Comparative analysis of classification techniques for topic-based biomedical literature categorisation.

Introduction: Scientific articles serve as vital sources of biomedical information, but with the yearly growth in publication volume, processing such vast amounts of information has become increasingly challenging. This difficulty is particularly pronounced when it requires the expertise of highly qualified professionals. Our research focused on the domain-specific articles classification to determine whether they contain information about drug-induced liver injury (DILI). DILI is a clinically significant condition and one of the reasons for drug registration failures. The rapid and accurate identification of drugs that may cause such conditions can prevent side effects in millions of patients. Methods: Developing a text classification method can help regulators, such as the FDA, much faster at a massive scale identify facts of potential DILI of concrete drugs. In our study, we compared several text classification methodologies, including transformers, LSTMs, information theory, and statistics-based methods. We devised a simple and interpretable text classification method that is as fast as Naïve Bayes while delivering superior performance for topic-oriented text categorisation. Moreover, we revisited techniques and methodologies to handle the imbalance of the data. Results: Transformers achieve the best results in cases if the distribution of classes and semantics of test data matches the training set. But in cases of imbalanced data, simple statistical-information theory-based models can surpass complex transformers, bringing more interpretable results that are so important for the biomedical domain. As our results show, neural networks can achieve better results if they are pre-trained on domain-specific data, and the loss function was designed to reflect the class distribution. Discussion: Overall, transformers are powerful architecture, however, in certain cases, such as topic classification, its usage can be redundant and simple statistical approaches can achieve compatible results while being much faster and explainable. However, we see potential in combining results from both worlds. Development of new neural network architectures, loss functions and training procedures that bring stability to unbalanced data is a promising topic of development.

CD39 abrogates platelet-derived factors induced IL-1ß expression in the human placenta.

Tissue insults in response to inflammation, hypoxia and ischemia are accompanied by the release of ATP into the extracellular space. There, ATP modulates several pathological processes, including chemotaxis, inflammasome induction and platelet activation. ATP hydrolysis is significantly enhanced in human pregnancy, suggesting that increased conversion of extracellular ATP is an important anti-inflammatory process in preventing exaggerated inflammation, platelet activation and hemostasis in gestation. Extracellular ATP is converted into AMP, and subsequently into adenosine by the two major nucleotide-metabolizing enzymes CD39 and CD73. Here, we aimed to elucidate developmental changes of placental CD39 and CD73 over gestation, compared their expression in placental tissue from patients with preeclampsia and healthy controls, and analyzed their regulation in response to platelet-derived factors and different oxygen conditions in placental explants as well as the trophoblast cell line BeWo. Linear regression analysis showed a significant increase in placental CD39 expression, while at the same time CD73 levels declined at term of pregnancy. Neither maternal smoking during first trimester, fetal sex, maternal age, nor maternal BMI revealed any effects on placental CD39 and CD73 expression. Immunohistochemistry detected both, CD39 and CD73, predominantly in the syncytiotrophoblast layer. Placental CD39 and CD73 expression were significantly increased in pregnancies complicated with preeclampsia, when compared to controls. Cultivation of placental explants under different oxygen conditions had no effect on the ectonucleotidases, whereas presence of platelet releasate from pregnant women led to deregulated CD39 expression. Overexpression of recombinant human CD39 in BeWo cells decreased extracellular ATP levels after culture in presence of platelet-derived factors. Moreover, platelet-derived factors-induced upregulation of the pro-inflammatory cytokine, interleukin-1ß, was abolished by CD39 overexpression. Our study shows that placental CD39 is upregulated in preeclampsia, suggesting an increasing demand for extracellular ATP hydrolysis at the utero-placental interface. Increased placental CD39 in response to platelet-derived factors may lead to enhanced conversion of extracellular ATP levels, which in turn could represent an important anti-coagulant defense mechanism of the placenta.

AICAR Improves Outcomes of Metabolic Syndrome and Type 2 Diabetes Induced by High-Fat Diet in C57Bl/6 Male Mice.

The aim of the study was to investigate the effect of AMP-activated protein kinase activator 5-aminoimidazole-4-carboxamide ribonucleoside (AICAR) on the consequences of metabolic syndrome and type 2 diabetes induced by the consumption of a high-fat diet (HFD) in male C57Bl/6 mice. Additionally, the animals from group 6 were administered Methotrexate (MTX) at a dose of 1 mg/kg in parallel with AICAR, which slows down the metabolism of AICAR. The animals were recorded with signs of metabolic syndrome and type 2 diabetes mellitus by recording their body weights, glucose and insulin levels, and the calculating HOMA-IRs. At the end of the study, at the end of the 13th week, during necropsy, the internal organs were assessed, the masses of the organs were recorded, and special attention was paid to visceral fat, assessing its amount and the mass of the fat surrounding epididymis. The biochemical parameters and histology of the internal organs and tissues were assessed. The animals showed signs of metabolic syndrome and type 2 diabetes, namely, weight gain, hyperglycemia, hyperinsulinemia, an increase in the amount and mass of abdominal fat, and metabolic disorders, all expressed in a pathological change in biochemical parameters and pathological changes in internal organs. The AICAR treatment led to a decrease in body weight, a decrease in the amount and mass of abdominal fat, and an improvement in the pathomorphological picture of internal organs. However, some hepatotoxic effects were observed when the animals, on a received standard diet (STD), were treated with AICAR starting from the first day of the study. The additional administration of MTX, an AICAR metabolic inhibitor, did not improve its efficacy. Thus, AICAR has therapeutic potential for the treatment of metabolic syndrome and type 2 diabetes.

A history of the MetaSUB consortium: Tracking urban microbes around the globe.

The MetaSUB Consortium, founded in 2015, is a global consortium with an interdisciplinary team of clinicians, scientists, bioinformaticians, engineers, and designers, with members from more than 100 countries across the globe. This network has continually collected samples from urban and rural sites including subways and transit systems, sewage systems, hospitals, and other environmental sampling. These collections have been ongoing since 2015 and have continued when possible, even throughout the COVID-19 pandemic. The consortium has optimized their workflow for the collection, isolation, and sequencing of DNA and RNA collected from these various sites and processing them for metagenomics analysis, including the identification of SARS-CoV-2 and its variants. Here, the Consortium describes its foundations, and its ongoing work to expand on this network and to focus its scope on the mapping, annotation, and prediction of emerging pathogens, mapping microbial evolution and antibiotic resistance, and the discovery of novel organisms and biosynthetic gene clusters.

Scientists without borders: lessons from Ukraine.

Conflicts and natural disasters affect entire populations of the countries involved and, in addition to the thousands of lives destroyed, have a substantial negative impact on the scientific advances these countries provide. The unprovoked invasion of Ukraine by Russia, the devastating earthquake in Turkey and Syria, and the ongoing conflicts in the Middle East are just a few examples. Millions of people have been killed or displaced, their futures uncertain. These events have resulted in extensive infrastructure collapse, with loss of electricity, transportation, and access to services. Schools, universities, and research centers have been destroyed along with decades' worth of data, samples, and findings. Scholars in disaster areas face short- and long-term problems in terms of what they can accomplish now for obtaining grants and for employment in the long run. In our interconnected world, conflicts and disasters are no longer a local problem but have wide-ranging impacts on the entire world, both now and in the future. Here, we focus on the current and ongoing impact of war on the scientific community within Ukraine and from this draw lessons that can be applied to all affected countries where scientists at risk are facing hardship. We present and classify examples of effective and feasible mechanisms used to support researchers in countries facing hardship and discuss how these can be implemented with help from the international scientific community and what more is desperately needed. Reaching out, providing accessible training opportunities, and developing collaborations should increase inclusion and connectivity, support scientific advancements within affected communities, and expedite postwar and disaster recovery.

Annotating unknown species of urban microorganisms on a global scale unveils novel functional diversity and local environment association.

In urban ecosystems, microbes play a key role in maintaining major ecological functions that directly support human health and city life. However, the knowledge about the species composition and functions involved in urban environments is still limited, which is largely due to the lack of reference genomes in metagenomic studies comprises more than half of unclassified reads. Here we uncovered 732 novel bacterial species from 4728 samples collected from various common surface with the matching materials in the mass transit system across 60 cities by the MetaSUB Consortium. The number of novel species is significantly and positively correlated with the city population, and more novel species can be identified in the skin-associated samples. The in-depth analysis of the new gene catalog showed that the functional terms have a significant geographical distinguishability. Moreover, we revealed that more biosynthetic gene clusters (BGCs) can be found in novel species. The co-occurrence relationship between BGCs and genera and the geographical specificity of BGCs can also provide us more information for the synthesis pathways of natural products. Expanded the known urban microbiome diversity and suggested additional mechanisms for taxonomic and functional characterization of the urban microbiome. Considering the great impact of urban microbiomes on human life, our study can also facilitate the microbial interaction analysis between human and urban environment.

Niche partitioning of bacterial communities along the stratified water column in the Black Sea.

The Black Sea is the largest semi-closed permanently anoxic basin on our planet with long-term stratification. The study aimed at describing the Black Sea microbial community taxonomic and functional composition within the range of depths spanning across oxic/anoxic interface, and to uncover the factors behind both their vertical and regional differentiation. 16S rRNA gene MiSeq sequencing was applied to get the data on microbial community taxonomy, and the PICRUSt pipeline was used to infer their functional profile. The normoxic zone was mainly inhabited by primary producers and heterotrophic prokaryotes (e.g., Flavobacteriaceae, Rhodobacteraceae, Synechococcaceae) whereas the euxinic zone-by heterotrophic and chemoautotrophic taxa (e.g., MSBL2, Piscirickettsiaceae, and Desulfarculaceae). Assimilatory sulfate reduction and oxygenic photosynthesis were prevailing within the normoxic zone, while the role of nitrification, dissimilatory sulfate reduction, and anoxygenic photosynthesis increased in the oxygen-depleted water column part. Regional differentiation of microbial communities between the Ukrainian shelf and offshore zone was detected as well, yet it was significantly less pronounced than the vertical one. It is suggested that regional differentiation within a well-oxygenated zone is driven by the difference in phytoplankton communities providing various substrates for the prokaryotes, whereas redox stratification is the main driving force behind microbial community vertical structure.

A global metagenomic map of urban microbiomes and antimicrobial resistance.

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

The Naphthalene Catabolic Genes of Pseudomonas putida BS3701: Additional Regulatory Control.

Pseudomonas microorganisms are used for bioremediation of soils contaminated with petroleum hydrocarbons. The overall remediation efficiency is largely dependent on the presence of macro- and micronutrients. Widely varying concentrations of available nitrogen and iron (Fe) in soils were shown to affect residual hydrocarbons in the course of biodegradation. The regulatory mechanisms of expression of hydrocarbon catabolic genes in low nitrogen/low iron conditions remain unclear. The catabolism of naphthalene, a two-ring polycyclic aromatic hydrocarbon, has been well studied in pseudomonads in terms of the involvement of specific transcriptional activators, thus making it useful in revealing additional regulatory control of the adaptation of hydrocarbon destructors to a low level of the essential nutrients. The Pseudomonas putida strain BS3701 is a component of the "MicroBak" preparation for soil remediation. Previously, this strain was shown to contain genes encoding the key enzymes for naphthalene catabolism: naphthalene 1,2-dioxygenase, salicylate hydroxylase, catechol 2,3-dioxygenase, and catechol 1,2-dioxygenase. Our study aimed to clarify whether the naphthalene catabolic gene expression is dependent on the amount of nitrogen and iron in the growth culture medium, and if so, at exactly which stages the expression is regulated. We cultivated the strain in low nitrogen/low iron conditions with the concurrent evaluation of the activity of the key enzymes and the mRNA level of genes encoding these enzymes. We are the first to report that naphthalene catabolic genes are subject not only to transcriptional but also post-transcriptional regulation.

Genome Sequence of the Yeast Saprochaete ingens CBS 517.90.

Chromosome-scale genome assembly of the yeast Saprochaete ingens CBS 517.90 was determined by a combination of technologies producing short (HiSeq X; Illumina) and long (MinION; Oxford Nanopore Technologies) reads. The 21.2-Mbp genome sequence has a GC content of 36.9% and codes for 6,475 predicted proteins.

Regulatory antibodies against GPCR in women ten years after early-onset preeclampsia.

Preeclampsia is associated with an increased cardiovascular risk later in life. Anti-GPCR autoantibodies have been shown to contribute to the development of cardiovascular disease. We investigated whether anti-GPCR autoantibodies are elevated in women with a history of early-onset preeclampsia 8-11 years postpartum, and whether they correlate with clinical outcomes. We investigated data from the Preeclampsia Risk EValuation in FEMales cohort, a retrospective matched case-control study. Anti AT1R-, beta1AR-, ETAR-, PAR1- and CXCR3- autoantibodies were determined in 485 samples by using commercially available ELISA. Women with the lowest combined levels of autoantibodies and a history of early preeclampsia had significantly higher SBP, DBP and MAP (all p<0.001) compared to the controls. The individual titer levels of autoantibodies were not different between controls and former early PE groups 8-11 years postpartum. In conclusion, regulatory autoantibodies alone are not sufficient to explain hypertension or other cardiovascular pathologic conditions, but together with other risk factors such as a previous hypertensive pregnancy, lower levels of autoantibodies are associated with increased blood pressure.

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution.

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.

Genome Sequence of Flavor-Producing Yeast Saprochaete suaveolens NRRL Y-17571.

Saprochaete suaveolens is an ascomycetous yeast that produces a range of fruity flavors and fragrances. Here, we report the high-contiguity genome sequence of the ex-holotype strain, NRRL Y-17571 (CBS 152.25). The nuclear genome sequence contains 24.4 Mbp and codes for 8,119 predicted proteins.

Placental CX3CL1 is Deregulated by Angiotensin II and Contributes to a Pro-Inflammatory Trophoblast-Monocyte Interaction.

CX3CL1, which is a chemokine involved in many aspects of human pregnancy, is a membrane-bound chemokine shed into circulation as a soluble isoform. Placental CX3CL1 is induced by inflammatory cytokines and is upregulated in severe early-onset preeclampsia. In this study, the hypothesis was addressed whether angiotensin II can deregulate placental CX3CL1 expression, and whether CX3CL1 can promote a pro-inflammatory status of monocytes. qPCR analysis of human placenta samples (n = 45) showed stable expression of CX3CL1 and the angiotensin II receptor AGTR1 throughout the first trimester, but did not show a correlation between both or any influence of maternal age, BMI, and gestational age. Angiotensin II incubation of placental explants transiently deregulated CX3CL1 expression, while the angiotensin II receptor antagonist candesartan reversed this effect. Overexpression of recombinant human CX3CL1 in SGHPL-4 trophoblasts increased adhesion of THP-1 monocytes and significantly increased IL8, CCL19, and CCL13 in co-cultures with human primary monocytes. Incubation of primary monocytes with CX3CL1 and subsequent global transcriptome analysis of CD16⁺ subsets revealed 81 upregulated genes, including clusterin, lipocalin-2, and the leptin receptor. Aldosterone synthase, osteopontin, and cortisone reductase were some of the 66 downregulated genes present. These data suggest that maternal angiotensin II levels influence placental CX3CL1 expression, which, in turn, can affect monocyte to trophoblast adhesion. Release of placental CX3CL1 could promote the pro-inflammatory status of the CD16⁺ subset of maternal monocytes.

Distributed Bayesian networks reconstruction on the whole genome scale.

BACKGROUND: Bayesian networks are directed acyclic graphical models widely used to represent the probabilistic relationships between random variables. They have been applied in various biological contexts, including gene regulatory networks and protein-protein interactions inference. Generally, learning Bayesian networks from experimental data is NP-hard, leading to widespread use of heuristic search methods giving suboptimal results. However, in cases when the acyclicity of the graph can be externally ensured, it is possible to find the optimal network in polynomial time. While our previously developed tool BNFinder implements polynomial time algorithm, reconstructing networks with the large amount of experimental data still leads to computations on single CPU growing exceedingly. RESULTS: In the present paper we propose parallelized algorithm designed for multi-core and distributed systems and its implementation in the improved version of BNFinder-tool for learning optimal Bayesian networks. The new algorithm has been tested on different simulated and experimental datasets showing that it has much better efficiency of parallelization than the previous version. BNFinder gives comparable results in terms of accuracy with respect to current state-of-the-art inference methods, giving significant advantage in cases when external information such as regulators list or prior edge probability can be introduced, particularly for datasets with static gene expression observations. CONCLUSIONS: We show that the new method can be used to reconstruct networks in the size range of thousands of genes making it practically applicable to whole genome datasets of prokaryotic systems and large components of eukaryotic genomes. Our benchmarking results on realistic datasets indicate that the tool should be useful to a wide audience of researchers interested in discovering dependencies in their large-scale transcriptomic datasets.