Vaginitis is a widespread issue for women worldwide, yet current diagnostic tools are lacking. Bacterial vaginosis (BV) is the most prevalent type of vaginitis, found in 10-50% of reproductive aged women. Current diagnostic methods for BV rely on clinical criteria, microscopy, or detection of a few microbes by qPCR. However, many vaginal infections lack a single etiological agent and are characterized by changes in the vaginal microbiome community structure (e.g. BV is defined as a loss of protective lactobacilli resulting in an overgrowth of anaerobic bacteria). Shotgun metagenomic sequencing provides a comprehensive view of all the organisms present in the vaginal microbiome (VMB) allowing for a better understanding of all potential etiologies. Here, we describe a robust VMB metagenomics sequencing test with a sensitivity of 88.5%, specificity of 96.2%, and a positive predictive value of 95.8% certified by Clinical Laboratory Improvement Amendments (CLIA), the College of American Pathologist (CAP) and the Clinical Laboratory Evaluation Program (CLEP). We sequenced over 7,000 human vaginal samples with this pipeline and described general findings and comparison to US census data.

The intense emergence of mucilage in the Marmara Sea in 2021 has raised concerns due to its potential impact on the global marine system. Considering the potential of mucilage threatening the diverse ecosystems, it is important to define the mucilage microbiome. However, studies dedicated to exploring the biodiversity of mucilage are limited and de novo approaches are needed to understand unexplored biodiversity of mucilage microenvironment. This study aimed to investigate mucilage and water samples from certain stations in Marmara Sea. For this reason, 11 mucilage, 2 pre-mucilage water and 3 clean sea water were collected from 16 stations. DNA isolation, shotgun metagenome sequencing and bioinformatics analysis were performed. It was revealed that the mucilage microbiome and the clean water microbiome were different from each other, and the reads that could not be assigned to any taxon (dark matter) accounted for 58% (p=0.014) of the mucilage metagenome. The clean water had a higher presence of Euryarchaeota (p=0.014), Proteobacteria (p=0.019) and Rhodothermaeota (p=0.034), while Chlamydiae (p=0.014) and Fusobacteria (p=0.034) were found in excess in the mucilage. The study produced the first comparative data on clean sea water and the mucilage microbiome using shotgun metagenomics approaches.

Bacterial phylogenetics has largely been determined via 16S rRNA gene sequencing and phylogenetic tree reconstruction. Observed utility of this approach has driven the popularity of the 16S rRNA gene amplicon metagenomics method for profiling and identifying diverse microbes from specific habitats. This work sought to develop universal primers for amplifying the 16S rRNA gene from a consortium of disparate microbial species. Using multiple sequence alignment of the 16S rRNA gene of a variety of microbes, the resulting highly conserved region of the consensus sequence was used for design of universal polymerase chain reaction (PCR) primers for 16S rRNA gene. Application of the universal primers in simulated PCR reveals poor amplification efficiency where only 12 species out of 31 generated an amplicon. BLAST analysis of the resulting amplicons reveals a classification error of 50%. More significantly, analysis of the amplicon length indicates variable read length ranging from 81 to 122 base pair compared to the predicted read length of 100 base pairs. This suggests that the 16S rRNA gene harbours significant hitherto underappreciated sequence diversity, and may have unknown alternative splicing and recombination mechanisms. Overall, results from this study suggests that primer design for 16S rRNA amplicon metagenomics may be application and habitat specific, where it is difficult to design universal primers for all bacterial species. Conceptually, this meant that there may be sequence co-evolution in 16S rRNA gene for microbial species in the habitat where environmental and nutritional conditions impact on 16S rRNA gene structure and sequence. In essence, 16S rRNA gene may habour epigenetics signals at the gene level.

Switchgrass (Panicum virgatum L.) remains the preeminent American perennial (C4) bioenergy crop for cellulosic ethanol that could help displace over a quarter of the US current petroleum consumption. Intriguingly, there is often little response to nitrogen fertilizer once stands are established. The rhizosphere microbiome plays a critical role in nitrogen cycling and overall plant nutrient uptake. We used high-throughput metagenomic sequencing to characterize the switchgrass rhizosphere microbial community (5.37 billion Illumina reads at 805 Gbp of data) before and after a nitrogen fertilization event for established stands on marginal land. We examined community structure, bulk metabolic potential, and resolved 29 individual bacteria genomes via metagenomic de novo assembly. Community structure and diversity were not significantly different before and after fertilization; however, the bulk metabolic potential of carbohydrate-active enzymes was depleted after fertilization. We resolved 29 metagenomic assembled genomes including some from the ‘most wanted’ soil taxa such as Verrucomicrobia, Candidate phyla UBA10199, Acidobacteria (rare subgroup 23), Dormibacterota, and the very rare Candidatus Eisenbacteria. The Dormibacterota (formally candidate division AD3) we identified have the potential for autotrophic CO utilization, which may impact carbon partitioning and storage. Our study also suggests that the rhizosphere microbiome may be involved in providing associative nitrogen fixation (ANF) via the novel diazotroph Janthinobacterium, which may partially explain why switchgrass growth is insensitive to fertilizer.

Background: With continuous advances in next-generation sequencing (NGS), novel hepadnaviruses have been discovered in many species over the last 10 years. Methods: In this study, the cloud search and analysis of NGS data published in Nature by Edgar et al. was used as a basis to re-mine and reanalyze public NGS data for new hepadnaviruses. Results: Ultimately, at least 41 new species of hepadnaviruses were identified, including hepadnaviruses from the model animals hamster and mouse, frog hepadnavirus with pan-species infectivity, and diverse African cichlid hepadnaviruses that circulate within populations. Conclusions: The discovery of the new species of hepadnaviruses not only provides new clues for the study of the origin and evolution of hepadnaviruses, but also can be used to construct new hepadnavirus animal infection models, which will be helpful for the research of eradicative drugs for hepatitis B virus (HBV).

Motivation: 16S rRNA gene amplicon based sequencing has significantly expanded the scope of metagenomics research by enabling microbial community analyses in a cost-effective manner. The possibility to infer functional potential of a microbiome through amplicon sequencing derived taxonomic abundance profiles has further strengthened the utility of 16S sequencing. In fact, a surge in 'inferred function metagenomic analysis' has recently taken place, wherein most 16S microbiome studies include inferred functional insights in addition to taxonomic characterization. Tools like PICRUSt, Tax4Fun, Vikodak and iVikodak have significantly eased the process of inferring function potential of a microbiome using the taxonomic abundance profile. A platform that can enable hosting of inferred function 'metagenomic studies' with comprehensive metadata driven search utilities (of a typical database), coupled with on-the-fly comparative analytics between studies of interest, can be a major improvement to the state of art. ReFDash represents an effort in the proposed direction. Methods: This work introduces ReFDash - a Repository of Functional Dashboards. ReFDash, developed as a significant extension of iVikodak (function inference tool), provides three broad unique offerings in inferred function space - (i) a platform that hosts a database of inferred function data being continously updated using public 16S metagenomic studies (ii) a tool to search studies of interest and compare upto three metagenomic environments on the fly (iii) a community initiative wherein users can contribute their own inferred function data to the platform. ReFDash therefore provides a first-of-its-kind community-driven frame-work for scientific collaboration, data analytics, and sharing in this area of microbiome research. Results: Overall, the ReFDash database is aimed at compiling together a global ensemble of 16S-derived Functional Metagenomics projects. ReFDash currently hosts close to 50 ready-to-use, re-analyzable functional dashboards representing data from approximately 18,000 microbiome samples sourced from various published studies. Each entry also provides direct downloadable links to associated taxonomic files and metadata employed for analysis. Conclusion: The vision behind ReFDash is creation of a framework, wherein users can not only analyze their microbiome datasets in functional terms, but also contribute towards building an information base by submitting their functional analyses to ReFDash database. ReFDash web-server may be freely accessed at https://web.rniapps.net/iVikodak/refdash/

Advancements in DNA methods and biotechnology have enabled forensic scientists to explore the DNA evidence found as part of a criminal investigation on a much more comprehensive and predictive level. This has led to a rise in research into DNA intelligence tools such as phenotypic prediction (i.e., eye and hair colour) and inference of biogeographical ancestry. Both of which can be applied to gain further insights about a scene or sample in question. Although microorganisms have played a role in forensics for decades, investigations were focused on the pathogenicity aspect, mainly to determine the cause and time of death. Recent progress in studying the human microbiome has implicated the potential use of this data in forensics. Since each individual, place, or item has its own microbial pattern, a new suite of tools are now available to be exploited in criminal investigations. Although there is much interest and potential for these emerging metagenomic and microbial forensic tools, best practices and reference ranges need to be established before they are implemented. Here, we discuss existing DNA intelligence tools applied to forensic science, the application of microbial forensics and metagenomics along with the challenges and concerns that future developments entail.

The makeup of human microbiota has been linked to a number of autoimmune disorders. Recent developments in whole metagenome sequencing and 16S rRNA sequencing technology have considerably aided research into the microbiome and its relationship to disease. Due to the inherent high dimensionality and complexity of data generated by high-throughput platforms, conventional bioinformatics techniques could only provide an inadequate explanation for the most relevant changes and seldom provide correct predictions. Machine learning, on the other hand, is a subset of artificial intelligence applications that enable the untangling of high-dimensional systems and intricate knots in correlation by learning complex patterns and improving automatically from training data without being explicitly programmed. Machine learning is increasingly being utilized to research the influence of microbes on the onset of illness and other clinical features since computer power has increased dramatically in the last few decades. In this review paper, we focused on emerging methodological approaches of supervised machine learning algorithms for identification of autoimmune disorders utilizing metagenomics data, as well as the potential benefits and limitations of machine learning models in clinical applications.

The frequency of non-alcoholic fatty liver disease (NAFLD) has exacerbated setting diagnostic challenges, which increases the need for reliable non-invasive diagnostic tools. Due to the importance of gut-liver axis in the progression of NAFLD, studies try to reveal microbial signatures in NAFLD, evaluate them as diagnostic biomarkers and to predict the disease progression. The gut microbiome affects human physiology by processing the ingested food to bioactive metabolites. These molecules can penetrate the portal vein and the liver to promote or prevent hepatic fat accumulation. Here findings of human fecal metagenomic and metabolomic studies in relation to NAFLD are reviewed. The studies present mostly distinct and even contradictory findings on microbial metabolites and functional genes in NAFLD. The most reproducing microbial biomarkers are increased lipopolysaccharides and peptidoglycan biosynthesis, enhanced degradation of lysine, increased levels of branched chain amino acids as well as altered lipid and carbohydrate metabolism. Among other causes, the discrepancies between the studies may be related to the obesity status of the patients and severity of NAFLD. In none of the studies except one, diet was considered, though it is an important factor driving the gut microbiota metabolism. The future studies should consider diet in the analyses.

Background: The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenges. To facilitate routine implementation of microbiome profiling in clinical settings, portable, real-time, and low-cost sequencing technologies are needed. Results: Here, we propose a computational and experimental protocol for whole genome quantitative metagenomics studies of human gut microbiome with Oxford Nanopore sequencing technology (ONT) that could be applied to other microbial ecosystems. We developed a bioinformatic protocol to analyse ONT sequences taxonomically and functionally and optimized pre-analytic protocols including stool collection and DNA extraction methods to maximize read length. This is a critical parameter for the sequence alignment and classification. Our protocol was evaluated using simulations of metagenomic communities which reflect naturally occuring compositional variations. Next, we validated both protocols using stool samples from a bariatric surgery cohort, sequenced with ONT, Illumina and SOLiD technologies. Results revealed similar diversity and microbial composition profiles. Conclusion: This protocol can be implemented in the clinical or research setting, bringing rapid personalized whole genome profiling of target microbiome species.

Crop output is directly impacted by plant infections (with fungi as the major pathogen), making accurate diagnosis of these threats crucial. Developing technology and multidisciplinary approaches are turning to genomic analyses in addition to traditional culture methods in diagnosing fungal plant diseases. The metagenomic next-generation sequencing (mNGS) method is preferred for genotyping identification of organisms, identification at the species level, illumination of metabolic pathways, and determination of microbiota. Moreover, the data obtained so far show that this new approach shows promise as an emerging new trend in fungal disease detection. Another approach covered by mNGS technologies, known as metabarcoding, enables use of specific markers specific to a genetic region and allows for genotypic identification by facilitating the sequencing of certain regions. Although the core concept of mNGS remains constant across applications, the specific sequencing methods and bioinformatics tools used to analyze the data do differ. In this review, we focus on how mNGS technology, including metabarcoding, is applied in fungal pathogenesis and its promising developments for the future.

Abstract: Assessing infection by a parasite, such as Haemonchus contortus, requires time and experienced personnel. Field-based diagnostics using metagenomic species-specific targeting methods would be beneficial. Here, we examine two helminth control methods, zoledronic acid (ZA), an activator of γ δ T cells, and a neutralizing antibody (AB) against γ δ T cells. We conducted a randomized complete block designed investigation for the effects of Haemonchus contortus (Hc) infection on Alpine wethers (young castrated male goats) to identify if metagenomic methods will provide strong evidence for diagnostics. Different tissues were collected from wethers and the microbiome compositions were identified. The relative proportion of microbial community members in the environments; the richness of the microbial community; and the evenness of distribution in microbial community members were determined. It was hypothesized that numerous parameters that include many data points will provide a more precise means to identify infection or health based on similarity to uninfected control data parameters. We found that samples did not sequence well, when multiplexed with high concentration libraries, giving taxonomic numbers that had residual and unmeasured confounding bias related to analysis or selection that define significance of OTUs in the tissue samples at the phylum or species level.

The black-necked crane is the only species that lives in the plateau. At present, there is little re-search on viral diseases of the black-necked crane. In this study, a virus metagenomics approach was employed to investigate the viral composition of black-necked cranes in Saga County, Shi-gatse City, Tibet, China. The identified virus families carried by black-necked cranes mainly in-clude Genomoviridae, Parvoviridae, and Picornaviridae. Among them, one picornavirus genome is characterized as a novel species in the genus Grusopivirus of the family Picornaviridae, four new parvoviruses genome were obtained and classified into four different novel species within the genus Chaphamaparvovirus of the subfamily Hamaparvovirinae, and four novel genomoviruses ge-nome were also acquired and identified as members of three different species including Ge-mykroznavirus haeme1, Gemycircularvirus ptero6, and Gemycircularvirus ptero10. All of these viruses were firstly detected in fecal samples of black-necked cranes. This study provides valuable in-formation for understanding the viral community composition in the digestive tract of black-necked cranes in Tibet and for monitoring, preventing, and treating black-necked cranes viral diseases.

The human gut microbiome (GM) plays an important role in human health and diseases. However, while substantial progress has been made in understanding the role of bacterial inhabitants of the gut, much less is known regarding the viral component of the GM. Bacteriophages (phages) are viruses attacking specific host bacteria and likely play important roles in shaping the GM. Although metagenomic approaches have led to the discoveries of many new viruses, they largely remain uncultured as their hosts have not been identified, which hampers our understanding of their biological roles. Existing protocols for isolation of viromes generally require relatively high input volumes and are generally more focused on extracting nucleic acids of good quality and purity for down-stream analysis and less on purification of still infective viruses. Here we report the development of an efficient protocol requiring low sample input yielding purified viromes containing still infective phages which also are of sufficient purity for genome sequencing. We validated the method through spiking of known phages followed by plaque assays, qPCR and metagenomic sequencing. The protocol should facilitate the culturing of novel viruses from the gut as well as large scale studies on gut viromes.

Artemia (brine shrimp), holds significant value as a live feed for larval fish and crustaceans, owing to their distinctive dietary requirements. However, it is vital to acknowledge that Artemia also carries potential risk as a vector of infection. We conducted a metagenomic analysis to explore the virome present in Artemia cysts collected from inland salt lakes across four distinct regions in Kazakhstan. The study identified the presence of dsDNA phages and RNA virus sequences, with a predominant representation from the Reoviridae, Nodaviridae, Dicistroviridae, Picornaviridae, Astroviridae, Tombusviridae, and Solemoviridae families. In general, this study has significantly enhanced our understanding of the virome of Artemia cysts in the saline lakes of Kazakhstan. It has also furnished crucial insights for the identification, surveillance, and management of viral infections that impact brine shrimp and fish species populations.

Buruli ulcer (BU), caused by Mycobacterium ulcerans, is a neglected tropical disease associated with freshwater habitats. A variety of limnic organisms harbor this pathogen, including aquatic bugs (Hemiptera: Heteroptera), which have been hypothesized to be epidemiologically important reservoirs. Aquatic Hemiptera exhibit high levels of diversity in the tropics, but species identification remains challenging. In this study, we collected aquatic bugs from emerging foci of BU in the Southwest Region of Cameroon, which were identified using morphological and molecular methods. The bugs were screened for mycobacterial DNA and a selection of 20 mycobacteria-positive specimens from the families Gerridae and Veliidae were subjected to next-generation sequencing. Only one individual revealed putative M. ulcerans DNA, but all specimens contained sequences from the widespread alpha-proteobacterial symbiont, Wolbachia. Phylogenetic analysis placed the Wolbachia sequences into supergroups A, B and F. Circularized mitogenomes were obtained for seven gerrids and two veliids, the first from these families for the African continent. This study suggests that aquatic Hemiptera may have a minor role (if any) in the spread of BU in Southwest Cameroon. Our metagenomic analysis provides new insights into the incursion of Wolbachia into aquatic environments and generates valuable resources to aid molecular taxonomic studies of aquatic Hemiptera.

"Public legal information from all countries and international institutions is part of the common heritage of humanity. Maximizing access to this information promotes justice and the rule of law". In accordance with the aforementioned declaration on Free Access to Law by Legal information institutes of the world, a plethora of legal information is available through the Internet, while the provision of legal information has never before been easier. Given that law is accessed by a much wider group of people, the majority of whom are not legally trained or qualified, diversification techniques, should be employed in the context of legal information retrieval, as to increase user satisfaction. We address diversification of results in legal search by adopting several state of the art methods from the web search, network analysis and text summarization domains. We provide an exhaustive evaluation of the methods, using a standard data set from the Common Law domain that we subjectively annotated with relevance judgments for this purpose. Our results i) reveal that users receive broader insights across the results they get from a legal information retrieval system, ii) demonstrate that web search diversification techniques outperform other approaches (e.g., summarization-based, graph-based methods) in the context of legal diversification and iii) offer balance boundaries between reinforcing relevant documents or sampling the information space around the legal query.

The aim of this study was to investigate the physicochemical characterization and biological activities of chitosan (CH) based composite films with the incorporation of chestnut flower essential oil (CFEO). The composite films were prepared by casting method and characterized in terms of structural, morphological and mechanical properties via FT-IR, XRD, UV, SEM and TGA. The results proved the significantly increased water vapor permeability (WVP), heat resistance, antibacterial and antioxidant capabilities of CH-CFEO films. The incorporation of CH and CFEO enhanced the UV blocking, which made the film shield almost all UV light. Films with the tensile strength of 6.37 ± 0.41 MPa and elongation at break of 22.57 ± 0.35% were got with 6 mg mL-1 CFEO. Subsequently, the fruit preservation experiments also confirmed that the composite films could effectively extend the shelf life of bananas through their excellent water vapor and oxygen barrier. These desirable performances enable our newly developed composite films to be a remarkable packaging material to solve the fresh fruit preservation dilemma.

Abstract Objective: Endometriosis is a chronic disease characterized by the growth of endometrial cells outside the uterine cavity. The dysfunction of the immune system is strongly associated with the progression of endometriosis, and is also correlated to the diversity of microbiota in the genital tract. According to previous studies, the microbiota significantly contributes to multi-systemic function, but the evidence of endometriosis and adenomyosis remains insufficient. Thus, the present study attempted to identify the characteristics of microbiota in endometriosis patients, and the connection between microbiota and immunological dysfunction. Methods: In order to compare and explore the potential microbiota correlated to endometriosis and adenomyosis in the genital tract, 134 samples obtained from the cervical canal, posterior fornix and uterine cavity were analyzed by 16s-rRNA sequencing. The raw data was filtered, analyzed and visualized, and bio-information methods were used to identify the different and distinctive characteristics of microbiota. Results: Two different locations near the cervix, cervical canal and posterior fornix, exhibited no differences in alpha diversity. Among the different disease groups, five microbiota were distinctive in the genus level, and Atopobium presented with the greatest significance in adenomyoisis-endometriosis patients. The LEfSe analysis failed to identify the special biomarkers, while several characteristic functions were identified through PICRUSt. Conclusion: Lactobacillus is dominant in the female lower genital tract, and Atopobium is distinctively higher in patients with endometriosis combined with adenomyosis. Several different functions of microbiota were explored, and these are found to be associated with endometriosis and adenomyosis. These findings may provide a new concept of microbiota/immune system/endometriosis system. There is an urgent need to investigate the potential microbial biomarkers of endometriosis in the future.

Here we present an overview of speleothem δ18O records from South America, which mostly are available in the Speleothem Isotopes Synthesis and Analysis (SISAL_v1) database. South American tropical and subtropical δ18O time series are primarily interpreted as being driven by the amount effect and, consequently show the past history of the convection intensity of convergence zones such as the Intertropical Convergence Zone and the South America Monsoon System. We investigate past hydroclimate scenarios in South America related to the South American Monsoon System in three different time scales: Late Pleistocene, Holocene and the last two millennia. The precession driven insolation is the main driver of convective variability over the continent during the last 250 kyrs, including the Holocene period. However a dipole is observed between the west and east portions of the continent. Records located in the central region of Brazil appear to be weakly affected by insolation driven variability and more susceptible to the South Atlantic Convergence Zone. Cold episodic events in Northern Hemisphere increase the activity of the South American Monsoon System on all time scales, in turn increasing rainfall amounts in South America, as was documented during Heinrich events in the late Pleistocene and Bond events in the Holocene, as well as during the Little Ice Age.

Here we describe ARSA-16S, a tool and accompanying reference database for the analysis of bacterial 16S amplicons. Among other features, ARSA-16S is based on a new model, approach, and algorithm for sequence-level assignment of reads understood as probability distributions, assigns reads individually, and is designed with non-overlapping amplicons covering two non-contiguous regions. A new set of primers for the amplification and sequencing of the V4 and V6 regions is also provided.

Pregnancy is a dynamic state with multiple metabolic changes occurring including insulin resistance. Gestational diabetes mellitus (GDM), a form of diabetes that appears during pregnancy, develops if metabolic aberrations occur, in particular, in normal pregnancy-induced insulin resistance. Multi-omics is a powerful approach for uncovering the mechanisms driving metabolic change in different physiologic and pathologic states. A recent study demonstrated that the gestational gut microbiome mediates pregnancy metabolic adaptations through effects on gut indoleamine-2,3 dioxygenase 1 activity and the production of kynurenine. Using the dataset generated from this highly controlled study, we performed a comprehensive analysis of the pregnancy-specific physiological and metabolic profiles, 16S rRNA microbiome, and plasma untargeted LC-MS metabolome data. To facilitate the utilization of these analysis results by other researchers, we developed MOMMI-MP, a database that provides an easy-to-use platform to browse and search differential abundant microbial taxa and metabolites, and to examine metabolic pathways. The datasets consist of data collected from 3 genetically diverse strains of mice (C57BL/6J, CD1, and NIH-Swiss) over 6 time points during the gestational (days 0, 10, 15, and 19 during gestation) and postpartum (days 3 and 20 after delivery) states, totaling 180 samples for each strain. The computational results are presented in various tables and plots, and organized in MOMMI-MP to empower exploratory analyses by other researchers. In conclusion, MOMMI-MP is a resource to facilitate the investigation of novel mechanisms governing metabolic changes during pregnancy.

Understanding the factors which control endothelial cell (EC) function and angiogenesis is crucial for developing the horse as a disease model, but equine ECs remain poorly studied. In this study we have optimised methods for the isolation and culture of equine aortic endothelial cells (EA-oECs) and characterised their angiogenic functions in vitro. Mechanical dissociation, followed by magnetic purification using an anti-VE-cadherin antibody, resulted in EC-enriched cultures suitable for further study. Fibroblast growth factor 2 (FGF2) increased EAoEC proliferation rate and stimulated scratch wound closure and tube formation by EAoECs on extracellular matrix. Pharmacological inhibitors of FGFR1 (SU5402) or MEK (PD184352) blocked FGF2-induced ERK1/2 phosphorylation and functional responses, suggesting that these are dependent on FGFR1/MEK-ERK signalling. In marked contrast, VEGF-A had no effect on EAoEC proliferation, migration or tubulogenesis and did not promote ERK1/2 phosphorylation, indicating a lack of sensitivity to this classical pro-angiogenic growth factor. Gene expression analysis showed that, unlike human ECs, FGFR1 is expressed by EAoECs at a much higher level than both VEGFR1 and VEGFR2. These results suggest a predominant role for FGF2 versus VEGF-A in controlling the angiogenic functions of equine ECs. Collectively, our novel data provide a sound basis for stud-ying angiogenic processes in the horse and lay the foundations for comparative studies of EC biology in horses versus humans.

Amphetamine is a psychostimulant drug with a high risk of toxicity and death when misused. Abuse of amphetamines is associated with an altered organic profile, which includes omega fatty acids. Low omega fatty acid levels are linked to mental disorders. Using the Comparative Toxicogenomic Database (CTD), we investigated the chemical profile of the brain in amphetamine-related fatalities and the possibility of neurotoxicity. We classified amphetamine cases as low (0-0.5 g/ml), medium (>0.5 to 1.5 g/ml), and high (>1.5 g/ml) based on amphetamine levels in brain samples. All three groups shared 1-octadecene, 1-tridecene, 2,4-di-tert-butylphenol, arachidonic acid, docosahexaenoic acid (DHA), eicosane, and oleylamide. We identified chemical-disease associations using the CTD tools and predict an association between docosahexaenoic and arachidonic acids and curated conditions like autistic disorder, disorders related to cocaine, Alzheimer's disease, and cognitive dysfunction. An amphetamine challenge may cause neurotoxicity in the human brain due to a decrease in omega-3 fatty acids and an increase in oxidative products. Therefore, in cases of amphetamine toxicity, supplement therapy may necessitate preventing omega-3 fatty acid deficiency.

Mediterranean Diet (MD), rich in minimally processed plant foods and in monounsaturated fats, but low in saturated fats, meat and dairy products, represents one of the most studied diets for cardiovascular health. It has been shown, from both observational and randomized controlled trials, that MD reduces body weight, improves cardiovascular disease surrogates such as waist-to-hip ratio, lipids, and inflammation markers, and even prevents the development of fatal and non-fatal cardiovascular disease, diabetes, obesity, and other diseases. However, it is unclear whether it offers cardiovascular benefits from its individual components or as a whole. Furthermore, limitations in the methodology of studies and meta-analyses have raised some concerns on its potential cardiovascular benefits. MD is also associated with characteristic changes in the intestinal microbiota, mediated through its constituents. These include increased growth of species producing short-chain fatty acids, such as Clostridium leptum and Eubacterium rectale, increased growth of Bifidobacteria, Bacteroides and Faecalibacterium prausnitzii species, and reduced growth of Firmicutes and Blautia species. Such changes are known to be favorably associated with inflammation, oxidative status, and overall metabolic health. This review will focus on the effects of MD on cardiovascular health through its action on gut microbioma.

The majority of investigations on microbial communities from various environments are presently built on culture-independent methods. Many studies point to the pivotal, selective role of primers targeting hypervariable regions of 16S rRNA in the metabarcoding of bacteria, including cyanobacterial communities. The selectivity of primers designed to amplify targeted regions of the 16S rRNA gene, which has been highlighted by many authors, limited effective amplification. Moreover, the type and specificity of the studied material can also negatively influence the results of 16S metabarcoding. Most of the studies of cyanobacterial communities have been performed for planktonic microbial communities that are often represented by common, well-studied species. In this study, we present the results of 16S metabarcoding analysis using three primer pairs - two already well-known and a third designed in this study - that amplify divergent regions of the 16S rRNA gene (V3-V4, V4-V6, V6) for benthic, microbial mat-forming cyanobacteria communities. Such communities can be a source of toxigenic cyanobacterial taxa and should be monitored with adequate primers. The comparison of three primer pairs suggested that those designed within the present study describe the structure and composition of highly heterogeneous cyanobacterial mats’ communities better than the others

This study centered on examining 60 different antibiotics by assessing their primary toxicity parameters through the pkCSM database. The parameters included Max. Tolerated Dose (Human) (log mg/kg/day), Oral Rat Acute Toxicity (LD50) (mol/kg), Oral Rat Chronic Toxicity (LOAEL) (log mg/kg_bw/day), and Minnow Toxicity (LC50) (log mM). The results highlight four potential antibiotics—cefotaxime, ceftriaxone, imipenem, and meropenem—that exhibited lower toxicity effects compared to other compounds. These findings imply a relatively favorable safety profile for these antibiotics concerning the specified toxicity parameters. However, it is crucial to interpret these outcomes within the context of the specific clinical application and to consider additional factors for a comprehensive safety assessment. It's essential to acknowledge that evaluating toxicity is intricate, and the determination of what is considered "less toxic" can rely on specific criteria and the context of use. Furthermore, individual responses to antibiotics may vary, and the selection of an antibiotic should be based on diverse factors, including the specific infection being treated, the patient's health, and potential side effects.

We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

In this study, based on a new quantum integral identity, the authors establish some quantum estimates of Hermite-Hadamard type inequalities for convex functions. These results generalize and improve some known results given in literatures.

Since the implementation of the Materials Genome Project by the Obama administration in the United States, the development of various computational materials databases has fundamentally expanded the choices of industries such as materials and energy. In the field of thermoelectric materials, the thermoelectric figure of merit ZT quantifies the performance of the material. From the viewpoint of calculations for vast materials, the ZT values are not easily obtained due to their computational complexity. Here, we show how to build a database of thermoelectric materials based on first-principles calculations for the electronic and heat transport of materials. Firstly, the initial structures are classified according to the values of bandgap and other basic properties using the clustering algorithm K-means in machine learning, and high-throughput first principles calculations are carried out for narrow-bandgap semiconductors which exhibiting potential thermoelectric application. The present framework of calculations mainly includes deformation potential module, electrical transport performance module, mechanical and thermodynamic properties module. We have also set up a search webpage for the calculated database of thermoelectric materials, providing searching and viewing the related physical properties of materials. Our work may inspire the construction of more computational databases of first-principle thermoelectric materials and accelerate research progress in the field of thermoelectrics.

To date, viruses closely related to SARS-CoV-2 have been reported in four bat species: Rhinolophus acuminatus, Rhinolophus affinis, Rhinolophus malayanus, and Rhinolophus shameli. Here, we analysed 343 sequences of the mitochondrial cytochrome c oxidase subunit 1 gene (CO1) from georeferenced bats of the four Rhinolophus species identified as reservoirs of SARS-CoV-2-like viruses. Haplotype networks were constructed in order to investigate patterns of genetic diversity among bat populations of Southeast Asia. No strong geographic structure was found for the four Rhinolophus species, suggesting high dispersal capacity. The ecological niche of SARS-CoV-2 like viruses was predicted using the four localities of bat SARS-CoV-2-like viruses and the localities where bats showed identical or very similar CO1 haplotypes than virus-positive bats. The ecological niche of SARS-CoV-like viruses was deduced from the localities where bat SARS-CoV-like viruses were previously detected. The results show that the ecological niche of SARS-CoV2-like viruses includes several regions of mainland Southeast Asia whereas that of SARS-CoV-like viruses is mainly restricted to China. In agreement with these results, human populations in Laos, Vietnam, Cambodia, and Thailand appear to be much less affected by the Covid-19 pandemic than other countries of Southeast Asia. In the climatic transitional zone between the two ecological niches (southern Yunnan, northern Laos, northern Vietnam, and possibly Hainan and Taiwan), genomic recombination between highly divergent viruses is more likely to occur. Since recombinant viruses can threaten the benefit of vaccination campaigns, these regions should be under surveillance.

Neural stem cell (NSC) based therapies are at the forefront of regenerative medicine strategies to combat illness and injury of the central nervous system (CNS). In addition to their ability to produce new cells, NSCs secrete a variety of products, known as the NSC secretome, that have been shown to ameliorate CNS disease pathology and promote recovery. As pre-clinical and clinical research to harness the NSC secretome for therapeutic purposes advances, a more thorough understanding of the endogenous NSC secretome can provide useful insight into the functional capabilities of NSCs. In this review, we focus on research investigating the autocrine and paracrine functions of the endogenous NSC secretome across life. We also compare the NSC secretome across species, finding signs of conserved parallels between rodent, human and zebrafish NSC secretomes. Throughout development and adulthood, we find evidence that the NSC secretome is a critical component of how endogenous NSCs regulate themselves and their niche. We also find gaps in current literature, most notably in the clinically relevant domain of endogenous NSC paracrine function in the injured CNS. Future investigations to further define the endogenous NSC secretome and its role in CNS tissue regulation are necessary to bolster our understanding of NSC-niche interactions and to aid in the generation of safe and effective NSC-based therapies.

To characterize the fecal microbiota of lactating Bactrian camels, this study employed a random selection of camels, assigning them to three groups: the first parity group, the third parity group, and the fifth parity group. The fecal microbial community of lactating camels was assessed using 16S rRNA amplicon sequencing, and the resulting library was sequenced on an Illumina NovaSeq platform. The first parity group was characterized by Verrucomicrobiaceae as a distinctive bi-omarker, whereas Clostridiaceae exhibited a similar role to the third parity group. In terms of functional analysis, the relative abundance of the Steroid biosynthesis pathway was highest in the first parity group, whereas the fifth parity group demonstrated a higher relative abundance of the Tuberculosis pathway compared to the other groups. The first parity group exhibited the greatest presence of seven types of enzymes, whereas the fifth parity group displayed the highest levels of two specific enzymes. Additionally, a positive association was observed between the relative abundance of the Steroid biosynthesis pathway and Verrucomicrobiaceae. Furthermore, the relative abundance of the Tuberculosis pathway displayed positive correlations with 14 enzymes. In conclusion, this study revealed that different parity was associated with distinct fecal microbial ecologies in lactating Bactrian camels.

This study aimed to determine shifts in microbial populations regarding richness and diversity from the daily use of a popular over-the-counter nasal spray. In addition, the finding of nasal commensal bacterial species that overlap with the oral microbiome may prove to be potential probiotics for the “gateway microbiomes.” Nasal swab samples were obtained before and after using the most popular over-the-counter (OTC) nasal spray in 10 participants aged 18–48. All participants were healthy volunteers with no significant medical histories. The participants were randomly assigned a number by randomizing software and consisted of five men and five women. The sampling consisted of placing a nasal swab atraumatically into the nasal cavity. The samples were preserved and sent to Northwestern University Sequencing Center for whole-genome deep sequencing. After 21 days of OTC nasal spray use twice daily, the participants returned for further nasal microbiome sampling. The microbial analysis included all bacteria, archaea, viruses, molds, and yeasts via deep sequencing for species analysis. The Northwestern University Sequencing Center utilized artificial intelligence analysis to determine shifts in species and strains following nasal spray use that resulted in changes in diversity and richness.

In the modern world where research is taking a huge leap, the collaboration network between authors is also expanding, increasing the probability of different authors coming together to work on the same project, same research paper making them co-authors. In coauthorship, link prediction is used to anticipate new interactions between its members that are likely to occur in the future. Researchers have concentrated their efforts on studying and suggesting methods for providing effective reviews for authors who can collaborate on a scientific endeavor. In order to provide a precise link prediction, a graph database approach is proposed in this paper using nodes to determine most possible co-authors in future. In order to forecast the connections, we preprocessed the data set for the maximum relative contents. A supervised learning approach is used to execute the solution, which includes random forest classifier and logistic regression. The first findings of our technique reveal that the total of two author node’s research collaboration indices has the greatest influence on the performance of supervised link prediction than that of the traditional approach, which stimulates us to conduct further study on employing such a forecast.

We tested the hypothesis that concatemers of ancestral tRNAs gave rise to the 16S ribosomal RNA. We built an ancestral sequence of proto-tRNAs that showed a significant identity of 51.69% and a percentage of structural identity of 0.941 with the 16S ribosomal molecule. We also propose a hypothesis for the emergence of translation.

Solvents are widely-used in all aspects of chemical sciences. One of the disadvantages of conventional solvents is attributed to the adverse impacts they pose on human health and ecological systems. Emerging class of solvents such as ionic liquids have been proposed to alleviate this problem. In this study, aquatic toxicity and biodegradability of two common industrial solvents are compared to those of two ionic liquids. Results from this study highlight the importance of solvent selection considering the information on the toxicity, biodegradability and fate and transport properties of selected solvents altogether.

Elevated carbon dioxide (eCO₂) stimulates wheat grain yield, but simultaneously reduces protein (N) concentration. Also other essential nutrients are subject to change. This study is a comprehensive synthesis of wheat experiments with eCO₂, estimating effects on N, minerals (B, Ca, Cd, Fe, K, Mg, Mn, Na, P, S, Zn), and starch. Analysis was made by i) deriving response functions for the relative effect on element concentration in relation to CO₂ concentration, ii) meta-analysis to test the magnitude and significance of observed effects, and iii) relating CO₂ effects on minerals to effects on N and grain yield. Responses range from zero to strong negative effects of eCO₂ on mineral concentration, with largest reductions for the nutritionally important elements N, Fe, S, Zn and Mg. Together with the positive but small and non-significant effect on starch concentration, the large variation in effects suggests that CO₂-induced responses cannot be explained by a simple dilution model. To explain the observed pattern, uptake and transport mechanisms may have to be considered, along with the link of different elements to N uptake. Our study shows that eCO₂ has a significant effect on wheat grain stoichiometry, with implications for human nutrition in a world of rising CO₂.

Background and Objectives: Cancer as the second leading cause of death in the United States poses a huge healthcare burden. Barriers to access to advanced therapies influence the outcome of cancer treatment. In this study, we examined whether insurance types affect the quality of cancer clinical care regarding access to an important monoclonal antibody, ramucirumab. Materials and Methods: Data for 13,340 cancer patients with Purchased or Medicaid insurance from the All of Us Database were collected for this study. The Chi-square test of proportions was employed to determine the significance of patient cohort characteristics and ramucirumab usage between Purchased and Medicaid insurance groups. The independent t-test was utilized to assess the influences of other determinants on insurance types. Results: Cancer patients who are African American, with lower socioeconomic status, or with lower educational attainment are more likely to be insured by Medicaid. Analysis of survey questions demonstrated the relationship between income and education level with insurance type as Medicaid cancer patients were less likely to receive primary care and specialist physician access and more likely to request lower cost medications. In addition, those with Medicaid insurance were identified to have poorer access to expensive therapeutics like ramucirumab compared to those with Purchased insurance.  Conclusions: The inequities of the US healthcare system are observed for cancer patient care; access to physicians and therapeutics are highly varied and dependent on insurance types. Socioeconomic status determines insurance type, which unfortunately generates a significant impact on cancer treatment and disease outcome.

Every land plant exists in close relationship with microbial communities of several niches: rhizosphere, endosphere, phyllosphere, etc. The growth and yield of potato – a critical food crop worldwide – highly depend on the diversity and structure of bacterial and fungal communities with which the potato plant coexists. The potato plant has a specific part – tubers, and the soil near the tubers as sub-compartment is usually called “geocaulosphere”, which is associated with storage process and tare soil microbiome. Specific microbes can help the plant to adapt to particular environment conditions and resist to pathogens. There is a number of approaches to modulate the microbiome that provides organisms with desired traits during inoculation. The mechanisms of plant–bacterial communication remain understudied, and for the further engineering of microbiomes with particular features the knowledge on potato microbiome should be summarized. The most recent approaches to microbiome engineering include construction of a synthetic microbial community or management of plant microbiome using genome engineering. In this review, the various factors that form the microbiome of potato and the role of these factors in overcoming the negative impact of drought and pathogens are surveyed.

In this paper, we have established Hermite-Hadamard inequalities for r-preinvex functions via fractional integrals.

Prostate cancer is the second leading cause of death in males in America, with advanced prostate cancers exhibiting a 5-year survival rate of only 32%. Castration-resistance is often developed during the course of treatment, though its influences require further understanding. This study explores the human microbiome for its implications in castration-resistance and metastasis in prostate cancer. RNA sequencing data was downloaded for bone and soft tissue biopsies of patients with metastatic castration-resistant prostate cancer. These sequences were mapped to bacterial sequences to yield species-level abundance approximations. Numerous species were found to correlate to the expression of known markers of castration-resistance, including AR, PI3K, and AKT. Castration-resistance-associated signaling pathways were also enriched with these species, including PI3K-AKT signaling and endocrine resistance. For their implications in cancer aggression and metastasis, cancer stem cell markers were further explored for relation to these species. EGFR and SLC3A2 were widely downregulated with greater abundance of most species. Our results suggest that the microbiome is heavily associated with castration-resistance and stemness in prostate cancer. By considering the microbiome’s importance in these factors, we may better understand the highly aggressive and highly invasive nature of prostate cancer, allowing for needed improvement in the treatment of this disease.

Hepatitis E virus (HEV) is a common cause of acute hepatitis worldwide, accounting for approximately 25% of deaths among pregnant women. We previously reported that pregnancy serum facilitates HEV replication in vitro. However, the differences in host cells with HEV infection induced by pregnancy serum and fetal bovine serum (FBS) are unclear. In this study, differentially expressed proteins were identified in HEV-infected hepatoma cells (HepG2) supplemented with different sera by using isobaric tags for relative and absolute quantitation. Proteomic analysis indicated that HEV infection significantly induced 1014 differentially expressed proteins in HEV-infected HepG2 cells when supplemented with FBS compared with pregnancy serum. Further validation by Western blot confirmed that filamin A, heat-shock proteins 70 and 90, Cytochrome c, and Thioredoxin were associated with HEV infection. This comparative analysis provides an important basis to further investigate HEV pathogenesis in pregnant women and HEV replication.

In this work, Gaussian Tribonacci functions are defined and investigated on the set of real numbers $\mathbb{R},$ \textit{i.e}., functions $f_{G}$ $:$ $\mathbb{R}\rightarrow \mathbb{C}$ such that for all $% x\in \mathbb{R},$ $n\in \mathbb{Z},$ $f_{G}(x+n)=f(x+n)+if(x+n-1)$ where $f$ $:$ $\mathbb{R}\rightarrow \mathbb{R}$ is a Tribonacci function which is given as $f(x+3)=f(x+2)+f(x+1)+f(x)$ for all $x\in \mathbb{R}$. Then the concept of Gaussian Tribonacci functions by using the concept of $f$-even and $f$-odd functions is developed. Also, we present linear sum formulas of Gaussian Tribonacci functions. Moreover, it is showed that if $f_{G}$ is a Gaussian Tribonacci function with Tribonacci function $f$, then $% \lim\limits_{x\rightarrow \infty }\frac{f_{G}(x+1)}{f_{G}(x)}=\alpha \ $and\ $\lim\limits_{x\rightarrow \infty }\frac{f_{G}(x)}{f(x)}=\alpha +i,$ where $% \alpha $ is the positive real root of equation $x^{3}-x^{2}-x-1=0$ for which $\alpha >1$. Finally, matrix formulations of Tribonacci functions and Gaussian Tribonacci functions are given. In the literature, there are several studies on the functions of linear recurrent sequences such as Fibonacci functions and Tribonacci functions. However, there are no study on Gaussian functions of linear recurrent sequences such as Gaussian Tribonacci and Gaussian Tetranacci functions and they are waiting for the investigating. We also present linear sum formulas and matrix formulations of Tribonacci functions which have not been studied in the literature.

This review paper gives Excel functions for highly precise Colebrook’s pipe flow friction approximations developed by users. All shown codes are implemented as User Defined Functions – UDFs written in Visual Basic for Applications – VBA, a common programming language for MS Excel spreadsheet solver. Accuracy of the friction factor computed using nine to date the most accurate explicit approximations is compared with the sufficiently accurate solution obtained through an iterative scheme which gives satisfying results after sufficient number of iterations. The codes are given for the presented approximations, for the used iterative scheme and for the Colebrook equation expressed through the Lambert W-function (including its cognate Wright ω-function). The developed code for the principal branch of the Lambert W-function has additional and more general application for solving different problems from variety branches of engineering and physics. The approach from this review paper automates computational processes and speeds up manual tasks.

Fermented foods have long been known to have immunomodulatory capabilities and fermentates derived from the lactic acid bacteria of dairy products can modulate the immune system. We have used skimmed milk powder to generate novel fermentates using Lb. helveticus strains SC234 and SC232 and we demonstrate here that these fermentates can enhance key immune mechanisms that are critical to the immune response to viruses. We show that our novel fermentates SC234 and SC232 can positively impact on cytokine and chemokine secretion, nitric oxide (NO) production, cell surface marker expression, and phagocytosis in macrophage models. We demonstrate that fermentates SC234 and SC232 increase the secretion of cytokines IL-1β, IL-6, TNF-α, IL-27, and IL-10, promote an M1 proinflammatory phenotype for viral immunity via NO induction, decreases chemokine expression of Monocyte Chemoattractant Protein (MCP), increasing cell surface marker expression, and enhance phagocytosis in comparison to their starting material. These data suggest that these novel fermentates have potential as novel functional food ingredients for the treatment, management and control of viral infection.

It has been shown that Human papillomavirus (HPV) infection is associated with several forms of cancer. Additionally, although there are more than 100 types of HPV, more than ten types of it, including types 16 and 18, are considered high-risk. The two proteins that make up the viral capsid of HPV 16 are L1, the major capsid protein, and L2, the minor capsid protein. FDA (The Food and Drug Administration) approved HPV vaccines mostly target L1 and L2 capsid proteins, which facilitate intracellular entry during infection. In this study, it was set out to analyze the creation of phylogenetic relations of L1 nucleic acid sequences of viral isolates. This study also analyzed sequences of three key elements within the amino acid sequences of HPV 16 L1: loops critical for structural stability, nuclear localization signal sequences, and residues implicated in viral attachment. As highlighted by the literature, these elements represent pivotal aspects of viral function. Furthermore, the report highlighted the particular inter-sequence variability within the HPV 16 L1 protein sequences. Overall analysis revealed clustering of sequences primarily due to geographical and characterized by more phylogenetic relatedness within location-specific clusters.

Plant roots host various microorganisms around and inside their roots, known as the root microbiome. To become healthy and productive, plants should keep under surveillance niches around the roots to recognize disease-causing microbes and similarly exploit the services of beneficial microorganisms in nutrient acquisition, stress mitigation and growth promotion. Here we presented the communication strategies between plant roots and root-associated microbes in improving plant growth and yield. Understanding how plant root and root-associated microbes communicate is vital in designing ecofriendly strategies for targeted disease suppression and improved plant growth that will help in sustainable agriculture.

“Pecorino” is a typical semi-hard cheese obtained with raw or heat-treated sheep milk using procedures to valorize the raw material's chemical and microbiological properties. In the present study, using a high throughput method of 16S rRNA gene sequencing, we assessed the evolution of the microbiome composition from milk to Pecorino cheese in artisanal processes using milk from Comisana and Lacaune sheep breeds. The comparative analysis of the bacterial com-munity composition revealed significant differences in the presence and abundance of specific taxa in the milk microbiome of the Comisana and Lacaune breeds. NGS analysis also revealed differences in the curd microbiome related to dairy farming practices, which have a relevant effect on the final structure of the Pecorino-cheese microbiome.

This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of using general purpose digital signal processors. Frist, we obtained the lab-scale backend performance benchmark from simulating beamforming, pulse compression, and Doppler filtering based on MicroTCA chassis using Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the performance of a barebone design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including Open Computing Language.

Based on screening in computational biology and biological in vitro assays, five natural products isolated from extracts of the herbal medicine toad skin, such as cinobufagin (CBFi), bufalin (BFi), arenobufagin (ABFi), telocinobufagin (TBFi), bufotalin (BFTi), were subjected to molecular docking calculations with the use of SARS-CoV-2 main protease (PDB 6LU7 and 7BTF) and top-scoring ligand-receptor complexes were obtained. The results showed that the binding energy of ABFi to the 3CL protein was -17.044kcal/mol, which was higher than CBFi and TBFi. However, the binding energy of ABFi to the RdRp protease was -23.250 kcal/mol, which was much lower than that of CBFi and TBFi, EVEN lower than that of ABFi to the 3CL protein. ABFi also has polar interactions with amino acids such as Glu811, Ser814, Ser681 and Thr680 of RdRp enzyme. The results revealed that ABFi had a moderate inhibitory effect on the cell proliferation of SARS-CoV-2 in vitro, with an inhibition rate of 61.12%, even weaker than Remdesivir. This new discovery provides us with new ideas for in-depth studies on the development of natural products with this class of structural generalizations as inhibitors of SARS-CoV-2, and provides an experimental basis for the next step of mechanistic studies.

A better understanding of background tropospheric ozone delivers multiple benefits. Robust estimates of regional background ozone assist policy makers to understand the limits to reducing ozone by controlling anthropogenic emissions alone and assist in characterising changes in the atmospheric environment and its composition. Long time series of background ozone measurements can also help quantify the influence of human activity on the global and regional atmosphere. Background tropospheric ozone measurements representative of continental air masses are however scarce in Australia, limiting our knowledge of background atmospheric composition. Here we use k-means clustering to identify a cluster of measurements from the long-term monitoring station at Oakdale, NSW which are likely to be representative of background air. The cluster is associated with NOx-limited air masses of continental origin. From this analysis we estimate background ozone representative of Eastern Australia. We find recent (2017-2022) mean ozone mixing ratios of 28.5 ppb and identify a statistically significant (α=0.05) trend in the mean of +1.8 (1.0 – 2.8) ppb/decade. Our methods demonstrate that some long-term monitoring stations within or near urban areas can provide suitable conditions and datasets for regional Global Atmosphere Watch monitoring.

Microbes are the most prevalent and widely-distributed life form on planet Earth. They are also cognitive organisms with memory and superior problem-solving skills that use quantum phase transitions during their remarkably-effective gathering and dissemination of information. This narrative review explores the biological ramifications of human holobionts physically embodying the human microbiome and connecting to the Internet of Microbes (IOM) beyond our body. Within the review, we consider: 1) the ways in which our microbial co-partners exerted control over our ancestors and continue to influence our current human generation, 2) how they mold virtually every key aspect of our life and even remain with our body in death and 3) how inward-looking contemplative tools such as meditation and embodied cognition provide an ideal opportunity to connect to the microbial information super highway and tap the full range of human holobiont capacities.

(1) Introduction: Karstic springs are used worldwide by rural communities as sources of fresh water for human use and livestock survival. In Romania, 1/3 of the population has no direct access to the public water supply. The present study is part of a country-wide project on developing simple, quick and cheap methods for seasonal environmental and microbiological monitoring of karstic springs used as drinking water supply by rural populations. Critical steps for the monitoring workflow consist in the evaluation of water quality and choosing of suitable membrane filters to efficiently capture environmental DNA for further microbial diversity estimation by 16S rRNA gene-based metabarcoding; (2) Methods: Several commercial membrane filters of different composition and pore sizes were tested on the water sampled from three karstic springs in Romania, followed by water chemistry and whole community 16S rRNA gene-based metabarcoding analysis; (3) Results: We found that the different types of applied membrane filters provide a varying recovery of diversities and abundances of both overall and pathogenic bacteria; and (4) Conclusions: The result of the experiment with different filters shows which are the best for amplicon-based metabarcoding monitoring of karst springs.

DIEP-based breast reconstruction necessitates wide undermining at the abdominal donor-site, creating large wound areas. Flap harvesting is usually conducted using electrosurgical dissection devices. This study sought to compare the clinical outcomes in patients after using the PEAK PlasmaBlade (PPB) versus monopolar electrocautery (MPE). This retrospective cohort study included 128 patients with DIEP-based breast reconstruction. Patient characteristics as well as information on the postoperative course were collected and a comparative evaluation was conducted. The MPE group exhibited significantly (p* = 0.0324) higher abdominal drainage volume (351.11 ± 185.96 ml) compared to the PPB group (279.38 ± 183.38 ml). Subgroup analysis demonstrated that PPB significantly reduced postoperative wound fluid in patients with BMI > 30 kg/m² (p* = 0.0284), without prior neoadjuvant chemotherapy (p** = 0.0041), and among non-smokers (p = 0.0046). Furthermore, postoperative pain was significantly (p**** < 0.0001) lower in the PPB cohort. This study confirms the non-inferiority of the PEAK PlasmaBlade to conventional electrocautery for abdominal flap harvesting. The PPB demonstrated advantages, notably reduced drainage volume and lower postoperative pain levels. Recognizing patient subsets that benefit more from the PPB highlights the importance of personalized device selection based on patient characteristics.

The pathogen Cryptococcus neoformans is a major cause of fungal meningitis in humans. As with other melanotic microorganisms associated with human diseases, the cell wall-associated melanin of C. neoformans is a major virulence factor that contributes to its ability to evade host immune responses. The levels of melanin substrate and the regulation of melanin formation could be influenced by the microbiota-gut-brain axis. Moreover, recent studies show that C. neoformans infection causes dysbiosis in the human gut microbiome. In this review, we discuss the potential association between cryptococcal meningitis and the gut microbiome. Additionally, we emphasize the promising prospects of targeting the gut microbiome as a means of diagnosing and treating this debilitating disease.

The human microbiome is an extremely complex ecosystem considering the amount of bacterial species, their interactions, and its variability over time. Here we untangle the complexity of the human microbiome for the Irritable Bowel Syndrome (IBS) that is the most prevalent functional gastrointestinal disorder in human populations. Based on a novel information theoretic network inference model we detect species interaction networks that are functionally and structurally different for healthy and unhealthy individuals. Healthy networks are characterized by a neutral symmetrical pattern of species interactions and scale-free topology versus random unhealthy networks. We detect an inverse scaling relationship between species total outgoing information flow, meaningful of node interactivity, and relative species abundance (RSA). The top ten interacting species are also the least relatively abundant for the healthy microbiome and the most detrimental. These findings support the idea about the diminishing role of network hubs and hubs should be defined considering the total outgoing information flow rather than the node degree. Macroecologically, the healthy microbiome is characterized by the highest total species diversity growth rate, the lowest species turnover, and the smallest variability of RSA for all species. This result challenges current views that posit a universal association between healthy states and the highest absolute species diversity in ecosystems. Additionally, we show how the transitory microbiome is unstable and microbiome criticality is not at the phase transition between healthy and unhealthy states. We stress out the importance of considering interacting pairs versus single node dynamics when characterizing the microbiome and of ranking these pairs in terms of their dynamics. Interactions (i.e. species collective behavior) shape transition from healthy to unhealthy states.\\ The macroecological characterization of the microbiome is useful for diagnostic purposes and disease etiognosis, while species-specific analyses can detect species that are more beneficial leading to personalized design of pre- and pro-biotic treatments and microbiome engineering.

Rice is currently the most important food crop in the world and we are only just beginning to study the bacterial associated microbiome. It is of importance to perform screenings of the core rice microbiota and also to develop new plant-microbe models and simplified communities for increasing our understanding about the formation and function of its microbiome. In order to begin to address this aspect, we have performed the isolation of bacterial strains from the endorhizosphere of two rice cultivars from Venezuela. The validation of plant-growth promoting bacterial activities in vitro has led us to select and characterize 15 isolates for in planta studies such as germination test, endophytism ability and plant growth promotion. Consequently, a set of 10 isolates was selected for the set-up of an endophytic consortium as a simplified model of the natural rice bacterial endomicrobiota. Upon inoculation, the colonization and abundance of each strain within the rice roots was tracked by a culture-independent technique in gnotobiotic conditions in a 30 days period. Four strains belonging to Pseudomonas, Agrobacterium and Delftia genera have shown a promising capacity for colonizing and coexistence in root tissues. On the other hand, a bacterial community taxonomic profiling of the rhizosphere and the endorhizosphere of both cultivars were obtained and are discussed. This study is part of a growing body of research on core crops microbiome and simplified microbiomes, which strengthens the formation process of the endophytic community leading to a better understanding of the rice microbiome.

In this work, two plasmonic structures with two different periodic nanostructures (nanodisk and nanostrip arrays) separated from the gold layer by an ultrathin dielectric Al2O3 layer are proposed, and their optical properties are simulated as 3-dimensional models using COMSOL Multiphysics software tool. The optical responses, such as the amplification of the electric field and the scattering, absorption and extinction cross sections of the two structures, are investigated and compared. The results show that both structures show strong field enhancement in their gap layer, and the structure with the periodic array of metal nanodisks shows stronger field enhancement and larger absorption, extinction, and scattering cross sections in its dipole resonance wavelength, which is defined as a bright plasmonic mode. In addition, some weaker resonant modes are observed for both structures and the reason for their generation is dis-cussed. The analysis of different possible modes in such structures is crucial for their application in various fields.

Addressing the pressing challenge of global warming, reducing greenhouse gas emissions in the transportation sector is a critical imperative. Battery and fuel-cell electric vehicles have emerged as promising solutions for curbing emissions in this sector. In this study, we conducted a comprehensive life cycle assessment (LCA) for typical passenger vehicles, heavy duty trucks and city buses using either proton-exchange membrane fuel cells or Li-ion batteries with different cell chemistries. To ensure accuracy, we supplemented existing studies with data from the literature, particularly for the recycling phase, as database limitations were encountered. Our results highlight that fuel cell and battery systems exhibit large emissions in the production phase. Recycling can significantly offset some of these emissions, but a comparison of the technologies examined revealed considerable differences. Overall, battery electric vehicles consistently outperform fuel cell electric vehicles regarding absolute greenhouse gas emissions. Hence, we recommend prioritizing battery electric over fuel cell vehicles. However, deploying fuel cell electric vehicles could become attractive in a hydrogen economy scenario where other factors, e. g. the conversion and storage of surplus renewable electricity via electrolysis, become important.

Microbiota plays a key role in various body’s functions, physiological, metabolic and immunological processes, through different mechanisms such as the regulation of the development and/or functions of different types of immune cells in the intestines. Several evidences indicate that alteration in the gut microbiota can influence infectious and non-infectious diseases. Bacteria that resides on the mucosal surface or within the mucus layer participate in interactions with the host immune system, and a healthy gut microbiota is essential for the development of mucosal immunity. The immunomodulatory activity of probiotics has been proposed in several bowel disorders or in aging-related dysfunctions. In HIV infected patients, the intestinal immune system is affected and inflammation persists during ART therapy too. Several studies are in progress to investigate the ability of probiotics to modulate epithelial barrier functions, microbiota composition and microbial translocation in HIV infection. This mini-review aims to suggest how the use of probiotics is beneficial not only in maintaining a healthy status but also to improve conditions in HIV subjects.

A total of 473 metabolites were identified from 4 sour cherry genotypes using UPLC-TOF-MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour-cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP &gt; 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites, representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of select sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment were used to test a polygenic selection model. Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. The PS of 161 GWAS significant SNPs in a recent meta-analysis was highly correlated to population IQ (r=0.863) and to the polygenic score of four alleles independently associated with general cognitive ability. High correlations with PISA scores for a subsample were observed.SNP p value predicted correlation to population IQ and factors from the two previous GWAS (r= -.25). Factor analysis produced similar estimates of selection pressure for educational attainment across the three datasets. Polygenic and factor scores computed using the top 20 significant SNPs showed very high correlation to population IQ (r=0.88; 0.9). Similar findings were obtained using 52 populations from another database (ALFRED). The results together constitute a replication of preliminary findings and provide strong evidence for recent diversifying polygenic selection on educational attainment and underlying cognitive ability.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

Abstract Background: Periodontitis is associated with systemic chronic inflammatory diseases. There is limited evidence on the influence of anti-cytokine therapies on the periodontal condition and microbiome in the tooth pocket of such patients, so the aim of this study was to elucidate this issue. Methods: In this observational trial, the periodontal status and the gingival crevicular fluid of 13 patients with different chronic inflammatory diseases were obtained before initiation of anti-cytokine treatment and 14 weeks after. Gingival crevicular fluid was collected for 16S rRNA gene sequencing from a clinically healthy tooth and the deepest measured pocket. Results: In participants with advanced attachment loss at baseline, the clinical attachment level significantly decreased from 2.9 (2.3-3.4) to 2.4 (1.3-3.0) mm (p = 0.04), and the bleeding- on-probing index dropped from 19.4 (10.0-21.0) to 7.3 (6.9-9.9) mm (p = 0.02) without any further periodontal treatment. Shannon’s diversity index significantly increased in the deepest pockets of patients (p = 0.039). Conclusion: The data showed alterations in diversity of the subgingival microbiome and improvement of periodontal parameters over the course of the study, implying a shift towards a healthier condition after starting anti-cytokine therapy. Additional investigations are needed to analyze whether the administration of selective biologicals can improve periodontal conditions in patients with or without chronic inflammatory diseases.

The detection of Fasciola eggs in ruminant fecal samples typically occurs around 15 weeks post-infection during patent infections. The recent introduction of coproantigen ELISA (cELISA) diagnostics, which capture antigenic enzymes in fecal material, holds promise for monitoring Fasciola fecal egg count (FFEC) to implement control programs, particularly targeted treatments. This study compared two study groups, those with positive FFEC (FFEC+ve) and negative FFEC (FFEC-ve), to assess the sensitivity of Flukefinder sedimentation and a cELISA kit. This study reports that the coproantigen ELISA detection limit was 4.5 eggs per gram (epg) for a 100% positivity rate. Additionally, a moderate, statistically significant positive correlation (r²=0.716, p-value < 0.01) and an odds ratio of 1.96 (p-value < 0.01) were observed between FFEC and Fasciola coproantigen from cELISA. This implies that for every single unit increase in FFEC, there is a 96% likelihood of obtaining a higher optical density (OD) reading from the cELISA test. The results suggest that cELISA can complement fecal sedimentation tests, serving as a valuable tool for detecting cattle with high FFEC. This capability facilitates targeted treatment strategies, thereby aiding in the control and prevention of the spread of fasciolosis within the studied area.

With the growing of university chemistry experiment projects, scientific research personnel, specialized equipment, laboratory accident is increasing yearly. And accident data lacks a safety platform to store related information and cannot be guaranteed for efficient conditional sharing. To solve these problems, we designed a laboratory accident system to store, share related data and predict risk level. In this paper, we manually collected chemistry laboratory accidents by python software and class assignments, then analyses risk factor variables using Spsspro, finally established a prediction model using Stata. We intended to register laboratory related data into proposed chemistry accident system based on data ownership safety architecture. The chemistry accident system can break data barriers using confirmation and authorization key technology to trace non-tampered data source in real time when emergency accident happens. Meanwhile, our proposed system can use our designed accident risk model to predict risk level of any experiment project. It can also recommend appropriate safety education models.

Binary star DataBase (BDB) is the database of binary/multiple systems of various observational types. BDB contains data on physical and positional parameters of 260,000 components of 120,000 stellar systems of multiplicity 2 to more than 20, taken from a large variety of published catalogues and databases. We describe the new features in organization of the database, integration of new catalogues and implementation of new possibilities available to users. The development of the BDB index-catalogue, Identification List of Binaries, is discussed. This star catalogue provides cross-referencing between most popular catalogues of binary stars. We describe ideas and methods for reliable cross-identification of different entities (systems, pairs, components) in binary and multiple stellar systems.

Illumina and nanopore sequencing technologies are powerful tools that can be used to determine the bacterial composition of complex microbial communities. In this study, we compared nasal microbiota results at genus level using both Illumina and nanopore 16S rRNA gene sequencing. We also monitored the progression of nanopore sequencing in the accurate identification of species, using pure, single species cultures, and evaluated the performance of the nanopore EPI2ME 16S data analysis pipeline. Fifty-nine nasal swabs were sequenced using Illumina MiSeq and Oxford Nanopore 16S rRNA gene sequencing technologies. In addition, five pure cultures of relevant bacterial species were sequenced with the nanopore sequencing technology. The Illumina MiSeq sequence data were processed using bioinformatics modules present in the Mothur software package. Albacore and Guppy base calling, a workflow in nanopore EPI2ME and an in house developed bioinformatics script were used to analyze the nanopore data. At genus level, similar bacterial diversity profiles were found, and five main and established genera were identified by both platforms. However, probably due to mismatching of the nanopore sequence primers, the nanopore sequencing platform identified Corynebacterium in much lower abundance compared to Illumina sequencing. Further, when using default settings in the EPI2ME workflow, almost all sequence reads that seem to belong to the bacterial genus Dolosigranulum and a considerable part to the genus Haemophilus were only identified at family level. Nanopore sequencing of single species cultures demonstrated at least 88% accurate identification of the species at genus and species level for 4/5 strains tested, including improvements in accurate sequence read identification when the basecaller Guppy and Albacore, and when flowcell versions R9.4 and R9.2 were compared.

Gestational diabetes mellitus (GDM) triggers alterations in the maternal gut microbiome. Alongside metabolic shifts, microbial products may impact clinical factors and influence pregnancy outcomes. Here, we performed two separate analyses to integrate the maternal microbiome-metabolomic differences from a subset of the “Choosing Healthy Options in Carbohydrate Energy” (CHOICE) study. Women diagnosed with GDM were randomized to a diet higher in complex carbohydrates (CHOICE, n=18, 60% complex carbohydrate/25% fat/15% protein) or a conventional GDM diet (CONV, n=16, 40% carbohydrate/45% fat/15% protein). All meals were provided, diets were eucaloric, and fiber content was similar. CHOICE diet was associated with increases in TMAO, lysophosphotidylcholines, indoxyl sulfate, and several triglyceride (TG) species, while CONV diet was associated with higher plasma hippuric acid, aspartic acid, betaine, glutamic acid, indole propionic acid, and indoleacetic acid, suggesting that differences in lipid metabolism and tryptophan utilization pathways are linked to specific maternal diets. We also identified two latent metabolic groups not associated with either diet treatment: one metabolome associated with higher fasting glucose, and the other associated with higher fasting TGs after 7 weeks on either diet. Our study underscores the importance of utilizing dietary approaches to optimize maternal-fetal health outcomes in GDM treatment.

Abstract: Background/Objectives: There are indications that the microbial composition of the maternal mucosal surfaces is associated with adverse events during pregnancy. The aim of this review is to investigate the link between vaginal microbiome alterations and gestational com-plications risk. Methods: This comprehensive literature review was performed using Medline and Scopus databases. The following search algorithm was used "Pregnancy Complications"[Mesh] AND (Vagin*) and after literature screening 44 studies were included in the final review. Results: The studies that were included investigated the association between vaginal microbial composi-tion and preterm birth, miscarriage, preeclampsia, ectopic pregnancy, gestational diabetes mellitus, chorioamnionitis and preterm premature rupture of membranes. In most of the studies, it was well established that increased microbial diversity is associated with these conditions. Also, the depletion of Lactobacillus species is linked to most of the gestational complication, while the increased relative abundance and especially L. crispatus may exerts a protective effect in favor of the pregnant woman. Several pathogenic taxa including Gardnerella, Prevotella, Sneathia, Bac-terial Vaginosis-Associated Bacteria-2, Atopobium and Megasphera seem to be correlated to higher maternal morbidity. Conclusions: Vaginal microbiome aberrations seem to have an as-sociation with pregnancy related adverse events, but more high-quality homogenous studies are necessary to reliably verify this link.

Microbiome First Medicine is a suggested 21st century healthcare paradigm that prioritizes the entire human, the human superorganism, beginning with the microbiome. To date, much of medicine has protected and treated patients as if they were a single species. This has resulted in unintended damage to the microbiome and an epidemic of chronic disorders [e.g., noncommunicable diseases and conditions (NCDs)]. Along with NCDs came loss of colonization re-sistance, increased susceptibility to infectious diseases, and increasing multimorbidity and polypharmacy over the life course. To move toward sustainable healthcare, the human micro-biome needs to be front and center. This paper presents microbiome-human physiology from the view of systems biology regulation. It also details the ongoing NCD epidemic including the role of existing drugs and other factors that damage the human microbiome. Examples are provided for two entryway NCDs, asthma and obesity, regarding their extensive network of comorbid NCDs. Finally, the challenges of ensuring safety for the microbiome are detailed. Under Microbiome First Medicine and considering the importance of keystone bacteria and critical windows of development, changes in even a few microbiota-prioritized medical decisions could make a significant difference in health across the life course.

Over the last 15 years, the advent of high-throughput ‘omics’ techniques has revealed the multiple roles and interactions occurring among hosts, their microbial partners and their environment. This microbiome revolution has radically changed our views of biology, evolution and individuality. Sitting at the interface between a host and its environment, the microbiome is a relevant yet understudied compartment for ecotoxicology research. Various recent works confirm that the microbiome reacts to and interacts with contaminants, with consequences for hosts and ecosystems. In this paper, we thus advocate for the development of a “microbiome-aware ecotoxicology” of organisms. We emphasize its relevance and discuss important conceptual and technical pitfalls associated with study design and interpretation. We identify topics such as functionality, quantification, temporality, resilience, interactions and prediction as major challenges and promising venues for microbiome research applied to ecotoxicology.

Molecular markers, including Simple Sequence Repeat (SSR), Single Nucleotide Polymorphism (SNP), and Intron Length Polymorphism (ILP), are widely utilized in crop improvement and population genetics studies. However, these marker resources remain insufficient for Musa species. In this study, we developed genome-wide SSR, SNP, and ILP markers from Musa and its sister species, creating a comprehensive molecular marker repository for the improvement of Musa species. This database contains 2115474 SSR, 63588 SNP, and 91547 ILP markers developed from thirteen Musa species and two of its relative species. We found that 77% of the SSR loci are suitable for marker development; 38% of SNP markers originated from the genic region, and transition mutations (C↔T; A↔G) were more frequent than transversion. The database is freely accessible and follows a ‘three-tier architecture,’ organizing marker information in MySQL tables. It has a user-friendly interface, written in JavaScript, PHP, and HTML code. Users can employ flexible search parameters, including marker location in the chromosome, transferability, polymorphism, and functional annotation, among others. These distinctive features distinguish the Musa Marker Database (MMdb) from existing marker databases by offering a novel approach that is tailored to the precise needs of the Musa research community. Despite being an in silico method, searching for markers based on various attributes holds promise for Musa research. These markers serve various purposes, including germplasm characterization, gene discovery, population structure analysis, and QTL mapping.

This publication aims to create 4K UHD video sequences with a specific focus on smart cities and transport. The created database will be accessible to all experts in the field and can be further used for research purposes. All reference video sequences will be transcoded into different quality settings. The resolution, compression standard, and bitrate will be changed. The work will aim to find out the best combination of video parameters from the measured values. Thanks to the overall evaluation, we will ensure for each single video sequence the quality with the best experience for the providers that will offer the service. The database will also be available with its objective and subjective ratings, with dynamicity information characterized by spatial and temporal information. After, It will be possible to compare the results of the subjective evaluation of a selected sample of our respondents with the work of other researchers who can evaluate with a different sample of evaluators.

The COST Action ‘PED-EU-NET’, JPI Urban Europe, IEA EBC Annex 83 and EERA JP Smart Cities can be considered as the main promoters and pioneer initiatives of the research on Positive Energy Districts (PEDs), that collaborated to develop a tool called 'PED Database'. The tool aims to map, filter, sort, and compare PED experiences, providing a balanced overview of the technological and non-technological solutions adopted in different PED projects and case studies around Europe and beyond. The paper aims to present the collaborative step-by-step process leading to the PED DB implementation, describing the adopted methodology, the current results and potentials of the online version platform and introducing its future possible developments towards a more user-friendly and stakeholders-tailored tool.

(1) Background: National health system databases represent one of the most obvious sources of information about epidemiology of adverse drug reactions including drug-induced allergy and anaphylaxis. (2) Methods: Retrospective analysis of data from national database of pharmacovigilance in the Russian Federation (analyzed period 02.04.2019 - 21.06.2023) was performed. The prevalence of anaphylactic reactions (ARs) was determined, the structure of drugs involved was estimated together with patients’ characteristics. (3) Results: ARs were reported in 8.3% of drug-induced allergic reactions (2304/27,727), mean age of patients was 48.2 ± 15.8 years, 53.2% were females. Main causative groups of drugs were antibiotics, ABs (44.62%), local anesthetics, (19.97%), and cyclooxygenase (COX)-inhibitors (10.07%). Fatal ARs was reported in 9.5% (218/2304), mean age 48.0 ± 16.7 years, 56.2% females. Pediatric population accounted for 5.8% (133/2304), mean age 11.8± 4.5 years, 51.9% females. Elderly population accounted for 2.8% (65/2304), mean age 73.0±5.3 years, 43.5% (27/65) females. ABs were the leading causative groups of ARs in the elderly (40%), children (42.86%), and among fatal cases (50%). (4) Conclusions: ARs accounted for 8.3% of all drug-induced allergic reactions, and ABs were the most common causative agents. Females predominated in all groups except elderly patients.

This research deals with the possibility for construction of the database on the braking friction coefficient for actual roads from the viewpoint of traffic safety especially for automated driving such as level 4 or higher. In an automated driving such levels, the controller needs to control the vehicle, but the road surface condition, especially the road friction coefficient on wet roads, snowy or icy roads, changes greatly, and in some cases, changes by almost one order. Therefore, it is necessary for the controller to constantly collect environment information such as the road friction coefficients and prepare for emergencies such as obstacle avoidance. However, at present, the measurement of the road friction coefficients is not systemically performed, and a method for accurately measuring has not been established. In order to improve this situation, this study examines a method for continuously measurement for the road friction characteristics such as μ-s characteristics.

Boulder dynamics may provide essential data for the coastal evolution and hazards assessment and can be focused as a proxy for the onshore effect of intense storm waves. In this work, detailed observations of currently available satellite imagery of the Earth surface allowed to identify several coastal boulders displacements in the Southern Apulia coast (Italy), in a period between July 2018 and June 2020. Field surveys confirmed the displacements of several dozens of boulders up to several meters in size, also allowing the determination of the initial position for many of them. Archive weather analyses identified two possible causative storms during the same period, and calculations based on analytical equations are found in agreement with the displacement by storm waves for most of the observed boulders. The results help to give insights about the onshore effect of high storm waves on the coastal hydrodynamics and the possible future flooding hazard in the studied coast.

This study investigates the vertical structure of the dynamical properties of a warm-core ring in the Gulf of Mexico (Loop Current ring) using glider observations. We introduce a new method to correct the glider’s along-track coordinate which is, in general, biased by the unsteady relative movements of the glider and the eddy, yielding large errors on horizontal derivatives. Here, we take advantage of the synopticity of satellite along-track altimetry to apply corrections on the glider’s position, by matching in situ steric height with satellite-measured sea surface height. This relocation method allows to recover the eddy’s azimuthal symmetry, to precisely estimate the rotation axis position, and to compute reliable horizontal derivatives. It is shown to be particularly appropriate to compute the eddy’s cyclo-geostrophic velocity, relative vorticity, and shear strain, which are otherwise out of reach when using the glider’s raw traveled distance as an horizontal coordinate. The Ertel potential vorticity (PV) structure of the warm core ring is studied in details, and we show that the PV anomaly is entirely controlled by vortex stretching. Sign reversal of the PV gradient across the water column suggests that the ring might be baroclinically unstable. The PV gradient is also largely controlled by gradients of the vortex stretching term. We also show that the ring’s total energy partition is strongly skewed, with available potential energy being 3 times larger than kinetic energy. The possible impact of this energy distribution on the Loop Current rings longevity is also discussed.

The phylogenetic relationships among the Peninsular Malaysian orchid genus Coelogyne were studied by morphological characteristics and by sequencing the internal transcribed region (ITS) from the nuclear ribosomal DNA (nrDNA). Coelogyne is a large genus of about 200 species distributed in pantropical areas from the Himalayas, Sri Lanka, India, Southern China and throughout South East Asia to Papua New Guinea. The widely accepted previous classification system was exclusively based on floral morphology. There were very few molecular systematic studies of Coelogyne done in Peninsular Malaysia thus far. In this study, 59 Coelogyne taxa were collected from throughout Peninsular Malaysia and 57 of them were identified to the species level. To study the phylogeny of this genus, morphological characters were utilized together with molecular evidences to generate the systematic hypotheses. Cluster analysis was performed using both the vegetative and floral characters. The results showed that three sections of Peninsular Malaysian Coelogyne, namely Longifoliae, Speciosae and Fuliginosae were sister groups which were more closely related by forming one clade than they were with the other sections. Another clade consisted of four other sections, namely Flaccidae, Coelogynae, Tomentosae and Verrucosae. Molecular phylogenies obtained by using the Neighbour Joining method revealed the close relationship between the sections Tomentosae and Verrucosae, whereas usage of the Maximum Likelihood method demonstrated that three sections namely Longifoliae, Speciosae and Fuliginosae were sister groups since they formed a single clade.

Background: The Coronavirus Disease 2019 (COVID-19) pandemic presented a new challenge in modern medicine. The development of vaccines was followed by massive population vaccinations. A few reports on post-vaccination allergic reactions have made patients and medical personnel uneasy as to anti-COVID-19 vaccines’ allergising potential. Most of the studies in this area to date have been small, and some that were based on global databases skipped most of the allergic diseases and concentrated only on anaphylaxis. We aimed to analyse the incidence of serious allergic reactions based on the EudraVigilance (EV) database, regardless of the reported symptoms and allergy mechanism. Methods: The total number of administrated vaccine doses was extracted on the 5th October 2023 from Vaccine Tracker and included all administrations since vaccinations began in the European Economic Area (EEA). Data on serious allergic reactions to COVID-19 vaccines was extracted from the EudraVigilance database with the same time point. The code names of 147 allergic symptoms or diseases were used. Results: The frequency of serious allergic reactions per 100,000 administered vaccine doses was 1.53 for Comirnaty, 2.16 for Spikevax, 88.6 for Vaxzevria, 2.11 for Janssen, 7.9 for Novavax, 13.3 for VidPrevtyn Beta and 3.1 for Valneva. The most prevalent reported reactions were oedema (0.46) and anaphylaxis (0.40). Only 6% of these reactions were delayed hypersensitivity-oriented. Conclusions: The overall frequency of potential serious allergic reactions to COVID-19 is very rare. Therefore, COVID-19 vaccines seem to be safe for human use. The lowest frequency of allergic reaction was observed for Comirnaty and the highest for Vaxzevria.

The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have abnormally hard outer shell (low M disorder; i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far was found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2 especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 amd later in Omicron, is associated with attenuation according to the Shell-Disorder-Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

Maintaining the high overall health of farmed animals is a central tenant of their well-being and care. Intense animal crowding in aquaculture promotes animal especially in the absence of straightforward methods for monitoring their health. Here, we used bacterial 16S ribosomal RNA gene sequencing to measure population dynamics occurring during P. salmonis outbreaks. Our findings revealed a complex bacterial community consisting of a previously undescribed core pathobiome. Notably, we detected Aliivibrio wodanis and Tenacibaculum dicentrarchi on the skin ulcers of salmon infected with P. salmonis, while Vibrio spp. were enriched on infected gills. The prevalence of these co-occurring networks indicates the influence that coinfection plays in P. salmonis pathogenicity.

: Cattle farming is an ancient practice, with roots in the early Neolithic era that has retained its status in the food industry today, with global beef market revenue amounting to $385.7B, as of 2018. Hence, cattle maintenance is naturally essential to cater to nutritional requirements of modern civilization. This extensive review aims to provide a holistic overview of cattle microbiome, analysing the native microbial composition within respiratory tract, gastrointestinal tract, reproductive tract, and skin. The dysbiosis associated with various diseases such as bovine respiratory disease, bovine digital dermatitis, mastitis, Johne's disease, uterine diseases (metritis and endometritis) and metabolic disorders (ruminal acidosis and ketosis) has been discussed. Moreover, various non-antibiotic microbial therapies including phage therapy, prebiotics and probiotics have been examined as potential means to reduce disease-associated dysbiosis. In general, this review highlights the importance of the microbiome in maintenance of health in cattle and its potential in alleviating bovine diseases, with an aim to enhance cattle health and production.

The mammalian gut ecosystem plays critical roles in multiple functions related to health and homeostasis. In many cases, disturbances in the gut ecosystem are associated with a large number of metabolic and chronic diseases and disorders such as diabetes, cancer, and obesity. A diverse community of microorganisms ranging from viruses to bacteria comprise the gut microbiota, which is often considered as an organ in itself. Recent studies have profiled the influence of lifestyles and dietary behavior by comparing the gut microbiome of populations with different cultural underpinnings. In this review, we provide an overview of the studies which report the influence on the gut microbial composition of dietary and lifestyle patterns in different contexts such as western industrialized countries and indigenous cultures (corresponding to different lifestyle gradients such as hunter-gatherers and pastoralists) and how this association may influence health and disease.

Background and Objectives: In this current state, Type 2 Diabetes Mellitus (T2DM) is more prevalent in the population, and metformin is used as a first-line medication for treating it. There was up surge in the utilization of alternative therapies in the management of diabetes. Especially in diabetes, Herbal medicines are considered safe and reliable by majority of the population. Aim: The purpose of this research is aimed to estimate the safety and efficacy of Polyherbal Metabolite Compounds (PHMC) capsules in adults with T2DM. Materials and Methods: In this study, 60 T2DM patients aged 18-60 years were randomly assigned to Groups A (30) receiving Metformin 500 mg twice a day after food and Group B (30) receiving PHMC capsule 500 mg twice a day after food in a prospective, randomized and open-label clinical study. The in-silico simulation study was performed to selected plants major compounds on target protein Insulin-like Growth Factor-1 (1K3A). Result: The PHMC is found to be safe and effective in the management of T2DM. The FBS, PPBS and HbA1c were significantly lowered (p

Our study reviews the significance of archaeological parks in the tourism sector, with a specific focus on how digital presence and visitor feedback impact their cultural and touristic appeal. Utilizing statistical analyses such as regression and cluster analysis on data sourced from both Hungarian and Western European parks, the research scrutinizes TripAdvisor and Google ratings, alongside the volume of photographs and reviews. The findings highlight a modest correlation between digital visibility and overall visitor ratings, underscoring the complex relationship between online engagement and the quality of visitor experience. Notably, the cluster analysis identified two distinct groups, signifying diverse levels of visitor engagement and digital visibility across the parks. The conclusions drawn advocate for a comprehensive strategy to enhance visitor experiences, emphasizing the integration of digital engagement with the promotion of the parks cultural and historical values. By exploring the influence of digital presence on the appeal of archaeological parks, our study sheds light on the evolving interface between urban studies and digital heritage, highlighting how digital tools and online platforms are becoming increasingly integral in shaping the perceptions and experiences of urban cultural sites.

Gut microbiota is a complex and dynamic ecosystem that influences various aspects of human health. Unfortunately, there is a lack of literature highlighting the importance of gut microbiome especially in diabetes management. This paper performs bibliometric analysis to establish the rising interest of researchers in this area and the importance of gut microbiota in diabetes management. Subsequently, the study performs a narrative review to provide an overview of the gut microbiota consisting of bacteria, archaea, fungi, and viruses, and its diversity, composition, and variation among individuals. The paper further discusses the role of the gut microbiota in different diseases, including Clostridium difficile infection, behavioral disorders, cancer, obesity, diabetes, atherosclerosis, and inflammatory bowel disease, among others. It emphasizes the link between gut dysbiosis (imbalanced gut microbiota) and the development of chronic metabolic disorders. Additionally, the paper discusses the factor negatively impacting the gut microbiota. The paper concludes by explaining the mechanistic abnormalities that link dysbiosis to type 2 diabetes, including changes in short-chain fatty acid production, amino acid metabolism, bile acid regulation, and the production of specific bacterial products. Thus, the paper highlights the importance of understanding gut microbiota and related mechanisms for developing therapeutic interventions targeting the gut microbiota.

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with themselves, their environment, and hosts via metabolites and signaling molecules. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metagenomics methods, and modeling formalisms. Furthermore, the review explains model building, examples of microbiome model applications for prediction, optimization, and control. It concludes with guidelines, software, and repositories for modeling. Each section provides entry-level information, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

Background: To prioritize the development of antiviral compounds, it is necessary to compare their relative preclinical activity and clinical efficacy. Methods: We reviewed in vitro, animal model, and clinical studies of candidate anti-coronavirus compounds and placed extracted data in an online relational database. Results: As of July 2020, the Coronavirus Antiviral Research Database (CoV-RDB; covdb.stanford.edu) contained &gt;2,400 cell culture, entry assay and biochemical experiments, 240 animal model studies, and 56 clinical studies from &gt;300 published papers. SARS-CoV-2, SARS-CoV, and MERS-CoV account for approximately 85% of the data. Approximately 75% of experiments involved compounds with a known or likely mechanism of action, including receptor binding inhibitors and monoclonal antibodies (20%); viral protease inhibitors (18%); polymerase inhibitors (9%); interferons (8%); fusion inhibitors (8%); host endosomal trafficking inhibitors (7%); and host protease inhibitors (5%). For 724 compounds with a known or likely mechanism, 95 (13%) are licensed in the US for other indications, 72 (10%) are licensed outside the US or are in human trials, and 557 (77%) are pre-clinical investigational compounds. Conclusion: CoV-RDB facilitates comparisons between different candidate antiviral compounds, thereby helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development.

Concrete being one of the most frequently used construction materials in the field of construction. The use of concrete has increased with the passage of time as the more and more construction activities are taking place around the globe. Different materials have been added in to the concrete mix to provide the concrete more strength and make it more durable and long lasting. This paper looks into a detailed comparison of concrete strength when casted with in the presence of carbon fibers, steel fibers and glass fibers. The compressive strength for cubes and cylinder with carbon fibers is the highest as compare to steel fibers as well as glass fibers. The compressive strength of concrete is measured on 3 day, 7 day, 14 day and 28 day strength. The compressive strength of cube on 28th day strength is 37.52 MPa for carbon fiber steel, for steel fiber it is 34.22 MPa and with glass fiber the strength is 29.335 MPa whereas the compressive strength of cylinder with carbon fibers the 34.88 MPa, with steel fiber it is 34.22 MPa and with glass fiber the strength is 27.447 MPa. For the cubes the maximum difference between different fibers inducted concrete sample is 28% approximately and for cylinder it is 27%, respectively. On the other hand, the tensile strength of concrete was also gained with the carbon fiber. It was determined that carbon fiber provided about 16% and 12.8% tensile strength higher than glass and steel fibers respectively.

Effective oral care is important to maintain a high quality of life. Therefore, plaque control can prevent the development and recurrence of periodontitis. Brushing with a toothbrush and toothpaste is a common way to remove plaque; however, excessive brushing or brushing with abrasive toothpaste can cause wear and tear on the dental crown. Hence, we aimed to quantitatively compare the plaque-removal efficiency and tooth wear of toothbrushes using bioelectric effect (BE) with those of mechanical electric toothbrushes. To generate the BE signal, an electronic circuit was developed and embedded in a toothbrush. Further, typodonts were coated with cultured artificial plaques and placed in a brushing simulator. A toothpaste slurry was applied, and the typodonts were eluted with tap water after brushing. The plaques of the typodonts were captured, and the images were quantified. For the tooth wear experiment, polymethyl methacrylate disk resin blocks were brushed twice a day, and the thickness of the samples was measured. Subsequently, statistical differences between the experimental toothbrushes and typical toothbrushes were analyzed. The BE toothbrush had a higher plaque-removal efficiency and could minimize tooth wear. This study suggests that the application of BE may be a new solution for oral care.

To investigate the bioactivities of fresh garlic and its processed product, black garlic, we conducted comparative analyses of antioxidant, anti-inflammatory, innate immune activation and anti-cancer activities, in addition to chemical composition (sugar, amino acid, polyphenol contents) of these materials. Simultaneous assay using neutrophil-like cells showed that fresh garlic exhibited antioxidant and innate immunostimulatory activities, whereas black garlic displayed a potent anti-inflammatory effect. The antioxidant activity index was correlated with phenol and flavonoid contents, while the innate immunostimulatory activity was correlated with fructan content. Furthermore, some black garlics with low fructose content were found to inhibit the proliferation of UM-UC-3 cancer cells, while other black garlics rich in fructose increased UM-UC-3 cell proliferation. It was shown that the thermal processing steps of fresh garlic could change the composition of sugars, antioxidants, and amino acids, which have different effects on neutrophil-like cells and UM-UC-3 cells, as well as on bioactivities.

Molecular mechanisms associated with the pathogenesis of Vesicular stomatitis virus (VSV) in livestock remain poorly understood. Several studies have highlighted the relevant role of macrophages in controlling the systemic dissemination of VSV during infection in different animal models, including mice, cattle and pigs. To gain more insight on the molecular mechanisms used by VSV to impair the immune response in macrophages, we used microarrays to determine the transcriptomic changes produced by VSV infection in primary cultures of porcine macrophages. The results indicated that VSV infection induced the massive expression of multiple anorexic, pyrogenic, proinflammatory and immunosuppressive genes. Overall, the interferon (IFN) response appeared suppressed, leading to the absence of stimulation of interferon-stimulated genes (ISG). Interestingly, VSV infection promoted the expression of several genes known to downregulate the expression of IFNb. This represents an alternate mechanism for VSV control of the IFN response, beyond the recognized mechanisms mediated by the matrix protein. Although there was no significant differential gene expression in macrophages infected with a highly virulent epidemic strain compared to a less virulent endemic strain, the endemic strain consistently induced higher expression of all upregulated cytokines and chemokines. Collectively, this study provides novel insights into VSV molecular pathogenesis and immune evasion that warrants further investigation

Although researchers have proposed various indentation size effect (ISE) models, these models often involve different form and number of parameters that can make our wonder which is the best in existed ISE models. Three types of ISE test data, namely, normal ISE, reverse ISE and transition of normal to reverse ISE, are used to evaluate the sixteen ISE models. The comparatively study indicates that H-J, N-G-Fs, N-G-H, N-G-A and N-G-Qs models can accurately predict the normal ISE. The reason for this is that the friction stress that is not related to dislocation activities or the indentation size effect of plastic zone has been introduced into these models. Therefore, these two factors should be considered in future ISE models. The sixteen ISE models are originally proposed to describe the normal ISE of different materials. However, to our surprise, some of these models are able to capture the reverse ISE and the transition of normal to reverse ISE of different materials. The determination coefficients (DC) of the sixteen ISE models are also determined for different materials. For reverse ISE, the highest DC value for NiCSi, TC4 and PED Ni are given by the EXP, N-G-Fs and N-G-A models, respectively. For the transition of normal to reverse ISE, the N-G-YC, N-G-Fs, and N-G-H models produce the maximum DC for ZrO2, Cu and Y2O3-ZrO2, respectively. Moreover, the mean DC of the N-G-Fs model is the maximum among the sixteen ISE models, followed by the N-G-H model, but they cannot accurately predict the reverse ISE. Therefore, the N-G-Fs and N-G-H models should be further modified to accurately predict the reverse ISE.

Drosophila melanogaster serves as a important research model both for genetic investigations and for the study of metal toxicity, facilitating the elucidation of physiological mechanisms comparable to those of human organisms. In our research, we evaluated the toxicity effect resulting from exposure to various concentrations of lead and copper on the prolificity rates throughout the life cycle (egg-adult) of four genotypes of Drosophila melanogaster: wild-type (control), white, brown, and white-vestigial. During our study, the prolificity rates were examined across three repetitions under the impact of exposure to concentrations of 0.50, 1.00, 2.00, and 4.00 mM of copper (CuSO₄) and lead (Pb(C₂H₃O₂₎₂). Prolificity rates throughout the life cycle exhibited variations as a direct consequence of genetic factors, the concentration of exposure, and the specific type of metal, either copper or lead. The mutant white-vestigial genotype revealed an IC₅₀ concentration for prolificity inhibition at lower doses of 2.00 mM for copper and 4.00 mM for lead, in contrast to the control genotype (wild-type), which exhibited an inhibition concentration rate >IC₅₀ of 4.00 mM only in the case of copper. Our results concluded that the (i) dose influences the prolificity rate in a directly proportional manner, (ii) comparative analyses between copper and lead revealed that copper displayed toxicity across all genotypes within the concentration range of 0.50 mM to 2.00 mM. In contrast, lead exhibited toxicity within the concentration range of 1.00 mM to 4.00 mM, highlighting a (iii) more acute toxicity characteristic in the case of copper. Thus, the results of this research reflect the importance of using Drosophila melanogaster as a genetic model in the comparative study of the interaction between genetic factors and the toxicity of metals, offering significant insights into monitoring their impact and defining the maximum permissible doses on organisms.

Fermented foods and ingredients, including fermentates derived from lactic acid bacteria (LAB) in dairy products, can modulate the immune system. Here we describe the use of reconstituted skimmed milk powder to generate novel fermentates from Lactobacillus helveticus strains SC232, SC234, SC212, and SC210, and from Lacticaseibacillus casei strains SC209 and SC229, and demonstrate using in vitro assays that these fermentates can differentially modulate cytokine secretion by bone marrow derived dendritic cells (BMDCs) when activated with either the viral ligand, loxoribine, or an inflammatory stimulus, lipopolysaccharide. Specifically, we demonstrate that SC232 and SC234 increase cytokines IL-6, TNF-α, IL-12p40, IL-23, IL-27 and IL-10, and decreased IL-1β in primary bone marrow derived dendritic cell (BMDCs) stimulated with a viral ligand. In contrast exposure of these cells to SC212 and SC210 resulted in increased IL-10, IL-1β, IL-23, and decreased IL-12p40 following activation of the cells with the inflammatory stimulus LPS. Interestingly SC209 and SC229 had little or no effect on cytokine secretion by BMDCs. Overall, our data demonstrates that these novel fermentates have specific effects and can differentially enhance key immune mechanisms that are critical to viral immune responses, or can suppress responses involved in chronic inflammatory conditions, such as Ulcerative Colitis (UC), and Crohn’s disease (CD).

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 minutes) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA 3 regulated store, given the observation of increased Ca2+ release inducible by low dose tBHQ. Intriguingly, longer-term (&gt;12 hours) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools, yet decreased Ca2+ release responses from tBHQ-sensitive SERCA 3 pool. Our results reveal differential effects of CDN1163 on Ca2+ stores regulated by distinct SERCA isoforms, prompting the need for careful interpretation of the compound’s effects, particularly in cells expressing multiple SERCA isoforms.

The aim of this paper is to evaluate the surface concentration of nitrogen dioxide (NO2) inferred from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (S5P/TROPOMI) NO2 tropospheric column densities over Central Europe for two time periods, the summer of 2019 and the winter of 2019-2020. Simulations of the NO2 tropospheric vertical column densities and surface concentrations from the LOng-Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) chemical transport model are also applied in the methodology. More than two hundred in-situ air quality monitoring stations, reporting to the European Environment Agency (EEA) air quality database, are used to carry out comparisons with the model simulations and the space-borne inferred surface concentrations. Stations are separated into seven types (urban traffic, suburban traffic, urban background, suburban background, rural background, suburban industrial and rural industrial) in order to examine the strengths and shortcomings of the different air quality markers, namely the NO2 vertical column densities and NO2 surface concentrations. S5P/TROPOMI NO2 surface concentrations are inferred by multiplying the fraction of the satellite and model NO2 vertical column densities with the model surface concentrations. The estimated inferred TROPOMI NO2 surface concentrations are examined further with the altering of three influencing factors: the model vertical levelling scheme, the versions of the TROPOMI NO2 data and the air mass factors applied to the satellite and model NO2 vertical column densities. Overall, the inferred TROPOMI NO2 surface concentrations show a better correlation with the in-situ measurements for both time periods and all station types, especially for the industrial stations (R&gt;0.6) in winter. The calculated correlation for background stations is moderate for both periods (R~0.5 in summer and R&gt;0.5 in winter), whereas for traffic stations it improves in the winter (from 0.20 to 0.50). After the implementation of the air mass factors from the local model, the bias is significantly reduced for most of the station types, especially in winter for the background stations, ranging from +0.49% for the urban background to +10.37% for the rural background stations. The mean relative bias in winter between the inferred S5P/TROPOMI NO2 surface concentrations and the ground-based measurements for industrial stations is about -15%, whereas for traffic urban stations it is approximately -25%. In summertime, biases are generally higher for all station types, especially for the traffic stations (~ -75%), ranging from -54% to -30% for the background and industrial stations.