras can observe and detect pest animals and their habitats, and estimate their population size around the clock. However, their effectiveness becomes limited due to manual detection of cryptic species in hours of captured flight videos, failure in habitat disclosure and the requirement of expensive high-resolution cameras. Therefore, the cost and efficiency trade-off often restricts the use of these systems. In this paper, we present an invasive animal species detection system that uses cost-effectiveness of consumer-level cameras while harnessing the power of transfer learning and an optimised small object detection algorithm. Our proposed optimised object detection algorithm named Optimised YOLO (OYOLO) enhances YOLO (You Only Look Once) by improving its training and structure for remote detection of elusive targets. Our system, trained on the massive data collected from New South Wales and Western Australia, can detect invasive species (rabbits, Kangaroos and pigs) in real-time with a higher probability of detection (85–100 %), compared to the manual detection. This work will enhance the visual analysis of pest species while performing well on low, medium and high-resolution thermal imagery, and equally accessible to all stakeholders and end-users in Australia via a public cloud.

The mass concentration of particulate matter (PM) has been systematically used in epidemiological studies as exposure indicator, to relate airborne concentrations with a wide variety of human health effects, which can be hardly explained by using this single parameter. In fact, PM is a “particle cocktail” that includes a complex mixture of compounds with a wide range of sizes, chemical compositions and emission sources. Current research hypothesizes that many of the adverse health effects are derived from oxidative stress in biological systems caused by the deposition of PM into the lungs. This emerging hypothesis is called the oxidative stress paradigm. In this commentary article we analize how this new paradigm could help to answer the as-of-yet unanswered questions related to the mechanism of action of PM pollution on human health. Acellular oxidative potential (OP) assays have been emerged as a promising approach to quantify the PM potential to induce oxidative stress and to relate it with the chemical composition and size distribution of PM. Recent researches have shown that the OP is related to the presence of metals, organic carbon, polyaromatic hydrocarbons and quinones. However, the association between PM and particle-induced toxicity is still largely unknown. Therefore, additional research is needed to identify the specific PM characteristic(s), such as its specific size, emission source or chemical content, which contribute the most to its redox activity. Thus, the OP measurements provide information that allows us to evaluate and integrate the toxic potential of PM in a unique parameter, whose relationships with emission sources, size distribution and/or chemical composition should be faced in the near future.

As semi-airborne mineral exploration has limited budgets, it is critical to design experimental procedures that generate data maximizing the desired information We investigate the effects of transmitter-receiver geometries for a variety of anomalies and semi-airborne layouts. Our simulations indicate that 200 m flight line spacing and 100 m point distance are the optimal trade-off between coverage and survey progress for various targets. Based on the target size and distance between the transmitter and the target, the transmitter length should be at least equal to the length of the target and for more than 1 km, at least two or three times the target size. Likewise important are the location and direction of the transmitter cables, which can have great impact on the result of inversion and should be parallel to the target strike. By using more than one transmitter, better results are obtained. If the strike of the target is known, transmitters should be parallel to each other and if not, it is better to use perpendicular transmitters. Results showed that the optimal distance between transmitters is 3 km. Our simulations show that it is even possible to recover targets just below the transmitter in corresponding areas of masked data.

The Compact Midwave Imaging System (CMIS) is a wide field of view, multi-angle, multi-spectral pushframe imager that relies on the forward motion of the satellite to create a two-dimensional (2D) image swath. An airborne demonstration of CMIS was successfully completed in January-February 2021 on the NASA Langley Research Center Gulfstream III. The primary objective of the four-flight campaign was to demonstrate the capability of this unique instrument to perform stereo observations of clouds and other particulates (e.g. smoke) in the atmosphere. It is shown that the midwave infrared (MWIR) spectral bands of CMIS provide a unique 24/7 capability with high resolution for accurate stereo sensing. The instrument relies on new focal plane array (FPA) technology, which provides excellent sensitivity at much warmer detector temperatures than traditional technologies. This capability enabled a compact, low-cost design that can provide atmospheric motion vectors and cloud heights to support requirements for atmospheric winds in the 2017-2027 Earth Science Decadal Survey. Applications include day/night observations of the planetary boundary layer, severe weather, and wildfires. A comparison with current space-based earth science instruments demonstrates that the SWIR/MWIR multi-spectral capability of CMIS is competitive with larger, more expensive instrumentation. Imagery obtained over a controlled burn and operating nuclear power plant demonstrated the sensitivity of the instrument to temperature variations. The system relies on a mature stereoscopic imaging technique applied to the same scene from two independent platforms to unambiguously retrieve atmospheric motion vectors (AMVs) with accurate height assignment. This capability has been successfully applied to geostationary and low-earth orbit satellites to achieve excellent accuracy. When applied to a ground-point validation case, the accuracy for the CMIS aircraft observations was 20 m and 0.3 m/s for cloud heights and motion vectors, respectively. This result was confirmed by a detailed error analysis with analytical and covariance models. The results for CMIS cases with underflights of Aeolus, CALIPSO and Aqua provided a good validation of expected accuracies. The paper also showed the feasibility of accommodating CMIS on CubeSats to enable multiple instruments to be flown in a leader-follower mode.

Airborne wind energy (AWE) systems use tethered flying devices to harvest higher-altitude winds to produce electricity. For a successful deployment of these systems, it is crucial to understand how the public perceives them. If public concerns about the technology are not taken seriously, implementation could be delayed or, in some cases, prevented, resulting in increased costs for project developers and a lower contribution of the sector to renewable energy targets. This literature review assessed the current state of knowledge on public responses to AWE. An exhaustive literature search led to the identification of 40 relevant publications that were reviewed. The literature assumed that the safety, visibility, acoustic emissions, ecological impacts, and the siting of AWE systems shape public responses to the technology. The reviewed literature views people’s responses to AWE very optimistically but lacks scientific evidence to back up its claims. It seems to overlook that the influence of AWE’s characteristics (e.g., visibility) on public responses will also depend on a range of situational and psychological factors (e.g., people’s general attitude towards AWE, the public’s trust in project developers). Therefore, empirical social scientific research is needed to increase the field’s understanding of public responses to AWE and thereby facilitate deployment.

Influenza A viruses (IAV) are widespread viruses affecting avian and mammalian species worldwide. Outbreaks of IAV in poultry are usually associated with substantial morbidity and mortality, significantly affecting the poultry industry and food security. IAVs from avian species can be transmitted to mammals including humans and, thus, they are of inherent pandemic concern. Most of the efforts to understand the pathogenicity and transmission of avian origin IAVs have been focused on H5 and H7 subtypes due to their highly pathogenic phenotype in poultry. However, IAV of the H9 subtype that circulate endemically in poultry flocks in some regions of the world have also been associated with cases of zoonotic infections. As a result, the World Health Organization includes avian origin H9N2 IAV among the top in the list of IAVs of pandemic concern. In this review, we discuss the interspecies transmission of H9N2 between avian and mammalian species and the molecular factors that are thought relevant for this spillover. Additionally, we discuss factors that have been associated with the ability of these viruses to transmit through the respiratory route in mammalian species.

This paper presents a comparison between a kite model with a constant-length tether and a model based on a system identification algorithm. The concept of system identification is applied to predict the uncertainties related to the variation of the wind speed and the shape deformation of the tethered membrane wing during flight. A pole-placement controller is used to ensure that the kite follows the planned flight path. Thus, we can determine the required locations of the closed loop poles, and then enforce them by changing the controller's gains in real-time. The capability of the system identification algorithm to recognize sudden changes in the dynamic model, and the ability of the controller to stabilize the system in the presence of such changes are confirmed. Furthermore, the system identification algorithm is applied to determine the parameters of a kite with variable-length tether used in a flight test of the 20 kW kite power system of TU Delft. Experimental data of this test were compared with the system identification results in real-time and significant changes were observed in the parameters of the dynamic model which heavily affect the resulting response.

For many tick-borne organisms, dogs may be utilized as sentinel hosts to estimate the risk of human infection. The detection of antibodies in these animals indicates the circulation of pathogens in each location for a set period of time. The standard protocol for the surveillance of tick-borne diseases established by the Brazilian National Reference Laboratory for Rickettsiosis at the Ezequiel Dias Foundation (FUNED) includes testing the seropositivity of dogs for Rickettsia spp. and Ehrlichia canis. Dog serum samples were collected during FUNED’s surveillance protocol in a preserved area in Brazil. Despite Anaplasma phagocytophilum being endemic in Brazil, this agent is not included in FUNED’s standard protocol. To determine if A. phagocytophilum should be included in the standard testing protocol, a collaboration with Fuller Laboratories was established and the seropositivity for A. phagocytophilum was tested. The estimated prevalence for singular infections: 25% Rickettsia spp.; 52.3% E. canis; and 70.5% A. phagocytophilum. The estimated prevalence for co-infections: 17% Rickettsia spp. and E. canis; 18.2% Rickettsia spp. and A. phagocytophilum; 39.8% E. canis and A. phagocytophilum; and 13.6% Rickettsia spp., E. canis, and A. phagocytophilum. These results confirmed a significant presence of A. phagocytophilum and establishes a potential threat upon the public health.

A series of eight 5-nitrofuran-tagged oxazolyl tetrahydropyrazolopyridines (THPP’s) has been prepared in six stages with excellent regioselectivity. The testing of these compounds against pathogens of ESKAPE panel showed a good activity of lead compound 1-(2-methoxyethyl)-5-(5-nitro-2-furoyl)-3-(1,3-oxazol-5-yl)-4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c] pyridine (13g), which is superior to nitrofurantoin. These results confirmed the benefit of combining a THPP scaffold with a nitrofuran warhead. Certain structure-activity relationships were established in the course of this study which were rationalized by the induced-fit docking experiments in silico.

Pathogens, especially invasive species, have caused significant global ecological, economic, and social losses in forests. Plant disease research has traditionally focused on direct interactions between plants and pathogens in an appropriate environment. However, recent research indicates that the microbiome can interact with the plant host and pathogens to modulate plant resistance or pathogen pathogenicity, thereby altering the outcome of plant–pathogen interactions. Thus, this presents new opportunities for studying the microbial management of forest diseases. Compared to parallel studies on human and crop microbiomes, research into the forest tree microbiome and its critical role in forest disease progression has lagged. The rapid development of microbiome sequencing and analysis technologies has resulted in the rapid accumulation of a large body of evidence regarding the association between forest microbiomes and diseases. These data will aid the development of innovative, effective, and environmentally sustainable methods for the microbial management of forest diseases. Herein, we summarize the most recent findings on the dynamic structure and composition of forest tree microbiomes in belowground and aboveground plant tissues (i.e., rhizosphere, endosphere, and phyllosphere), as well as their pleiotropic impact on plant immunity and pathogen pathogenicity, highlighting representative examples of biological control agents used to modulate relevant tree microbiomes. Lastly, we discuss the potential application of forest tree microbiomes in disease control as well as their future prospects and challenges.

Urinary tract infections (UTIs) remain one of the most important problems of modern urology and medicine. Infections bring great discomfort and significantly reduce the quality of life. UTIs rank second after respiratory tract infections in outpatients. The most common pathogen of UTI are E.coli. The study of the etiology of UTI has great clinical and epidemiological importance in routine practice. Objective: To assess the etiological significance of pathogens in the occurrence of urinary tract infections in the Karaganda region of Kazakhstan. Methods: A total of 2378 patients presenting UTIs were enrolled and each provided a urine sample. The study was carried out in the Clinical Microbiology Laboratory MediTEC-NS between 2 January and 29 December 2018. Identification of isolated microorganisms was carried out on a WalkAway 96 Plus microbiological analyzer, Microscan model manufactured by Beckman Coulter (USA). Statistical Analysis was performed using the STATISTICA-6 package. Results: Out of 2378 patients a total of 1177 (49,5%) urine samples tested positive by culture test. From these samples, 1356 strains of microorganisms were isolated, of which 84.79% were monoculture and 21% were of a mixed culture. Gram-positive bacteria 690 (50, 88%), Gram-negative bacteria 630 (46, 46%), and Candida 36 (2.65%) were identified. Gram-negative rods were represented by Enterobacterales 557 (88.41%) and non-fermenting bacteria 73 (11.59%). In the Enterobacterales group included Escherichia coli 371 (66.61%) of which 108 (29,1%) ESBL strains. The next etiologically significant uropathogens were Klebsiella- 99 (17, 77%), Enterobacter-36 (6,46%) and Proteus-32 (8,09). K.pneumoniae prevailed in comparison with other Klebsiella spp. ESBL producing was 34 (57, 6%) out of 59 K.pneumoniae isolates. Gram-negative non-fermenting rod were represented by Acinetobacter spp-34 (46.57%) and Pseudomonas spp 31 (42.47%). Of 34 Acinetobacter spp. isolates 22 (64.7%) were identified as Acinetobacter lwoffii. Among the gram-positive pathogens of UTI, Staphylococcus spp prevailed - 411 (59.57%), followed by Enterococcus spp 197 (28.55%) and Streptococcus spp 81 (11.73%). Coagulase-negative staphylococci 381 (92,7%) isolates out of total 411 staphylococcal isolates. Staphylococcus epidermidis 245 (59,61%) and Staphylococcus haemolyticus 81 (21,17%) were the most frequent isolated coagulase-negative staphylococci. Of 411 staphylococcal isolates, 182 (44.28%) were MRS Conclusion: We found that UTIs among our study population were predominantly caused by ten opportunistic pathogens. The most common uropathogens with a frequency of 66.9% were E. coli- 30.53%, S. epidermidis -20.16%, and Enterococcus spp. -16.21%. Frequently isolated pathogens included Klebsiella, S. haemolyticus spp., and Streptococcus spp. which amounted to 21.98%. The distribution within the patient group was equable and ranged from 6,67% to 8,15%. Etiologically significant pathogens included Enterobacter spp., Proteus spp., Acinetobacter spp., Pseudomonas spp. These bacteria accounted for 11.11%. The distribution within the group was again equable and ranged within 2,55% to 2,96%.

Introduction: Urinary tract infections (UTIs) remain one of the most important problems of modern urology and medicine. Infections bring great discomfort and significantly reduce the quality of life. UTIs rank second after respiratory tract infections in outpatients. The most common pathogen of UTI are E.coli. The study of the etiology of UTI has great clinical and epidemiological importance in routine practice.Objective: To assess the etiological significance of pathogens in the occurrence of urinary tract infections in the Karaganda region of Kazakhstan.Methods: A total of 2378 patients presenting UTIs were enrolled and each provided a urine sample. The study was carried out in the Clinical Microbiology Laboratory MediTEC-NS between 2 January and 29 December 2018. Identification of isolated microorganisms was carried out on a WalkAway 96 Plus microbiological analyzer, Microscan model manufactured by Beckman Coulter (USA). Statistical Analysis was performed using the STATISTICA-6 package.Results: Out of 2378 patients a total of 1177 (49,5%) urine samples tested positive by culture test. From these samples, 1356 strains of microorganisms were isolated, of which 84.79% were monoculture and 21% were of a mixed culture. Gram-positive bacteria 690 (50, 88%), Gram-negative bacteria 630 (46, 46%), and Candida 36 (2.65%) were identified. Gram-negative rods were represented by Enterobacterales 557 (88.41%) and non-fermenting bacteria 73 (11.59%). In the Enterobacterales group included Escherichia coli 371 (66.61%) of which 108 (29,1%) ESBL strains. The next etiologically significant uropathogens were Klebsiella- 99 (17, 77%), Enterobacter-36 (6,46%) and Proteus-32 (8,09). K.pneumoniae prevailed in comparison with other Klebsiella spp. ESBL producing was 34 (57, 6%) out of 59 K.pneumoniae isolates. Gram-negative non-fermenting rod were represented by Acinetobacter spp-34 (46.57%) and Pseudomonas spp 31 (42.47%). Of 34 Acinetobacter spp. isolates 22 (64.7%) were identified as Acinetobacter lwoffii. Among the gram-positive pathogens of UTI, Staphylococcus spp prevailed - 411 (59.57%), followed by Enterococcus spp 197 (28.55%) and Streptococcus spp 81 (11.73%). Coagulase-negative staphylococci 381 (92,7%) isolates out of total 411 staphylococcal isolates. Staphylococcus epidermidis 245 (59,61%) and Staphylococcus haemolyticus 81 (21,17%) were the most frequent isolated coagulase-negative staphylococci. Of 411 staphylococcal isolates, 182 (44.28%) were MRSConclusion: We found that UTIs among our study population were predominantly caused by ten opportunistic pathogens. The most common uropathogens with a frequency of 66.9% were E. coli- 30.53%, S. epidermidis -20.16%, and Enterococcus spp. -16.21%. Frequently isolated pathogens included Klebsiella, S. haemolyticus spp., and Streptococcus spp. which amounted to 21.98%. The distribution within the patient group was equable and ranged from 6,67% to 8,15%. Etiologically significant pathogens included Enterobacter spp., Proteus spp., Acinetobacter spp., Pseudomonas spp. These bacteria accounted for 11.11%. The distribution within the group was again equable and ranged within 2,55% to 2,96%.

Abstract Introduction: Urinary tract infections (UTIs) remain one of the most important problems of modern urology and medicine. Infections bring great discomfort and significantly reduce the quality of life. UTIs rank second after respiratory tract infections in outpatients. The most common pathogen of UTI are E.coli. The study of the etiology of UTI has great clinical and epidemiological importance in routine practice. Objective: To assess the etiological significance of pathogens in the occurrence of urinary tract infections in the Karaganda region of Kazakhstan. Methods: A total of 2378 patients presenting UTIs were enrolled and each provided a urine sample. The study was carried out in the Clinical Microbiology Laboratory MediTEC-NS between 2 January and 29 December 2018. Identification of isolated microorganisms was carried out on a WalkAway 96 Plus microbiological analyzer, Microscan model manufactured by Beckman Coulter (USA). Statistical Analysis was performed using the STATISTICA-6 package. Results: Out of 2378 patients a total of 1177 (49,5%) urine samples tested positive by culture test. From these samples, 1356 strains of microorganisms were isolated, of which 84.79% were monoculture and 21% were of a mixed culture. Gram-positive bacteria 690 (50, 88%), Gram-negative bacteria 630 (46, 46%), and Candida 36 (2.65%) were identified. Gram-negative rods were represented by Enterobacterales 557 (88.41%) and non-fermenting bacteria 73 (11.59%). In the Enterobacterales group included Escherichia coli 371 (66.61%) of which 108 (29,1%) ESBL strains. The next etiologically significant uropathogens were Klebsiella- 99 (17, 77%), Enterobacter-36 (6,46%) and Proteus-32 (8,09). K.pneumoniae prevailed in comparison with other Klebsiella spp. ESBL producing was 34 (57, 6%) out of 59 K.pneumoniae isolates. Gram-negative non-fermenting rod were represented by Acinetobacter spp-34 (46.57%) and Pseudomonas spp 31 (42.47%). Of 34 Acinetobacter spp. isolates 22 (64.7%) were identified as Acinetobacter lwoffii. Among the gram-positive pathogens of UTI, Staphylococcus spp prevailed - 411 (59.57%), followed by Enterococcus spp 197 (28.55%) and Streptococcus spp 81 (11.73%). Coagulase-negative staphylococci 381 (92,7%) isolates out of total 411 staphylococcal isolates. Staphylococcus epidermidis 245 (59,61%) and Staphylococcus haemolyticus 81 (21,17%) were the most frequent isolated coagulase-negative staphylococci. Of 411 staphylococcal isolates, 182 (44.28%) were MRS Conclusion: We found that UTIs among our study population were predominantly caused by ten opportunistic pathogens. The most common uropathogens with a frequency of 66.9% were E. coli- 30.53%, S. epidermidis -20.16%, and Enterococcus spp. -16.21%. Frequently isolated pathogens included Klebsiella, S. haemolyticus spp., and Streptococcus spp. which amounted to 21.98%. The distribution within the patient group was equable and ranged from 6,67% to 8,15%. Etiologically significant pathogens included Enterobacter spp., Proteus spp., Acinetobacter spp., Pseudomonas spp. These bacteria accounted for 11.11%. The distribution within the group was again equable and ranged within 2,55% to 2,96%.

Inhalation is the main route of exposure to airborne pollutants. To evaluate the safety and assess the risks of occupational hazards different testing approaches are used. 3D airway epithelial tissues allow to mimic exposure conditions in vitro, generates human-relevant toxicology data, allows to elucidate mode of action of pollutants. Gilian 3500 pumps equipped with Standard Midget Impingers were used to collect the airborne particulate from woodworking and metalworking environments. EpiAirway™ tissues were used to model half working day (4 h), full working day (8 h), and 3 working day exposures to occupational pollutants. Tissue viability was assessed using MTT assay. RT-qPCR analyses performed to analyze the expression of gelsolin, caspase-3, and IL-6. Tissue morphology was assessed by hematoxylin/eosin staining. Acute exposure to workspace pollutants slightly affected tissue viability and did not change the morphology. Both types of particles suppressed expression of gelsolin, with metalworking samples showing the most pronounced effect. A slight reduction in caspase-3 expression was observed. Particles from metalworking suppressed IL-6 expression. 3D Epithelial tissues can be used to model exposures to airborne pollutants. Exposure to particles from woodworking and metalworking had a minor effect on tissue viability but affected the expression of inflammation and apoptosis-related genes.

Microplastics (of size < 5mm) pollution in our environment is of current concern by researchers, public media and non-governmental organizations. Implications by their presence in aquatic and soil ecosystems have been well studied and documented, but less attention has been paid on airborne microplastics (MPs). Studies concerning airborne microplastics started from 2016 and only a few (n=7) have been published till date. Although, studies may increase in the following years, since air is very important for human survival. Microplastics have been observed in atmospheric fallouts in indoor and outdoor environments using a sampling or vacuum pump, rain sampler and/or particulate fallout collector. Identification and quantification have been carried out by visual, spectroscopic and spectrometric techniques. Factors such as meterological, climatic and anthropogenic influence the distribution and movement of airborne MP. Human exposure may be through inhalation or dermal route with their potential biopersistence and translocation. Ingestion may cause localized inflammation and cancer due to responses by the immune cells, especially in individuals with compromised metabolism and poor clearance mechanisms. Ecological risks involve possible contamination of the ecosystem through a dynamic relationship of MPs in soil, water and air forming a MP contamination cycle. The present review aimed at providing a comprehensive overview of current knowledge or information regarding microplastics in air, identifies gap in knowledge and give suggestions for future research.

Human milk reduces risk for necrotizing enterocolitis in preterm infants. Necrotizing enterocolitis occurs in the ileocecal region where thousands of milk protein-derived peptides have been released from digestion. Digestion-released peptides may exert bioactivity, such antimicrobial and immunomodulatory activities, in the gut. In this study, we applied mass spectrometry-based peptidomics to characterize peptides present in colostrum before and after in vitro digestion. Sequence-based computational modeling was applied to predict peptides with antimicrobial activity. We identified more peptides in undigested samples, yet the abundances were much higher in the digested samples. Heatmapping demonstrated highly different peptide profiles between undigested and digested samples. Four peptides (αS1-casein [157–163], αS1-casein [157–165], β-casein [153–159] and plasminogen [591–597]) were selected, synthesized and tested against common pathogenic bacteria associated with necrotizing enterocolitis. All four exhibited bacteriostatic, though not bactericidal, activities against Klebsiella aerogenes, Citrobacter freundii and Serratia marcescens, but not Escherichia coli.

: Crohn’s disease (CD) is a multifactorial chronic disorder that involves a combination of factors as genetic, immune response and gut microbiota. Actually, the therapy comprises salicylates, immunosuppressive agents, corticosteroids, biologic drugs. International guidelines don’t recommend the use of antibiotics except for septic complications of CD patients. The increased evidence of the implication of gut bacteria in this chronic disease support the rationale for using antibiotics as primary treatment of active CD. In the last decades several pathogens have been reported to be involved in the development of CD, but only Escherichia coli (E.coli) species and Mycobacterium avium paratubercolosis (MAP), aroused the interest due to their strong association with CD pathogenesis. Several meta-analyses have been published concerning antibiotic treatment in CD patients but randomized trials of antibiotic treatments against E.coli and MAP did not show prolonged benefits, and only generated conflicting results so much so that several questions are still unresolved regarding trial design, antibiotic dosing, the formulation used, the treatment course and the outcome measures. In this article we attempted to provide an overview and update of the trials on antibiotic treatment in active CD patients taking into account the role of pathogens, the mechanism by which the different antibiotics act on harmful pathogens, and antibiotic resistance. Finally, we also tried to draw new lines for future studies to use antibiotics to treat active CD patients

Poplar (Populus) is a genus of woody plants of value for the pulp industry, green energy, urban landscaping, soil phytoremediation and as an ornamental plant. Due to the increasing economic importance of poplar, there is a need to ensure its stable growth by increasing its resistance to pathogens, as one of the main problems in poplar cultivation is its susceptibility to numerous diseases. Currently, breeding poplars with reduced susceptibility to infections is receiving increasing attention. Genetic engineering can produce organisms with improved traits faster than traditional methods, and with the development of CRISPR/Cas-based genome editing systems, scientists have a new highly efficient tool at their disposal to create valuable genotypes. In this review, we summarize recent research data on poplar diseases, the biology of their pathogens, and how these plants resist pathogens. In the final section, we discuss genetic engineering, genome editing, and microbiome strategies that we believe are suitable for obtaining new improved poplar lines.

The objective of the study was to analyse the antimicrobial susceptibility trends of Spanish porcine bacteria to quinolones, cephalosporins and polymyxins. Isolates of Actinobacillus pleuropneumoniae, Pasteurella multocida, and Escherichia coli were isolated from sick pigs from 2019 to 2022. Antimicrobial susceptibility test was determined by minimal inhibitory concentration (MIC) following internationally accepted methodology. MIC categorization was based on distributing the range of MIC values in four categories being category one the most susceptible (lowest MIC value) and four the less susceptible one (highest MIC value). Moreover, clinical susceptibility (susceptible/resistant) was also determined according to CLSI and EUCAST clinical breakpoints. A logistic and multinomial logistic regression model was used to analyze the susceptibility data for dichotomized and categorized MIC data, respectively for any pair of antimicrobial/microorganism. In general terms, the antimicrobial susceptibility of pig bacteria to these antimicrobials remained stable or increased in the last four years in Spain. In the case of A. pleuropneumoniae and quinolones, it was observed a significant temporal trend where isolates from 2020 had significantly increased odds of being more susceptible than isolates from 2019. In the case of E. coli and polymyxins, a significant temporal trend was observed where isolates from 2020 and 2021 had significantly increased odds of being more susceptible than isolates from 2019 and 2020, respectively. Finally, a significant odd of being less susceptible was only observed for cephalosporins and E. coli for 2020 versus 2019, stagnating for the rest of study period. These results provide sound data on critical important antimicrobials in swine medicine.

Trees provide key ecosystem services, but the health and sustainability of these plants is under increasing biotic and abiotic threat, including from the growing incidences of non-native invasive plant pests (including pathogens). The island of Ireland (Ireland and Northern Ireland) is generally accepted to have a high plant health status, in part due to its island status and because of the national and international regulations aimed at protecting plant health. To establish a baseline of the current pest threats to tree health for the island of Ireland, the literature and unpublished sources were reviewed to produce a dataset of pests of trees on the island of Ireland. The dataset contains 396 records of pests of trees on the island of Ireland, the majority of pests being arthropods and fungi, and indicating potentially more than 44 non-native pest introductions. The reliability of many (378) of the records was judged to be high, therefore the dataset provides a robust assessment of the state of pests of trees recorded on the island of Ireland. We analyse this dataset and review the history of plant pest invasions, including (i) discussion on notable native and non-native pests of trees, (ii) pest interceptions at borders and (iii) pests and climate change. The dataset establishes an important baseline for the knowledge of plant pests on the island of Ireland, and will be a valuable resource for future plant health research and policy making.

Food pathogens contaminate food products that allow their growth on the shelf and also under refrigerated conditions. Therefore, it is of utmost importance to lower the limit of detection (LOD) of the method used and to obtain the results within hours to few days. Biosensor methods exploit the available technologies to individuate and provide an approximate quantification of the bacteria present in a sample. The main bottleneck of these methods depend on the aspecific binding to the surfaces and on a change in sensitivity when bacteria are in a complex food matrix in respect to bacteria in a liquid food sample. In this review we introduce Surface Plasmon Resonance (SPR), new advancements in SPR techniques, and Electrochemical Impedance Spectroscopy (EIS), as label-free biosensing technologies for the detection of L. monocytogenes in foods. The application of the two methods has made possible the detection of L. monocytogenes with LOD of 1 log CFU/mL. Further advancement are envisaged through the combination of biosensor methods with immunoseparation of bacteria from larger volumes.

Coxsackievirus A6 (CV-A6) has emerged as the predominant causative agent of hand, foot, and mouth disease (HFMD) in young children. Since the declaration of coronavirus disease 2019 (COVID-19) as a global pandemic, the incidence of infectious diseases, including HFMD, has decreased markedly. When social mitigation was relaxed during the COVID-19 pandemic in 2022, re-emergence of HFMD was observed in Gwangju, South Korea, and seasonal characteristics of the disease appeared to have changed. To investigate the molecular characteristics of enterovirus (EV) associated with HFMD during 2022, 277 specimens were collected. Children aged under 5 years accounted for the majority of affected individuals. EV detection and genotyping were performed using real-time RT-PCR and nested RT-PCR followed by sequence analysis. EV detection rate was found to be 82.3%, and the main genotype identified was CV-A6. Sixteen CV-A6 samples were selected for whole genome sequencing. According to phylogenetic analysis, all CV-A6 strains from this study belonged to the sub-genotype D3 clade based on VP1 sequences. Analysis of 3D polymerase phylogeny showed that only the recombinant RF-A group was identified. In conclusion, circulating EV types should be continuously monitored to understand pathogen emergence and evolution during the post-pandemic era.

In this paper we present AWEbox, a Python toolbox for modeling and optimal control of multi-aircraft systems for airborne wind energy (AWE). AWEbox provides an implementation of optimization-friendly multi-aircraft AWE dynamics for a wide range of system architectures and modeling options. It automatically formulates typical AWE optimal control problems based on these models, and finds a numerical solution in a reliable and efficient fashion. To obtain a high level of reliability and efficiency, the toolbox implements different homotopy methods for initial guess refinement. The first type of methods produces a feasible initial guess from an analytic initial guess based on user-provided parameters. The second type implements a warmstart procedure for parametric sweeps. We investigate the software performance in two different case studies. In the first case study we solve a single-aircraft reference problem for a large number of different initial guesses. The homotopy methods reduce the expected computation time by a factor of 1.7 and and the peak computation time by a factor of 8, compared to when no homotopy is applied. Overall, the CPU timings are competitive to timings reported in the literature. When the user initialization draws on expert a priori knowledge, homotopies do not increase expected performance, but the peak CPU time is still reduced by a factor of 5.5. In the second case study, a power curve for a dual-aircraft lift-mode AWE system is computed using the two different homotopy types for initial guess refinement. On average, the second homotopy type, which is tailored for parametric sweeps, outperforms the first type in terms of CPU time by a factor of 3. In conclusion, AWEbox provides an open-source implementation of efficient and reliable optimal control methods that both control experts and non-expert AWE developers can benefit from.

The key factor that enables pathogenic bacteria to establish successful infections lies largely in their ability to escape the host's immune response and adhere to host surfaces. Vitronectin (Vn) is a multi-domain glycoprotein ubiquitously present in blood and extracellular matrix of several tissues, where it plays important roles as regulator of membrane attack complex (MAC) formation and as mediator of cell adhesion. Vn has emerged as intriguing target for several microorganisms. Vn-binding by bacterial receptors confers protection from lysis resulting from MAC deposition. Furthermore, through its Arg-Gly-Asp (RGD) motif, Vn can bind several host cell integrins. Therefore, Vn recruited to the bacterial cell functions as a molecular bridge between bacteria and host surfaces, where it triggers several host signalling events that could promote bacterial internalisation. Each bacterium uses different receptors that recognise specific Vn-domains. In this review, we update the current knowledge of Vn receptors of major bacterial pathogens, emphasising the role they may play in the host upon Vn-binding. Focusing on the structural properties of bacterial proteins, we provide details on the residues involved in their interaction with Vn. Furthermore, we discuss the possible involvement of Vn adsorption on biomaterials in promoting bacterial adhesion on abiotic surfaces.

In contrast to “frank” pathogens, like Salmonella entrocolitica, Shigella dysenteriae, and Vibrio cholerae, that always have a probability of disease, “opportunistic” pathogens are organisms that cause an infectious disease in a host with a weakened immune system and rarely in a healthy host. Historically, drinking water treatment has focused on control of frank pathogens, particularly those from human or animal sources (like Giardia lamblia, Cryptosporidium parvum, or Hepatitis A virus), but in recent years outbreaks from drinking water have increasingly been due to opportunistic pathogens. Characteristics of opportunistic pathogens that make them problematic for water treatment include: 1) they are normally present in aquatic environments, 2) they grow in biofilms that protect the bacteria from disinfectants, and 3) under appropriate conditions in drinking water systems (e.g., warm water, stagnation, low disinfectant levels, etc.) these bacteria can amplify to levels that can pose a public health risk. The three most common opportunistic pathogens in drinking water systems include Legionella pneumophila, Mycobacterium avium, and Pseudomonas aeruginosa. This report focuses on these organisms to provide information on their public health risk, occurrence in drinking water systems, susceptibility to various disinfectants and other operational practices (like flushing and cleaning of pipes and storage tanks). In addition, information is provided on a group of nine other opportunistic pathogens that are less commonly found in drinking water systems, including Aeromonas hydrophila, Klebsiella pneumoniae, Serratia marcescens, Burkholderia pseudomallei, Acinetobacter baumannii, Stenotrophomonas maltophilia, Arcobacter butzleri, and several free-living amoebae including Naegleria fowleri and species of Acanthamoeba. The public health risk for these microbes in drinking water is still unclear, but in most cases, efforts to manage Legionella, mycobacteria, and Pseudomonas risks will also be effective for these other opportunistic pathogens. The approach to managing opportunistic pathogens in drinking water supplies focuses on controlling the growth of these organisms. Many of these microbes are normal inhabitants in biofilms in water, so the attention is less on eliminating these organisms from entering the system and more on managing their occurrence and concentrations in the pipe network. With anticipated warming trends associated with climate change, the factors that drive the growth of opportunistic pathogens in drinking water systems will likely increase. It is important, therefore, to evaluate treatment barriers and management activities for control of opportunistic pathogen risks. Controls for primary treatment, particularly for turbidity management and disinfection, should be reviewed to ensure adequacy for opportunistic pathogen control. However, the major focus for the utility’s opportunistic pathogen risk reduction plan is the management of biological activity and biofilms in the distribution system. Factors that influence the growth of microbes (primarily in biofilms) in the distribution system include, temperature, disinfectant type and concentration, nutrient levels (measured as AOC or BDOC), stagnation, flushing of pipes and cleaning of storage tank sediments, and corrosion control. Pressure management and distribution system integrity are also important to the microbial quality of water but are related more to the intrusion of contaminants into the distribution system – rather than directly related to microbial growth. Summarizing the identified risk from drinking water, the availability and quality of disinfection data for treatment, and guidelines or standards for control showed that adequate information is best available for management of L. pneumophila. For L. pneumophila the risk for this organism has been clearly established from drinking water, cases have increased worldwide, and it is one of the most identified causes of drinking water outbreaks. Water management best practices (e.g., maintenance of a disinfectant residual throughout the distribution system, flushing and cleaning of sediments in pipelines and storage tanks, among others) that have been shown to be effective for control of L. pneumophila in water supplies. In addition, there are well documented management guidelines available for the control of the organism in drinking water distribution systems. By comparison, management of risks for Mycobacteria from water are less clear than for L. pneumophila. Treatment of M. avium is difficult due to its resistance to disinfection, the tendency to form clumps and attachment to surfaces in biofilms. Additionally, there are no guidelines for management of M. avium in drinking water and one risk assessment study suggested a low risk of infection. The role of tap water in the transmission of the other opportunistic pathogens is less clear and in many cases actions to manage L. pneumophila (e.g., maintenance of a disinfectant residual, flushing, cleaning of storage tanks, etc.) will also be beneficial in helping to manage these organisms as well.

Zingiber cassumunar Roxb. is a powerful medicinal plant that has been used as traditional medicine to cure respiratory problems, pain, and inflammation in China, Indonesia, Thailand and other Asian countries by using the crude extracts. The objective of this research is to identify phytochemical composition of Z. cassumunar Roxb. and to analyze antibacterial activity of crude extract, purified compounds, and their microencapsulated products of Rhizome Z. cassumunar Roxb. Identification of phytochemical composition in crude extract of rhizome Z. cassumunar Roxb. was achieved by chromatography-mass spectrophotometer. The major phytochemical composition in crude extract of Z. cassumunar Roxb. is essential oils, including terpinen4-ol (37.7%), β-pinene (20.8%), and (E)-1-(3,4-dimethoxyphenyl)but-1-ene (13.3%). Crude extract of Z. cassumunar Roxb. was purified with silica gel flash column chromatography, resulting two purified compounds. The antibacterial activity of crude extract, purified compounds, and their microencapsulated products of Rhizome Z. cassumunar Roxb. were evaluated against agricultural and foodborne pathogens by using disc agar diffusion and broth microdilution techniques. All of the samples studied (crude extracts, purified compounds, and microencapsulated of Z. cassumunar Roxb.) were effective against all the bacteria. Based on the results of the disc-diffusion assay suggested that amongst the samples studied, purified compounds (compound 1 and 2) and microencapsulated purified compounds (compound 1 and 2) exhibited more effective against all the bacteria compared to the crude extracts. Antibacterial activity of the rhizome of Z. cassumunar Roxb. was contributed mainly by the essential oils components as the active compounds. Gram-negative bacteria (X. oryzae, X. translucens, Pseudomonas spp, E. coli, and S. typhimurium) appeared to the most resistant to the crude extracts, purified compounds, and microencapsulated of Z. cassumunar Roxb. compared to the gram-positive bacteria (S. aureus, B. cereus, and L. monocytogenes). Microencapsulated of the tested samples (crude extract, purified compound 1, and purified compound 2) of the rhizome Z. cassumunar Roxb. exhibited high antibacterial activity with no significantly different with the tested samples without microencapsulation. These results suggest potential antibacterial properties of Z. cassumunar Roxb., which useful for agricultural plant health, food preservation, natural therapies, and pharmaceuticals.

Biosensors are measurement devices that can sense several biomolecules, and are widely used for the detection of relevant clinical pathogens such as bacteria and viruses, showing outstanding results. Because of the latent existing risk of facing another pandemic like the one we are living due to COVID-19, researchers are constantly looking forward to developing new technologies for diagnosis and treatment of infections caused by different bacteria and viruses. Regarding that, nanotechnology has improved biosensors design and performance through the development of materials and nanoparticles that enhance their affinity, selectivity, and efficacy in detecting these pathogens, such as employing nanoparticles, graphene quantum dots, and electrospun nanofibers. Therefore, this work aims to present a comprehensive review that exposes how biosensors work in terms of bacterial and viral detection, and the nanotechnological features that are contributing to achieving a faster yet still efficient COVID-19 diagnosis at the point-of-care.

Evidence for the potential for airborne transmission of SARS-CoV-19 continues to accumulate, with important implications for healthcare workers, as well as the general public. Three lines of evidence support this conclusion.

Emergence of zoonotic-human pathogens is proven to be a lethal threat to public health, and RNA virus including influenza viruses, severe acute respiratory syndrome coronavirus, middle east respiratory syndrome coronavirus, Wuhan coronavirus (COVID-19), plays a pivotal role. As those viruses as airborne microorganisms spread mainly by tiny airborne particles, it is important to de-active those airborne particles before their entry into human bodies. In this study, we investigated the effect of far infrared (FIR) radiation on inhibition of airborne microorganisms. The result confirmed that double stand DNA from airborne microorganisms were stable under mild FIR radiation. However, single strand RNA from them was found to be sensitive to FIR radiation, indicating that RNA virus in airborne particles is instable under FIR radiation. Based on this observation, two models on usage of FIR radiation to prevent RNA virus transmission and cure RNA virus infection were proposed, implying that FIR radiation might be a cheap, convenient, and efficient method in clinic to treat RNA virus.

In this paper, an offshore airborne wind energy (AWE) farm consisting of three non-reversing pumping mode AWE systems is modelled and simulated. The AWE systems employ permanent magnet synchronous generators (PMSG). A direct interconnection technique is developed and implemented for AWE systems. This method is a new approach invented for interconnecting offshore wind turbines with the least number of required offshore-based power electronic converters. The direct interconnection technique can be beneficial in improving the economy and reliability of marine airborne wind energy systems. The performance and interactions of the directly interconnected generators inside the energy farm internal power grid are investigated. The results of the study conducted in this paper, show the directly interconnected AWE systems can exhibit a poor load balance and significant reactive power exchange which must be addressed. Power control strategies for controlling the active and reactive power of the AWE farm are designed, implemented, and promising results are discussed in this paper.

Multi-object tracking (MOT) in airborne videos is a challenging problem due to the uncertain airborne vehicle motion, vibrations of the mounted camera, unreliable detections, size, appearance and motion of the moving objects as well as occlusions due to the interaction between the moving objects and with other static objects in the scene.To deal with these problems, this work proposes a four-stage Hierarchical Association framework for multiple object Tracking in Airborne video (HATA). The proposed framework combines data association-based tracking (DAT) methods and target tracking using a Compressive Tracking approach, to robustly track objects in complex airborne surveillance scenes. In each association stage, different sets of tracklets and detections are associated to efficiently handle local tracklet generation, local trajectory construction, global drifting tracklet correction and global fragmented tracklet linking. Experiments with challenging airborne video datasets show significant tracking improvement compared to existing state-of-art methods.

In airborne sensor networks (ASNs), the media access control (MAC) protocol is facing with serious unfairness problem due to the traditional protection mechanism of air-to-air communications among aircrafts. Actually by using the binary exponential back-off algorithm at high traffic loads to minimize collisions among users, the latest successful node can always benefit from this kind of MAC to obtain channel resources. Moreover, when taking the existence of the hidden nodes in ASNs into account, the inaccurate traffic load information will further aggravate the system’s unfairness. In this paper, a neighbor-channel-aware (NCA) protocol is proposed to improve the fairness of MAC protocol in ASNs. In the proposal, the NCA frame is firstly added and exchanged between neighbor nodes periodically, which helps to resolve the inaccurate traffic load information, so as to avoid reducing the probability of successful message transmission. Then a traffic-loading based back-off algorithm is involved to make the neighbor nodes cooperatively adjust the inter-frame space (IFS) interval to further reduce the unfairness. The simulation results show that, the proposed MAC protocol can guarantee the satisfied fairness, simultaneously avoiding heavy network overloads to protect key messages’ successful transmissions in ASNs.

Migratory and local birds may disperse ticks and their associated pathogens. The aim of this study was to provide information regarding tick infesting birds in Asturias, region that accounts for most of the Lyme disease hospitalizations in Spain. From September 2021 and April 2023 trained and experienced bird- banders collected ticks from birds in six estuary and forest locations. A total of 1,698 birds (52 species, 38 genera and 26 families) were captured. A total 51 ticks (28 larvae, 20 nymphs and 3 females) were collected from 43 birds, belonging to three species: Ixodes ricinus (31), I. frontalis (18) and Haemaphysalis concinna (1). The average prevalence of tick infestation was 2.5% and the average tick burden was 1.2 ticks per host. The bird species Turdus merula, Parus major, Luscinia svecica and Anthus pratensis were among the most infested. Anaplasma phagocytophilum was detected from one Turdus merula. We have not detected B. burgdorferi s.l., Rickettsia spp., Coxiella burnetii or piroplasmids in any of the 51 analyzed ticks. The results of the study suggest low infestation rate in migratory/estuary birds and a higher rate in forest/sedentary ones. Despite this, the detection of pathogens, although with low prevalence, can pose a risk to public health.

Main pathogens affecting carob (Ceratonia siliqua) tree in the Mediterranean basin are described in this overview. The most widespread diseases periodically occurring on carob orchards are powdery mildew (Pseudoidium ceratoniae) and cercospora leaf spot (Pseudocercospora ceratoniae). The causal agents of so-called “black leaf spots” (e.g. Pestaliotiopsis, Phyllosticta and Septoria spp.) are responsible for similar symptoms to above mentioned foliar diseases but are reported on carob orchards with a negligible frequency. Likewise, canker and branch diebacks caused by fungal species belonging to Botryosphaeriaceae are almost never recorded. Among wood diseases that may compromise old or previously damaged carob specimens, “brown cubical heart rot” caused by Laetiporus sulphureus is the most widespread and recurrent issue; this pathogen is also well-known for edible fruit bodies that are also appreciated for pharmaceutical and industrial purposes. On the other hand, “white decays” caused by Fomes and Ganoderma species are less common and reported for the first time in this review. Like-gall protuberances on twigs at uncertain aetiology or tumours on branches associated to Rhyzobium radiobacter are described although these symptoms are seldom detected as it happens also for necrotic leaf spots caused by Pseudomonas syringae pv. ciccaronei. A list of worldwide pathogens not yet recorded but at high-risk potential of introduction in Italian carob producing area is also provided. Finally, some concerns are addressed to new phytopathogenic fungi vectored by invasive Xylosandrus compactus ambrosia beetle. Comprehensively, all described pathogens could potentially in near future become limiting factors for carob production, because they could be favoured by high-density orchards, increasing global network of trade exchanges and high frequency through which extreme events of climate changes globally occur. Thus, symptoms and signs, causal agents, epidemiology and whenever applicable recommendations for disease prevention and management are provided in this review.

Particulate matter (PM) contains heavy metals that affect various cellular functions and gene expression associated with an array of acute and chronic diseases, in humans. However, their specific effects on the stem cells remain unclear. Here, we report the effects of PM collected from Jeddah city on bone marrow mesenchymal stem cells (BM-MSCs) on proliferation, cell death, related gene expression and systems biological analysis aiming to understand the underlying mechanisms. Two different sizes (PM_2.5-₁₀) were tested in vitro at various concentrations (15 to 300 µg/ml) and durations (24 to 72 h). PMs induced cellular stress including membrane damage, shrinkage and death. Lower concentrations of PM_2.5 increased BM-MSCs proliferation, while higher concentrations decreased it. PM₁₀ decreased BM-MSCs proliferation in a concentration-dependant manner. The X-Ray Fluorescence spectrometric analysis showed that PM contains high levels of heavy metals. Ingenuity Pathway Analysis (IPA) and hierarchical clustering analyses showed that heavy metals were associated with signalling pathways involving cell stress/death, cancer and chronic diseases. qRT-PCR results showed differential regulation of the apoptosis genes (BCL2, BAX); upregulation of inflammation associated genes (TNF-a and IL-6) and downregulation of cell cycle regulation gene (P53). We conclude that PM could affect different cellular functions and predispose to debilitating diseases.

Mapping and prediction of inundated areas is increasingly important for climate change adaptation and emergency preparedness. Flood forecasting tools and flood risk models have to be compared to observed flooding patterns for training, calibration, validation and benchmarking. At regional to continental scale, satellite earth observation is the established method for surface water extent (SWE) mapping and several operational global-scale data products are available. However, the spatial resolution of satellite-derived SWE maps remains a limiting factor, especially in low-lying areas with complex hydrography, such as Denmark. We collected thermal imagery using an unmanned airborne system (UAS) for three areas in Denmark shortly after major flooding events. We combined the thermal imagery with an airborne lidar-derived high-resolution digital surface model of the country to retrieve high-resolution (40 cm) SWE maps. The resulting SWE maps were compared to low-resolution SWE maps derived from satellite earth observation (EO). We conclude that UAS have significant potential for SWE mapping at intermediate scales, can bridge the scale gap between ground observations and satellite EO and can be used to benchmark and validate SWE mapping products derived from satellite EO as well as models predicting inundation.

Airborne transmission of seasonal and pandemic influenza viruses is responsible for their epidemiological success and public health burden in humans. Efficient airborne transmission of H1N1 influenza virus relies on receptor specificity and pH of fusion of the surface glycoprotein hemagglutinin (HA). In this study, we examine the role of HA pH of fusion on transmissibility of a cell culture-adapted H3N2 virus. Mutations in the HA head at positions 78 and 212 of A/Perth/16/2009 (H3N2), which were selected after cell culture adaptation, decrease the acid stability of the virus from a pH of 5.5 (WT) to 5.8 (mutant). In addition, we observed that this mutant H3N2 virus replicated to higher titers in cell culture but had reduced airborne transmission in the ferret model. These data demonstrate that, like H1N1 HA, the pH of fusion for H3N2 HA is a determinant of efficient airborne transmission. Surprisingly, we demonstrate that the NA segment noncoding regions can impact the pH of fusion of reassortant viruses. Taken together, our data confirm that HA acid stability is an important characteristic of epidemiologically successful human influenza viruses and is influenced by HA/NA balance.

The science on the anthropogenic airborne aerosols impacting upon the World Heritage marble monument, the Taj Mahal, at Agra has been studied in the light of modern physico-chemical approaches. The study is an effort to understand yet unrecognized airborne species which were found on the surface of the Taj Mahal monument. These species have been analyzed in the light of current analytical methods to impart characterization features and their possible impacts on the surface of the marble. Chemical constituents of these substrates which were incorporated over the top surface of the monument have been identified. Interestingly, the carbon particulates which were thought in the micro level, popularly called “particulate matters” has now been identified even in the nano domain entity, which are chemically more reactive, have been found on the surface of the monument. Because of their high chemical activity these nano carbons do play newer chemistry in the presence of air and sunlight generating several reactive oxygen species (ROS).These ROS are capable to respond to complicated chemical reactions on the surface of the marble in association with deposited cyanophyceae and other deposits of plant origin causing rapid degradation. This study provides the nature of onslaught borne out by such monument exposed under the prevalent smoggy environmental scenario.

Dearth of information on extent of genetic variability in cassava limits the genetic improvement of cassava in Sierra Leone. This study aimed at assessing the genetic variability and relationships within 103 cassava genotypes using agro-morphological and culinary markers. A field trial was conducted in the School of Agriculture and Food Sciences research site. The experiment was laid in an augmented randomized block design. Morphological classification based on qualitative and quantitative traits categorized the germplasm into three different groups. A total of ten principal components (PCs) in the qualitative and six PCs in the quantitative trait sets accounted for 66.74% and 67.27% of the total genetic variation, respectively. Traits with significantly strong and positive correlations included presence of fruit (PFRT) and presence of seed (PSE)(r = 0.86***),root yield per plant (RYPP) and number of storage root (NSR) (r = 0.76***), RYPP and number of commercial root (NCR) (r = 0.68***), length of leaf lobe (LLL) and width of leaf lobe (WLL) (r = 0.66***),and between NSR and NCR (0.84***). Cooking time, cooking percentage, texture, mealiness, taste and aroma varied widely among the accessions. Findings established that the cassava germplasm possess useful genetic variability that could be exploited through selection for short term release programme, genetic conservation of valuable germplasm and genetic improvement of the crop.

Background: While it is established that intravenous catheter placement duration is strongly linked to the risk of catheter colonization and bloodstream infections, there are still substantial knowledge gaps concerning the varying durations of PICC placement that lead to either infection or colonization by common pathogens, particularly MDR pathogens. The present study aims to compare the dwell time required for MDR pathogens to colonize with the time required to cause Central Line-Associated Bloodstream Infections (CLABSIs) in critically ill patients with PICCs and compares it with non-MDR pathogens, shedding light on the significance of preventive procedures to control MDR infections in clinical settings. Methods: Data from critically ill patients with PICCs admitted consecutively to «Metropolitan» Hospital in Athens, Greece, from May 2017 to May 2020 were retrospectively analysed. Results: In this study, 86 hospitalized patients, consisting of 56 (65.1%) males and 30 (34.9%) females, with a mean age of 55.67±21.1 years (range 16-91 years), presented with both CLABSIs and colonization following PICC placements. Specifically, 42 (48.8%) of them presented with CLABSIs, while 44 (51.2%) presented with colonization. Among the total participants, an MDR pathogen was isolated from 26 (30.2%) PICCs, while other pathogens were isolated from 60 (69.8%). The mean duration of catheter dwell time for all participants was 20.94±14.22 days (range 3-72 days). When analysed separately for each group, the dwell time for PICCs with CLABSIs was 25.73±16.19 days and 16.36±10.28 days for those with colonization (T test, p=0.002). Additionally, the mean dwell time for PICCs infected by non-MDROs was 22.48±15.64 days whereas for PICCs with MDROs, it was 17.38±9.5 days (T test, p=0.005). In PICCs with CLABSIs, the mean indwelling time for MDR pathogens was 21.50±12.31 days, while for non-MDROs, it was 27.73±16.98 days (T test, p=0.417). In PICCs with colonization, the mean dwell time for MDR pathogens was 15.55±7.73 days, while for non-MDROs, it was 16.92±11.85 days (T test, p=0.124). Among PICCs with MDR pathogens (n=26), the mean duration in CLABSIs events (n=18) was 21.5±12.31 days and in colonization events 15.55±7.73 days, (n=8) (T test, p=0.146). Conclusions: The present study reveals that colonization of PICCs exhibited a shorter dwell time compared to those with CLABSIs. Moreover, PICCs infected by MDROs had a shorter mean dwell time than those with non-MDROs. These findings underscore the importance of considering infection status and microbial resistance patterns when evaluating PICC dwell times.

Suicide remains a persistent global health challenge, resisting widespread prevention efforts. According to previous findings, toxoplasmosis is particularly associated with altered deci-sion-making, which could lead to risk-taking behavior thereby increasing the likelihood for sui-cidal behavior (SB). In addition, discussion about the role of microbiome in psychiatric disorders has emerged lately, which also makes it relevant to investigate its role in the context of SB. Therefore, the current review aimed to comprehensively summarize existing knowledge regard-ing the association between microbial pathogens and SB. We conducted a systematic search with keywords including suicide and Toxoplasma gondii (Suicid* AND Toxoplasm*) and microbiome (Microbiome AND Suicid*) throughout PubMed to retrieve the related studies up to 09.11.2023. Most results reported significant association between toxoplasmosis and SB, suggesting a higher likelihood of SB in the infected population. Regarding the microbiome, only very few studies in-vestigated an association between SB and alterations in microbiota. Based on those few studies, changes in the microbiome were significantly associated with SB. The cognitive aspects of deci-sion-making in T. gondii infected individuals with SB should be further investigated to unravel underlying mechanisms. Further sufficiently powered studies are needed to establish a link be-tween SB and gut microbiota.

The COVID-19 pandemic exposed the vulnerability of current vaccine technologies characterized by a slow onset of action and antigen-specific immune response. Although parental vaccines offer long-term protection against homologous strains, they rely exclusively on adaptive immune memory to produce neutralizing antibodies that are ineffective against new vaccine variants. Moreover, growing evidence highlights the multifaceted functions of trained immunity to elicit a rapid and enhanced innate response against unrelated stimuli or pathogens to subsequent triggers. This review discusses the protective role of trained immunity against respiratory pathogens and the experimental models essential for evaluating novel inducers of trained immunity. We further elaborate on the potential of trained immunity to leverage protection against emerging pathogens via recognition of diverse antigens by pathogen recognition receptors (PPRs) on innate immune cells. We also propose integrating trained- with adaptive- immunity to shape next-generation vaccines by coupling each one's unique characteristics.

Eukaryotic enteric pathogens (EEP) are a public health issue in tropical areas. Yet, their interactions with the gut mycobiota remain poorly understood. We conducted a cross-sectional study in Malian children to analyze the impact of EEP on the gut fungal community. EEP were assessed by qPCR and the gut mycobiota was characterized by ITS1-2 metabarcoding in stool samples collected from 296 children. The 100 controls, in whom no EEP was detected, were compared to: a) 196 children with ≥1 EEP; b) 91 with only Blastocystis; c) 35 with only Giardia intestinalis; and d) 12 with another (&lt;1% each) EPP. The gut fungal community structure was homogenous in each children’s group. Linear size-effect discriminant analysis highlighted five relatively more abundant species, including Fusarium longipes and Penicillium caseifulvum, in children with ≥1 EEP, whereas 28, including Aspergillus sydowii and Microdochium colombiense were more abundant in controls. Fusarium, Pyxidiophora, and Stereum abundance was higher in Blastocystis-infected children, whereas Ogataea and Allocryptovalsa were more abundant in controls. Sordariales and Mortierellales abundance was higher in Giardia intestinalis-infected children, whereas Agaricales and Capnodiales abundance was higher in controls. In conclusion, EEP do not significantly alter the gut fungal community structure, and further studies are warranted to confirm our findings that particular taxa are associated with susceptibility or resistance to specific EEP.

The digital model of airborne frequency selective surface radomes (AFSSRs) is the basis of design, simulation analysis, manufacturing, and other related research of AFSSRs. This paper proposes a rapid modeling method of AFSSRs based on dynamic customizable primitives. Firstly, a layered digital model construction scheme of AFSSR is presented based on the typical radome wall structure. Then, according to the characteristics of various surface configurations and complex wireframe information of AFSSRs, the dynamic primitives are raised to express the boundary and contour information of all kinds of radomes. Focusing on the undevelopable characteristics of the aero-dynamic shape surface of the AFSSR, the arrangement solution and mapping method for frequency selective elements on undevelopable surfaces are proposed. Furthermore, the imple-mentation logic of this method on the creation of each layer model and the assembly of the whole machine model is introduced. Finally, according to this method, a rapid modeling system (RMS) is established, and the modeling effect and efficiency of the RMS are demonstrated and compared, which verifies the feasibility and effectiveness of this method.

Vegetation classifications on large geographic scales are necessary to inform conservation decisions and monitor keystone, invasive, and endangered species. These classifications are often effectively achieved by applying models to imaging spectroscopy, a type of remote sensing, data, but such undertakings are often limited in spatial extent. Here we provide accurate, high-resolution spatial data on the keystone species Metrosideros polymorpha, a highly polymorphic tree species distributed across bioclimatic zones and environmental gradients on Hawai'i island, using airborne imaging spectroscopy and LiDAR. We compare two tree species classification techniques, support vector machine (SVM) and spectral mixture analysis (SMA), to assess their ability to map M. polymorpha over 28,000 square kilometers where differences in topography, background vegetation, sun angle relative to the aircraft, and day of data collection, among others, challenge accurate classification. To capture spatial variability in model performance, we applied gaussian process classification (GPC) to estimate the spatial probability density of M. polymorpha occurrence using only training sample locations. We found that, while SVM and SMA models exhibit similar raw score accuracy over the test set (96.0% and 93.4%, respectively), SVM better reproduces the spatial distribution of M. polymorpha than SMA. We developed a final 2 m x 2 m M. polymorpha presence dataset and a 30 m x 30 m M. polymorpha density dataset using SVM classifications that have been made publicly available for use in conservation applications. Accurate, large-scale species classifications are achievable, but metrics for model performance assessments must account for spatial variation of model accuracy.

Proper treatment of infectious air could potentially mitigate the spread of airborne viruses such as porcine reproductive and respiratory syndrome virus (PRRSV). The objective of this research is to test the effectiveness of ultraviolet (UV) in inactivating aerosolized PRRSV, specifically, four UV lamps, UV-A (365 nm, both fluorescent and LED-based), "excimer" UV-C (222 nm), and germicidal UV-C (254 nm), were tested. The two UV-C lamps effectively irradiated fast-moving PRRSV aerosols with short treatment times (<2 s). One-stage and two-stage UV inactivation models estimated the UV doses needed for target percentage (%) reductions on PRRSV titer. UV-C (254 nm) dose needed for 3-log (99.9%) reduction was 0.521 and 0.0943 mJ/cm2, respectively, based on one-stage and two-stage models. An order of magnitude lower UV-C (222 nm) doses were needed for a 3-log reduction, i.e., 0.0882 and 0.048 mJ/cm2, based on one-stage and two-stage models, respectively. However, the cost of 222-nm excimer lamps is still economically prohibitive for scaling-up trials. The UV-A (365 nm) lamps could not reduce PRRSV titers for tested doses up to 4.11 mJ/cm2. Pilot-scale or farm-scale testing of UV-C on PRRSV aerosols simulating barn ventilation rates are recommended based on its effectiveness and reasonable costs comparable to HEPA filtration.

Verification of inclusivity of molecular detection methods gives indications on the reliability of viral infections diagnosis because of the tendency of viral pathogens to undergo sequence variation. This study was aimed to select inclusive probe based reverse transcription quantitative PCR (RT-qPCR) assays for the diagnosis of the most widespread and detrimental viruses infecting honeybees, namely the acute bee paralysis virus (ABPV), the black queen cell virus (BQCV), the chronic paralysis bee virus (CBPV), the deformed wing virus variants A (DWVA) and B (DWVB), and the sacbrood virus (SBV). Therefore, detection methods previously described were re-evaluated in silico for specificity and inclusivity. Based on this evaluation, selected methods were modified or new ones were designed and tested in duplex RT-qPCR reactions. The limits of detection (LODs), effect of multiplexing on sensitivity and viral RNA quantification potential in bees and hive debris were assessed. This study made available diagnostic assays able to detect an increased number of virus variants compared to previously described tests and two viral pathogens in a single PCR reaction.

The increased cultivation of high THC-containing Cannabis sativa L. (cannabis), particularly in greenhouses, has resulted in a greater incidence of diseases and molds that can negatively affect the growth and quality of the crop. Among them, the most important diseases are root rots (Fusarium and Pythium spp.), Botrytis bud rot (Botrytis cinerea), powdery mildew (Golovinomyces ambrosiae), cannabis stunt disease (caused by Hop latent viroid), and a range of microbes that reduce post-harvest quality. An integrated management approach to reduce the impact of these diseases/microbes requires combining different approaches that target the reproduction, spread and survival of the associated pathogens, many of which can occur on the same plant simultaneously. These approaches will be discussed in the context of developing an integrated plan to manage the important pathogens of greenhouse-grown cannabis at different stages of plant development. These stages include maintenance of stock plants, propagation through cuttings, vegetative growth of plants, and flowering. The cultivation of cannabis genotypes with tolerance or resistance to various pathogens is a very important approach, followed by the maintenance of pathogen-free stock plants. When combined with cultural approaches (sanitation, management of irrigation, and monitoring for diseases) and environmental approaches (greenhouse climate modification), a significant reduction in pathogen development and spread can be achieved. The use of preventive applications of microbial biological control agents and reduced risk biorational products can also reduce disease development at all stages of production in jurisdictions where they are registered for use. The combined use of promising strategies for integrated disease management on cannabis plants during greenhouse production will be reviewed. Future areas for research are identified.

Ticks and tick-borne pathogens (TBPs) are major constraints to camel health and production, yet epidemiological data on their diversity and impact on dromedary camels are limited. We sur-veyed the diversity of ticks and TBPs associated with camels and co-grazing sheep at 12 sites in Marsabit County, northern Kenya. We screened blood and ticks (858 pools) collected from 296 camels and 77 sheep for bacterial and protozoan TBPs by high-resolution melting analysis and sequencing of PCR products. Hyalomma (75.7%), Amblyomma (17.6%) and Rhipicephalus (6.7%) spp. ticks were morphologically identified and confirmed by molecular analyses. We detected TBP DNA in 80.1% of blood samples from 296 healthy camels. “Candidatus Anaplasma camelii”, “Candidatus Ehrlichia regneryi” and Coxiella burnetii were detected in both camels and associ-ated ticks, and Ehrlichia chaffeensis, Rickettsia africae, Rickettsia aeschlimannii and Coxiella endo-symbionts were detected in camel ticks. We also detected Ehrlichia ruminantium, responsible for heartwater disease in ruminants, in Amblyomma ticks infesting camels and sheep and in sheep blood, indicating its endemicity in Marsabit. Our findings also suggest that camels and/or the ticks infesting them are reservoirs of zoonotic Q fever (C. burnetii), ehrlichiosis (E. chaffeensis), and rickettsiosis (R. africae), which pose a public health threat to pastoralist communities.

The quality of photogrammetric-based derived products like orthophotos, digital terrain models (DTMs) and digital line maps as well as the global digital elevation models (DEM) are rigorously dependent on the accuracy of image orientation. This paper evaluates the vertical accuracy of aerial photogrammetric Digital Terrain Model (DTM), Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), and TerraSAR-X's twin satellite of TanDEM-X (TDX) datasets against in-situ orthometric heights computed from ellipsoidal heights and the 2008 Earth Gravitational Model (EGM2008) derived geoid heights in Ethiopia. The quality of the four global digital elevation models was also validated against the aerial photogrammetric DTM measurements. Besides, the accuracies of the photogrammetric DTM and the four DEM products were checked for their compliance to the American Society for Photogrammetry and Remote Sensing (ASPRS) standards as well as the Ethiopian national vertical data evaluation standards. The study showed that the photogrammetric DTM is in a good agreement with the reference orthometric heights compared to SRTM, ASTER and TDX datasets. More precisely, the result has an absolute accuracy of 1.67 m at Linear Error (LE) 95% confidence level, while the absolute accuracy of SRTM3 arc seconds (SRTM3) at LE 90% (11.91 m) is better than its product specification (16 m). The absolute accuracy of SRTM1 arc second (SRTM1) (7.70 m at LE 90%) surpasses that of SRTM3, whereas the absolute accuracy of ASTER DEM is somehow below its product specification. TDX also has the same vertical accuracy (10.29 m at LE 90%) compared to its product specification (10 m). Furthermore, the vertical accuracy of the photogrammetric DTM meets the100 cm vertical accuracy of the 2015 ASPRS standard. However, it does not meet the Ethiopian national vertical data accuracy requirement standard, i.e., RMSEz of ± 0.45 m. In general, the photogrammetric DTM, SRTM1, and TDX have been proven a superior product over the SRTM3 and ASTER DEMs, and better to use these products for high-level precision and accuracy required applications.

The increased cultivation of Cannabis sativa L. in North America, represented by high Δ9-tetrahydrocannabinol-containing (high-THC) cannabis genotypes and low THC-containing hemp genotypes, has been impacted by an increasing number of plant pathogens. These include fungi which destroy roots, stems and leaves, in some cases causing a build-up of populations and mycotoxins in the inflorescences that can negatively impact quality. Viroids and viruses have also increased in prevalence and severity and can reduce plant growth and product quality. Rapid diagnosis of the occurrence and spread of these pathogens is critical. Techniques in the area of molecular diagnostics have been applied to study these pathogens in both cannabis and hemp. These include polymerase chain reaction (PCR)-based technologies, including RT-PCR, multiplex RT-PCR, RT-qPCR, and ddPCR, as well as whole genome sequencing (NGS) and bioinformatics. In this study, examples of how these technologies have enhanced the rapidity and sensitivity of pathogen diagnosis on cannabis and hemp will be illustrated. These molecular tools have also enabled studies on the diversity and origins of specific pathogens, specifically viruses and viroids, and these will be illustrated. Comparative studies on the genomics and metabolomics of healthy and diseased plants are urgently needed to provide insight into their impact on quality and composition of cannabis and hemp-derived products. Management of these pathogens will require monitoring of their spread and survival using the appropriate technologies to allow accurate detection, followed by appropriate implementation of disease control measures.

Post-COVID-19 bacterial infections are a significant threat to global health, mainly due to the overuse and misuse of antibiotics. The review highlights the importance of using antibiotics judiciously and following appropriate guidelines and recommendations. The article also examines the potential indirect contribution of steroids to antibiotic resistance through immune suppression in severe cases of COVID-19. Anti-microbial resistance (AMR) is one of the leading causes of death worldwide that continues as a silent pandemic caused by the major AMR superbug includes Carbapenem-resistant Acinetobacter baumannii (CRAB), Methicillin-resistant Staphylococcus aureus (MRSA), Carbapenem-resistant Enterobacterales (CRE), Extended-spectrum Beta Lactamase producing Enterobacterales (ESBL) which is resistant to cephalosporin and Multidrug-resistant (MDR) Pseudomonas aeruginosa. Ongoing surveillance and monitoring of antibiotic use and resistance helped to minimize the risk of antibiotic resistance and shrink it from pandemic to endemic.

Healthcare-associated infections (HAI) worldwide includes infections by ESKAPE-E pathogens. Environmental surfaces and fomites are important components in HAI transmission dynamics, and shoe soles are vectors of HAI. Ultraviolet (UV) disinfection is an effective method to inactivate pathogenic microorganisms. In this study, we investigated whether the SANITECH UVC shoe sole decontaminator equipment that provides germicidal UVC radiation could effectively reduce this risk of different pathogens. Six standard strains and four clinical MDR strains in liquid and solid medium were exposed to a UVC System at specific concentrations at other times. Bacterial inac-tivation (growth and cultivability) was investigated using colony counts and resazurin as meta-bolic indicators. SEM was performed to assess the membrane damage. Statistically significant reduction in cell viability for all ATCCs strains occurred after 10 sec of exposure to the UVC sys-tem, except for S enterica, which only occurred at 20 sec. The cell viability of P. aeruginosa (90.9%), E. faecalis and A. baumannii (85.3%), S. enterica (82.9%), E. coli (79.2%) and S. aureus (71.9%) was re-duced considerably at 20 sec. In colony count, after 12 sec of UVC exposure, all ATCC strains showed a 100% reduction in CFU counts, except for A. baumannii, which reduced 97.7%. A sub-stantial reduction of colonies above 3 log10 was observed at 12 and 20 sec in all bacterial strains tested, except for A. baumannii ATCC 19606 (12 sec). The exposure of ATCCs bacterial strains to the UVC system for only 2 sec was able to reduce 100% in the CFU count in all ATCCs strains, S. au-reus, P. aeruginosa, E. coli, A. baumannii, E. faecalis, except the S. enterica strain which had a statis-tically significant reduction of 99.7%. In ATCC strains, there was a substantial decrease in colonies after 4 sec (sec) of exposure to the UVC system, with a reduction ranging from 3.78-4.15 log10 CFU/mL. This reduction was observed in MDR/ESKAPE-E strains within 10 sec, showing that UVC could eliminate above 3.84 log10 CFU/mL. SEM showed a reduction of pili-like appendages after UVC treatment in all strains except for E. coli (ATCC 25922). The Sanitech UVC shoe sole decontaminator equipment from Astech Co. effectively killed in vitro a series of ATCCs and MDR/ESKAPE-E bacteria of sanitary interest, commonly found in the hospital environment.

The pollution caused by nitrogen dioxide is a major environmental problem in China. This study introduces a new type of atmospheric trace gas remote-sensing instrument, an airborne fiber imaging spectrometer. This spectrometer has a spectral range of 300–410 nm and works in push-broom mode with a 30° field of view on a flight path. Flight experiments were conducted on December 30, 2022 and January 5, 2023, covering heavily polluted areas of east of Beijing and Tangshan. This equipment obtained the density distribution of NO2 over the flight area. The results showed that pollution was mainly concentrated in the Caofeidian area and at the power station in the north, and the main source of pollution was anthropogenic. Satellite and airborne data near the pollution points were compared, and the two datasets showed a positive correlation with a correlation coefficient of 0.78 and 0.7, on the two days, respectively. This study demonstrates the capability of an airborne fiber imaging spectrometer for NO2 regional emission remote sensing and identifying the pollution points.

The dual-station Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of single-station dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration.Unmanned aerial vehicles (UAV) equipped with dual-station InSAR, with relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne dual-station InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne dual-station InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision dual-station InSAR imaging and interferometric processing. Height inversion results based on the proposed method is also provided, demonstrating the effectiveness of the proposed method and improving interferometric accuracy at calibration points from 0.66 meters to 0.42 meters.

This study aimed to investigate the airborne release of N-nitrosodimethylamine (NDMA) as a result of the dry heat cooking of some meats using charcoal grilling and pan broiling methods. Three types of meat, beef sirloin, pork belly, and duck, were chosen and cooked in a temporary building using the above methods. Air samples were collected in Thermosorb-N cartridges, which were qualitatively and quantitatively analyzed for NDMA using ultra-high performance liquid chromatography–mass spectrometry and high-performance liquid chromatography–fluorescence detection, respectively. Overall, the charcoal grilling method showed higher average NDMA concentrations than the pan broiling method for all types of meat. The highest average concentration was observed for charcoal-grilled beef sirloin (410 ng/m3) followed by pork belly, suggesting that meat protein content and cooking duration are important determinants of NDMA formation. Cancer risk assessment showed that the charcoal grilling of such meats can pose an additional cancer risk for restaurant customers.

The literature shows that both in laboratory and in industrial conditions, photocatalytic oxidation method copes quite well with the degradation of the most organic substances, including environmental toxins and molecular components of pathogenic microorganisms. However, the effective utilization of photocatalytic processes for environmental decontamination and disinfection require significant technological advancement both in the area of semiconductor material synthesis and its application. Here we focused on the presence and ‘photocatalytic capability‘ of photocatalysts among soil minerals, and their potential contribution to the environmental decontamination in vitro and in vivo. (The issue is sketched from the perspective of chemists and environmental scientist.) Reactions caused by sunlight on the soil surface are involved in its normal redox activity. It appears that some of them may take part in the soil decontamination. However, their importance for decontamination in vivo cannot be overstated due to diversity of soils on the Earth caused by the environmental conditions, such as climate, parent material, relief, vegetation etc. The solar-light induced reactions are just a part of extremely complicated processes dependent on a plethora of environmental determinates. Such multiplicity of affecting factors, which we tried to sketch from the perspective of chemists and environmental scientist, makes us rather sceptical about the effectiveness of the photocatalytic processes in vivo. On the other hand, there is a huge potential of the soils as the alternative source of useful photocatalytic materials of unique properties

In this study, we aimed to determine the trend of antimicrobial resistance pattern of pathogens isolated in samples collected from patients hospitalized in the intensive care unit (ICU), in selected periods before and after COVID-19. A retrospective study of bacterial pathogens was performed on 1267 patients. The resistance patterns were analyzed using Vitek 2 Compact system. Positive-bacterial culture data of 1695 samples from pre-COVID-19 period and 1562 from post-COVID-19 period were obtained. The most frequently isolated in both periods were Staphylococcus aureus and Klebsiella spp. Klebsiella spp. had a statistically significant increase in resistance rates in the post COVID-19 period, against colistin, gentamicin and aztreonam. For E. coli strains, it was registered a significant increase against colistin and a significant decrease against levofloxacin and imipenem. For Acinetobacter spp. strains it was observed a significant increase against colistin. More than 50% from the Staphylococcus aureus strains were MRSA with statistically significant increases in antimicrobial resistance rate in the post-COVID-19 period against doxycycline, linezolid, rifampicin and teicoplanin. The study revealed a significantly increasing trend of the antimicrobial resistance rate of Gram-negative pathogens (Klebsiella spp., Acinetobacter spp.) against certain antibiotics, including those used only in cases where there are no other therapeutic options.

Respiratory tract infections (RTIs) are one of the main causes of hospitalization and mortality causing substantial economic burden to healthcare systems globally. As opposed to the previous belief that respiratory infections are caused by a single pathogen, studies have shown that most RTIs are a result of a combination of bacterial and/or viral pathogens infecting the host. The clinical manifestation of RTIs is very similar (i.e., syndrome), often showing Influenza-like illness (ILI) symptoms. While COVID-19 has dominated ILI over the past few years, there are many other pathogens that are responsible for ILI. In addition, it is not uncommon to have coinfections with multiple pathogens in patients presenting with ILI and that such coinfections can even exacerbate the disease severity of RTIs. Therefore, an insight into coinfections can help with accurate disease prognosis, patient care management and outcomes. The goal of this study was to identify the different organisms in symptomatic patients presenting with ILI.

Since life on earth developed, parasitic microbes have thrived. Increases in host numbers, or the conquest of a new species, provides an opportunity for such a pathogen to enjoy, before host defense systems kick in, a similar upsurge in reproduction. Outbreaks ‒ caused by ‘endemic’ pathogens ‒ and epidemics ‒ caused by ‘novel’ pathogens ‒ have thus been creating chaos and destruction since prehistorical times. To study such (pre)historic epidemics, recent advances in the ancient DNA field, applied to both archeological and historical remains, have helped tremendously to elucidate the evolutionary trajectory of pathogens. These studies offered new and unexpected insights in the evolution of, for instance, smallpox virus, hepatitis B virus and the plague-causing bacterium Yersinia pestis. Furthermore, burial patterns and historical publications can help in tracking down ancient pathogens. Another source of information is our genome, where selective sweeps in immune-related genes relate to past pathogen attacks, while multiple viruses have left their genomes behind for us to study.

The outbreak of COVID-19 has caused a global public health crisis. The spread of SARS-CoV-2 by contact is widely accepted, but the relative importance of aerosol transmission for the spread of COVID-19 is controversial. Here we characterize the distribution of SARA-CoV-2 in 123 aerosol samples, 63 masks, and 30 surface samples collected at various locations in Wuhan, China. The positive percentages of viral RNA included 21% of the aerosol samples from an intensive care unit and 39% of the masks from patients with a range of conditions. A viable virus was isolated from the surgical mask of one critically ill patient while all viral RNA positive aerosol samples were cultured negative. The SARS-CoV-2 detected in masks from patients, ambient air, and respirators from health workers compose a chain of emission, transport, and recipient of the virus. Our results indicate that masks are effective in protecting against the spread of viruses, and it is strongly recommended that people throughout the world wear masks to break the chain of virus transmission and thus protect themselves and others from SARS-CoV-2.

To decrease oral pathogens and increase the number of beneficial bacteria, probiotics and bioactive compounds made via microbial bioconversion are recently used. In addition, the interest regarding probiotics-mediated bioconversion with popular medicinal plants is increasing. These compounds produced during the process exhibit synergistic effect and enhance a variety of biological activities including pathogen inhibition in host. Therefore, we developed bioconverted milk with high inhibitory activity against oral pathogens and α-glucosidase. Lactiplantibacillus plantarum SMFM2016-RK was chosen as the probiotic due to its beneficial characteristics such as high acid and bile tolerance, antioxidant activity, and α-glucosidase inhibition. Based on the minimal bactericidal concentration against three oral pathogens, the following appropriate concentrations of Artemisia herba-alba extract were added to milk: 5 mg/mL of A. herba-alba ethanol extract and 25 mg/mL of A. herba-alba hot-water extract. Four bioconverted milks (BM), BM1, BM2, BM3, and BM4, were produced by combining L. plantarum SMFM2016-RK alone, L. plantarum SMFM2016-RK and ethanol extract, L. plantarum SMFM2016-RK and hot-water extract, and L. plantarum SMFM2016-RK with both extracts. As a result of antimicrobial activity, BM3 inhibited the growth of Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis the most, and BM4 suppressed the growth of Fusobacterium nucleatum the most. In addition, bioconverted milk containing A. herba-alba (BM2, BM3, and BM4) inhibited α-glucosidase more effectively than BM1. In conclusion, A. herba-alba-added milk bioconverted by L. plantarum SMFM2016-RK displayed the growth inhibitory effect on oral pathogens and the α-glucosidase inhibitory activity, thus it necessitates to evaluate the effects on the alleviation of oral diseases and glycemic control through future animal experiments.

Modern commercial air travel connects disparate human populations with the global airline industry transporting up to 4.5 billion passengers annually in the years leading up to the COVID-19 pandemic. While such connections are convenient for commerce and tourism, air travel networks can also be efficient distributors of infectious diseases such as influenza, SARS-CoV-1, hemorrhagic fevers, and more recently SARS-CoV-2 and monkeypox. During the COVID-19 pandemic, public health agencies used multi-layered control strategies including pre-departure testing and vaccination requirements, masking, post-arrival testing, and quarantine to manage the risk of COVID-19 transmission associated with air travel. Simultaneously, the surveillance of aircraft wastewater emerged as a promising new data source to screen for SARS-CoV-2 infections, including newly emergent lineages, among international air travelers. Herein, we review the potential of aircraft wastewater for public health surveillance. The known contributing population and flight itinerary combined with the highly concentrated waste stream and convenient sampling during routine lavatory servicing make aircraft wastewater a strategic opportunity for unintrusive surveillance of the global fluxes of human pathogens. We estimate for the cases of fecal- or urine-shed pathogens, sampling from 3,500 and 1,250 flights per week, respectively, would be required to survey 10% of all global long-haul flight passengers. In the case of the United States, achieving 10% coverage of all international arrivals would require sampling from 925 and 322 flights per week, respectively. Aircraft wastewater surveillance could also be integrated with network and infectious disease models to better inform traditional public health control measures during emerging epidemics. Given the tremendous potential for public good and the massive economic costs of epidemics, governments should consider international collaboration to create a global aircraft wastewater surveillance system.

Commonly the periodontitis has been linked to periodontopathogens categorized in Socransky's microbial complexes, however, there is a lack of knowledge regarding “other microorganisms” or "cryptic microorganisms", which are rarely thought of as significant oral pathogens and are neither previously categorized nor connected to illnesses in the oral cavity. This study hypothesized that these cryptic microorganisms could contribute to the modulation of oral microbiota present in health or disease (periodontitis and/or OSA patients). For this purpose, the presence and the correlation among these cultivable cryptic oral microorganisms were identified and their possible role in both conditions was determined. Data from oral samples of individuals with or without periodontitis and with or without OSA were obtained from a previous study. Demographic data, clinical oral characteristics, and genera and species of cultivable cryptic oral microorganisms identified by MALDI-TOF were recorded. The data of 75 participants were analyzed to determine the relative frequencies of cultivable cryptic microorganisms’ genus and species, microbial clusters and correlations tests were performed. According to periodontal condition, Gingivitis - dental biofilm-induced in reduced periodontium and stage III periodontitis were found to have the highest diversity of cryptic microorganism species. Based on the experimental condition these findings showed that there are genera related to disease conditions and others related to healthy conditions, with species that could be related to different chronic diseases being highlighted as comorbidities periodontitis and OSA. The cryptic microorganisms within the oral microbiota of patients with periodontitis and OSA are present as potential pathogens, promoting the development of dysbiotic microbiota, and the occurrence of chronic diseases, which have been previously proposed to be common risk factors for periodontitis and OSA. Understanding the function of possible pathogens in the oral microbiota will take more research.

Organisms release their nucleic acid in the environment including the DNA and RNA which can be used to detect their presence. eDNA/eRNA techniques are being used in different sectors to identify organisms from soil, water, air, and ice since long. The advancement in technology led to easier detection of different organisms without impacting the environment and the organism itself. These methods are being employed in different areas including surveillance, history, and conservation. eDNA and eRNA methods are being extensively used in aquaculture and fisheries setting to understand the presence of different fish species and pathogens in water. However, there are some challenges associated with the reliability of the results because of the degradation of nucleic acid by several factors. In aquaculture there are several diseases and parasites detected with these methods. In this review we discuss different aquaculture diseases and parasites detected with eDNA/eRNA approach and the fate of these nucleic acids when subjected to different water quality and environmental parameters. This review intends to help the researcher about the potential of eDNA/eRNA based detection of pathogens in aquaculture; this will be useful to predict the potential outbreak before it occurs. Along with that this paper intends to make people understand several factors that degrade and can hamper the detection of these nucleic acids.

Abstract Plant fungal pathogens are frequently found as one of limiting factors for crop production. More than 10,000 species of fungi can cause disease in plants. To control the diseases, many farmers are still rely on the use of chemical fungicides, however most synthetic fungicides can cause acute toxicity, and some cause chronic toxicity as well. Thus, an appropriate technological improvement towards a more effective use of natural resources is required in agriculture to develop environmentally friendly sustainable farming system. This paper highlights the potential of extracts of tropical plants as antifungal agent to control plant fungal diseases. Information and data presented in this paper are mainly derived from selected and related references that previously published in the scientific journals. Many higher plants of tropical origin with fungicidal activities and their potential for fungal disease control of agricultural crops have been studied, however most of the studies have been done under in vitro condition. Some plant extracts showed strong antifungal activities on in vitro as well as in vivo tests, but some plant extracts showed significant antifungal activities on in vitro test, but did not obvious on in vivo tests. A great variation in antifungal activities were shown by plants extracts of different species and plant parts, in one hand, and on the other hand, variation was also observed on the responses of different fungal species to the same plant extract. Since the purpose of the use of plant extract is to control plant fungal diseases, the field trial is needed to ensure the stability of efficacy of certain plant extract. In addition, isolation and identification of active substances in the extracts is needed to assess possible mode of action and side effect of their use.

Accurately assessing forest structure and maintaining up-to-date information about forest structure is crucial for various forest planning efforts, including the development of reliable forest plans and assessments of the sustainable management of natural resources. Field measurements traditionally applied to acquire forest inventory information (e.g., basal area, tree volume, and aboveground biomass) are labor-intensive and time-consuming. To address this limitation, remote sensing tech-nology has been widely applied in modeling efforts to help estimate forest inventory information. Among various remotely sensed data, LiDAR can potentially help describe forest structure. This study was conducted to estimate and map forest inventory information across the Talladega Na-tional Forest by employing ALS-derived data and aerial photography. The quality of predictive models was evaluated to determine whether additional remotely sensed data can help improve forest structure estimates. Additionally, the quality of general predictive models was compared to that of species-group models. This study confirms that quality level 2 LiDAR data was sufficient for developing adequate predictive models (R2adj. ranging between 0.71 and 0.82) when compared to the predictive models based on LiDAR and aerial imagery. Additionally, this study suggests that species-group predictive models were of higher quality than general predictive models. Lastly, landscape-level maps were created from the predictive models, and these may be helpful to plan-ners, forest managers, and landowners in their management efforts.