bluuebunny/crossref_metadata_2025 huggingface dataset:
A fitness distribution law for amino-acid replacements
Authors: Sun Mengyi , Stoltzfus Arlin , McCandlish David M.
Published: October 2024

The effect of replacing the amino acid at a given site in a protein is difficult to predict. Yet, evolutionary comparisons have revealed highly regular patterns of interchangeability between pairs of amino acids, and such patterns have proved enormously useful in a range of applications in bioinformatics, evolutionary inference, and protein design. Here we reconcile these apparently contradictory observations using fitness data from over 350,000 experimental amino acid replacements. Almost one-quarter of the 20×19 = 380 types of replacements have broad distributions of fitness effects (DFEs) that closely resemble the background DFE for random changes, indicating an overwhelming influence of protein context in determining mutational effects. However, we also observe that the 380 pair-specific DFEs closely follow a maximum entropy distribution, specifically a truncated exponential distribution. The shape of this distribution is determined entirely by its mean, which is equivalent to the chance that a replacement of the given type is fitter than a random replacement. In this type of distribution, modest deviations in the mean correspond to much larger changes in the probability of falling in the far right tail, so that modest differences in mean exchangeability may result in much larger differences in the chance of a highly fit mutation. Indeed, we show that under the assumption that purifying selection filters out the vast majority of mutations, the maximum entropy distributions of fitness effects inferred from deep mutational scanning experiments predict the characteristic patterns of amino acid change observed in molecular evolution. These maximum entropy distributions of mutational effects not only provide a tuneable model for molecular evolution, but also have implications for mutational effect prediction and protein engineering.
Comet fragment-ion indexing for enhanced peptide sequencing
Authors: McGann Christopher D. , Bergstrom Erik J. , Sharma Vagisha , Heil Lilian R. , Yu Qing , Eng Jimmy K. , Schweppe Devin K.
Published: October 2024

Fragment ion indexing has significantly improved the efficiency of proteomics database search tools. This work implements fragment ion indexing in Comet, a widely-used, open-source search engine. We demonstrate that this enhancement maintains scoring and identification accuracy while substantially increasing peptide spectral matching speeds across multiple applications, including open modification searches, immunopeptidomics, and real-time searches. Comet-FI reduced search speeds by up to 94% enabling the rapid analysis of complex data types like immunopeptidomes. Fragment-ion indexing enables Comet to keep pace with modern instrumentation and expanding applications in proteomics, reinforcing its utility in diverse proteomics workflows and its integration with a wide range of proteomics tools and platforms.
Assessment of high-efficacy agonism in synthetic cannabinoid receptor agonists containing l-tert-leucinate
Authors: Lucaj Christopher , Pitha Charlotte , Davis Jordan , Yano Hideaki
Published: October 2024

Synthetic cannabinoid receptor agonists (SCRAs) represent a class of new psychoactive substances that pose great health risks attributed to their wide-ranging and severe adverse effects. Recent evidence has shown that SCRAs with key moieties can confer superagonism, yet this phenomenon is still not well understood. In this study, we developed a structure-activity relationship (SAR) for SCRA superagonism by comparing eight compounds differing by their head moiety (l-valinate vs. l-tert-leucinate), core moiety (indole vs. indazole), and tail moiety (5-fluoropentyl vs. 4-fluorobenzyl) through different modes of bioluminescence resonance energy transfer (BRET). We found that l-tert-leucinate head moiety and indazole core moiety conferred superagonism across multiple Gαi/oproteins and β-arrestin 2. Finally, after generating CB1R mutant constructs, we found that transmembrane 2 (TM2) interactions to the head moiety of tested SCRAs at F170, F177, and H178 are key to eliciting activity.
Attentive graph neural network models for the prediction of blood brain barrier permeability
Authors: Collins Jesse W. , Ebrahimkhani Mahmoud , Ramirez Daniel , Deiloff Jonathan , Gonzalez Mauro , Abedi Mostafa , Philippe-Venec Laurence , Cole Bridget M. , Moore Brandon , Nwankwo Jennifer O.
Published: October 2024

The blood brain barrier’s (BBB) unique endothelial cells and tight junctions selectively regulate passage of molecules to the central nervous system (CNS) to prevent pathogen entry and maintain neural homeostasis. Various neurological conditions and neurodegenerative diseases benefit from small molecules capable of BBB penetration (BBBP) to elicit a therapeutic effect. Predicting BBBP often involvesin silicoassessment of molecular properties such as lipophilicity (logP) and polar surface area (PSA) using the CNS multiparameter optimization (MPO) method. This study curated an open-source dataset to benchmark rigorously machine learning (ML) and neural network (NN) models with each other and with MPO for predicting BBBP. Our analysis demonstrated that AI models, especially attentive NNs using stereochemical features, significantly outperform MPO in predicting BBBP. An attentive graph neural network (GNN), we refer to as CANDID-CNS™, achieved a 0.23-0.26 higher AUROC score than MPO on full test sets, and a 0.17-0.19 higher score on stereoisomers filtered subsets. Regarding stereoisomers that differ in BBBP, which MPO cannot distinguish, attentive GNNs correctly classify these with AUROC and MCC metrics comparable to or better than MPO’s AUROC and MCC on less difficult test molecules. These findings suggest that integrating attentive GNN models into pharmaceutical drug discovery processes can substantially improve prediction rates, and thereby reduce the timeline, cost, and increase probability of success of designing brain penetrant therapeutics for the treatment of a wide variety of neurological and neurodegenerative diseases.
Proximal Tubule-on-Chip for Predicting Cation Transport: Dynamic Insights into Drug Transporter Expression and Function
Authors: Petit Isy , Faucher Quentin , Bernard Jean-Sébastien , Giunchi Perrine , Humeau Antoine , Sauvage François-Ludovic , Marquet Pierre , Védrenne Nicolas , Meo Florent Di
Published: October 2024

Deciphering the sources of variability in drug responses requires to understand the processes modulating drug pharmacokinetics. However, pharmacological research suffers from poor reproducibility across clinical, animal, and experimental models. Predictivity can be improved by using Organs-on-Chips, which are more physiological, human-oriented, micro-engineered devices that include microfluidics. OoC are particularly relevant at the fundamental and preclinical stages of drug development by providing more accurate assessment of key pharmacokinetic events. We have developed a proximal tubule-on-a-chip model combining commercial microfluidic and chip technologies. Using the RPTEC/TERT1 cell line, we set up a dual-flow system with antiparallel flows to mimic the dynamics of blood and urine. We assessed transporters mRNA expression using RT-qPCR, cellular polarization and protein expression via immunofluorescence and confocal microscopy, and monitored the transcellular transport of a list of prototypic xenobiotics by determining their efflux ratios with LC-MS/MS. Our results show that flow exposure significantly modulate mRNA expression of drug membrane transporters compared to static conditions. Dynamic conditions also enhance cell polarization, as evidenced by preferential basal and apical expressions of Na+/K+-ATPase, P-gp, OCT2, and MATE1, as well as the cellular secretory profile. We demonstrated unidirectional transcellular transport of a cationic substrate (metformin) with a higher efflux than influx ratio, inhibited with a specific OCT2 inhibitor, thus confirming the relevance of our proximal tubule- on-a-chip set up for cation transport investigations. Our proximal tubule-on-a-chip can also be used to explore the interactions between transporters, xenobiotics, and endogenous metabolites, possibly involved in the variability of individual drug responses. This study provides additional evidence that OoC can bridge the gaps between systemic and local pharmacokinetics, i.e., drug concentration close to its target, at the fundamental and preclinical stages.

Highlights

Cell exposure to flow shear stress modulate mRNA drug membrane transporters and cell polarization of proximal tubule

Proximal tubule-on-chip relying on RPTEC/TERT1 cell line is a suitable platform for assessing transcellular cationic transport

OCT2 and MATE are involved in potential drug-endogenous metabolite interactions

Cell exposure to xenobiotics and endogenous metabolites modulate the drug transporters expression.

Graphical Abstract

Data Statement

Original microscopy pictures, raw data for metabolomics and other data are available upon reasonable request.
Images in red: A methodological and integrative approach for the usage of Near-infrared Hyperspectral Imaging (NIR-HSI) on collection specimens of Orthoptera (Insecta)
Authors: Tavares Gustavo Costa , da Silva Neirivaldo Cavalcante , Gutjahr Ana Lúcia Nunes , Fernandes José Antônio Marin
Published: October 2024

Anthropogenic actions have caused severe environmental changes, leading to a rapid and massive loss of biodiversity, called the Holocene Extinction or "Sixth Extinction." In this context, integrative methods, capable of quickly and reliably determining and differentiating species, have become constantly demanded in taxonomic studies. Near-infrared spectroscopical technologies have proved to be promising for application in the integrative taxonomy of insects, and it is a true-non-destructive method, causing no damage to the sample and being completely chemical-preparation-free. Near-infrared spectral profiles are known as the fingerprints of the chemical composition of a given sample, and a new layer of information may be accessed. Hyperspectral imaging technologies in the near-infrared range are among the most popular, although their usage is still incipient in insect studies. As in other animal taxa, katydids’ taxonomy has traditionally been based on morphological comparison, resulting in many misclassifications over the years. However, integrative methods are more and more required in taxonomic studies. Different methods and technologies have been used from an integrative perspective to minimize misidentifications, especially for non-taxonomist or untrained researchers. Here, we approach the applicability of near-infrared spectroscopy coupled with hyperspectral imaging technology to Ensifera specimens housed in collections, discussing the advantages, disadvantages, and challenges to future applications. As a result, we propose using only homologous body parts in comparing and modeling species using this kind of data due to the heterogeneity of the insects’ exoskeleton. Additionally, we made a case study by discriminating four species of the katydid genus Conocephalus Thunberg, one of the most speciose genera within Orthoptera that is known to have polymorphic species, with variations expressed in the wing development and postabdomen appendages. We generated a Partial Least Squares-Discriminant Analysis (PLS-DA) classification model for the species with an overall classification accuracy for the assigned pixels of 90% and specific accuracy for pixel discrimination ranging from 96% to 98%. This is one of the few research studies employing hyperspectral imaging in insects’ taxonomy, and it is the very first to use this technology in Orthoptera; therefore, this is a preliminary approach to usage as an integrative method.
Mixed evidence for intralocus sexual conflict from male-limited selection inDrosophila melanogaster
Authors: Thyagarajan Harshavardhan , Sayyed Imran , Baroody Mindy G. , Kowal Joshua A. , Day Troy , Chippindale Adam K.
Published: October 2024

Sexual conflict over shared traits – intralocus sexual conflict (IaSC) – may be common and consequential, but experimental tests of its relative magnitude are challenging and limited in number. We use a sex-limited selection experiment, designed to subject genomic haplotypes ofDrosophila melanogasterto selection for male fitness without opposing selection acting on female fitness. Importantly, we use three novel base populations to compare results with those from the LHMpopulation, the sole population investigated using this technique. In contrast with previous studies, we find that male fitness of haplotypes subject to male-limited selection (ML populations) are not consistently better than their matched (MC) controls when tested in the “wildtype” state. Males from ML lines did not outperform controls in competitive fitness assays, mate choice trials, fecundity induction or sperm offense tests. As predicted, genetic variation for male fitness was reduced, with low fitness haplotypes apparently removed by selection, but this was only surveyed in one replicate population pair and included a potential artefact in the protocol. Female fitness was markedly reduced by carriage of ML genomic haplotypes, as predicted by sexual antagonism. Hence, our results are only partially consistent with the IaSC hypothesis, raising questions about the relative contribution of sexual conflict to the standing genetic variation in these populations and the potential role of artefacts in the protocol that may have obscured our ability to detect IaSC.
Immunological Profiling in Knee Osteoarthritis: Treg Dysfunction as Key Driver of Pain
Authors: Binvignat Marie , Dubois Johanna , Marco Salvador Maria , Stys Paul , Pitoiset Fabien , Roux Alexandra , Barbié Michèle , Hassler Signe , Lorenzon Roberta , Ribet Claire , Mhanna Vanessa , Vantomme Hélène , Adda Leslie , Barennes Pierre , Coatnoan Nicolas , Le Gouge Kenz , Aheng Caroline , Courties Alice , Minssen Lise , Butte Atul J. , Six Adrien , Rosenzwajg Michelle , Tchitchek Nicolas , Berenbaum Francis , Klatzmann David , Mariotti-Ferrandiz Encarnita , Sellam Jérémie
Published: October 2024

Pain is the hallmark symptom of osteoarthritis (OA) and its biological drivers remain poorly understood. While the role of innate immunity in OA has been extensively studied, the involvement of adaptive immunity, in particular regulatory T cells (Tregs), is not well understood. Using a comprehensive multi-omic approach on the peripheral blood from 46 knee OA patients with similar radiographic stage, including deep immunophenotyping, cytokine profiling, transcriptomic and T-cell receptor analysis on sorted CD4 Tregs and effector T cells (Teff), we identified an immunological signature associated with OA-related pain. Cytokines promoting Treg expansion and activation (with increases of sIL2-RA, sTNFR1, sTNFR2) were correlated with the Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain subscore, suggesting a potential Treg dysfunction. Nineteen T cell subsets were correlated with WOMAC pain. Notably, we found a negative correlation of cell subsets associated with Treg expansion and activation (FoxP3+CTLA4+, CD4+CD57+, Treg CD95+, CD4 Treg CD45RA-). Differential gene expression analysis between patients with low and high WOMAC pain intensity (threshold ≥ 40/100) revealed an upregulation of inflammasome-related genes such asIL1RL1, IL31RA, IFITM3, NLRP3, IFNGin Tregs. Functional enrichment analysis highlighted an overrepresentation of innate immune response, IL-8, and interferon activation pathways suggesting a pro-inflammatory state in Tregs of patients with high pain intensity. Collectively, our systems immunology approach highlights multiple associations between Treg dysfunctionality and OA-related pain, providing new insights into the adaptive immune system’s contribution to OA-related pain.
DecoyFinder: Identification of Contaminants in Sets of Homologous RNA Sequences
Authors: Zhu Mingyi , Zuber Jeffrey , Tan Zhen , Sharma Gaurav , Mathews David H.
Published: October 2024

Motivation

RNA structure is essential for the function of many non-coding RNAs. Using multiple homologous sequences, which share structure and function, secondary structure can be predicted with much higher accuracy than with a single sequence. It can be difficult, however, to establish a set of homologous sequences when their structure is not yet known. We developed a method to identify sequences in a set of putative homologs that are in fact non-homologs.

Results

Previously, we developed TurboFold to estimate conserved structure using multiple, unaligned RNA homologs. Here, we report that the positive predictive value of TurboFold is significantly reduced by the presence of contamination by non-homologous sequences, although the reduction is less than 1%. We developed a method called DecoyFinder, which applies machine learning trained with features determined by TurboFold, to detect sequences that are not homologous with the other sequences in the set. This method can identify approximately 45% of non-homologous sequences, at a rate of 5% misidentification of true homologous sequences.

Availability

DecoyFinder and TurboFold are incorporated in RNAstructure, which is provided for free and open source under the GPL V2 license. It can be downloaded athttp://rna.urmc.rochester.edu/RNAstructure.html
MeNu GUIDE - a metabolite nutrition graph to uncover interactions with disease etiology
Authors: Würf Vivian , Pauling Josch K.
Published: October 2024

Abstract

The relationship between diet and disease is well-documented, yet the complex interactions among foods, metabolites, and genetics makes research challenging. This study explores the potential insights offered by a knowledge graph that connects nutrition and diseases on a metabolic level. Ten ontologies and data from six databases were merged, resulting in a graph with over 25 million triple statements, stored in a Turtle file and added to a GraphDB repository. SPARQL queries revealed biases towards specific foods and conditions within the integrated databases. Despite these biases, this knowledge graph serves as a proof-of-concept, demonstrating the feasibility of integrating information from diverse resources to yield valuable insights and enabling the drawing of meaningful conclusions. The graph allows efficient identification of disease-related compounds and their food sources and enables the exploration of changes in metabolite concentrations, such as those occurring during food processing. Researchers could use such a knowledge graph to identify biomarkers, help generate new hypotheses, and improve experimental designs. Expanding the graph with automated text-mining and recipe data would further enhance its utility for nutrition research. Such a resource could advance understanding of the molecular mechanisms behind diet-disease relationships, guiding more targeted interventions.
A modular approach to forecasting COVID-19 hospital bed occupancy
Authors: Tobin Ruarai J , Walker Camelia R , Moss Robert , McCaw James M , Price David J , Shearer Freya M
Published: October 2024

Monitoring the number of COVID-19 patients in hospital beds was a critical component of Australia’s real-time surveillance strategy for the disease. From 2021–2023, we produced short-term forecasts of bed occupancy to support public health decision making. In this work, we present a model for forecasting the number of ward and intensive care unit (ICU) beds occupied by COVID-19 cases. The model simulates the stochastic progression of COVID-19 patients through the hospital system and is fit to reported occupancy counts using an approximate Bayesian method. We do not directly model infection dynamics — instead taking independently produced forecasts of case incidence as an input — enabling the independent development of our model from that of the underlying case forecast(s). We evaluate the performance of 21-day forecasts of ward and ICU occupancy across Australia’s eight states and territories between March and September 2022, when major waves of the Omicron variant of SARS-CoV-2 were occurring throughout the country. Forecasts were on average biased downwards immediately prior to epidemic peaks and biased upwards post-peak. Forecast performance was best in jurisdictions with the largest population sizes. Our forecasts of COVID-19 hospital burden were reported weekly to national decision-making committees to support Australia’s public health response.
Who is asking ChatGPT health questions? Analysis of a nationally representative Australian community sample
Authors: Ayre Julie , Cvejic Erin , McCaffery Kirsten J
Published: October 2024

ChatGPT and other generative artificial intelligence (AI) tools have dramatically changed the health information environment. Discussions about their benefits and risks need clear evidence about who is using them and why. This nationally representative survey estimates that one in ten Australians asked ChatGPT a health question in the past 6 months (95%CI: 8.5%□11.4%), with higher use in key priority groups: people born in a non-English speaking country, who speak a non-English language at home, and who have low health literacy. As usage increases, we need to equip community with knowledge and skills to use these tools safely.
The first near-complete genome assembly of pig: enabling more accurate genetic research
Authors: Cao Caiyun , Miao Jian , Xie Qinqin , Sun Jiabao , Cheng Hong , Zhang Zhenyang , Wu Fen , Liu Shuang , Ye Xiaowei , Zhang Zhe , Wang Qishan , Pan Yuchun , Wang Zhen
Published: October 2024

Pigs are crucial sources of meat and protein, valuable animal models, and potential donors for xenotransplantation. However, the existing reference genome for pigs is incomplete, with thousands of segments and missing centromeres and telomeres, which limits our understanding of the important traits in these genomic regions. To address this issue, we present a near complete genome assembly for the Jinhua pig (JH-T2T), constructed using PacBio HiFi and ONT long reads. This assembly includes all 18 autosomes and the X and Y sex chromosomes, with only six gaps. It features annotations of 46.90% repetitive sequences, 35 telomeres, 17 centromeres, and 23,924 high-confident genes. Compared to the Sscrofa11.1, JH-T2T closes nearly all gaps, extends sequences by 177 Mb, predicts more intact telomeres and centromeres, and gains 799 more genes and loses 114 genes. Moreover, it enhances the mapping rate for both Western and Chinese local pigs, outperforming Sscrofa11.1 as a reference genome. Additionally, this comprehensive genome assembly will facilitate large-scale variant detection and enable the exploration of genes associated with pig domestication, such asGPAM,CYP2C18,LY9,ITLN2, andCHIA. Our findings represent a significant advancement in pig genomics, providing a robust resource that enhances genetic research, breeding programs, and biomedical applications.
Direct M2 macrophage co-culture overrides viscoelastic hydrogel mechanics to promote fibroblast activation
Authors: Astrab Leilani R. , Skelton Mackenzie L. , Caliari Steven R.
Published: October 2024

Fibroblast activation drives fibrotic diseases such as pulmonary fibrosis. However, the complex interplay of how tissue mechanics and macrophage signals combine to influence fibroblast activation is not well understood. Here, we use hyaluronic acid hydrogels as a tunable cell culture system to mimic lung tissue stiffness and viscoelasticity. We applied this platform to investigate the influence of macrophage signaling on fibroblast activation. Fibroblasts cultured on stiff (50 kPa) hydrogels mimicking fibrotic tissue exhibit increased activation as measured by spreading as well as type I collagen and cadherin-11 expression compared to fibroblasts cultured on soft (1 kPa) viscoelastic hydrogels mimicking normal tissue. These trends were unchanged in fibroblasts cultured with macrophage-conditioned media. However, fibroblasts directly co-cultured with M2 macrophages show increased activation, even on soft viscoelastic hydrogels that normally suppress activation. Inhibition of interleukin 6 (IL6) signaling does not change activation in fibroblast-only cultures but ameliorates the pro-fibrotic effects of M2 macrophage co-culture. These results underscore the ability of direct M2 macrophage co-culture to override hydrogel viscoelasticity to promote fibroblast activation in an IL6-dependent manner. This work also highlights the utility of using hydrogels to deconstruct complex tissue microenvironments to better understand the interplay between microenvironmental mechanical and cellular cues.
Identification of novel key genes and signaling pathways in hypertrophic cardiomyopathy: evidence from bioinformatics and next generation sequencing data analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya
Published: October 2024

Hypertrophic cardiomyopathy (HCM) is a global health problem characterized by left ventricle become thick and stiff with effect of indication including chest pain, fluttering, fainting and shortness of breath. In this investigation, we aimed to identify diagnostic markers and analyzed the therapeutic potential of essential genes. Next generation sequencing (NGS) dataset GSE180313 was obtained from the Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs) in HCM. DEGs were screened using the DESeq2 Rbioconductor tool. Then, Gene Ontology (GO) and REACTOME pathway enrichment analyses were performed. Moreover, a protein-protein interaction (PPI) network of the DEGs was constructed, and module analysis was performed. Next, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed and analyzed. Finally, diagnostic values of hub genes were assessed by by receiver operating characteristic (ROC) curve analysis. By performing DEGs analysis, total 958 DEGs (479 up regulated genes and 479 down regulated genes) were successfully identified from GSE180313, respectively. GO and REACTOME pathway enrichment analyses revealed that GO functions and signaling pathways were significantly enriched including response to stimulus, multicellular organismal process, metabolism and extracellular matrix organization. The hub genes of FN1, SOX2, TUBA4A, RPS2, TUBA1C, ESR1, SNCA, LCK, PAK1 and APLNR might be associated with HCM. The hub gens of FN1 and TPM3, together with corresponding predicted miRNAs (e.g., hsa-mir-374a-5p and hsa-miR-8052), and SH3KBP1 and ESR1 together with corresponding predicted TFs (e.g PRRX2 and STAT3) were found to be significantly correlated with HCM. This investigation could serve as a basis for further understanding the molecular pathogenesis and potential therapeutic targets of HCM.
Reactive Oxygen Detoxification Contributes toMycobacterium abscessusAntibiotic Survival
Authors: Bates Nicholas A. , Rodriguez Ronald , Drwich Rama , Ray Abigail , Stanley Sarah A. , Penn Bennett H.
Published: October 2024

When a population of bacteria encounter a bactericidal antibiotic most cells die rapidly. However, a sub-population, known as “persister cells”, can survive for prolonged periods in a non-growing, but viable, state. Persister cell frequency is dramatically increased by stresses such as nutrient deprivation, but it is unclear what pathways are required to maintain viability, and how this process is regulated. To identify the genetic determinants of antibiotic persistence in mycobacteria, we carried out transposon mutagenesis high-throughput sequencing (Tn-Seq) screens inMycobacterium abscessus(Mabs). This analysis identified genes essential in both spontaneous and stress-induced persister cells, allowing the first genetic comparison of these states in mycobacteria, and unexpectedly identified multiple genes involved in the detoxification of reactive oxygen species (ROS). We found that endogenous ROS were generated following antibiotic exposure, and that the KatG catalase-peroxidase contributed to survival in both spontaneous and starvation-induced persisters. We also found that that hypoxia significantly impaired bacterial killing, and notably, in the absence of oxygen, KatG became dispensable. Thus, the lethality of some antibiotics is amplified by toxic ROS accumulation, and persister cells depend on detoxification systems to remain viable.
Analysis of the functioning of temporary dialysis catheters in patients with COVID-19
Authors: Ponte Bruno Jeronimo , Dib Viviane Galli , Oliveira Portela Felipe Soares , Magnani Arthur Souza , Silva Marcela Juliano , Pinheiro Lucas Lembrança , Wolosker Nelson
Published: October 2024

2.

Introduction

Patients with acute renal failure requiring hemodialysis should use temporary hemodialysis catheters (THC) due to the urgency and potential reversibility of the condition. So far, three studies in North America indicate a higher risk of catheter-related issues in COVID-19 patients needing hemodialysis. This study examines the functionality and complications of temporary hemodialysis access in COVID-19 patients at a Brazilian hospital.

Methodology

A prospective analysis was conducted at a COVID-19 referral center between May and July 2020. During this time, the Vascular Surgery team implanted temporary hemodialysis catheters in 107 patients. The patients were followed, and demographic and clinical characteristics that could be correlated with catheter malfunction were analyzed.

Results

Of the 107 patients studied, 22 (20,6%) experienced complications related to the catheter. Eighteen (16,8%) had malfunctions, and 4 (3,7%) had infections. Five patients evolved with unfavorable clinical conditions and did not undergo catheter replacement. Thirteen patients with malfunctions had catheter tip thrombosis as the cause of the malfunction. Among the variables analyzed, only the need for orotracheal intubation(p 0,009), deep vein thrombosis(p 0,01), and a history of a previous catheter(p 0,002)were found to be correlated with a higher risk of malfunctioning.

Conclusion

The rate of temporary high-flow catheter malfunction in patients with COVID-19 is similar to that in patients without this disease. Previous catheter use, the necessity for OTI, and venous thrombosis were the main predictors of catheter malfunction.
An open annotated dataset and baseline machine learning model for segmentation of vertebrae with metastatic bone lesions from CT
Authors: Haouchine Nazim , Hackney David B. , Pieper Steve D. , Wells William M. , Sanhinova Malika , Balboni Tracy A. , Spektor Alexander , Huynh Mai A. , Kozono David E. , Doyle Patrick , Alkalay Ron N.
Published: October 2024

Automatic analysis of pathologic vertebrae from computed tomography (CT) scans could significantly improve the diagnostic management of patients with metastatic spine disease. We provide the first publicly available annotated imaging dataset of cancerous CT spines to help develop artificial intelligence frameworks for automatic vertebrae segmentation and classification. This collection contains a dataset of 55 CT scans collected on patients with various types of primary cancers at two different institutions. In addition to raw images, data include manual segmentations and contours, vertebral level labeling, vertebral lesion-type classifications, and patient demographic details. Our automated segmentation model uses nnU-Net, a freely available open-source framework for deep learning in healthcare imaging, and is made publicly available. This data will facilitate the development and validation of models for predicting the mechanical response to loading and the resulting risk of fractures and spinal deformity.
Antibiotic use in the past 8 years and gut microbiota composition
Authors: Baldanzi Gabriel , Larsson Anna , Sayols-Baixeras Sergi , Dekkers Koen F. , Hammar Ulf , Nguyen Diem , Graells Tíscar , Ahmad Shafqat , Volpiano Camila Gazolla , Meric Guillaume , Järhult Josef D. , Tängdén Thomas , Ludvigsson Jonas F. , Lind Lars , Sundström Johan , Michaëlsson Karl , Ärnlöv Johan , Kennedy Beatrice , Orho-Melander Marju , Fall Tove
Published: October 2024

BACKGROUND

Disruptions in gut microbiota have been implicated in cardiometabolic disorders and other health outcomes. Antibiotics are known gut microbiota disruptors, but their long-term consequences on taxonomic composition of the gut microbiome remain underexplored.

Methods

We investigated associations between register-based oral antibiotic use over 8 years and gut microbiota composition assessed with fecal shotgun metagenomics in 15,131 adults from the Swedish population-based studies SCAPIS, MOS, and SIMPLER. We applied multivariable regression models with the number of prescriptions in three pre-specified periods before fecal sampling (<1 year, 1–4, 4–8 years) as the main exposures and adjusted for sociodemographics, lifestyle, and comorbidities. Secondary analyses included participants with only one antibiotic course or none.

Results

Antibiotic use <1 year before fecal sampling was associated with the greatest reduction in gut microbiota species diversity; however, antibiotic use 1–4 years and 4–8 years earlier was also associated with decreased diversity. Clindamycin, fluoroquinolones, and flucloxacillin accounted for most of the associations between antibiotic use and the abundance of individual species across all periods. Use of these three antibiotics 4–8 years earlier was associated with altered abundance of 10–14% of the species studied; use of penicillin V, extended-spectrum penicillins, and nitrofurantoin were associated with altered abundance of only a few species. Similar results were found when comparing one antibiotic course 4–8 years before sampling vs. none in the past 8 years.

CONCLUSION

Commonly prescribed antibiotics like clindamycin, fluoroquinolones, and the narrow-spectrum flucloxacillin appear to have long-lasting consequences for the gut microbiota.
Integrated cell type-specific analysis of blood and gut identifies matching eQTL for 140 IBD risk loci and entrectinib as possible repurposing candidate
Authors: Perée Hélène , Petrov Viacheslav A , Tokunaga Yumie , Kvasz Alexander , Vieujean Sophie , Regimont Sarah , Mni Myriam , Wéry Marie , Azarzar Samira , Jacques Sophie , Fouillien Nicolas , Karim Latifa , Deckers Manon , Detry Emilie , Mayer Alice , Stephan Raafat , Harshman Keith , Mizoro Yasutaka , Reenaers Catherine , Van Kemseke Catherine , Warling Odile , Labille Virginie , Kropp Sophie , Poncin Maxime , Moreau Anne Catherine , Servais Benoit , Joly Jean-Philippe ,   SYSCID Consortium,   BRIDGE Consortium, Coppieters Wouter , Dermitzakis Emmanouil , Louis Edouard , Georges Michel , Takeda Haruko , Rahmouni Souad
Published: October 2024

Genes whose expression is affected in a consistent manner by GWAS-identified risk variants and the disease process, constitute preferred drug targets. We herein combine integrated cis-eQTL analysis in 27 blood cell populations and 43 intestinal cell types of the ileum, colon and rectum, and information on gene expression in patients, to search for putative drug targets for inflammatory bowel disease (IBD). We detect >95K cis-eQTL that affect >13K e-genes and cluster in >24K regulatory modules (RM). We uncover matching RM for 140 risk loci, implicating >300 e-genes not previously connected to IBD, and find 152 IBD-matching e-genes whose expression is perturbed in the blood or gut of patients. We identify entrectinib, a small molecule inhibiting the NRLP3 inflammasome by binding NEK7, as a promising repurposing candidate for IBD.
Optimizing Clinical Data Availability: Extracting Pulmonary Embolism Diagnoses from Radiology Impressions with GPT-4o
Authors: Mahyoub Mohammed , Dougherty Kacie , Shukla Ajit
Published: October 2024

Background

Pulmonary embolism (PE) is a life-threatening condition that requires timely diagnosis to reduce mortality. Radiology reports, particularly the Impression sections, play a critical role in diagnosing PE. However, manually extracting this information from large volumes of reports is challenging. This study aims to develop an advanced natural language processing (NLP) system using GPT-4o to automatically extract PE diagnoses from radiology report impressions, enhancing clinical workflows and decision-making.

Materials and Methods

We developed two text classification models: a fine-tuned Clinical Longformer (as a baseline model) and GPT-4o. Models were trained using 1,000 radiology report impressions and validated on 200 samples, with a post-deployment evaluation conducted using 500 operational records. The primary dataset was sourced from an electronic medical record relational database, and key metrics such as sensitivity, specificity, and F1 score were used to evaluate model performance.

Results

GPT-4o achieved superior performance with 100% sensitivity, specificity, and F1 score, outperforming the Clinical Longformer. Post-deployment, GPT-4o continued to perform flawlessly, identifying all positive PE cases without false positives or false negatives. The model successfully streamlined the clinical workflow, reducing the burden of manual review and enhancing diagnostic accuracy.
Molecular and cell phenotype programs in oral epithelial cells directed by co-exposure to arsenic and smokeless tobacco
Authors: Das Samrat , Thakur Shefali , Cahais Vincent , Virard François , Claeys Liesel , Renard Claire , Cuenin Cyrille , Cros Marie-Pierre , Keïta Stéphane , Venuti Assunta , Sirand Cécilia , Ghantous Akram , Herceg Zdenko , Korenjak Michael , Zavadil Jiri
Published: October 2024

Chronic arsenic exposure can lead to various health issues, including cancer. Concerns have been mounting about the enhancement of arsenic toxicity through co-exposure to various prevalent lifestyle habits. Smokeless tobacco products are commonly consumed in South Asian countries, where their use frequently co-occurs with exposure to arsenic from contaminated groundwater. To decipher thein vitromolecular and cellular responses to arsenic and/or smokeless tobacco, we performed temporal multi-omics analysis of the transcriptome and DNA methylome remodelling in exposed hTERT-immortalized human normal oral keratinocytes (NOK), as well as arsenic and/or smokeless tobacco genotoxicity and mutagenicity investigations in NOK cells and in human p53 knock-in murine embryonic fibroblasts (Hupki MEF). RNAseq results from acute exposures to arsenic alone and in combination with smokeless tobacco extract revealed upregulation of genes with roles in cell cycle changes, apoptosis and inflammation responses. This was in keeping with global DNA hypomethylation affecting genes involved in the same processes in response to chronic treatment in NOK cells. At the phenotypic level, we observed a dose-dependent decrease in NOK cell viability, induction of DNA damage, cell cycle changes and increased apoptosis, with the most pronounced effects observed under arsenic and SLT co-exposure conditions. Live-cell imaging experiments indicated that the DNA damage likely resulted from induction of apoptosis, an observation validated by a lack of exome-wide mutagenesis in response to chronic exposure to arsenic and/or smokeless tobacco. In sum, our integrative omics study provides novel insights into the acute and chronic responses to arsenic and smokeless tobacco (co-)exposure, with both types of responses converging on several key mechanisms associated with cancer hallmark processes. The generated rich catalogue of molecular programs in oral cells regulated by arsenic and smokeless tobacco (co-)exposure may provide bases for future development of biomarkers for use in molecular epidemiology studies of exposed populations at risk of developing oral cancer.
Aberrant glycosylation reveals unexpected clinical outcomes between Luminal B and Basal high stemness index breast cancer cohorts
Authors: Truter Mia , Naidoo Kevin J.
Published: October 2024

Cancer stem cells facilitate tumorigenesis by hijacking normal developmental pathways, the activity of which are modulated by glycosylation. Aberrant glycosylation is a key hallmark of cancer, but little is known of its functional role within the tumorigenesis system and integrated molecular and cellular cancer landscape. The clinical and phenotypic diversity in breast cancer suggests activation of various biochemical mechanisms, each likely accompanied by unique aberrations in glycosylation. Here we investigate the mechanistic links between glycosylation and breast cancer stemness for subtypes defined by the expression hormone receptors: estrogen (ER), progesterone (PR) and human epidermal growth factor (HER2). Specifically, we consider Basal and Luminal B, the two most highly stem subtypes. These two have significanlty different patient prognoses when accounting for degree of stemness. In the case of patient samples from the Basal subtype, the high stem state is protective, while in samples studied that were identified as Luminal B subtype, the high stem state becomes a risk factor over time. By undertaking a combined machine learning and bioinformatics analysis, we show that patient prognosis varies due to activation of distinct glycosylation pathways that fit into the wider tumorigenic landscape. In the high stem Basal cohort, glycosylation of immune cell surface receptors functions to maintain stemness and facilitates an activated immune response. In comparison, aberrant mannosylation and protein trafficking promote tumorigenesis through metabolic dysregulation in the high stem Luminal B cohort. These findings suggest that glycosylation plays an integral role in tumorigenesis far more so than the important role that has been identified for specific glycans, glycoenzymes or glycogens. In a systems analysis of Basal and Luminal B subtypes, we find that their aberrant glycosylation to be specific and different from each other particular with respect to high stem cases. This opens up an avenue for personalised glycosylation-based cancer diagnostics and therapeutics discovery.

Significance

Aberrant glycosylation gene expression screening of Basal and Luminal B breast cancer subtypes reveals differences in their phenotypic and clinical outcomes as a function of stemness helpful for personalised diagnostic and treatment.
Mechanistic insights into the inhibition of dengue virus NS5 methyltransferase by herbacetin
Authors: Bhutkar Mandar , Verma Shalja , Singh Vishakha , Kumar Pravindra , Tomar Shailly
Published: October 2024

Herbacetin (HC) is a naturally occurring flavonoid compound with a dual antiviral mechanism. It inhibits the polyamine biosynthetic pathway and targets the methyltransferase (MTase) enzyme of the dengue and chikungunya virus. However, understanding the detailed inhibition mechanism of DENV MTase by HC remains unclear. The crystal structure of DENV3 nonstructural protein 5 (NS5) MTase in complex with HC and S-adenosyl-L-homocysteine presented in this study gives structural insights into the inhibition mechanism. Structural analysis revealed that HC binds to the cap 0 RNA site near the GTP binding site in the DENV3 NS5 MTase, and fluorescence polarization assay demonstrated HC inhibits GTP binding with an inhibition constant Kivalue of ∼ 0.43 µM. This is the first study that identified an inhibitor that targets the conserved RNA-binding region of NS5 MTase, suggesting its potential as a highly effective scaffold for broad-spectrum antiviral agents against orthoflaviviruses.

Importance

Dengue virus (DENV) is a vector-borne disease affecting global health, and no antiviral treatment is available for Dengue fever. DENV NS5 methyltransferase (DENV NS5 MTase) is a viral RNA capping enzyme essential for the virus replication. This study demonstrated that herbacetin (HC), a natural flavonoid, blocked the binding of GTP to NS5 MTase and inhibited the enzyme. In addition to DENV3, HC effectively inhibited the replication of DENV1,2, and 4 serotypes. The crystal structure of the DENV3 NS5 MTase in complex with HC revealed that HC binds at the cap 0 RNA binding site, which is close to the GTP binding site and thereby perturbs the spatial arrangement of GTP binding site residues. HC, as the first identified inhibitor that targets the conserved RNA-binding site of DENV3 NS5 MTase, presents a potential scaffold for the development of new antiviral drugs.
Characterisation ofPseudomonas aeruginosa’smetal-responsive TonB-dependent transporters
Authors: Ferry Manon , Ferriz Hortense , Sharp Connor , Paschalidis Christos , Boutant Emmanuel , Schalk Isabelle J. , Cunrath Olivier
Published: October 2024

Pseudomonas aeruginosa, a versatile bacterium, relies on several TonB-dependent transporters (TBDTs) for nutrient acquisition (such as iron-siderophore complexes) and adaptation to various environments. While some TBDTs are well characterized, a significant number remain unexplored despite their potential role in pathogenicity. In this study, we developed fluorescent reporter plasmids to investigate TBDT promoter activity. Initially, we characterized their promoter activity in commonly used laboratory conditions, revealing diverse expression patterns among all TBDTs. Subsequently, we classified the TBDTs into distinct metal-responsive groups based on their stress-responsive behaviour, shedding light on their functional roles. Additionally, we show that these reporter constructs can be used as a powerful tool for siderophore detection. Finally, single cell analysis of TBDT promoter activity during coculture with an enterobactin-producingKlebsiella pneumoniaestrain shows homogenous expression of key TBDT inP. aeruginosa. Our findings provide valuable insights into the expression profiles and functional diversity ofP. aeruginosaTBDTs in complex conditions, reaching from commonly used lab media to complex co-culturing conditions.
Bacteroides thetaiotaomicron enhances H2S production in Bilophila wadsworthia
Authors: Davies Jade , Mayer Melinda J. , Juge Nathalie , Narbad Arjan , Sayavedra Lizbeth
Published: October 2024

Sulfate- and sulfite-reducing bacteria (SRB) are a group of strict anaerobes found within the human gut.Bilophila wadsworthia, a sulfite-reducing bacterium which produces hydrogen sulfide (H2S) from taurine and isethionate respiration is a common member of the healthy commensal human gut microbiota, but has been implicated in several disease states including inflammatory bowel disease and colorectal cancer.Bacteroides thetaiotaomicron, one of the most prominent gut bacteria, has sulfatases which release sulfate, serving as a potential substrate for sulfate-reducing bacteria. Here, we showed that whenB. thetaiotaomicronandB. wadsworthiawere in co-culture, there was a significant increase inB. thetaiotaomicron’s growth and in H2S production byB. wadsworthia. Differential gene expression analysis revealed increased expression ofB. wadsworthia’sdsrMKJOPcomplex in co-culture, which delivers electrons for sulfite reduction to H2S. This was accompanied by a decreased expression of genes associated with taurine, sulfolactate and thiosulfate respiration, indicating thatB. thetaiotaomicronmay provide an alternative source of sulfite toB. wadsworthia. We hypothesised adenosine 5’-phosphosulfate (APS) to be this intermediate. Indeed,B. wadsworthiawas able to grow using APS or sulfite as electron acceptors. Endometabolomic and transcriptomic analyses revealed decreased production of indole byB. thetaiotaomicronin co-culture withB. wadsworthiadue to enhanced tryptophan utilisation byB. wadsworthia. The results of this microbe-microbe interaction could have significant pro-inflammatory effects in the human gut environment.