bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geology and climate drive alpine plant compositional variation among peaks in the Cascade Range of Washington
Authors: Ertsgaard Erik W. , Gjording Nicholas L. , Bakker Jonathan D. , Kleinkopf Joseph A. , Giblin David E. 
Published: December 2024

AbstractAlpine areas are host to diverse plant communities that support ecosystems through structural and floral resources and persist through specialized adaptations to harsh high-elevation conditions. An ongoing question in these plant communities is whether composition is shaped by stochastic processes (e.g., dispersal limitations) or by deterministic processes (e.g., climate, geology), and if those processes select for common phylogenetic clades across space. This study evaluates the drivers of dissimilarity in alpine vascular plant communities across 32 peaks in the Cascade Mountain Range of Washington State and examines the effects of incorporating phylogenetic relatedness to these conclusions. We documented an average of 54 species per peak and used our overall inventory of 307 taxa to construct a phylogenetic tree for the entire mountain range plant community sampled. We used multivariate techniques to quantify the phylogenetic and taxonomic differences between alpine plant communities and to relate those differences to each peak’s climate, geology, and topography. Our models indicate that the age of each peak’s parent material formation, precipitation, latitude, and temperature had the largest role in shaping alpine plant communities relative to the baseline effects of distance between peaks and time of sampling. A unique result was a distinct plant community in peaks with ultramafic geologic parent material formed in the Paleozoic Era, which has an extreme geochemistry that we found to form evolutionarily distinct lineages compared to all other peaks. With changing climate conditions and disturbance regimes, understanding facets of alpine plant communities like species turnover, geologic endemism, and responses to precipitation changes are vital to conserving these ecosystems.
Computational Analysis of the Gut Microbiota-Mediated Drug Metabolism
Authors: Chum Sammie , Naveira Montalvo Alberto , Hassoun Soha 
Published: December 2024

AbstractThe gut microbiota, an extensive ecosystem harboring trillions of bacteria, plays a pivotal role in human health and disease, influencing diverse conditions from obesity to cancer. Among the microbiota’s myriad functions, the capacity to metabolize drugs remains relatively unexplored despite its potential implications for drug efficacy and toxicity. Experimental methods are resource-intensive, prompting the need for innovative computational approaches. We present a computational analysis aimed at predicting gut microbiota-mediated drug metabolism (MDM). This computational analysis incorporates data from diverse sources, e.g., UHGG, MagMD, MASI, KEGG, and RetroRules. An existing tool, PROXIMAL2, is used iteratively over all drug candidates from experimental databases queried against biotransformation rules from RetroRules to predict potential drug metabolites along with the enzyme commission number responsible for that biotransformation. These potential metabolites are then categorized into gut microbiota-mediated drug metabolites by cross referencing UHGG. The analysis’ efficacy is validated by its coverage on each of the experimental databases in the gut microbial context, being able to recall up to 74% of experimental data and producing a list of potential metabolites, which an average of about 65% are relevant to the gut microbial context. Moreover, explorations into ranking metabolites, iterative applications to account for multi-step metabolic pathways, and potential applications in experimental studies showcase its versatility and potential impact beyond raw predictions. Overall, this study presents a promising computational analysis for further research and application in the fields of gut MDM, drug development and human health.
Verkko2: Integrating proximity ligation data with long-read De Bruijn graphs for efficient telomere-to-telomere genome assembly, phasing, and scaffolding
Authors: Antipov Dmitry , Rautiainen Mikko , Nurk Sergey , Walenz Brian P. , Solar Steven J. , Phillippy Adam M. , Koren Sergey 
Published: December 2024

AbstractThe Telomere-to-Telomere Consortium recently finished the first truly complete sequence of a human genome. To resolve the most complex repeats, this project relied on the semi-manual combination of long, accurate PacBio HiFi and ultra-long Oxford Nanopore sequencing reads. The Verkko assembler later automated this process, achieving complete assemblies for approximately half of the chromosomes in a diploid human genome. However, the first version of Verkko was computationally expensive and could not resolve all regions of a typical human genome. Here we present Verkko2, which implements a more efficient read correction algorithm, improves repeat resolution and gap closing, introduces proximity-ligation-based haplotype phasing and scaffolding, and adds support for multiple long-read data types. These enhancements allow Verkko to assemble all regions of a diploid human genome, including the short arms of the acrocentric chromosomes and both sex chromosomes. Together, these changes increase the number of telomere-to-telomere scaffolds by twofold, reduce runtime by fourfold, and improve assembly correctness. On a panel of 19 human genomes, Verkko2 assembles an average of 39 of 46 complete chromosomes as scaffolds, with 21 of these assembled as gapless contigs. Together, these improvements enable telomere-to-telomere comparative and pangenomics, at scale.
Navigating the Maze: Identifying Potential Pitfalls in Attention State Classification from fMRI Brain Patterns
Authors: Bressler Ruben Andreas , Ciarlo Assunta , Raible Sophie , Valente Giancarlo , Lührs Michael , Tier Ralph , Linden David E. , Goebel Rainer 
Published: December 2024

AbstractMulti-voxel pattern analysis (MVPA) is a powerful technique to decode brain states from functional magnetic resonance imaging (fMRI) activity patterns. In neurofeedback (NF) applications, it has been used to perform real-time classification of brain activity patterns, establishing a closed-loop system that provides immediate feedback to the participants, enabling them to learn to control a complex mental state. However, MVPA has many potential limitations when applied to fMRI datasets (especially in real-time analysis) arising from small effect sizes, small number of training samples, high dimensionality of the data and, more generally, design choices. All these factors might produce inaccurate classification results. In this work, we followed a previous NF paradigm for sustained attention training. Participants were presented with composite images superimposing faces and scenes. They were instructed to focus on one class (either face or scene) for an extended period. A logistic regression classifier was trained to determine whether participants were adequately focusing on the instructed category based on their fMRI data. We analysed the classification outputs of the no-feedback training runs using various classifier settings, including whole brain data and different masking approaches, combined with different methods for the computation of single-trial fMRI responses. Furthermore, a ventricle mask was used as a control condition for the classification task, and simulations were carried out to assess the influence of the class order on the classification performances. We found inflation of the decoding accuracy for several common design choices and confounders. In particular, motion artefacts and low frequency drifts coupled with the task timing might have artificially increased the accuracy scores. Furthermore, the simulations revealed that fixed order in the presentation of experimental conditions resulted in further inflation of the classification accuracies especially in GLM-based and average-based trial estimate methods. We discuss the drawbacks of applying MVPA using the analysed sustained attention paradigm and provide insights for future improvements.
An evolutionarily conserved tryptophan cage promotes folding of the extended RNA recognition motif in the hnRNPR-like protein family
Authors: Atsrim Ernest S. , Eichhorn Catherine D. 
Published: December 2024

AbstractThe heterogeneous nuclear ribonucleoprotein (hnRNP) R-like family is a class of RNA binding proteins in the hnRNP superfamily that has diverse functions in RNA processing. Here, we present the 1.90 Å X-ray crystal structure and solution NMR studies of the first RNA recognition motif (RRM) of human hnRNPR. We find that this domain adopts an extended RRM (eRRM1) featuring a canonical RRM with a structured N-terminal extension (Next) motif that docks against the RRM and extends the β-sheet surface. The adjoining loop positions the Nextfor docking to the RRM and forms a tryptophan cage motif, which has only been reported previously in a synthetic peptide. Using a combination of mutagenesis, solution NMR spectroscopy, and thermal denaturation studies we evaluate the importance of residues in the Next-RRM interface and adjoining loop on eRRM folding and conformational dynamics. We find that these sites are essential for protein solubility, thermal stability, and conformational ordering. Consistent with their importance, mutations in the Next-RRM interface and loop are associated with several cancers in a survey of somatic mutations in cancer studies. Sequence and structure comparison of the human hnRNPR eRRM1 to experimentally verified and predicted hnRNPR-like proteins reveal conserved features in the eRRM.Significance statementThis study provides the first structural and thermodynamic analysis of the hnRNPR extended RNA recognition motif (eRRM1). Here an N-terminal extension docks alongside a canonical RRM, stabilized by an intervening loop containing a tryptophan cage motif. Highly conserved among hnRNPR-like proteins, this motif has only been previously observed in a synthetic peptide. Substitutions that disrupt observed interactions reduce thermal stability and are associated with cancers. These findings significantly advance our understanding of atypical RRM folding.
Genomic and transcriptomic profiling of high-risk bladder cancer reveals diverse molecular and microenvironment ecosystems
Authors: Meghani Khyati , Yu Yanni , Frydenlund Noah , Li Erik Z. , Choy Bonnie , Abdulkadir Sarki A. , Meeks Joshua J. 
Published: December 2024

AbstractDespite surgical resection, rigorous endoscopic surveillance, and immunotherapy with the Bacillus Calmette–Guérin (BCG) vaccine, 30% of high-risk bladder cancers recur, and 10% result in fatal outcomes within two years of diagnosis. The global shortage of BCG underscores the urgent need for alternative or complementary therapeutic strategies. To address this, we integrated transcriptomic profiling and targeted genomic sequencing to identify four consensus intrinsic subtypes of bladder cancer. Initially derived from bulk RNA profiling, these subtypes were further validated at the cellular and tissue-compartment levels using single-cell RNA sequencing and spatial transcriptomics. Notably, we identified a subtype of inflamed tumors with enhanced endogenous retroelement expression and increased commensal bacterial presence, which showed the highest responsiveness to BCG therapy. Additionally, we developed a machine learning-based model incorporating composite molecular features to predict recurrence risk, achieving a high accuracy (AUC = 0.90). Our findings establish a molecular precision framework for bladder cancer and nominate novel therapeutic targets to reduce reliance on BCG immunotherapy.
Leukemia escapes immunity by imposing a Type-1 regulatory program on neoantigen-specific CD4+ T cells
Authors: Venkatesh Hrishi , Arroyo Miriam , Heltemes-Harris Lynn , Knutson Todd P. , Qiu Yinjie , Haaning Allison , Webber Beau R. , Bachanova Veronika , Farrar Michael A. , Tracy Sean I. 
Published: December 2024

AbstractThe significance of endogenous immune surveillance in acute lymphoblastic leukemia (ALL) remains controversial. Using clinical B-ALL samples and a novel mouse model, we show that neoantigen-specific CD4+ T cells are induced to adopt type-1 regulatory (Tr1) function in the leukemia microenvironment. Tr1s then inhibit cytotoxic CD8+ T cells, preventing effective leukemia clearance. Leukemic cells induce Tr1s by phenocopying hematopoietic stem cells, which normally are subject to effective surveillance by this CD4+ subset. This mechanism effectively redirects Tr1 cells from a role in preventing cancer to maladaptively promoting clinical relapse. In mouse models, inhibition of Tr1 expansion with IL10 receptor (IL10R) blockade is insufficient to improve leukemia control. In contrast, combined therapy with a cytotoxic agent and anti-PDL1 blockade eradicated measurable residual disease. This correlates with polarization of the neoantigen-specific CD4+ T-cell population from Tr1 towards Th1 states. Our findings uncover a mechanism that enables leukemic relapse and resolves existing controversies on the role of immune surveillance towards this cancer type. Therapeutic polarization of neoantigen-specific CD4+ T cells towards Th1 states may improve contemporary immune therapies by reshaping the immune microenvironment towards states permissive for cytotoxic attack of residual leukemia.Key PointsB-ALL induces neoantigen-specific CD4+ T cells to adopt Type-1 regulatory states, which protect leukemic cells from immune pressure.Repolarizing neoantigen-specific CD4+ T-cells towards Th1 states eradicates measurable residual disease.
Cytochrome ‘Nanowires’ are Physically Limited to Sub-Picoamp Currents that Suffice for Cellular Respiration
Authors: Guberman-Pfeffer Matthew J. , Herron Caleb L. 
Published: December 2024

AbstractMineral-respiring microorganisms from hydrothermal vents to terrestrial soils express filaments that electrically connect intracellular respiration to extracellular geochemistry. Filaments dubbed “cytochrome nanowires” (CNs) have been resolved by CryoEM, but whether they are the two-decades-long sought-after physiological ‘nanowires’ remains unproven. To assess their functional competence, we analyzed biological redox conduction in all CNs by computing driving forces in the presence of redox anti-cooperativities, reorganization energies with electronic polarizability, and Marcus rates for diffusive and protein-limited flux models. The chain of heme cofactors in any CN must be densely packed to realize weak (≤0.01 eV) electronic coupling for electron transfer, as evidenced by a single Soret band produced from coincidental absorptions on multiple hemes. Dense packing, in turn, has three consequences: (1) limited driving forces (≤|0.3| eV) due to shared electrostatic microenvironments, (2) strong (≤0.12 eV) redox anti-cooperativities that would accentuate the free energy landscape if the linear heme arrangement did not dictate a contra-thermodynamic oxidation order, and (3) an entropic penalty that is offset by thioether ‘tethers’ of the hemes to the protein backbone. These linkages physically necessitate the rate-throttling T-stacked motif (10-fold slower than the other highly conserved slip-stacked motif). If the sequence of slip- and T-stacked hemes in the CNs had the fastest known nanosecond rates at every step, a micron-long filament would carry a diffusive 0.02 pA current at a physiological 0.1 V, or a protein-limited current of 0.2 pA. Actual CNs have sub-optimal (≤102-fold lower), but sufficient conductivities for cellular respiration, with at most thousands of filaments needed for total cellular metabolic flux. Since cells likely discharge less than the 1.0 pA assumed here, and there are multiple pathways besides CNs for expelling electrons, the micro-to-milli-Siemens/cm conductivities are more than sufficient. Reported conductivities once used to argue for metallic-like pili against the cytochrome hypothesis and now illogically attributed to CNs remain inconsistent by 102-105-fold with the physical constraints imposed on biological redox conduction through multiheme architectures.
Discovery of a novel bandavirus using metagenomic sequencing in a retrospective analysis of an unresolved 2020 mortality event involving black vultures in the northeastern United States
Authors: Mwakibete Lusajo , Hoarau Axel O. G. , Ahyong Vida , Waltari Eric , Bender Susan J. , Davison Sherrill , Niedringhaus Kevin D. , Gibison Michelle L. , Gagne Roderick B. , Miller Erica A. , Murphy Lisa A. , Kistler Amy , Tato Cristina M. 
Published: December 2024

AbstractInvestigations of wildlife diseases and mortality events can sometimes lead to inconclusive results due to limitations in diagnostics combined with an ever-increasing number of emerging viruses. The use of tools such as unbiased metagenomic next generation sequencing (mNGS) can facilitate the identification of causative agents where conventional investigation methods fail. We performed a retrospective mNGS analysis on RNA isolated from postmortem samples collected during a black vulture (Coragyps atratus, family: Cathartidae) mortality event that occurred in eastern Pennsylvania and western New Jersey in 2020. We describe the discovery and identification of a novel species of bandavirus (Phenuiviridaefamily) in case specimens from this die-off, as well as some of the associated pathological findings. TheBandavirusgenus comprises tickborne viral species that have been reported across five continents and implicated in outbreaks in a variety of mammalian hosts, including humans, and in avian species making them important potential sources of zoonotic spillover events. Genomic and phylogenetic analysis of the bandavirus detected in this study indicate its closest relative corresponds to Hunter Island virus, a bandavirus previously implicated in albatross mortality events off the coast of Tasmania, Australia. Follow-up PCR testing of samples from additional vultures from the same cohort confirmed that this new bandavirus is the likely cause of death.
Myeloid-derived Suppressor Cells Mitigate Inflammation in Periodontal Disease
Authors: Naqvi Raza Ali , Valverde Araceli , Nares Salvador , Van Dyke Thomas E. , Naqvi Afsar R. 
Published: December 2024

AbstractMyeloid derived suppressor cells (MDSCs) are a heterogeneous population of immature, immune suppressive myeloid cells. However, their role in periodontal disease (PD), a microbially induced inflammatory oral disease, remains understudied. Here we show that gingiva (gums) from PD patients exhibit significantly higher levels of MDSC markers including Granulocytic (G)-MDSC and Monocytic (M)-MDSC subsets as well as CD4+T cells and CD19+B cells. Gingival MDSC subsets exhibit potent immunoregulatory activity as marked by attenuated autologous CD4+ T cells proliferation and IFNγ production. In a murine model of ligature-induced periodontitis (LIP), we noticed time-dependent gingival MDSC infiltration, which correlates with CD4+T cell and CD19+B cell infiltration. To test whether MDSC confer immunoregulatory functionin vivo, we adoptively transferred G-MDSCs and M-MDSCs in mice. Interestingly, we observed significant reduction in inflammatory marker expression (IL6, TNF-α, and IL-1β), infiltration of CD4+T cells, and concomitant increase in MDSC-derived immune suppressive molecules, ARG1 and IL-10, and CD4+CD25+FoxP3+Tregs compared to mock. Conversely, depletion of MDSC using anti-Gr1 antibody resulted in marked induction of periodontal inflammation, reduced Treg population, and significantly higher alveolar bone loss. These findings, for the first time, suggest an anti-inflammatory and osteoprotective function of MDSCs in PD and offer a promising target to treat unresolved periodontal inflammation.
SenSet, a novel human lung senescence cell gene signature, identifies cell-specific senescence mechanisms
Authors: Hasanaj Euxhen , Beaulieu Delphine , Wang Cankun , Hu Qianjiang , Bueno Marta , Sembrat John C , Pineda Ricardo H , Melo-Narvaez Maria Camila , Cardenes Nayra , Yanwu Zhao , Yingze Zhang , Lafyatis Robert , Morris Alison , Mora Ana , Rojas Mauricio , Li Dongmei , Rahman Irfan , Pryhuber Gloria S , Lehmann Mareike , Alder Jonathan , Gurkar Aditi , Finkel Toren , Ma Qin , Póczos Barnabás , Bar-Joseph Ziv , Eickelberg Oliver , Königshoff Melanie 
Published: December 2024

AbstractCellular senescence is a major hallmark of aging. Senescence is defined as an irreversible growth arrest observed when cells are exposed to a variety of stressors including DNA damage, oxidative stress, or nutrient deprivation. While senescence is a well-established driver of aging and age-related diseases, it is a highly heterogeneous process with significant variations across organisms, tissues, and cell types.The relatively low abundance of senescence in healthy aged tissues represents a major challenge to studying senescence in a given organ, including the human lung. To overcome this limitation, we developed a Positive-Unlabeled (PU) learning framework to generate a comprehensive senescence marker gene list in human lungs (termed SenSet) using the largest publicly available single-cell lung dataset, the Human Lung Cell Atlas (HLCA). We validated SenSet in a highly complex ex vivo human 3D lung tissue culture model subjected to the senescence inducers bleomycin, doxorubicin, or irradiation, and established its sensitivity and accuracy in characterizing senescence. Using SenSet, we identified and validated cell-type specific senescence signatures in distinct lung cell populations upon aging and environmental exposures. Our study presents the first comprehensive analysis of senescent cells in the healthy aging lung and uncovers cell-specific gene signatures of senescence, presenting fundamental implications for our understanding of major lung diseases, including cancer, fibrosis, chronic obstructive pulmonary disease, or asthma.
The Rodent Electronic Nicotine Delivery System: Apparatus for Voluntary Nose-Only E-Cigarette Aerosol Inhalation
Authors: Odum Amy L. , Willis-Moore Mariah E. , Callister Kiernan T. , Haynes Jeremy M. , Frye Charles C. J. , Scribner Lucy N. , Legaspi David N. , Da Silva Daniel Santos , Olsen Aaron L. , Truscott Tadd T. , Alden Preston T. , Bevins Rick A. , Leventhal Adam M. , Lee Stephen T. , Gomer Brenna , Benninghoff Abby D. 
Published: December 2024

AbstractTobacco use is the leading cause of death globally and in the U.S. After decades of decline, driven by decreases in combusted tobacco use, nicotine product use has increased due to Electronic Nicotine Delivery Systems, also known as e-cigarettes or vapes. Preclinical models of nicotine self-administration can serve as important lodestars in the search for effective intervention and prevention tactics. Current variants of the task have substantial limitations, however. Therefore, we created the Rodent Electronic Nicotine Delivery System, a novel low-cost non-proprietary nose-only preclinical model of nicotine aerosol self-administration. We confirmed that RENDS sequesters nicotine aerosol in the nose port by measuring fine particulate matter (PM < 2.5 microns) generated by e-cigarettes. We also showed that rats robustly self-administer flavored nicotine aerosol, resulting in high blood levels of cotinine (the major nicotine metabolite) and spontaneous somatic withdrawal symptoms. Thus, we provide strong validation of the operation and function of the RENDS, opening the door to an open-source preclinical aerosol model of nicotine self-administration that is relatively low cost. Four existing operant chambers can be retrofitted with the RENDS for less than $325/chamber. All RENDS diagrams and plans for custom designed components are on Open Science Framework (https://osf.io/x2pqf/?view_only=775b55435b8e428f98e6da384ef7889d).