This study aims to assess using a smartphone app (DecibelX), as a noise measuring alternative to the more costly traditional use of measuring noise levels with a Sound Level Meter (SLM). The study compares the accuracy of the app to readings taken with a SLM and dosimeter, and also evaluates the app’s performance for pure tone and narrow band noise. And a usability study identifies strengths and weaknesses related to usability of the app.

Low-cost particle sensors are now used worldwide to monitor outdoor air quality. However, they have only been in wide use for a few years. Are they reliable? Does their performance deteriorate over time? Are the algorithms for calculating PM2.5 provided by the Plantower company for PurpleAir monitors accurate? We investigate these questions using continuous measurements of four monitors (8 sensors) under normal conditions inside and outside a home for 1.5-3 years. A recently-developed algorithm (called ALT-CF3) is compared to the two existing Plantower algorithms. The Plantower CF1 algorithm was shown to lose 25-50% of all indoor data due to the questionable practice of assigning zero to all concentrations below a threshold. None of these data were lost using the ALT-CF3 algorithm. About 92% of all data showed precision better than 20% using the ALT-CF3 algorithm, but only about 45-75% of data achieved that level using the Plantower CF1 algorithm. The limits of detection (LODs) using the ALT-CF3 algorithm were mostly under 1 ug/m3, compared to about 3-10 ug/m3 using the Plantower CF1 algorithm. The percent of observations exceeding the LOD was 53-92% for the ALT-CF3 algorithm, but only 16-44% for the Plantower CF1 algorithm. For indoor air in homes, the Plantower algorithms are inappropriate.

Low-cost monitors have made possible for the first time measurements of long-term (months to years) potential indoor exposures to fine particles. Indoor and outdoor measurements made over nearly 5 years (2017-2021) by the largest network of low-cost monitors in the United States (PurpleAir) are compared to the prevalence of adult smokers in 1650 Zip codes within the three West Coast states of California, Oregon, and Washington. The results show that mean indoor exposures above the 75th percentile of adult smoking prevalence are more than 50% higher than those below the 25th percentile. Mean outdoor concentrations are also elevated, but by a smaller amount (20%). Both comparisons are significant at the p<0.001 level. The elevation of the PM2.5 concentrations with increasing smoking prevalence is evidence of environmental disparities in income, education, and other socioeconomic indices..

An immune-inflammatory response is accompanied by increased nitro-oxidative stress. The aims of this mechanistic review are to review: a) the role of redox sensitive transcription factors and enzymes, ROS/RNS production and the activity of cellular antioxidants on the activation and performance of macrophages, dendritic cells, neutrophils, T cells, B cells and natural killer cells; b) the involvement of high-density lipoprotein (HDL), apolipoprotein (Apo)A1, paraoxonase (PON)-1, and oxidized phospholipids in the regulation of the immune response; and c) the detrimental effects of hypernitrosylation and chronic nitro-oxidative stress on the immune response. The redox changes during immune-inflammatory responses are orchestrated by the actions of nuclear factor (NF)-κB, HIF1alpha, the mechanistic target of rapamycin (mTor), the phosphatidylinositol 3‑kinase (PI3K) / protein kinase B (AKT) signalling pathway, mitogen-activated protein (MAP) kinases, 5' AMP-activated protein kinase (AMPK), and peroxisome proliferator-activated receptor (PPAR). The performance and survival of individual immune cells is under redox control and sensitive to intracellular and extracellular levels of ROS/RNS and is heavily influenced by cellular anti-oxidants including the glutathione and thioredoxin systems, nuclear factor erythroid 2-related factor 2 (Nrf-2), and the HDL complex. Chronic nitro-oxidative stress and hypernitrosylation inhibit the activity of those antioxidant systems, the tricarboxylic acid cycle, mitochondrial functions, and the metabolism of immune cells. In conclusion, those redox-associated mechanisms modulate metabolic reprogramming of immune cells, macrophage and T helper cell polarization, phagocytosis, production of pro- versus anti-inflammatory cytokines, immune training and tolerance, chemotaxis, pathogen sensing, antiviral and antibacterial effects, Toll-like receptor activity, and endotoxin tolerance.

This paper investigates calendar anomalies, volatility patterns, and the best forecasting model for predicting volatility in the cryptocurrency market, focusing on ten prominent cryptocurrencies: Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Spanning from January 2016 to December 2023, the study utilizes sophisticated statistical models such as GARCH (p,q), EGARCH (p,q), and GJR-GARCH (p,q) to analyze precise changes in market dynamics and the impact of day-of-week fluctuations on cryptocurrency returns. Empirical evidence reveals significant findings regarding the persistence of volatility, positive and negative news effects on volatility, and day-of-week effects on cryptocurrency returns. Post-COVID-19, Sunday emerges as the least volatile day for cryptocurrencies, while Thursdays and Tuesdays exhibit greater volatility. Binance, Ethereum, Dogecoin, and Tether show anomalies where returns on Tuesday and Thursday significantly differed from those on other days of the week. Many other currencies, like the USD coin, Cardano, and Ripple, show anomalies only in the pre-COVID-19 period. The findings highlight the best forecast model for volatility for each top cryptocurrency, offering practical implications for investors, traders, regulators, and policymakers. These insights emphasize the importance of understanding and addressing calendar anomalies in the cryptocurrency market for informed decision-making, trading strategies, regulatory frameworks, and market stability.

This paper investigates portfolio optimization methodologies and short-term investment strate-gies in the context of the cryptocurrency market, focusing on ten major cryptocurrencies from January 2020 to November 2023. We employ high frequency data and utilize the Kurtosis Mini-mization methodology, alongside other optimization strategies, to construct and evaluate port-folios under different rebalancing frequencies. The empirical analysis reveals that cryptocurren-cies exhibit significant volatility, skewness, and kurtosis, necessitating sophisticated portfolio management techniques. We find that the Kurtosis Minimization methodology consistently outperforms other optimization strategies, delivering optimal returns to investors, particularly in shorter-term investment horizons. We demonstrate the diversification benefits of integrating cryptocurrencies into multi-asset portfolios and emphasize the importance of regular portfolio rebalancing in the volatile cryptocurrency market. Our findings offer insights for portfolio man-agers and investors seeking to optimize their investment outcomes in the cryptocurrency market, highlighting the importance of risk management, diversification, and dynamic portfolio man-agement strategies.

In this work we present VaccineHero, an eXtended Reality system that aims to reduce children’s discomfort during vaccination. In our proposal the child wears a headset during vaccination and watches a short story in VR. The story includes a hero touching the child’s arm and the doctor synchronises the insertion of the needle with the VR content, so that the child is distracted efficiently. A clinical trial has been carried out, involving 2 doctors and a cohort of 16 children, and has shown that the use of VaccineHero reduces children’s discomfort during vaccination by a staggering 40% and totally eliminates extreme discomfort. The implemented solution is extremely affordable, as it can be deployed on simple headsets or even Cardboard devices, a feature that makes it a realistic option for any paediatric practice. It can also be extended to support other medical activities that involve needles, such as blood draw and blood donation.

Low-cost monitors make it possible now for the first time to collect long-term (months to years) measurements of potential indoor exposure to fine particles. Indoor exposure is due to two sources: particles infiltrating from outdoors and those generated by indoor activities. Calculating the relative contribution of each source requires identifying an infiltration factor. We develop a method of identifying periods when the infiltration factor is not constant, and searching for periods when it is relatively constant. From an initial regression of indoor on outdoor particle concentrations, a Forbidden Zone can be defined with an upper boundary below which no observations should appear. If many observations appear in the Forbidden Zone, they falsify the assumption of a single constant infiltration factor. This is a useful quality assurance feature, since investigators may then search for subsets of the data in which few observations appear in the Forbidden Zone. The usefulness of this approach is illustrated using examples drawn from the PurpleAir network of optical particle monitors. An improved algorithm is applied with reduced bias, improved precision, and a lower limit of detection than either of the two proprietary algorithms offered by the manufacturer of the sensors used in PurpleAir monitors.

The draconian regulation required by the inherent instability of cognitive phenomena -- gene expression, immune function, cancer suppression, wound healing, animal consciousness, machine intelligence, network stabilization, institutional cognition, and their many and varied composites -- can be viewed through the lens of the asymptotic limit theorems of both information and control theories. Here, we explore the dynamics and sometimes highly punctuated failures of the regulation of cognition under increasing `noise'. The approach parallels, and indeed generalizes, the Data Rate Theorem of control theory, extending the theorem's requirement of a minimum channel capacity necessary for stabilization of an inherently unstable system. Various models are explored across different basic underlying probability distributions characteristic of the system under study, and across different hierarchical scales, finding the addition of adaptive -- learned -- regulation greatly extends the reach of innate -- e.g., AI-driven or otherwise pre-programmed -- regulation. This work points toward the construction of new statistical tools for the analysis of observational and empirical data across a wide spectrum of inherent pathologies and adversarial challenges afflicting a wide variety of cognitive processes.

Spatial variation of indoor and outdoor PM2.5 within three states for a 5-year period is studied using regulatory and low-cost PurpleAir monitors. Most of these data were collected in an earlier study1 investigating the relative contribution of indoor-generated and outdoor-infiltrated particles to indoor exposures. About 260 regulatory monitors and ~10,000 outdoor and ~4,000 indoor PurpleAir monitors are included. Daily mean PM2.5 concentrations, correlations, and coefficients of divergence (COD) are calculated for pairs of monitors at distances ranging from 0 (collocated) to 200 km. We use a transparent and reproducible open algorithm that avoids use of the proprietary algorithms provided by the manufacturer of the sensors in PurpleAir PA-I and PA-II monitors. The algorithm is available on the PurpleAir API website under the name “PM2.5_alt”. This algorithm is validated using several hundred pairs of regulatory and PurpleAir monitors separated by up to 0.5 km. The PM2.5 spatial variation outdoors is homogeneous with high correlations to at least 10 km, as shown by the COD index under 0.2. There is also a steady improvement in outdoor PM2.5 concentrations with increasing distance from the regulatory monitors. The spatial variation of indoor PM2.5 indoors is not homogeneous even at distances <100 m. We document substantial differences between Federal Reference Methods (FRM) and Federal Equivalent Methods (FEM).

The GPA is a universally recognised and utilised metric of academic performance that is considered to also measure a student’s potential for academic performance in the future. In this short communication we examine to what extent the GPA of the first grade of high school predicts performance in the later grades of high school, either generally (as classified in excellent student, strong student, weak student or very weak student) or more accurately (as indicated by the exact GPA in the next grade). We also put to the test the widely held notion that it might be best if core courses such as language and mathematics contributed more to the calculation of the GPA compared to secondary courses such as physical education or music. Our findings confirm the predictive properties of the GPA but strongly rebut the notion that a weighted GPA might achieve a better reflection of students’ potential. The study is based on the academic records of every student in Greece that progressed from first to third grade of high school in the 2016-2019 period. This data set contains records of more than 85,000 students, making it one of the most extensive studies ever conducted on the topic of the properties of the GPA.

Recently, the destructive impact of wildfires has proliferated; for instance, the August Complex wildfire in 2020 burned around 4% of California's landmass. This has caused increased economic damage and risk to human life. Additionally, climate change is anticipated to increase the severity of wildfires, making it imperative for accurate and efficient detection of wildfires. Machine Learning approaches allow for the automatic detection of wildfires, simultaneously prioritizing accuracy and efficiency, with minimal human intervention, thus decreasing the likelihood of increased economic damage and increasing firefighting responses. Convolutional Neural Networks (CNNs), while showing promise, are often limited by their inability to learn and capture deep spatial dependencies in satellite imagery tasks. In this paper, we propose FlameViT, a novel wildfire detection architecture based on Vision Transformers (ViT). Satellite images are more efficient to obtain and can cover wide areas prone to wildfires. We obtain a dataset of 40K+ satellite images from Canada's Open Government Portal, allowing FlameViT to be optimized to detect wildfires in satellite imagery. FlameViT uses Patch Extractor and Patch Embedding layers, followed by multiple Transformer Encoder layers with Multi-Head Self-Attention and feed-forward neural networks. FlameViT is hyperparameter-tuned and achieves a validation accuracy of 95%, outperforming various baselines in the wildfire detection task. FlameViT shows the power of Vision Transformers for wildfire detection tasks, and in conjunction with the use of satellite imagery, can provide an efficient and accurate way of detecting wildfires.

River estuaries are dynamic and complex ecosystems influenced by various natural processes, including climatic fluctuations and anthropogenic activities. The Pearl River estuary (PRE), one of the largest in China, receives significant land-based pollutants due to its proximity to densely populated areas and urban development. This study aimed to characterize the composition, diversity, and distribution patterns of sediment microbial communities (Bacteria, Archaea, and Eukaryotes) and investigated the connection with environmental parameters within the PRE and adjacent shelf. Physicochemical conditions, such as oxygen levels, nitrogen compounds, and carbon content, were analyzed. The study found that the microbial community structure was mainly influenced by site location and core depth, which together explained approximately 67% of the variation in each kingdom. Sites and core depths varied in sediment properties such as organic matter content and redox conditions, leading to distinct microbial groups associated with specific chemical properties of the sediment, notably C/N ratio and NH4+ concentration. Despite these differences, certain dominant taxonomic groups were consistently present across all sites: Gammaproteobacteria in Bacteria; Bathyarchaeia, Nitrososphaeria, and Thermoplasmata in Archaea; and SAR in Eukaryota. The community diversity index was the highest in the bacteria kingdom, while the lowest values were observed at site P03 across the three kingdoms and were significantly different from all other sites. Overall, this study underscores the critical role of microbial communities in shaping biogeochemical processes in estuarine environments and their sensitivity to environmental changes, providing valuable information for managing and preserving the health of estuaries and coastal ecosystems.

Large quantities of real-time particle data are becoming available from low-cost particle monitors. However, it is crucial to determine the quality of these measurements. The largest network of monitors in the United States is maintained by the PurpleAir company, which offers two monitors: PA-I and PA-II. PA-I monitors have a single sensor (PMS1003) and PA-II monitors employ two independent PMS5003 sensors. We determine a new calibration factor for the PA-I monitor and revise a previously published calibration algorithm for PA-II monitors (ALT-CF3). From the PurpleAir API site, we downloaded 83 million hourly average PM2.5 values in the PurpleAir database from Washington, Oregon, and California between January 1, 2017 and September 8, 2021. Daily outdoor PM2.5 means from 194 PA-II monitors were compared to daily means from 47 nearby Federal regulatory sites using gravimetric Federal Reference Methods (FRM). We find a revised calibration factor of 3.4 for the PA-II monitors. For the PA-I monitors, we determined a new calibration factor (also 3.4) by comparing 26 outdoor PA-I sites to 117 nearby outdoor PA-II sites. These results show that PurpleAir PM2.5 measurements can agree well with regulatory monitors when an optimum calibration factor is found.

Unlike electron microscopy, which can achieve very high resolutions, but to date can only be used to study static structures, time-resolved X-ray diffraction from contracting muscles can, in principle, be used to follow the molecular movements involved in force generation on a millisecond timescale albeit at moderate resolution. However, previous X-ray diffraction studies of resting muscles have come up with structures for the head arrangements in resting myosin filaments that are different from the apparently ubiquitous interacting heads motif (IHM) found by single particle analysis of electron micrographs of isolated myosin filaments from a variety of muscle types. This head organization is supposed to represent the super-relaxed state of the myosin filaments where ATP usage is minimized. Here we have tested whether the interacting heads motif structures will satisfactorily explain the observed low-angle X-ray diffraction patterns from resting vertebrate (bony fish) and invertebrate (insect flight) muscles. We find that the interacting heads motif does not, in fact, explain what is observed. Previous X-ray models fit the observations much better. We conclude that the X-ray diffraction evidence has been well interpreted in the past and that there is more than one ordered myosin head state in resting muscle. There is, therefore, no reason to question some of the previous X-ray diffraction results on myosin filaments; time-resolved X-ray diffraction should be a reliable way to follow crossbridge action in active muscle and may be one of the few ways to follow molecular changes in myosin heads on a millisecond timescale as force is actually produced.

In this work the influence of the structure forming agent on the composition, morphology and oxygen reduction reaction (ORR) activity of Fe-N-C catalysts was investigated. As structure forming agent (SFA), dicyandiamide (DCDA) (nitrogen source) or oxalic acid (oxygen source) or mixtures thereof were used. For characterization, cyclic voltammetry and rotating disc electrode (RDE) experiments were performed in 0.1 M H2SO4. In addition to this, N2 sorption measurements and Raman spectroscopy were performed for the structural characterization. The role of metal, nitrogen and carbon sources within the synthesis of Fe-N-C catalysts has been pointed out before. Here, we show that the optimum in terms of ORR activity is achieved if both N- and O-containing SFAs are used in almost similar fractions. All catalysts display a redox couple, whereat its position depends on the fractions of SFAs. The SFA has also a strong impact on the morphology: Catalysts that were prepared with a larger fraction of N-containing SFA revealed a higher order in graphitization, indicated by bands in the 2nd order range of the Raman spectra. Nevertheless, the optimum in terms of ORR activity is obtained for the catalyst with highest D/G band ratio. Therefore, the results indicate that the presence of an additional oxygen-containing SFA is beneficial within the preparation.

Background. The characterization of new biomarkers of COVID-19 is extremely important. Few studies measured the soluble receptor for advanced glycation end product (sRAGE), angiotensin-converting enzyme 2 (ACE2), calcium and magnesium in COVID-19. Aims: To measure sRAGE, ACE2, interleukin (IL)-6, IL-10, CRP, calcium, magnesium, and albumin in COVID-19 patients in association with peripheral oxygen saturation (SpO2) and chest CT scan abnormalities (CCTA) including ground glass opacities. Methods. This study measured sRAGE, ACE2, IL-6, IL-10, CRP using ELISA techniques, and calcium, magnesium, and albumin using a spectrophotometric method in 60 COVID-19 patients and 30 healthy controls.Results. COVID-19 is characterized by significantly increased IL-6, CRP, IL-10, sRAGE, ACE2, and lowered levels of SpO2, albumin, magnesium and calcium. Neural networks showed that a combination of calcium, IL-6, CRP, and sRAGE yielded an accuracy of 100% in detecting COVID-19 patients with calcium being the most important predictor followed by IL-6, and CRP. COVID-19 patients with CCTAs showed lower SpO₂ and albumin levels than those without CCTAs. SpO2 was significantly and inversely correlated with IL-6, IL-10, CRP, sRAGE, and ACE2, and positively with albumin, magnesium and calcium. Patients with positive IgG results showed a significant elevation in the serum level of IL-6, sRAGE, and ACE2 compared to the negatively IgG patient subgroup.Conclusion. The results show that immune-inflammatory and RAGE pathway biomarkers may be used as external validating criterion for the diagnosis COVID-19. Those pathways coupled with lowered SpO2, calcium and magnesium are drug targets that may help to reduce the consequences of COVID-19.

Background: Smoking is disproportionately prevalent among Aboriginal and Torres Strait Islander Australian peoples, with 39% of Indigenous Australians aged over 15 years smoking daily. Efforts to reduce this high prevalence include culturally focused media campaigns, designed using community consultation, highlighting the need to determine how such health messaging is received by smokers. This study aimed to examine Indigenous Australian smokers’ reactions to a culturally focused anti-smoking mass media campaign—'Give up Smokes’. Methods: Intercept surveying across health services and events used recorded demographics, smoking status, quit attempts, smoking health effects, anti-smoking campaign recall, social support, and campaign reactions. Participants rated campaign images in five domains: 1) whether it made them stop and think; 2) personal relevance; 3) believability of design and message; 4) prompting concern about smoking; and 5) motivation towards quitting. Cluster analysis was used to segment smoker types. Results: Smoking health effects knowledge was high, and did not differ by quit readiness, attempts, or social support. Cessation support access was higher among those with greater readiness to quit. Social smoking behaviour and confidence to support others quitting did not significantly differ between participants, however importance of others quitting did. Quit readiness, attempts, and social support were associated with reaction to campaign design, but not message recall. Four types of smokers were described, using smoking characteristics, who differed in campaign message reactions. Conclusions: Strategies using campaign-exposed smoker characteristics to inform culturally focused health promotion are discussed in relation to four identified types of smokers.

Consumer food environments have transformed dramatically in the last decade. The number of food outlets has increased, and a large proportion of the UK population now purchase food from a takeaway or restaurant at least once a week. Despite these developments, national spending on food control has reduced and many Local Authorities struggle to meet health inspection targets. This work presents a data driven approach to enhance current inspection processes with a view to reduce consumer risk of foodborne illness whilst eating outside the home. We explore the utility of three machine learning algorithms to predict non-compliant food outlets in England and Wales as defined by Food Hygiene Rating Scheme scores >= 2. Using socio-demographic, business type and urbanness features we experiment with under and over sampling strategies at five ratios to address problems of class imbalance in the dataset prior to analysis. We find that Synthetic Minority Over Sampling Technique alongside a Random Forest algorithm with a 1:1 sampling strategy provides the best predictive power. Our final model retrieves 84% of total non-compliant outlets in a test set of 92,595 (sensitivity=0.843, specificity=0.745, precision=0.274). We discuss the utility of machine learning algorithms to prioritise high risk establishments for inspection by Local Authority officials and make recommendations for weighting outcomes to improve their appropriateness in an applied setting.

A well-prepared public health workforce is essential for reducing disease burdens and improving population health, requiring an education that addresses global and complex challenges. This paper examines the integration of the relational employability framework in public health education to cultivate critical global citizenship among students and graduates. Our research, conducted at Edith Cowan University in Perth, Western Australia, involved two case studies using qualitative interviews. Case Study 1, drawn from Cook’s doctoral research, explored student experiences with the relational employability framework within an undergraduate capstone unit. Case Study 2, a school-funded project, gathered graduate perspectives to inform ongoing curriculum development. The findings indicate that the relational employability framework enhances global competencies among students and graduates, through research skills development and critical reflective practice. Students reported improved awareness of their learning needs, self-confidence, and an increased ability to engage with diverse perspectives and societal challenges. Graduates highlighted the framework’s role in understanding ethical standards, conducting rigorous research and applying evidence-based practices in professional settings. Additionally, the framework supported the development of a reflective mindset, enabling graduates to make informed, value-based career decisions and advance their professional growth. The study suggests that adopting a relational employability approach can effectively prepare globally competent and reflective public health professionals. We advocate for the broader implementation of this framework in health education and higher education, offering practical recommendations for curriculum transformation. Such an approach will equip future professionals to contribute meaningfully to public health debates and embody the principles of global citizenship in their practice.

COVID-19 has been extremely difficult to control. The lack of understanding of key aspects of pandemics has affected virus transmission. On the other hand, there is a demand to incorporate Computational Thinking (CT) in the curricula with applications in STEM. However, there are still no exemplars in the curriculum that apply CT to real-world problems such as controlling a pandemic or other similar global crises. In this paper, we fill this gap by proposing exemplars of CT for modeling the pandemic. We designed exemplars following the three pillars of the APEC InMside framework for CT: algorithmic thinking, computational modeling, and machine learning. For each pillar, we designed a progressive sequence of activities that covers from elementary to high school. In an experimental study with elementary and middle school students from 2 schools of high vulnerability, we found that the computational modeling exemplar can be implemented by teachers and correctly understood by students. We conclude that it is feasible to introduce the exemplars at all grade levels, and that this is a powerful example of STEM integration that helps reflect and tackle real-world and challenging public health problems of great impact for students and their families.

Sudden cardiac arrest (SAC) is a leading cause of mortality. In recent years, though, many lives have been saved through the use of defibrillators by random bystanders. As a result, defibrillators have been popping up in various locations. In this work we propose a state mandate demanding the presence of a defibrillator at every pharmacy store and argue that it could greatly enhance and augment the impact of the defibrillator network. We support our claim via detailed calculations of the immediate (a defibrillator readily available) and partial (a defibrillator available at a reasonable distance) population coverage achievable by the implementation of our proposal, taking the Argolis area in Peloponnese Greece as a case study. Our findings indicate that, in addition to other benefits, the use of pharmacies to establish a defibrillator network could bring an eight-fold increase in the immediate population coverage of defibrillators and would provide immediate / partial access to a defibrillator to 18 / 24 incidents of SCA per year that would otherwise lead to death, potentially leading to the saving of numerous lives. Alternative scenaria are also discussed.

Given the high prevalence of cutaneous genus beta human papillomavirus (β-HPV) infections, it is important to understand how they are manipulating their host cells. This is particularly true for cellular responses to UV damage, since our skin is continually exposed to UV. The E6 protein from β-HPV (β-HPV E6) decreases the abundance of two essential UV-repair kinases (ATM and ATR). Since β-HPV E6 reduces their availability, the impact on downstream signaling events has been uncertain. We demonstrate that β-HPV E6 decreases ATM and ATR activation. This inhibition extended to XPA, an ATR target necessary for UV repair, lowering both its phosphorylation and accumulation. β-HPV E6 hinders POLη phosphorylation and foci formation, critical steps in translesion synthesis. ATM’s phosphorylation of BRCA1 is also attenuated by β-HPV E6. However, β-HPV E6’s hindrance of ATM/ATR signaling during UV-associated cell cycle arrest was incomplete. While there was less phosphorylation of immediate downstream targets (CHK1), events further down the cascade were not decreased. These observations are consistent with β-HPV infections making UV radiation more deleterious and support the proposed role of β-HPV in early stages of non-melanoma skin cancer development.

Pathogenic adenovirus (Ad) infections are widespread but typically mild and transient, except in the immunocompromised. As vectors for gene therapy, vaccine and oncology applications, Ad based platforms offer advantages including ease of genetic manipulation, scale of production and well established safety profiles, making them attractive tools for therapeutic development. However, the immune system often poses a significant challenge that may need to be overcome for adenovirus based therapies to be truly efficacious. Both pre-existing anti-Ad immunity in the population as well as the rapid development of an immune response against engineered adenoviral vectors can have detrimental effects upon the downstream impact of an adenovirus-based therapeutic. This review focusses on the different challenges posed, including pre-existing natural immunity and anti-vector immunity induced by a therapeutic, both in context of the innate and adaptive immune responses. We summarize different approaches developed with the aim of tackling these problems, as well as their outcomes and potential future applications.

Most pathogens are capable of infecting multiple host species and such cross-species transmission (CST) can have dramatic consequences, as highlighted by recent disease emergence events affecting human, animal and plant health. Understanding the ecological and evolutionary factors that constrain or facilitate the ability of disease agents to infect and establish in a novel host is therefore a timely and important research area. Previous work across different pathogens, including rabies virus (RABV), found that increased evolutionary distance between hosts reduces the frequency of cross-species transmission and of permanent host shifts. However, whether this effect of host relatedness still holds for transmission among recently diverged hosts, and the importance of this effect relative to other predictors, is not well understood. We addressed this question by quantifying the CST frequency of RABV between North American bat species within the genus Myotis, using a multi-decade data set containing 128 nucleoprotein (N) sequences from ten host species. For comparison, we also conducted an equivalent analysis of a RABV dataset from North American bat species comprising nine genera. We found that at the within genus scale, host relatedness failed to explain the frequency of CST events. However, CST frequency increased with overlap in species’ host range. Moreover, we found evidence of CST occurring among a higher proportion of species, and CST more frequently resulting in sustained transmission in the novel host in the Myotis dataset compared to the multi-genus dataset. Our results suggest that among recently diverged species, the ability to infect a novel host is no longer restricted by physiological barriers but instead is limited by physical contact. Our results improve predictions of where future CST events for RABV might occur and clarify the relationship between host divergence and pathogen emergence.

This paper is a follow-up to a previous study that was conducted in a research forest and identified the optimal method for Diameter at Breast Height (DBH) estimation as a circular scanning and fitting ellipses to 4cm stem cross-sections at breast height. The aim of this study was to determine whether the identified method is applicable to natural boreal forests as well. The iPad Pro LiDAR scanner was used to acquire point clouds for 15 sites representing a range of natural boreal forest conditions in Ontario, Canada, and estimate DBH. The secondary objective was to determine if tested stand (Species composition, age, density, understory) or tree (Species, DBH) factors affected the accuracy of estimated DBH. Overall, estimated DBH values were within 1cm of actual DBH values for 78 of 133 measured trees (59%). An RMSE of 1.5cm (8.6%) was achieved. Stand age had a large effect (&gt;0.15) on the accuracy of estimated DBH values, while density, understory, and DBH had moderate effects (0.05-0.14). No trend was identified between accuracy and stand age. Accuracy improved as understory density decreased and as tree DBH increased. Inertial Measurement Unit (IMU) and positional accuracy errors with the iPad Pro scanner limit the feasibility of using this device for forest inventories.

A U.S. government health agency conducted epidemiological studies to evaluate whether exposures to drinking water contaminated with volatile organic compounds at U.S. Marine Corps Base Camp Lejeune, North Carolina, were associated with increased health risks to children and adults. These health studies required knowledge of contaminant concentrations in drinking water—at monthly intervals—delivered to family housing, barracks, and other facilities within the study area. Because concentration data were limited or unavailable during much of the period of contamination (1950s–1985), the historical reconstruction process was used to quantify estimates of monthly mean contaminant-specific concentrations. This paper integrates many efforts, reports, and papers into a synthesis of the overall approach to, and results from, a drinking-water historical reconstruction study. Results show that at the Tarawa Terrace water treatment plant (WTP) reconstructed (simulated) tetrachloroethylene (PCE) concentrations reached a maximum monthly average value of 183 micrograms per liter (ug/L) compared to a one-time maximum measured value of 215 ug/L and exceeded the U.S. Environmental Protection Agency’s current maximum contaminant level (MCL) of 5 ug/L during the period November 1957–February 1987. At the Hadnot Point WTP, reconstructed trichloroethylene (TCE) concentrations reached a maximum monthly average value of 783 ug/L compared to a one-time maximum measured value of 1,400 ug/L during the period August 1953–December 1984. The Hadnot Point WTP also provided contaminated drinking water to the Holcomb Boulevard housing area continuously prior to June 1972, when the Holcomb Boulevard WTP came on line (maximum reconstructed TCE concentration of 32 ug/L) and intermittently during the period June 1972–February 1985 (maximum reconstructed TCE concentration of 66 ug/L). Applying the historical reconstruction process to quantify contaminant-specific monthly drinking-water concentrations is advantageous for epidemiological studies when compared to using the classical exposed versus unexposed approach.

Open-pit uranium mining in the south Texas Gulf Coast region was active during the second half of the 20th century. Although some mines have extensive records documenting the locations and extents with descriptions of reclamation procedures and timelines, abandoned and reclaimed mines with minimal documentation concurrently exist where little is known about locations, mine waste volumes, and reclamation status. Advanced mapping of these mining operations is helpful for producing basic mine land inventories and assessments of mine waste; identifying potential undeveloped resources and environmental health issues; and for developing proper management, restoration, and reclamation strategies. We studied known reclaimed and unreclaimed mine sites to develop a spatiotemporal mapping approach utilizing multiple techniques in remote sensing as a proof of concept. A mapping classification system was developed to identify uranium mine waste-rock piles, mine pits (with and without waste water), the total area of land disturbance due to mining, and to differentiate abandoned and reclaimed mine features using lidar (Light Detection and Ranging) analysis and multispectral temporal analysis. Visual interpretation of Landsat imagery and time-series analysis revealed the temporal life-cycle of mining, historical areas of disturbance, and reclamation; however, mine features below vegetation canopies are not always visible in satellite imagery. Lidar laser scanning penetrates the vegetation canopy to measure the topographic elevation and exposes anthropogenic modifications to the landscape. Lidar analysis (bare earth elevation surface, slope, topographic contours, topographic textures, and overland-flow hydrography) revealed mine features, and expansive areas of mining disturbance. The spatiotemporal mapping approach proved to be useful for identifying and characterizing known mine features, areas of disturbance, and reclamation status. Historical pre-mining topographic data were available at only 4 of the mines for comparison where the cut-and-fill tool estimated 21% less waste-rock volume, indicating that information about pre-mining terrain topography and/or subsurface mine waste geometry is needed to improve accuracies for quantifying buried mine waste volume at reclaimed mine sites.

Mount Hamiding Protected Forest is located in North Halmahera Regency, North Maluku Province, the Wallace zone has an important role in providing protection functions, life support systems and regulating water management, preventing floods, preventing seawater intrusion, and controlling soil fertility. The protected forest area in the Wallace Zone is globally renowned for its endemic characteristics of flora and fauna. The condition of the protected forest of Mount Hamiding HMPF is currently experiencing anthropogenic damage as a result of forest encroachment, illegal logging, shifting cultivation, grazing and poaching to meet social needs. Anthropogenic damage has been in the spotlight for decades and has become a global issue. This study aims to determine damage to protected forests, changes in land cover, and mitigation of protected forest areas. This research uses quantitative and descriptive qualitative methods. Determination of research locations by purposive sampling. Parameters measured in this study were damage to protected forests, changes in land cover and area mitigation strategies. To identify forest damage, snowball sampling was carried out, and land cover changes through land cover data processing were obtained from the Ministry of Environment and Forestry of the Republic of Indonesia. Then using Imagery 7 ETM+ and 8 OLI to calculate changes in forested land to non-forested from 2006 -2021, analysis of land cover change using supervised classification, developing a strategy based on identity verification of forest damage and analysis of land cover change. The results showed that damage to protected forests was caused by anthropogenic disturbances in the form of forest encroachment, shifting cultivation, illegal logging, grazing and hunting of wild animals. Changes in land cover experienced the greatest damage in 2006-2021 amounting to 1,796.54 ha (16.17%). Strategic efforts are carried out using forest engineering, namely the agroforestry system and social engineering through community empowerment, namely training and outreach.

Background: Complex bone defects are challenging to treat. Autografting is the gold standard for regenerating bone defects, however limitations include donor site morbidity and increased surgical complexity. Advancements in 3D bioprinting (3DBP) offer a promising alternative for viable bone grafts. Methods: Design of Experiments (DoE) was used to design 12 hydrogel bioinks of various Gelatin meth-acrylate/hydroxyapatite (GelMA/HA) concentrations. These bioinks were assessed for pipettability and equilibrium modulus. An optimal bioink was designed using the DoE data to produce the greatest stiffness while still being pipettable. Two bioinks, the DoE designed maximal stiff-ness and the experimentally defined maximal stiffness vs. a literature based control were then printed using a 3D bioprinter and assessed for print fidelity. The resulting hydrogels were combined with human bone-marrow-derived mesenchymal stromal cells (hMSCs) and evaluated for cell viability. Results: DoE ANOVA analysis indicated that the augmented 3 level factorial design model used was a good fit (p < 0.0001). Using the model, DoE correctly predicted that a composite hydrogel consisting of 12.3% GelMA, 15.7% HA, and 2% Gelatin would produce the maximum equilibrium modulus while still being pipettable. The hydrogel with the most optimal print fidelity was 10% GelMA, 2% HA, and 5% Gelatin. There were no significant differences in cell viability within hydrogels from day 2 to day 7 (p > 0.05). There was however a significantly lower cell viability in the gel composed of 12.3% GelMA, 15.7% HA, and 2% gelatin compared to the other gels with lower HA concentration (p < 0.05), showing that higher HA or print pressure may be cytotoxic within hydrogels. Conclusions: Extrusion-based 3DBP offers significant advantages for bone-tissue implants due to its high customizability. This study demonstrates it is possible to create printable bone-like grafts from GelMA and HA with increased HA levels, favorable mechanical properties (145kPa) and >80% cell viability.

We present a data-driven, in situ proximal multi-sensor digital soil mapping approach to develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe was engineered that contains seven sensors, each of a distinct modality, including sleeve friction, tip force, dielectric permittivity, electrical resistivity, soil imagery, acoustics, and visible and near-infrared spectroscopy. The DSC System integrates components the DSC Probe, DSC software, and deployment equipment to sense soil characteristics at a high vertical spatial resolution (mm scale) along in situ soil profiles up to a depth of 120 cm in about 60 sec. The DSC Probe in situ proximal data are harmonized into a data cube providing vertical high-density knowledge associated with physical-chemical-biological soil conditions. In contrast, conventional ex situ soil samples derived from soil cores, soil pits, or surface samples analyzed using laboratory and other methods are bound by substantially coarser spatial resolution and multiple compounding errors. Our objective was to investigate the effects of mismatched scale between high-resolution in situ proximal sensor data and coarser resolution ex situ soil laboratory measurements to develop soil prediction models. Our study was conducted in central California soil in almond orchards. We collected DSC sensor data and spatially co-located soil cores that were sliced into narrow layers for laboratory-based soil measurements. Partial Least Squares Regression (PLSR) cross-validation was used to compare results testing four data integration methods. Method A reduced the high-resolution sensor data to discrete values paired with layer-based soil laboratory measurements. Method B used stochastic distributions of sensor data paired with layer-based soil laboratory measurements. Method C allocated the same soil analytical data to each one of the high-resolution multi-sensor data within a soil layer. Method D linked the high-density multi-sensor soil data directly to crop responses (crop performance and behavior metrics) bypassing costly laboratory soil analysis. Overall, the soil models derived from Method C outperformed Methods A and B. Soil predictions derived using Method D were most cost-effective for directly assessing soil-crop relationships, making this method well-suited for industrial-scale precision agriculture applications.

The present work focuses on developing miniaturized, light weight electrochemical sensors for detection of chemical warfare agents (CWAs) like sarin and tabun simulants, i.e., diisopropyl fluorophosphate (DFP), and O,S-diethyl methyl phosphonothioate (O,S-DEMPT). Differential pulse voltammetry (DPV) was employed to examine the redox properties of capturing molecular probe CE2 with the nerve agent stimulants. Coupling of a portable potentiostat with the drone technology could allow on-situ and remote detection of analytes such CWAs to be realized, which can be crucially important to the national and global securities.

Coronavirus-infected diseases have posed great threats to human health. In past years, highly infectious coronavirus-induced diseases, including COVID-19, SARS, and MERS, have resulted in world-wide severe infections. Our literature annotations identified 110 chemical drugs and 26 antibodies effective against at least one human coronavirus infection in vitro or in vivo. Many of these drugs inhibit viral entry to cells and viral replication inside cells or modulate host immune responses. Many antimicrobial drugs, including antimalarial (e.g., chloroquine and mefloquine) and antifungal (e.g., terconazole and rapamycin) drugs as well as antibiotics (e.g., teicoplanin and azithromycin) were associated with anti-coronavirus activity. A few drugs, including remdesivir, chloroquine, favipiravir, and tocilizumab, have already been reported to be effective against SARS-CoV-2 infection in vitro or in vivo. After mapping our identified drugs to three ontologies ChEBI, NDF-RT, and DrON, many features such as roles and mechanisms of action (MoAs) of these drugs were identified and categorized. For example, out of 57 drugs with MoA annotations in NDF-RT, 47 have MoAs of different types of inhibitors and antagonists. A total of 29 anticoronaviral drugs are anticancer drugs with the antineoplastic role. Two clustering analyses, one based on ChEBI-based semantic similarity, the other based on drug chemical similarity, were performed to cluster 110 drugs to new categories. Moreover, differences in physicochemical properties among the drugs were found between those inhibiting viral entry and viral replication. A total of 163 host genes were identified as the known targets of 68 anti-coronavirus drugs, resulting in a network of 428 interactions among these drugs and targets. Chlorpromazine, dasatinib, and anisomycin are the hubs of the drug-target network with the highest number of connected target proteins. Many enriched pathways such as calcium signaling and neuroactive ligand-receptor interaction pathways were identified. These findings may be used to facilitate drug repurposing against COVID-19.

In cystic fibrosis (CF), pulmonary infection with Pseudomonas aeruginosa is a cause of increased morbidity and mortality, especially in patients for whom infection becomes chronic and there is reliance on long-term suppressive therapies. Current antimicrobials, though varied mechanistically and by mode of delivery, are inadequate not only due to eradication failure in many cases, but also because they do not halt the progression of lung function decline over time. One of the reasons for this failure is thought to be the biofilm mode of growth of P. aeruginosa, wherein self-secreted exopolysaccharides (EPSs) provide physical protection against antibiotics and an array of niches with resulting metabolic and phenotypic heterogeneity. Targeting the three EPSs secreted by P. aeruginosa (alginate, Psl and Pel) is currently under investigation as a way of disrupting the biofilm extracellular matrix to potentiate the action of antibiotics. In this review, we look at each EPS as a potential therapeutic target for combatting pulmonary infection with P. aeruginosa in CF, with a particular focus on the current evidence for these emerging therapies and barriers to bringing these therapies into clinic.

Marek’s Disease (MD) has a significant impact on both the global poultry economy and animal welfare. The disease pathology can include neurological damage and tumour formation. Sexual dimorphism in immunity and known higher susceptibility of females to MD makes the chicken Z chromosome (GGZ) a particularly attractive target to study the chicken MD response. Previously, we used a Hy-Line F6 population from a full-sib advanced intercross line to map MD QTL regions (QTLRs) on all chicken autosomes. Here we mapped MD QTLRs on GGZ in the previously utilized F6 population with individual genotypes and phenotypes, and in eight elite commercial egg production lines with daughter-tested sires and selective DNA pooling (SDP). Four MD QTLRs were found from each analysis. Some of these QTLRs overlap regions from previous reports. All QTLRs were tested by indiviuals from the same eight lines used in the SDP and genotyped with markers located within and around the QTLRs. All QTLRs were confirmed. The results exemplify the complexity of MD resistance in chickens and the complex distribution of P-values and LD pattern and their effect on localization of the causative elements. Considering the fragments and interdigitated LD blocks while using LD to aid localization of causative elements, one must look beyond the insignificant markers, for possible distant markers and blocks in high LD with the significant block. The QTLRs found here may explain at least part of the gender differences in MD tolerance, and provide targets for mitigating the effects of MD.

Background: A large majority of primary school pupils fail to achieve 30-minutes in-school moderate-to-vigorous physical activity (MVPA). The aim of this study was to investigate MVPA accumulation and subject frequency during academic lesson segments and the broader segmented school day. Methods: 122 children (42.6% boys; 9.9±0.3yrs) from six primary schools in North East England, wore uniaxial accelerometers for eight consecutive days. Subject frequency was assessed by teacher diaries. Multilevel models (children nested within schools) examined significant predictors of MVPA across each school-day segment (lesson one, break, lesson two, lunch, lesson three). Results: Pupils averaged 18.33±8.34 minutes of in-school MVPA and 90.2% failed to achieve the in-school 30-minute MVPA threshold. Across all school-day segments, MVPA accumulation was typically influenced at the individual level. Lesson one and two - dominated by Math and English - were less active than lesson three. Break and lunch were the most active segments. Conclusion: This study breaks new ground, revealing MVPA accumulation and subject frequency varies greatly during different academic lessons. Morning lessons were dominated by the inactive delivery of Math and English, whereas afternoon lessons involved a greater array of subject delivery that resulted in marginally higher levels of MVPA.

Ridesharing effectively tackles urban mobility challenges by providing a service comparable to private vehicles while minimising resource usage. Our research primarily concentrates on dynamic ridesharing, which conventionally involves connecting drivers with passengers in need of transportation. The process of one-to-one matching presents a complex challenge, particularly when addressing it on a large scale, as the substantial number of potential matches make the attainment of a global optimum a challenging endeavour. This paper aims to address the absence of an optimal approach for dynamic ridesharing by refraining from conventional heuristic-based methods, commonly used to achieve timely solutions in large-scale ride-matching. We propose a novel approach that provides snapshot optimal solutions for various forms of one-to-one matching, ensuring they are generated within an acceptable timeframe for service providers. Additionally, we introduce and solve a new variant where the system itself provides the vehicles. The efficacy of our methodology is substantiated through experiments carried out with real-world data extracted from the openly available New York City taxicab dataset.

Background: Epithelial-mesenchymal transition (EMT) is a biological process where epithelial cells lose their adhesive properties and gain invasive, metastatic, and mesenchymal properties. Maintaining the balance between epithelial and mesenchymal stage is essential for tissue homeo-stasis. Many of the genes promoting mesenchymal transformation has been identified; however, our understanding of the genes responsible for maintaining the epithelial phenotype is limited. Our objective was to identify genes responsible for maintaining the epithelial phenotype and in-hibiting EMT. Methods: RNA seq was performed using an vitro model of EMT. CTGF expres-sion was determined by qPCR and Western blot analysis. Knockout of CTGF was done using the CTGF sgRNA CRISPR/CAS9. Tumorigenic potential was determined using NCG mice. Results: Knocked-out of CTGF in epithelial ovarian cancer cells leads to the acquisition of functional characteristics associated with the mesenchymal phenotype such as Anoikis resistance, cytoskel-eton remodeling, increased cell stiffness, and acquisition of invasion and tumorigenic capacity. Conclusions: We identified CTGF is an important regulator of the epithelial phenotype, and its loss is associated with early cellular modifications required for EMT. We describe a novel role for CTGF, regulating cytoskeleton and the extracellular matrix interactions necessary for conserva-tion of epithelial structure and function. These findings provide a new window to understand the early stages on mesenchymal transformation

Conductive hearing losses are typically present in disorders of the external/middle ear. However, there is a rare group of inner ear conditions called third windows that can also generate a conductive hearing loss. This is due to an abnormal connection between the middle and the inner ear or between the inner ear and the cranial cavity. X-linked gusher disorder is an extremely rare congenital inner ear dysplastic syndrome with such an abnormal connection due to a characteristic incomplete cochlear partition type 3 and an incomplete internal auditory meatus fundus. The disorder is inherited in an X-linked fashion due to the mutation of the POU3F4 gene. We present 2 siblings diagnosed with the condition and their long term follow ups. They both presented with audiovestibular symptoms and showed progressive mixed losses and bilateral vestibular weakness. They were treated with cochlear implant, digital amplification and with vestibular rehabilitation. Significant others around them were involved in their journey with the medical team and in both, a very favourable outcome was achieved. This is the first time that we are reporting evolving audiovestibular function with vestibular quantification in X-linked gusher disorder and emphasize on the multidisciplinary holistic approach to manage these children effectively.

Oyster mushroom (Pleurotus ostreatus), nopal (Opuntia ficus-indica) and amaranth (Amaranthus spp.) are pre-hispanic foods widely consumed in Mexico. However, there are no standard products developed with these ingredients as functional cookies. This study evaluated the impact of partial replacement (50%) of whole-wheat flour (WWF) with three formulations of P. ostreatus, nopal and amaranth flours (POF, NF and AF, respectively) in the nutritional/antioxidant properties of fortified cookies. The proportion of flours´ ingredients (WWF:AF:NF:POF) were 100% WWF (traditional cookies), 50:35:10:5 (formulation 1), 50:30:15:5 (formulation 2) and 50:40:5:5 (formulation 3). Proximal composition, phenolic/flavonoid contents, and ABTS+ scavenging activity were determined in flours and cookies. POF, NF and AF possess a high nutritional value comprising polyphenols/flavonoids and a significant antioxidant potential. Total protein, ashes and flavonoids were higher in fortified cookies than controls. Cookies prepared with Formulation 2 -highest nopal level- contained 5.29% of dietary fiber and 5-times higher polyphenol content than control cookies. The ABTS+ scavenging ability was similar in the three enriched cookies (87.73-89.58%) but higher than traditional cookies (75.60%). Applicability of POF/NF/AF for replacing up to 50% of WWF in production of functional cookies was demonstrated. The research promotes renewable local bioresouces for a sustainable agri-food chain, especially edible mushrooms.

Smoking during pregnancy remains one of the most significant risk factors for poor birth outcomes. The Loma Linda University Health Comprehensive Tobacco Treatment Program (CTTP) is the largest maternal tobacco cessation program in San Bernardino County – the largest county in the contiguous US. CTTP is an eight week, incentivized, behavioral intervention for tobacco cessation for pregnant smokers. As part of program evaluation, we used a retrospective cohort design to assess smoking abstinence and to identify predictors of relapse/smoking after enrollment. Among CTTP cohort enrollees (n=233) from 2012-2013 we found: 1) a 28.4% 8 week point prevalence abstinence (PPA), and at a median of 9 months of follow-up after the PPA, 81.6% continued to indicate tobacco cessation, and 2) a high rate of relapse or loss to follow-up (56%). Our modeling of relapse/smoking after enrollment indicated that this was higher in young mothers, non-Hispanic mothers (White, Black), first/third trimester mothers, and rural mothers. The evaluation identified efficacy of the behavioral model at 8 weeks, but that relapse/smoking was occurring in disparity populations. Formative research is needed to expand the programmatic outreach and enrollment of mothers wanting to quit smoking.

For decades since the central dogma, cancer biology research has been focusing on the involvement of genes encoding proteins. It has been not until more recent times that a new molecular class has been discovered, named non-coding RNA (ncRNA), which has been shown to play crucial roles in shaping the activity of cells. An extraordinary number of studies into shown that ncRNAs represent an extensive and prevalent group of RNAs, including both oncogenic or tumor suppressive molecules. Henceforth, various clinical trials involving ncRNAs as extra ordinary biomarkers or therapies have started to emerge. In this review, we will focus on the prognostic and diagnostic role of ncRNAs for breast cancer.

This paper presents the theory, design, and application of a dual-branch series-diode analog pre-distortion (APD) linearizer to improve the linearity and efficiency of a K-band high power amplifier (HPA). A first-of-its-kind, frequency-dependent large-signal APD model is presented. This model is used to evaluate different phase relationships between the linear and nonlinear branches, suggesting independent gain, and phase expansion characteristics with this topology. This model is used to assess the impact of diode resistance, capacitance, and ideality factor on the APD characteristics. This feature is showcased with two similar GaAs diodes to find the best fit for the considered HPA. The selected diode is characterized and modeled between 1-26.5 GHz. A comprehensive APD design and simulation workflow is reported. Before fabrication, the simulated APD is evaluated with the measured HPA to verify linearity improvements. The APD prototype achieves a large signal bandwidth of 6 GHz with 3 dB gain expansion and 8∘ phase rotation. This linearizer is demonstrated with a 17-21 GHz GaN HPA with 41 dBm output power and 35 % efficiency. Using a wideband 750 MHz signal, this APD improves the noise power ratio (NPR) by 6.5-8.2 dB over the whole HPA bandwidth. Next, the HPA output power is swept to compare APD vs. power back off for the same NPR. APD improves the HPA output power by 1-2 W and efficiency by approximately 5-9 % at 19 GHz. This efficiency improvement decreases by only 1-2 % when including the APD post-amplifier consumption, thus suggesting overall efficiency and output power improvements with APD at K-band frequencies.

Mucus plugging of the respiratory tract occurs in airway diseases, including asthma, chronic obstructive pulmonary disease and cystic fibrosis. It can cause blockage of airways, leading to breathlessness and lung failure. Here, we demonstrate the effect of BromAc® in dissolving mucus plugs in an novel ex-vivo ovine obstructive lung model using a ventilatory setup. Mucus simulant was filled into the trachea of freshly slaughtered ovine lungs and ventilated via an endotracheal tube (ETT) using Continuous Mandatory Ventilation. Predetermined single or repeated doses of Bromelain, Acetylcysteine (Ac), BromAc® and saline control were administered via an Aerogen® vibrating nebuliser and ventilated for 30 or 60 minutes. Ventilatory recording of resistance, compliance, tidal volume was conducted and rheology pre and post treatment were measured. A significant decline in airway resistance (p&lt;0.0001) compared to saline control was observed when treated with Bromelain, Ac and BromAc®, with the latter showing a stronger mucolytic effect than single agents. The decline in resistance was also effective in shorter timepoint (p&lt;0.05) at lower doses of the drugs. Changes in compliance, peak pressure and tidal volume was not observed post-administration of the drugs. Rheology measurements revealed that BromAc®™ significantly reduced the viscosity of the mucin at the end of 30-minute and 60-minute time points (p&lt;0.001) compared to the saline control. BromAc® showed complete dissolution of the respiratory mucus simulant and improved ventilatory airflow parameters in the ex-vivo ovine model.

Zika virus (ZIKV) co-circulates with several closely related flaviviruses which exhibit similar clinical manifestations thus, clinicians rely on molecular and serological techniques for diagnosis. Cross-reactivity of patient specimens to flaviviruses is a significant impediment to serological diagnosis in areas where multiple flaviviruses co-circulate. Furthermore, patient exposure history to any of these viruses could complicate serological response patterns which could result in over and/or underdiagnosis of ZIKV infection. Three strains of ZIKV, dengue serotypes 1-4, West Nile virus, Japanese Encephalitis virus, and Yellow Fever virus were evaluated for neutralizing properties against 3 monoclonal antibodies, 4 ZIKV-naïve patients with flavivirus exposure history, 5 patients with verified ZIKV exposure and unknown flavivirus exposure history, and 5 flavivirus-naive patients with ZIKV-only exposure. Patients naïve for ZIKV exposure effectively neutralized multiple strains of ZIKV. Overall, the prototype ZIKV isolate MR-766 did not behave like the other ZIKV isolated used in this study. MR-766 was neutralized more completely by polyclonal patient serum than recent ZIKV isolates. MR-766 was neutralized better than dengue virus in ZIKV-naïve patients with prior dengue exposure. MR-766 was neutralized significantly less than recent ZIKV isolates when treated with monoclonal antibodies. The data herein show that without RT-PCR, serological diagnosis may not be possible in areas where multiple flaviviruses are endemic.

Fusarium Head Blight (FHB) is a destructive disease affecting the grain yield and quality of wheat, barley, rye and triticale. Developing varieties with genetic resistance is integral to successfully managing FHB. However, significant knowledge gap exists in the genetic diversity present in triticale for FHB resistance. This information is critical for breeding new varieties of triticale as its production continues to increase. In the present study, a set of 298 winter triticale accessions from a worldwide collection were screened for their type-2 FHB resistance in an artificially inoculated misted nursery with high levels of inoculum density. Most of the triticale accessions were susceptible to FHB, and only 8% of accessions showed resistance in the field nursery screening. The resistant accessions identified in the nursery screening were selected and further screened for three years in greenhouse conditions. Seven accessions were found to show robust FHB resistance over the three years of greenhouse testing. Thirteen accessions showed significantly lower levels of Deoxynivalenol accumulation when compared to the susceptible triticale control. The accessions identified in the study will be useful in triticale and wheat breeding programs for enhancing FHB resistance and reducing DON accumulation.

This review focuses on developments that quantify grain quality with a range of spectral sensors in an on-farm setting. If the application of sensor technologies were expanded and adopted on-farm, growers could identify the impact and manage the harvesting operation to meet a range of quality targets and provide an economic advantage to the farming enterprise.

Fire detection from satellite sensors relies on an accurate estimation of the unperturbed state of a target pixel, from which an anomaly can be isolated. Methods for estimating the radiation budget of a pixel without fire depend upon training data derived from the location's recent history of brightness temperature variation over the diurnal cycle, which can be vulnerable to cloud contamination and the effects of weather. This study proposes a new method that utilises the common solar budget found at a given latitude in conjunction with an area's local solar time to aggregate a broad-area training dataset, which can be used to model the expected diurnal temperature cycle of a location. This training data is then used in a temperature fitting process with the measured brightness temperatures in a pixel, and compared to pixel-derived training data and contextual methods of background temperature determination. Results of this study show similar accuracy between clear-sky medium wave infrared upwelling radiation and the diurnal temperature cycle estimation compared to previous methods, with demonstrable improvements in processing time and training data availability. This method can be used in conjunction with brightness temperature thresholds to provide a baseline for upwelling radiation, from which positive thermal anomalies such as fire can be isolated.

This investigation pioneers an examination of the scarcely explored terrain of social diversity in medical education, assessing the complex impacts of socioeconomic status (SES), prior working experiences, and completed apprenticeships on a spectrum of psychological and academic facets among first-year medical students (n = 336) in an urban university setting. By utilizing a systematic and detailed approach, the study illuminates prior anatomical knowledge and various psycholog-ical constructs, marking a significant stride into a domain where knowledge remains profoundly limited. Analyses indicated that SES significantly affects financial anxiety (F(4, 331) = 17.391, p < .001) and academic behavioral confidence (F(4, 331) = 4.323, p = 0.002). Students with prior working experience reported higher self-perceived clinical experience but lower A-level grades (t(279.459) = -6.690, p < .001), competence in natural sciences (t(321.045) = -3.178, p = 0.002), and online competence (t(319.429) = -2.026, p = 0.044). Those who completed an apprenticeship showed higher resilience, academic confidence, self-efficacy, and greater concerns about balancing studies and work (t values ranging from 2.020 to 3.158, p < 0.05). Correlation analysis revealed a positive relationship between resilience (RQS) and coping with academic stress (CAS) (r = 0.632, p < .001), as well as between resilience and academic behavioral confidence (ABC) (r = 0.608, p < .001). Negative correlations were observed between resilience, coping with academic stress, academic confidence, and cognitive test anxiety (CTA) (r values from -0.235 to -0.404, p < .001). The findings emphasize the need for tailored support for students from diverse SES backgrounds and with varying expe-riences. The study highlights the value of a comprehensive approach in medical education, con-sidering the diverse backgrounds and experiences of students. Future research should explore the long-term impact of these factors on professional competencies and patient care, leveraging the diversity of the student body for a holistic educational experience.

ATLID (ATmospheric LIDar) is the atmospheric backscatter LIDAR (Light Detection and Ranging) on board of the EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) mission, the sixth Earth Explorer Mission of the ESA (European Space Agency) Living Planet Programme [1-5]. ATLID’s purpose is to provide vertical profiles of optically thin cloud and aerosol layers, as well as the altitude of cloud boundaries [6-10]. In order to achieve this objective ATLID emits short duration laser pulses in the UV, at a repetition rate of 51 Hz, while pointing in a near nadir direction along track of the satellite trajectory. The atmospheric backscatter signal is then collected by its 620 mm aperture telescope, filtered through the optics of the instrument focal plane assembly, in order to separate and measure the atmospheric Mie and Rayleigh scattering signals. With the completion of the full instrument assembly in 2019, ATLID has been subjected to an ambient performance test campaign, followed by a successful environmental qualification test campaign, including performance calibration and characterization in thermal vacuum conditions. In this paper the design and operational principle of ATLID is recalled and the major performance test results are presented, addressing the main key receiver and emitter characteristics. Finally, the estimated instrument, in-orbit, flight predictions are presented; these indicate compliance of the ALTID instrument performance against its specification and that it will meet its mission science objectives for the EarthCARE mission, to be launched in 2023.

Probiotics are increasingly used by consumers and practitioners to reduce gastrointestinal (GI) distress and improve gut function. Here, we sought to determine whether addition of supplemental bacteriophages (PreforPro) could enhance the effects of a common probiotic, Bifidobacterium animalis subsp. lactis (B. lactis) on GI health. We conducted a 4-week, randomized, parallel-arm, double-blind, placebo-controlled trial where primary outcomes included self-assessments of GI health, a daily stool log, and 16s rRNA analysis of gut microbial populations. We observed within group improvements in GI inflammation (p=0.01) and a trending improvement in colon pain (p=0.08) in individuals consuming B. lactis with PreforPro, but not in the group consuming only the probiotic. There was also a larger increase in Lactobacillus and short chain fatty acid-producing microbial taxa detected in stool of participants taking PreforPro with B. lactis compared to the probiotic alone. Overall, these results suggest the addition of PreforPro as a combination therapy may alter gut ecology to extend the GI benefits of consuming B. lactis or other probiotics.

There is significant lack of information on the presence of plant pathogens in aquifer, increasingly used for irrigation during last decades and considered mostly free of them. In this work, we report the presence of bacteria from the Pseudomonas syringae complex (referred as PsyC) including phytopathogenic bacteria, in groundwater of Avignon, France. Their concentration was variable and inversely correlated with water electrical conductivity. Their mean abundance were hundred times lower than in the river Durance, connected with the aquifer but surprisingly, their genetic structure were more homogeneous. Moreover, most strains (97 %) from groundwater were tested as potentially pathogenic on plants, when in the river they were only 71 %. Determinants of this low diversity and high aggressiveness remain to be identified. We conclude that aquifers must be considered potential plant pathogenic reservoirs even if more surveys are needed to understand the real impact on crops during irrigation. These results could be included in prediction models and new approaches to disease forecasting and surveillance and could lead to adaptation of agricultural practices.

Despite the recent launch of Tolvaptan, the search for safer polycystic kidney disease (PKD) drugs continues. Ciclopirox, as the free acid (CPX) and its olamine salt (CPX-O) , are contained in number of commercially available topical antifungal agents. CPX is reported in the literature to possess anticancer activity in number of solid tumor cancers and hematological malignancy by several proposed mechanisms of action including chelation of iron and inhibition of iron dependent enzymes. Here, we show that CPX-O inhibited in vitro cystogenesis of primary human cyst epithelial cells cultured in 3D collagen matrix. To determine if CPX-O inhibits PKD progression, we treated PKD mice with a low dose of 10 mg/kg CPX-O by daily intraperitoneal injections from day 21 to day 49 post- partum. CPX-O reduced the kidney to body weight ratio of the PKD mice. This was associated with decreased cell proliferation decrease cystic area and improved renal function. We found that ferritin levels were significantly elevated in cystic kidneys of PKD mice, and that CPX-O treatment reduced renal ferritin levels and increased ferritinophagy marker, NCOA4. Our data suggest that CPX-O dose dependently induces ferritin degradation via ferritinophagy which is associated with decreased cyst growth and disease progression in PKD mice. Most importantly these data indicate that CPX-O, a drug used to treat skin infections and currently in clinical trials for cancer, has the potential to treat ADPKD.

(1) Background: Some evidence suggests that cannabidiol (CBD) has potential to help alleviate HIV symptoms due to its antioxidant and anti-inflammatory properties. Here we examined acute CBD effects on various behaviors and the endocannabinoid system in HIV Tat transgenic mice. (2) Methods: Tat transgenic mice (female/male) were injected with CBD (3,10,30 mg/kg) and assessed for antinociception, activity, coordination, anxiety, and recognition memory. Brains were taken to quantify endocannabinoids and related lipids. Additionally, CBD and metabolite 7-hydroxy-CBD were quantified in the plasma and cortex. (3) Results: Tat decreased striatal-related nociception and locomotion, with some sex-dependent effects on coordination. CBD had no effect on nociception and coordination, but increased locomotor activity. For anxiety, differential CBD effects were noted for sex, with decreasing anxiety-like behavior in males only. In the striatum and spinal cord, male sex was associated with lower 2-arachidonoylglycerol and with elevated concentrations of its proinflammatory metabolite arachidonic acid. CBD metabolism was altered by sex and Tat. (4) Conclusion: Findings indicate that acute CBD effects are not altered by HIV Tat, and CBD has minimal effects on behavior and the endocannabinoid system. Interestingly, sex-dependent alterations were noted for endocannabinoids and related lipids, which may be of relevance in view of potential CBD-based treatment options for people living with HIV.

In vitro glucose uptake in yeast cell facilitated by Abelmoschus esculentus L. (okra seed) for management of type 2 diabetes was studied. Plant material was collected, identified, processed, and stored for further use. 80% methanol was employed for extraction and sonicated to release antidiabetic-bioactive component in solution and was filtered, concentrated, freeze-dried, and fractionated using standard techniques. Glucose uptake at an initial concentration of 5mM/L and 10mM/L by the crude extract was consistent to that of the known standard drug while at 25mM/L glucose concentration was equivalent with the crude extract. Also, at 0.625 mg/mL the linear equations, and R2 demonstrations that the crude extract was higher in dose predictability than the standard drug as presented by the equation; y = 35.754x - 57.822, and R² = 0.9502 (95%). The extract-fractions were employed to evaluate the ability of yeast cell line culture to take up glucose from the system through DPPH, FRAP, lipid peroxidation and anti-diabetes effect of extract-fraction assays. Extract-fractions were found to poses antioxidant activity high enough to inhibit stress-related diseases. The extract fractions were active as drug candidates both at low and high concentrations and were better compared with the standard drug and standard antioxidant was comparable. The high bioactive extract fractions require encapsulation with a nanoparticle as a drug candidate for type 2 diabetes patients. And an animal trial of the drug candidate may be necessary to monitor the in vivo performances of the extract fractions and subsequent human volunteered trial.

The requirement for developing tools capable of detecting and monitoring heavy metals (HMs) has recently taken on more significance due to worries about their toxic effect on human health and aquatic habitats. In this study, a simple electrochemical sensing carbon paste electrode (CPE) based on composite of Zinc/Iron layered double hydroxide (LDH) and polyaniline (PANI) was developed for the determination of lead ions in aquatic solutions. For this purpose, Zn-Fe LDH/PANI was prepared and characterized by Fourier transform infrared (FTIR), X ray diffraction (XRD), and scanning electron microscopy (SEM). Modified carbon electrode based Zn-Fe LDH/PANI was electrochemically characterized compared with unmodified electrode in FCN as a redox probe using cyclic voltammetry (CV). Thus, Zn-Fe LDH/PANI was utilized as sensing material for the electrochemical determination of lead ions using differential pulse voltammetry (DPV). Zn-Fe LDH/PANI/CPE show limits of detection (LOD) and quantification (LOQ) of 167.8 nM and 559.4 nM, respectively. Zn/Mg/Fe LDH was prepared using co-precipitation method and characterized by XRD, FTIR, SEM and BET, used for removal of Pb+2 ions. Removal process was investigated at different conditions as pH, metal ion concentrations, starting adsorbent dose at first and contact time. Zn/Mg/Fe LDH was evaluated as an effective adsorbent material for lead ions elimination in aquatic solutions, with capacity of adsorption 700 mg/g. The elimination of lead ions on Zn/Mg/Fe LDH fitted the pseudo first-order kinetics model and the isotherm was matched with Langmuir model. Studies revealed that the ideal removal conditions were pH = 5.0, an adsorbent mass of 0.05 g, and 20 ml of 50 ppm metal ion concentration at 60 min. The Zn-Fe LDH/PANI composite also showed potential anti-cancer properties against lung cancer cells (A549) while maintaining safety for normal lung fibroblast cells (WI-38). Collectively, advancements in electrochemical sensors offer promising solutions for lead ion detection, with wide-reaching applications in wastewater treatment and cytotoxicity assessment. These innovations have the potential to enhance environmental monitoring and public health safety.

Studies have shown that vehicle trajectory data are effective for calibrating microsimulation mod-els. Light Detection and Ranging (LiDAR) technology offers high-resolution 3-D data, allowing for detailed mapping of the surrounding environment, including road geometry, roadside infrastruc-tures, and moving objects such as vehicles, cyclists, and pedestrians. This research presents a comprehensive framework for integrating LiDAR sensor data into simulation models and accu-rately calibrating for proactive safety analysis. Vehicle trajectory data were extracted from LiDAR point cloud collected at six urban signalized intersections in Lubbock, Texas in USA. Each study intersection was modelled with PTV VISSIM and calibrated to replicate the observed field scenarios. The Directed Brute Force method was used to calibrate two car-following and two lane-change parameters of Wiedemann 1999 model in VISSIM, resulting in an average accuracy of 92.7%. Rear-end conflicts extracted from the calibrated models combined with a ten-year historical crash dataset were fitted into a Negative Binomial (NB) model to estimate the model's parameters. In all the six intersections, rear-end conflict count is a statistically significant predictor (p-value < 0.05) of observed rear-end crash frequency. The outcome of this study provides a framework for the com-bined use of LiDAR-based vehicle trajectory data, microsimulation and surrogate safety assessment tools to transportation professionals for proactive safety evaluation.

Acinetobacter baumannii is a nosocomial pathogen capable of causing serious infections associated with high rates of morbidity and mortality. Due to its antimicrobial drug resistance profile, A. baumannii is categorized as an urgent priority pathogen by the Centers for Disease Control and Prevention in the United States and priority group 1 critical microorganism by the World Health Organization. Understanding how A. baumannii adapts to different host environments may provide critical insights into strategically targeting this pathogen with novel antimicrobial and biological therapeutics. Exposure to human fluids was previously shown to alter the gene expression profile of a highly drug susceptible A. baumannii strain A118 leading to persistence and survival of this pathogen. Herein, we explore the impact of human pleural fluid (HPF) and human serum albumin (HSA) on the gene expression profile of a highly multi-drug resistant strain of A. baumannii AB5075. Differential expression was observed for ~30 genes, whose products are involved in quorum sensing, quorum quenching, iron acquisition, fatty acid metabolism, biofilm formation, secretion systems and type IV pilus formation. Phenotypic and further transcriptomic analysis using quantitative RT-PCR confirmed RNA-seq data and pointed out a distinctive role of HSA as the molecule involved in A. baumannii response.

‘Inner mitochondrial membrane peptidase 2 like’ (IMMP2L) is a nuclear encoded mitochondrial peptidase that has been conserved through evolutionary history as has its target enzyme ‘mitochondrial glycerol phosphate dehydrogenase 2’ (GPD2). IMMP2L is known to cleave the mitochondrial transit peptide from GPD2 and another nuclear encoded mitochondrial respiratory related protein cytochrome C1 (CYC1). However, it is not known whether IMMP2L peptidase activates or alters the activity or respiratory related functions of GPD2 or CYC1. Previous investigations found compelling evidence of behavioural change in the Immp2lKD-/- KO mouse and in this study EchoMRI analysis found that many organs of the Immp2lKD-/- KO mouse were smaller and that the KO mouse had significantly less lean mass and overall body weight compared with wildtype littermates (p&lt;0.05). Moreover, all of the organs analysed from the Immp2lKD-/- KO had lower relative levels of mitochondrial reactive oxygen species (mitoROS). The kidneys of the Immp2lKD-/- KO mouse displayed the greatest decrease in mitoROS levels that were over 50% less compared with wildtype litter mates. Mitochondrial respiration was also lower in the kidney of the Immp2lKD-/- KO mouse compared with other tissues when using succinate as the respiratory substrate, whereas respiration was similar to wildtype when glutamate was used as substrate. When glycerol-3-phosphate (G3P) was used as the substrate for Gpd2 we observed ~20% and ~7% respective decreases in respiration in female and male Immp2lKD-/- KO mice over time. Together these findings suggest that the respiratory related functions of mGpd2 and Cyc1 have been compromised to different degrees in different tissues in the Immp2lKD-/- KO mouse. Structural analyses using AlphaFold2-Multimer further predicted that the interaction between Cyc1 and mitochondrial encoded cytochrome b (Cyb) in Complex III had been altered as had the homodimeric structure of the mGpd2 enzyme within the inner mitochondrial membrane of the Immp2lKD-/- KO mouse. mGpd2 functions as an integral component of the glycerol phosphate shuttle (GPS) which positively regulates both mitochondrial respiration and glycolysis. Interestingly, we found that nonmitochondrial respiration (NMR) was also dramatically lowered in the Immp2lKD-/- KO mouse. Primary mouse embryonic fibroblast (MEF) cell lines derived from the Immp2lKD-/- KO mouse displayed a ~27% decrease in total respiration comprised of a ~50% decrease in NMR and a ~12% decrease in total mitochondrial respiration where the latter was consistent with the decreases in substrate specific mitochondrial respiration reported here. This study is the first to report the role of Immp2l in enhancing Gpd2 structure and function, mitochondrial respiration, nonmitochondrial respiration, organ size and homeostasis.

myfood24 is a comprehensive self-completed online 24-hour dietary recall tool currently used for nutritional assessments in epidemiological research. However, its clinical application has been unexplored. This mixed methods prospective observational study explores the acceptability and usability of myfood24 in a clinical population, women with gestational diabetes (GDM). Women were recruited at their first diabetes antenatal clinic appointment. To assess acceptability and usability, they were asked to complete five 24-hour dietary recalls using myfood24 over two weeks and a user experience questionnaire; with a subset invited to participate in a one-to-one semi-structured interview. Of the 199 participants, mean maternal age was 33 years, mean booking BMI 29.7kg/m2, 36% primiparous, 57% White, 33% Asian. Of these 121 (61%) completed myfood24 at least once and 73 (37%) completed the user questionnaire; 15 were interviewed. Usability of myfood24 was measured using the System Usability Scale (SUS) and found to be good (mean 70.9, 95%CI 67.1, 74.6). Interviews identified several areas for improvement, including optimising its use for mobile devices. myfood24 appears to be acceptable and have potential to support self-management and behaviour change for women with GDM but requires adaptation to record blood glucose results alongside real-time tracking of diet.

Importance: The rapidly expanding 2019 novel coronavirus pandemic (COVID-19, caused by the SARS-CoV-2 virus) has challenged the medical community to an unprecedented degree. Physicians and healthcare workers are at added risk of exposure and infection during the course of the patient care. Due to the rapid spread of this disease through respiratory droplets, healthcare providers such as otolaryngologists-head & neck surgeons who come in close contact with the upper aerodigestive tract during diagnostic and therapeutic procedures are particularly at risk. Here we present a set of safety recommendations based on our review of literature and communications with physicians with first-hand knowledge of safety procedures during the 2019 COVID-19 pandemic.Observations: A high number of healthcare providers were infected during the first phase of the pandemic in Wuhan province. Subsequently, by adopting strict safety precautions, other regions were able to achieve high levels of safety for healthcare providers without jeopardizing the care of patients. We reviewed the most common procedures related to the examination and treatment of upper aerodigestive tract diseases. Each category was reviewed based on the potential risk imposed to healthcare workers. Specific recommendations were made, based on the literature, when available, or consensus best practices. Specific safety recommendations were made for performing tracheostomy in COVID-19 patients. Conclusions and Relevance: Preserving highly skilled healthcare work force is a top priority for any community and healthcare system. Based on the experience of healthcare systems in Asia and Europe, by following strict safety guidelines, the risk of exposure and infection of healthcare providers could be significantly reduced, while providing high levels of care. The provided recommendations could be used as broad guidance for all healthcare workers who are involved with the care of COVID-19 patients.

Effectively preventing and controlling zoonotic diseases requires a One Health approach that involves collaboration across sectors responsible for human health, animal health (both domestic and wildlife), and the environment, as well as other partners. Here we describe the Generalizable One Health Framework (GOHF), a five-step framework that provides structure for using a One Health approach in zoonotic disease programs being implemented at the local, sub-national, national, regional, or international level. Part of the framework is a toolkit that compiles existing resources and presents them following a stepwise schematic, allowing users to identify relevant resources as they are required. Coupled with recommendations for implementing a One Health approach for zoonotic disease prevention and control in technical domains including laboratory, surveillance, preparedness and response, this framework can mobilize One Health and thereby enhance and guide capacity building to combat zoonotic disease threats at the human-animal-environment interface.

Abstract: The genus Acaryochloris is unique among phototrophic organisms due to the dominance of chlorophyll d in its photosynthetic reaction centres and light-harvesting proteins. This allows Acaryochloris to capture light energy for photosynthesis over an extended spectrum of up to ~760 nm in the near infra-red (NIR) spectrum. Acaryochloris sp. has been reported in a variety of ecological niches, ranging from polar to tropical shallow aquatic sites. Here, we report a new Acarychloris strain isolated from an NIR-enriched stratified microbial layer 4-6 mm under the surface of stromatolite mats located in the Hamelin Pool of Shark Bay, Western Australia. Pigment analysis, by traditional spectrometry/fluorometry, flow cytometry and spectral confocal microscopy identify unique patterns in pigment distribution that likely reflect niche adaption. For example, unlike the original A. marina species (type strain MBIC11017), this new strain, Acarychloris LARK001, shows little change in the chlorophyll d/a ratio in response to changes in light wavelength, displays a different Fv/Fm response and lacks detectable levels of phycocyanin. Indeed, 16S rRNA analysis supports the identity of the A. marina LARK001 strain as distinct from the A. marina HICR111A strain first isolated from Heron Island, previously found on the Great Barrier Reef, under coral rubble on the reef flat. Taken together, A. marina LARK001 is a new cyanobacterial strain adapted to the stromatolite matts in Shark Bay.

The cassava whitefly, Bemisia tabaci, causes direct damage to cassava in the tropics by feeding on the phloem of leaves, inducing leaf chlorosis and abscission which can result in considerable yield loss of up to about 50% on susceptible varieties. The pest is also known to impart its indirect damage through sooty mold formation. Most of the improved cassava varieties in Uganda were developed for CMD resistance and CBSD tolerance and little is known about their reaction to whitefly infestation. A study was conducted to evaluate the reaction of 24 improved cassava varieties which were sourced from 5 different countries in the region (Uganda, Kenya, Tanzania, Malawi, and Mozambique) to whitefly infestation. These varieties were evaluated in three agro-ecological zones of Uganda, namely; North-Western Savannah Grassland, Lake Victoria Crescent and the Kyoga Plains in the second rains of 2016. Monthly data were taken on adult and nymph counts, whitefly and sooty mold damage, CMD and CBSD severities from 2 up-to 9 Months after planting (MAP). Results show that the whitefly population was highly significantly (P

We aimed to explore university students’ perceptions and experiences of SARS-CoV-2 mass asymptomatic testing, social distancing and self-isolation during the COVID-19 pandemic. This qualitative study comprised of four rapid online focus groups conducted at a higher education institution in England during high alert (tier 2) national COVID-19 restrictions. Data were analysed thematically. Participants were purposively sampled university students (n = 25) representing a range of gender, age, living circumstances (on/off campus) and SARS-CoV-2 testing/self-isolation experiences. Six themes with 16 sub-themes emerged from the analysis of the qualitative data: ‘Term-time Experiences’, ‘Risk Perception and Worry’, ‘Engagement in Protective Behaviours’, ‘Openness to Testing’, ‘Barriers to Testing’ and ‘General Wellbeing’. Students described feeling safe on campus, believed most of their peers are adherent to protective behaviours and were positive towards asymptomatic testing in university settings. University communications about COVID-19 testing and social behaviours need to be timely and presented in a more inclusive way to reach groups of students who currently feel marginalised. Barriers to engagement with SARS-CoV-2 testing, social distancing and self-isolation were primarily associated with fear of the mental health impacts of self-isolation, including worry about how they will cope, high anxiety, low mood, guilt relating to impact on others and loneliness. Loneliness in students could be mitigated through increased intra-university communications and a focus on establishment of low COVID-risk social activities to help students build and enhance their social support networks. These findings are particularly pertinent in the context of mass asymptomatic testing programmes being implemented in educational settings and high numbers of students being required to self-isolate. Universities need to determine the support needs of students during self-isolation and prepare for the long-term impacts of the pandemic on student mental health and welfare support services.

Metallo-β-lactamases (MBLs) are members of the structurally conserved but functionally diverse MBL-fold superfamily of metallohydrolases. MBLs are a major concern for global health care as they efficiently inactivate β-lactam antibiotics, including the “last-resort” carbapenems, and no clinically suitable inhibitors are currently available. Increasingly, promiscuous β-lactamase activity is also observed in other members of the superfamily, including from viruses, which represents an underexplored reservoir for future pathways to antibiotic resistance. Here, two such MBL-fold enzymes from Bacillus phages, the cyclic mononucleotide-degrading proteins ApycGoe3 and ApycGrass, are shown to efficiently degrade β-lactam substrates in vitro. In particular, ApycGrass displays a distinct preference for carbapenem substrates with a catalytic efficiency that is within one order of magnitude of that of the clinically relevant MBL NDM-1. Mutagenesis experiments also demonstrate that the loss of a metal-bridging aspartate residue reduces nuclease activity up to 35-fold, but improves carbapenemase activity. In addition, we propose that the oligomeric state significantly influences β-lactamase activity by modifying access to the active site pocket. Together, these observations hint at a possible new avenue of resistance via the spread of phage-borne MBL-fold enzymes with β-lactamase activity.

We propose an experimental method for the unidirectional excitation of spin waves. By structuring Au nanowires arrays within a coplanar waveguide onto a thin yttrium iron garnet (YIG) film, we observe a chiral coupling between the excitation field geometry of the nanowires grating and several well-resolved propagating magnon modes. We report a propagating spin wave spectroscopy study with unprecedented spectral definition, wavelengths down to 130 nm and attenuation lengths well above the 100 μm over the 20 GHz frequency band. The proposed experiment paves the way for future non-reciprocal magnonic devices.

This paper focuses on the application of principal component analysis (PCA) to conduct a source apportionment of atmospheric aerosols from 8 sampling locations along the Marilao-Meycauayan-Obando River System (MMORS). Aerosols were collected on May 2016 during the same time that water samples were collected. Elemental analysis was conducted using a scanning electron microscope coupled with energy dispersive x-ray (SEM-EDX). Carbon (C), nitrogen (N), oxygen (O), sodium (Na), magnesium (Mg), aluminum (Al), silicon (Si), sulfur (S), chlorine (Cl), potassium (K), calcium (Ca), titanium (Ti), manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), bromine (Br), niobium (Nb), barium (Ba), mercury (Hg), and lead (Pb) concentrations were measured and used as inputs in Principal Component Analysis (PCA). The aerosol samples showed the presence of heavy metals Pb and Hg, elements that were also detected in trace amounts in the water measurements. Concentrations of heavy metals Fe, Pb, Hg in the aerosols were attributed to industrial sources. However, it was determined that the primary source of aerosols in the area were traffic and crustal emissions (C, N, O, Si, Al, Ca). Thus, control of traffic emissions would be more beneficial in reducing aerosol emissions in Meycauayan.

Low-cost particulate matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and their cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors but some models of sensors also report particle number concentrations (PNC) segregated into different PM size bins. In this study, 8 units of each Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors to different particle size distributions to quantify and better understand the low cost sensors performance across a range of relevant environmental ranges. The PNC reported by the sensors were analysed. This study showed that there is added value in directly using the PNC reported by the sensors instead of the mass concentrations, which could aid the efforts to calibrate these sensors to a known accuracy. It demonstrated that all sensors tested here could track the fine temporal variation of PNC, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it showed that particle size distribution and composition are more impactful on the sensors measurement than relative humidity.

During the COVID-19 pandemic, antibody-based vaccines targeting the SARS-CoV-2 spike glycoprotein were the key focus for development because neutralizing antibodies were associated with protection against the SARS-CoV-2 infection in pre-clinical models and human trials. While deploying these spike-based vaccines saved millions of lives worldwide, it has become clear that the immunological mechanisms of protection against severe disease are multifaceted and involve non-neutralizing antibody components. Here, we describe a novel pan-sarbecovirus T-cell vaccine, ChAdOx1.COVconsv12, designed to complement and broaden the protection of spike vaccines. The vaccine immunogen COVconsv12 employs the two regions in the viral proteome most conserved among sarbecoviruses delivered by replication-deficient vector ChAdOx1. It focuses T cells towards epitopes shared among sarbecoviruses including evolving SARS-CoV-2 variants. Here, we show that ChAdOx1.COVconsv12 induced broad T-cell responses in the BALB/c and C57BL/6 mice. In the Syrian hamster challenge model, ChAdOx1.COVconsv12 alone did not protect against the SARS-CoV-2 infection, but when co-administered with 1/50th of the ChAdOx1 nCoV-19 spike vaccine protective dose, faster recovery and lower oral swab viral load were observed. Induction of CD8+ T cells may decrease COVID-19 severity and extend the T-cell response coverage of variants to match the known (and as yet unknown) members of the beta-coronavirus family.

Despite the many advantages of lung ultrasound (LUS) in the diagnosis and management of patients with dyspnea, adoption among hospitalists has been slow. We performed semi-structured interviews of hospitalists from 4 diverse health systems in the US to understand determinants of adoption within a range of clinical settings. We used the Diffusion of Innovation Theory to guide a framework analysis of the data. Of 27 hospitalists invited, we performed in-terviews of 22 from 4 hospitals of diverse types. Median years post-residency of interviewees was 10.5 [IQR:5-15]. Four main themes emerged: 1) There are important clinical advantages to LUS despite operator dependence, 2) LUS enhances patient and clinician experience, 3) Investment of clinician time to learn and perform LUS is a barrier to adoption but yields improved efficiency for the health system and 4) Mandated training and use may be necessary to achieve broad adoption as monetary incentives are less effective. Despite perceived benefits of LUS for patients, clinicians and health systems, an important barrier to broad LUS adoption is the experience of time scarcity by hospitalists. Future implementation strategies should focus on changes to the clinical environment that address clinician barriers to learning and adoption of new skills.

Background: The methods used in low- and middle-income countries (LMICs) household surveys have not changed in four decades; however, LMIC societies have changed substantially and now face unprecedented rates of urbanisation and urbanisation of poverty. This mismatch may result in unintentional exclusion of vulnerable and mobile urban populations. We compare three survey method innovations with standard survey methods in Kathmandu, Dhaka, and Hanoi, and summarize feasibility of our innovative methods in terms of time, cost, skill requirements, and experiences. Methods: We used descriptive statistics and regression techniques to compare respondent characteristics in samples drawn with innovative versus standard survey designs and household definitions, adjusting for sample probability weights and clustering. Feasibility of innovative methods was evaluated using a thematic framework analysis of focus group discussions with survey field staff, and via survey planner budgets. Results: We found that a common household definition excluded single adult (46.9%) and migrant headed households (6.7%), as well as non-married (8.5%), unemployed (10.5%), disabled (9.3%), and studying adults (14.3%). Further, standard two-stage sampling resulted in fewer single adult and non-family households than an innovative area-microcensus design; however, two-stage sampling resulted in more tent and shack dwellers. Our survey innovations provided good value for money and field staff experiences were neutral or positive. Staff recommended streamlining field tools and pairing technical and survey content experts during fieldwork. Conclusions: This evidence of exclusion of vulnerable and mobile urban populations in LMIC household surveys is deeply concerning, and underscores the need to modernize survey methods and practices.

Background: The inflammation associated with overweight and obesity seems to alter iron metabolism, but there are few studies evaluating those conditions in children. Thus, we aimed to evaluate leukometric, immunological and hematimetric parameters of overweight and obese schoolchildren. Methods: This is a cross-sectional study, in which 39 children living in Chonim de Cima (Brazil), underwent anthropometric, hematological and immunological assessments. The evaluated parameters were compared between the study group (overweight/obesity, n=15) and the control group (n=24). Unpaired t-test, Mann-Whitney test and linear regression were used for statistical tests and the panoramic profile was used to illustrate differences between groups. Results: The study group had lower mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) and higher TNF levels compared to the control group. Positive correlations were observed between BMI-for-age percentile and total leukocytes (r=0.1493; p=0.0151) or neutrophils (r=0.1395; p=0.0192). Negative correlations between the BMI-for-age percentile and MCV (r=0.1464; p=0.0162) and MCH (r=0.1460; p=0.0164) were found. Furthermore, through the panoramic profile it was noted that the study group had a higher frequency of individuals with high levels of TNF and lower frequencies of individuals with increased hemoglobin and serum iron. Conclusions: Our data suggests that overweight and obesity contribute to a pro-inflammatory context (leukocytes, neutrophils and TNF) and MCV and MCH reduction in schoolchildren.

Outbreaks of Ebola ebolavirus (EBOV) have been associated with high morbidity and mortality. Milestones have been reached recently in the management of EBOV disease (EVD) with licensure of an EBOV vaccine and two monoclonal antibody therapies. However, neither vaccines nor therapies are available for other disease-causing filoviruses. In preparation for such outbreaks, and for more facile and cost-effective management of EVD, we seek a cocktail containing orally available and room temperature stable drugs with strong activity against multiple filoviruses. We previously showed that (bepridil + sertraline) and (sertraline + toremifene) synergistically suppress EBOV in cell cultures. Here we describe steps towards testing these combinations in a mouse model of EVD. We identified a vehicle suitable for oral delivery of the component drugs and determined that, thus formulated the drugs are equally active against EBOV as preparations in DMSO, and they maintain activity upon storage in solution for up to seven days. Pharmacokinetic (PK) studies indicated that the drugs in the oral delivery vehicle are well tolerated in mice at the highest doses tested. Collectively the data support advancement of these combinations to tests for synergy in a mouse model of EVD. Moreover, mathematical modeling based on human oral PK projects that the combinations would be more active in humans than their component single drugs.

Rutin, a flavonoid compound found in various plants, has gained attention for its potential applications in the cosmetic industry due to its antioxidant, anti-inflammatory, and potential photoprotective properties. Our review explored the use of rutin (rutoside, 3-O-rutinoside-quercetin) in cosmetics/dermocosmetics, focusing on its physicochemical properties and stability, cutaneous permeability, and efficacy in sunscreen systems, involving in vitro tests and the current state of clinical trials. Rutin's ability to scavenge free radicals, prevent peroxidation, and reduce vascular fragility makes this flavonoid a promising ingredient for photoprotection. Studies have shown that rutin can enhance the sun protection factor (SPF) of sunscreen formulations, especially when combined with organic UV filters. The encapsulation of rutin in nanostructures has also been investigated to improve its applicability. Overall, rutin shows potential as a safe and effective ingredient in cosmetic/dermocosmetic formulations, offering protection against the harmful effects of UV radiation and oxidative stress on the skin.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

The aim of this retrospective study was to compare the clinical outcomes of treating isolated surgical neck fractures of the humerus using either the intramedullary nail or the MIROS (Minimally Invasive Reduction and Osteosynthesis System®) system. The study included 42 patients who underwent surgical treatment at the Polyclinic from January 2014 to June 2020. The results indicated that both treatments were effective; however, the MIROS system exhibited a higher complication rate. Intramedullary nailing was more reliable, thus recommended as the primary treatment method. This study underscores the importance of selecting the appropriate fixation technique to minimize complications and enhance patient outcomes.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Excess nitrogen in agricultural drainage poses a serious threat to the water quality safety of the Yellow River basin. Utilizing aquatic plants to modify the rhizosphere microbial community structure and facilitate nitrogen transformation is a crucial strategy for mitigating regional water eutrophication. Our results revealed that the denitrification rate (DR), dissimilatory nitrate reduction to ammonium rate (DNRAR) and nitrogen fixation rate (NFR) of rhizosphere sediments exhibited a significant increase in artificially cultivated ditch. Compared with those in natural ditches, the richness of the bacterial community and the relative abundances of Bacteroidota, Verrucomicrobiota, Firmicutes, Anaeromyxobacter and Geobacter, which are involved mainly in the nitrogen cycle, in the rhizosphere sediments of artificially cultivated ditch were significantly greater due to improvements in environmental conditions. In artificially cultivated ditch, the dominant functional genes affecting DRNARs in the rhizosphere sediments of P. australis were nrfC and nrfA, while DRs were driven mainly by norB and napA, which were influenced by the nitrogen and carbon levels; and the dominant functional genes affecting NFRs in the rhizosphere sediments of T. orientalis were nifD, nifK and nifH. Our results provide a scientific basis for the use of aquatic plants for mitigating excess nitrogen levels in agricultural drainage.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

Our previous studies demonstrated a tight connection between simvastatin (SIM) inhibition of B16.F10 murine melanoma cell proliferation in vivo and in vitro and strong suppression of the subunit α of hypoxia inducible factor 1 (HIF-1) (HIF-1 α) production in these cancer cells. Since the translation of HIF-1α is modulated by signaling pathways coordinated by Akt, SIM effects on the link between these two regulatory factors and cancer cell metabolism under normoxia was investigated, which to our knowledge have never been described before. To achieve the proposed aim, SIM effects on cell metabolism were analysed at mRNA (via RNA-seq and RT-qPCR) as well as protein level (via western blot and catalytic activity of the key enzymes) Our data suggested that SIM might orientate glucose transport and metabolism to ensure replenishment of tricarboxylic acid (TCA) cycle activity. Moreover, it seems that SIM enhanced biosynthetic role of TCA over its energy role to further support synthesis of lipid-derived signaling molecules. Thus, under normoxia SIM treatment orientated lipid metabolism to stimulate isoprenoid and prostaglandin synthesis which might favor melanoma cell survival and aggressiveness.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

In this paper, we extend the KdVSKR equations in (1+1)-dimension and (2+1)-dimension to fractional KdVSKR equations with modified Riemann-Liouville derivative. The (2+1)-dimensional KdVSKR equation, which is a recent extension of (1+1)-dimensional KdVSKR equation, can model the resonances of solitons in shallow water. By means of the Hirota bilinear method, finite symmetry group method and consistent Riccati expansion method, many new interaction solutions have been derived. Soliton-cnoidal interaction solution of the (1+1)-dimensional fractional KdVSKR equation has been derived for the first time. For the (2+1)-dimensional frac-tional KdVSKR equation, two-wave interaction solutions and three-wave interaction solutions, including dark-soliton-sine interaction solution, bright-soliton-elliptic interaction solution, and lump-hyperbolic-sine interaction solution, have been derived. Impact of the fractional order on the shapes of these solutions has been illustrated by figures. Three-wave interaction solutions of fractional systems have not been reported in the existing references. The research idea in this paper can be applied to other fractional differential equations.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

Antimicrobial peptides represent a promising alternative to traditional drugs in relation to cost, toxicity and, primarily, the growing problem of drug resistance. Here we report on the activity against HSV-1 and HSV-2 of a previously described wide-spectrum synthetic decapeptide, Killer Peptide (KP). As determined by plaque reduction assays, treatment with KP at 100 μg/mL resulted in a reduction in the viral yield titer of 3.5 Logs for HSV-1 and 4.1 Logs for HSV-2. Further evaluation of KP antiviral activity focused on the early stages of virus replicative cycle, including the determination of the residual infectivity of viral suspensions treated with KP. A direct effect of the peptide on viral particles, impairing virus absorption and penetration, was shown. The toxicity profile proved to be extremely good with a selectivity index of 29.6 for HSV-1 and 156 for HSV-2. KP was also active against an acyclovir (ACV)-resistant HSV-1 strain, while HSV-1 subcultures in the presence of sub-inhibitory doses of KP did not lead to the emergence of resistant strains. Finally, the antiviral action of KP proved to be synergistic with that of ACV. Overall, these results demonstrate that KP could represent an interesting addition/alternative to acyclovir for antiviral treatment.