bluuebunny/crossref_metadata_2025_split huggingface dataset:
The EZH2 inhibitor tazemetostat mitigates HIV immune evasion, reduces reservoir formation, and promotes durable CD8⁺ T-cell revitalization
Authors: Gramatica Andrea , Miller Itzayana G. , Ward Adam R. , Khan Farzana , Kemmer Tyler J. , Weiler Jared , Huynh Tan Thinh , Zumbo Paul , Kurland Andrew P. , Leyre Louise , Ren Yanqin , Klevorn Thais , Copertino Dennis C. , Chukwukere Uchenna , Levinger Callie , Dilling Thomas R. , Linden Noemi , Board Nathan L. , Iversen Emma Falling , Terry Sandra , Mota Talia M. , Bedir Seden , Clayton Kiera L. , Bosque Alberto , Ehui Lynsay MacLaren , Kovacs Colin , Betel Doron , Johnson Jeffry R. , Paiardini Mirko , Danesh Ali , Jones R. Brad 
Published: October 2024

AbstractPersistent HIV reservoirs in CD4⁺ T-cells pose a barrier to curing HIV infection. We identified overexpression of enhancer of zeste homolog 2 (EZH2) in HIV-infected CD4⁺ T- cells that survive cytotoxic T lymphocyte (CTL) exposure, suggesting a mechanism of CTL resistance. Inhibition of EZH2 with the FDA-approved drug tazemetostat increased surface expression of major histocompatibility complex class I (MHC-I) on CD4⁺ T-cells, counterbalancing HIV Nef–mediated MHC-I downregulation. This improved CTL-mediated elimination of HIV-infected cells and suppressed viral replication in vitro. In a participant-derived xenograft mouse model, tazemetostat elevated MHC-I and the pro-apoptotic protein BIM in CD4⁺ T-cells, facilitating CD8⁺ T-cell–mediated reductions of HIV reservoir seeding. Additionally, tazemetostat promoted sustained skewing of CD8⁺ T-cells toward less differentiated and exhausted phenotypes. Our findings reveal EZH2 overexpression as a novel mechanism of CTL resistance and support the clinical evaluation of tazemetostat to enhance clearance of HIV reservoirs and improve CD8+ T-cell function.
Texture profile analysis and rheology of plant-based and animal meat
Authors: Dunne Reese A. , Darwin Ethan C. , Perez Medina Valerie A. , Levenston Marc E. , St. Pierre Skyler R. , Kuhl Ellen 
Published: October 2024

AbstractPlant-based meat can help combat climate change and health risks associated with high meat consumption. To create adequate mimics of animal meats, plant-based meats must match in mouthfeel, taste, and texture. The gold standard to characterize the texture of meat is the double compression test, but this test suffers from a lack of standardization and reporting inconsistencies. Here we characterize the texture of five plant-based and three animal meats using texture profile analysis and rheology, and report ten mechanical features associated with each product’s elasticity, viscosity, and loss of integrity. Our findings suggest that, of all ten features, the stiffness, storage, and loss moduli are the most meaningful and consistent parameter to report, while other parameters suffer from a lack of interpretability and inconsistent definitions. We find that the sample stiffness varies by an order of magnitude, from 418.9±41.7kPa for plant-based turkey to 56.7±14.1kPa for tofu. Similarly, the storage and loss moduli vary from 50.4±4.1kPa and 25.3±3.0kPa for plant-based turkey to 5.7±0.5kPa and 1.3±0.1kPa for tofu. All three animal products, animal turkey, sausage, and hotdog, consistently rank in between these two extremes. Our results suggest that–with the right ingredients, additives, and formulation–modern food fabrication techniques can create plant-based meats that successfully replicate the full viscoelastic texture spectrum of processed animal meat.
Ecological and socioeconomic factors associated with globally reported tick-borne viruses
Authors: Sambado Samantha , Ryan Sadie J 
Published: October 2024

ABSTRACTBackgroundPublic health resources are often allocated based on reported disease cases. However, for lesser-known infectious diseases, such as tick-borne viruses, disease risk reporting should account for more than just the biology of the disease and include mediating factors such as socioeconomics which can determine if an infection gets reported.ObjectivesWe aim to identify country-level ecological and socioeconomic factors important to reporting tick-borne viruses and examine whether countries with more economic resources have a higher likelihood of reporting resource intensive incidences. Our study goals are to determine potential country-level interventions that could enhance recognition of and reduce the health burden associated with tick-borne viruses.MethodsWe apply machine learning to the most comprehensive tick-borne virus database, ZOVER, with a curated global trait matrix of 23 environmental and socioeconomic predictors.ResultsWe identified socioeconomic factors driving reported tick-borne viruses captured in the database at a country level. Countries that were more likely to report tick-borne viruses had a lower Gini Index (i.e., countries with less inequalities such as Nordic countries), increased dollars spent on pesticide imports, and had institutions (i.e., IVSA chapter) or individuals with agricultural, forestry, or veterinary knowledge (i.e., % of tertiary grads) present. Additional characteristics included countries with a lower percent of population exposed to conflict also had a higher probability of reporting a tick-borne virus. As expected, broad environmental factors such as the Köeppen-Geiger climate classification zone was important and identified Mediterranean climate or humid subtropical climate as environmentally suitable zones for reported tick-borne viruses.DiscussionFor environmentally persistent pathogens, the role of ancillary factors mediating reporting must be considered for allocating resources to interventions. In addition, while direct interruption of transmission is important, socioeconomic interventions may be the greatest tool to reduce local disease burden.
ABI5 Binding Proteins are substrates of key components in the ABA core signaling pathway
Authors: Lynch Tim J , Erickson McNally B. Joy , Losic Teodora , Lindquist Jonas , Finkelstein Ruth 
Published: October 2024

ABSTRACTThe central components of the ABA core signaling pathway are families of receptors, clade A type 2C protein phosphatases (PP2Cs), SNF1-Related Protein Kinases (SnRK2s), and diverse sets of proteins regulated by phosphorylation via these kinases, including bZIP transcription factors such as ABA-INSENSITIVE(ABI)5. The larger network of ABA signaling factors includes additional kinases and E3 ligases that modify these components to affect their activity and stability. The ABI5-Binding Proteins (AFPs) are negative regulators of ABA response. This study shows that the AFPs interact with specific family members of all components of this pathway and are substrates for SnRK2s and PP2Cs. AFPs also interact with subsets of MAP kinases (MPKs) and 14-3-3 proteins previously found to regulate activity of the ABI5-related clade of transcription factors. Residues predicted to be phosphorylated are conserved between AFPs, but are located within regions predicted to be unstructured. ABA promotes phosphorylation of AFP2, but conditions that prevent phosphorylation of AFP2 result in decreased stability, a shift in localization toward dispersed foci, and reduced effectiveness for inhibiting ABA response at germination. Thus, AFP2 appears to be an important hub in the ABA core signaling pathway.
A fitness distribution law for amino-acid replacements
Authors: Sun Mengyi , Stoltzfus Arlin , McCandlish David M. 
Published: October 2024

AbstractThe 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

AbstractFragment 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

AbstractSynthetic 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

ABSTRACTThe 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

AbstractDeciphering 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.HighlightsCell exposure to flow shear stress modulate mRNA drug membrane transporters and cell polarization of proximal tubuleProximal tubule-on-chip relying on RPTEC/TERT1 cell line is a suitable platform for assessing transcellular cationic transportOCT2 and MATE are involved in potential drug-endogenous metabolite interactionsCell exposure to xenobiotics and endogenous metabolites modulate the drug transporters expression.Graphical AbstractData StatementOriginal 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

AbstractAnthropogenic 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

ABSTRACTSexual 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

ABSTRACTPain 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.