bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and Evaluation of Heart Failure Patients Oral Comfort Assessment Questionnaire
Authors: Lu Mei , Yang Runyu , Li Xiaona , Wang Xinkun , Tao Ming 
Published: February 2025

AbstractBackgroundOur objective was to develop a reliable and valid questionnaire to assess the oral comfort status of inpatients with heart failure, providing medical staff with a scientifically grounded tool for evaluating their oral comfort.MethodsA comprehensive pool of questionnaire items was developed through a literature review, qualitative interviews, and expert consultation. Six experts participated in two rounds of consultation to refine the items, followed by a pre-investigation involving 20 patients. Finally, 192 patients treated at Zun Yi Medical University between June and September 2020 were selected for project analysis and to assess the reliability and validity of the questionnaire.ResultsThrough exploratory factor analysis, four common factors were identified, accounting for a cumulative variance contribution rate of 59.611%. The finalized questionnaire comprised 24 items, demonstrating robust reliability and validity. The Cronbach’s α coefficient was 0.810, indicating high internal consistency, while the Spearman-Brown coefficient was 0.732. The Pearson correlation coefficient was 0.233 (P < 0.05) when compared with the Beck Oral Scoring Method (BOAS table). The content validity index (CVI) for individual items ranged from 0.833 to 1. The overall content validity index (S-CVI/UA) for the questionnaire was 0.875, with an average content validity index (S-CVI/Ave) of 0.979.ConclusionThe oral comfort assessment questionnaire developed in this study for inpatients with heart failure exhibits excellent reliability and validity, establishing it as an effective and valuable tool for assessing the oral comfort status of this patient population.
Liver transplant rejection features memory cell priming, spatially differentiated networks and novel drug targets
Authors: Ningappa Mylarappa , Ashokkumar Chethan , Murali Divya , Rajasundaram Dhivyaa , Higgs Brandon W , McDonald William , Schmitt Lori , Zhang Liang , Chattopadhyay Ansuman , Kane Matt , Murphy Patrick , Soltys Kyle , Mazariegos George , Gupta Shakti , Kar Upendra , Billiar Timothy , Zeevi Adriana , Xu Qingyong , Reyes-Múgica Miguel , Subramaniam Shankar , Sindhi Rakesh 
Published: February 2025

AbstractAcute T-cell-mediated transplant rejection, the earliest contributor to immunological graft failure responds variably to T-cell suppression. Early rejection can co-exist with donor-specific antibodies which also shorten graft survival, without affecting graft histology visibly. Here, during early liver transplant rejection, blood leukocytes manifest primed T-cells with heat shock protein (HSP) signaling and transcriptional programs for memory cell expansion. Corresponding biopsies demonstrate upregulated immune synapse and proteasomal genes in T-cell-infiltrated portal and central regions of the liver lobule. With donor-specific antibodies, the intervening intralobular region demonstrates a germinal-center-like allograft response with upregulated CD40, chemokine, T-follicular and complement signaling, which intensifies along the direction of sinusoidal blood flow from portal to central regions. Proteasomal and HSP90 inhibitors suppress donor-specific alloresponses of T- and B-cells in blood samples from patients with early rejection. The molecular injury spectrum of early rejection is complex, spatially differentiated and reveals novel early immunosuppressive strategies to extend graft survival.
Haplotype-based Parallel PBWT for Biobank Scale Data
Authors: Tang Kecong , Sanaullah Ahsan , Zhi Degui , Zhang Shaojie 
Published: February 2025

AbstractDurbin’s positional Burrows-Wheeler transform (PBWT) enables algorithms with the optimal time complexity ofO(MN) for reporting all vs all haplotype matches in a population panel withMhaplotypes andNvariant sites. However, even this efficiency may still be too slow when the number of haplotypes reaches millions. To further reduce the run time, in this paper, a parallel version of the PBWT algorithms is introduced for all versus all haplotype matching, which is called HP-PBWT (haplotype-based parallel PBWT). HP-PBWT parallelly executes the PBWT by splitting a haplotype panel into blocks of haplotypes. HP-PBWT algorithms achieve parallelization for PBWT construction, reporting all versus all L-long matches, and reporting all versus all set-maximal matches while maintaining memory efficiency. HP-PBWT has antime complexity in PBWT construction, and antime complexity for reporting all versus all L-long matches and reporting all versus all set-maximal matches, whereTis the number of threads andc*is the maximum number of matches (of length L or maximum divergence value for L-long matches and set-maximal matches, re-spectively) per haplotype per site. HP-PBWT achieves 4-fold speed-up in UK Biobank genotyping array data with 30 threads in the IO-included benchmarks. When applying HP-PBWT to a dataset of 8 million randomized haplotypes (random binary strings of equal length) in the IO-excluded benchmarks, it can achieve a 22-fold speed-up with 60 cores on the Amazon EC2 server. With further hardware optimization, HP-PBWT is expected to handle billions of haplotypes efficiently.
Regulatory T and activated T cells in the chronic unpredictable mild stress mice: sex differences and effects of treatments
Authors: Niu Mengqi , Zhang Yingqian , Chen Tangcong , Luo Yueyang , Li Mengdie , Maes Michael 
Published: February 2025

AbstractMajor Depressive Disorder (MDD) is strongly associated with immune dysregulation, which is characterized by excessive T-cell activation and a reduction in regulatory T cells (Tregs), leading to a disruption of immune homeostasis. Pharmacological treatments such as fluoxetine, simvastatin, curcumin, and S-adenosylmethionine (SAMe) have shown promise in alleviating depressive symptoms; however, their precise effects on immune responses remain inadequately understood. This study investigates the immune status of regulatory and activated T cells in MDD using the chronic unpredictable mild stress (CUMS) mouse model. Specifically, it examines how fluoxetine, simvastatin, curcumin, and SAMe modulate immune responses and mitigate depressive-like behaviors. Additionally, the study explores the impact of sex differences on immune responses. The study consisted of six groups, with 12 mice per group, ensuring equal male and female representation. These included a control group, a CUMS group, and groups treated with fluoxetine, simvastatin, curcumin, and SAMe. Behavioral changes were evaluated using sucrose preference and forced swimming tests. Immune cell markers from the spleen were analyzed by flow cytometry. The results showed that CUMS mice experienced a breakdown in immune tolerance due to Treg depletion and an increase in the CD154/CD152 ratio. Treatments with fluoxetine, simvastatin, curcumin, and SAMe improved depressive-like behaviors, with SAMe potentially exerting its antidepressant effects through the normalization of the CD154/CD152 ratio. Furthermore, sex differences played a critical role in immune responses: female mice exhibited lower levels of immune regulation and T-cell activation compared to males, along with a higher CD154/CD152 ratio, indicative of immune imbalance.
SpecImmune accurately genotypes diverse immune-related gene families using long-read data
Authors: Wang Shuai , Wang Xuedong , Wang Mengyao , Zhou Qian , Li Shuai Cheng 
Published: February 2025

ABSTRACTPolymorphic immune-related genes (HLA, KIR, IG, TCR, and CYP) exhibit significant complexity due to their extensive heterozygosity and inter-loci homology, necessitating specific methods for accurate characterization. We present SpecImmune, the first comprehensive tool leveraging long-read sequencing data to resolve the full spectrum of these immune-related genes. The method adopts an iterative graph-based algorithm for haplotype reconstruction. We validated SpecImmune across 1,019 samples from the 1kGP ONT cohort, 42 PacBio CLR and 9 PacBio HiFi samples from the HGSVC project, and 47 PacBio HiFi and 37 ONT samples from the HPRC project. SpecImmune achieved an accuracy of 98% in HLA typing, which represents a 12% improvement over both SpecHLA and HLA*LA. SpecImmune is the initial method to type multiple CYP loci, as well as the foremost approach to allow precise KIR and germline IG/TCR typing using long reads. Comprehensive genotyping of these loci by SpecImmune unveils a new observation of substantial linkage disequilibrium among HLA, KIR, and CYP loci. The proteins derived from these loci exhibit strong binding affinities, which suggest the origin of the marked linkage disequilibrium. Further, SpecImmune unveils a novel finding of elevated IG/TCR heterozygosity in African populations. Additionally, SpecImmune facilitates the detection ofde novomutations and enables allele-specific drug recommendations.
Chemotype diversity of foliar volatile emissions in Cork oak suggests independent geographic variations in quality and quantity
Authors: Staudt Michael , Rivet Coralie , Erdogan Meltem 
Published: February 2025

AbstractKnowledge of the intraspecific variability of volatiles produced by plants is central for estimating their fluxes from ecosystems and for understanding their evolution in an ecological and phylogenetic context. Past studies suggested that leaf volatile emissions from Cork oak (Quercus suberL.) exhibit a particular high degree of qualitative and quantitative polymorphism. However, the extent of inherent emission variability across its range is not known.We investigated leaf emissions and ecophysiological variables of 241 Cork oak seedlings from ten provenances. To minimize environmental influences, emissions were determined at 30 °C and saturating light on seed-grown saplings of similar age grown under the same conditions. All individuals, except for three apparent non-emitters, released the same five monoterpenes at a rate of 2559 ± 120 ng m-2s-1. Northern provenances tended to have higher mean emission rates and lower photosynthetic rates than southern populations, resulting in significant differences in their apparent carbon losses by volatile emissions. Independently, the emission composition varied discontinuously among individuals according to three distinct chemotypes, indicating inherent differences in the activity of two types of monoterpene synthases: one producing α-, β-pinene and sabinene, and the other limonene (plus myrcene as a by-product). Chemotype frequencies differed among provenances, particularly between South-Eastern Mediterranean and South-Western Atlantic provenances. Regarding ecophysiological leaf traits, we found no significant difference between chemotypes.The study confirms that Cork oak is a strong monoterpene emitter, showing independent intraspecific variability in emission quality and quantity, with non-emitters being rare. Comparison of the emission variability with those reported for other oak species suggests that an ancestral Pinene/sabine chemotype has diversified within the oak subgenusCerrisduring its radiation. This diversification is less pronounced in Cork oak than in other sympatric oaks, possibly due to differential fragmentation and expansion of their ranges in the past.
Harnessing subtractive genomics for drug target identification inStreptococcus agalactiaeserotype v (atcc baa-611 / 2603 v/r) strain: Anin-silicoapproach
Authors: Chowdhury Ashiqur Rahman Khan , Tithi Farjana Yasmin , Bhuiyan Nusrat Zahan , Ishita Afsana Ferdousi , Sohel Md Mahmodul Hasan 
Published: February 2025

AbstractDeveloping a therapeutic target for bacterial disease is challenging.In silicosubtractive genomics methodology offer a promising alternative to traditional drug discovery methods.Streptococcus agalactiaeinfections depend on two crucial criteria: drug-resistance and the existence of virulence factors. It is essential to underline thatS. agalactiaestrains have emerged to be resistant to several drugs. Hence, there is a need for research on novel drugs and techniques that are potent, economical, productive, and dependable to combatS. agalactiaeinfections. In this study advanced computational techniques were exploited to examine potential druggable targets exclusive to this pathogen. Our study uncovered 200 non-homologous proteins inS. agalactiaeserotype V (Strain ATCC BAA-611 / 2603 V/R) and identified 68 essential proteins indispensable for the bacterium’s survival. Therefore, these 68 proteins are potential targets for drug development. Subcellular localization analysis unveiled that the pathogen’s cytoplasmic membrane contained essential proteins among these vital non-homologous proteins. On the other hand, based on virulent protein predictions, six proteins were seen to be virulent. Among these, we prioritized two proteins (Sensor protein LytS and Galactosyl transferase CpsE which are exclusively found inS. agalactiae) as potential druggable targets and selected them for further structural investigation. The proteins chosen could serve as a foundation for the identification of a promising therapeutic compound that has the potential to neutralize these enzymatic proteins, thereby contributing to the reduction of risks linked to the drug-resistantS. agalactiae.
Conditioned versus innate effort-based tasks reveal divergence in antidepressant effect on motivational state in male mice
Authors: Xeni Foteini , Marangoni Caterina , Lin Lynn , Robinson Emma S J , Jackson Megan G 
Published: February 2025

AbstractAntidepressant-induced apathy syndrome is reported in a high number of patients. It is characterised by loss of motivation for daily activities and emotional blunting. It has a negative impact on quality of life and treatment outcome, yet the changes in underlying neurobiology driving this syndrome remain unclear. To begin to address this, a comprehensive understanding of how different classes of antidepressant treatment impact on behaviours relevant to apathy is critical. Rodent motivation for reward is commonly assessed using effort-based operant conditioning paradigms such as the Effort for Reward task. However, motivation to perform spontaneous/innate behaviours may provide additional insight into changes in behaviour reflective of daily activities. We tested the acute and chronic effects of antidepressants on the Effort for Reward task, and the spontaneous/innate Effort Based Forage task. Acute treatment revealed important divergence in drug effect between tasks, where selective serotonin reuptake inhibitor (SSRI)/serotonin and noradrenaline reuptake inhibitor (SNRI) treatment impaired foraging behaviour in the Effort Based Forage task, but enhanced high effort, high value reward responding in the Effort for Reward task. Treatment with a noradrenaline reuptake inhibitor (NRI) or multimodal agent impaired foraging behaviour but did not affect high reward responding in the Effort for Reward task. Conversely, chronic treatment with an SSRI but not SNRI enhanced motivated foraging behaviour but led to a general impairment in Effort for Reward task output. Together, these data demonstrate that SSRI treatment induces opposing effects on conditioned versus innate motivation which may have significant translational relevance when interpreting drug effect.
Encapsidic production and isolation of degradation-prone polypeptides
Authors: Gawin Agnieszka , Pankowski Jędrzej , Zarechyntsava Maria , Kwasna Dominika , Kloska Damian , Koziej Lukasz , Glatt Sebastian , Kachamakova-Trojanowska Neli , Azuma Yusuke 
Published: February 2025

AbstractDegradation during production and delivery is a significant bottleneck in developing biomolecular therapies. Here, we show that encapsulation in protein cages formed by engineered variants of a cage-forming lumazine synthase establishes an effective route for microbial production and isolation of otherwise difficult-to-express, degradation-prone polypeptides. In this system, genetic fusion to a cage component protomer ensures efficient guest packaging while being produced in host bacterial cells. Meanwhile, the controlled opening outside the cellular context allows facile isolation of cargo via sequence-specific protease cleavage. Furthermore, modular patchwork assembly avoids guest overloading, preventing unwanted incomplete cage assembly and the formation of insoluble aggregates. The general applicability of our “encapsidic” production approach was demonstrated by the efficient production of six intrinsically disordered polypeptides that have proven therapeutic potentials.
Old vs. New Local Ancestry Inference in HCHS/SOL: A Comparative Study
Authors: Chen Xueying , Wang Hao , Broce Iris , Dale Anders , Yu Bing , Zhou Laura Y , Li Xihao , Argos Maria , Daviglus Martha L , Cai Jianwen , Franceschini Nora , Sofer Tamar 
Published: February 2025

AbstractHispanic/Latino populations are admixed, with genetic contributions from multiple ancestral populations. Studies of genetic association in these admixed populations often use methods such as admixture mapping, which relies on inferred counts of “local” ancestry, i.e., of the source ancestral population at a locus. Local ancestries are inferred using external reference panels that represent ancestral populations, making the choice of inference method and reference panel critical. This study used a dataset of Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) to evaluate the “old” local ancestry inference performed using the state-of-the-art inference method, RFMix, alongside “new” inferences performed using Fast Local Ancestry Estimation (FLARE), which also used an updated reference panel. We compared their performance in terms of global and local ancestry correlations, as well as admixture mapping-based associations. Overall, the old RFMix and new FLARE inferences were highly similar for both global and local ancestries, with FLARE-inferred datasets yielding admixture mapping results consistent with those computed from RFMix. However, in some genomic regions the old and new local ancestries have relatively lower correlations (Pearson R < 0.9). Most of these genomic regions (86.42%) were mapped to either ENCODE blacklist regions, or to gene clusters, compared to 7.67% of randomly-matched regions with high correlations (Pearson R > 0.97) between old and new local ancestries.
scCompare: a web app for single-cell RNA sequencing dataset comparisons across multiple auto-immune diseases
Authors: Yadav Shweta , Sahasrabudhe Pranav , Pingili Mulini , Chang Dan , Wang Jing 
Published: February 2025

AbstractMotivationSingle-cell RNA sequencing (scRNA-seq) datasets have been widely used to identify the cell types and marker genes with pivotal roles in driving pathogenesis and progression of auto-immune diseases. Comparative analysis of different cell types or diseases across multiple scRNA-seq datasets can reveal the homogeneous and heterogeneous pathogenesis, and a comprehensive web-based comparison tool that could streamline this process is not yet available.ResultsWe introduce scCompare, a web-based platform for scRNA-seq comparisons in autoimmune diseases. scCompare includes 2,125 differential gene lists from 100 scRNA-seq datasets in 22 auto-immune diseases and a query system supporting 170 standardized keywords from four attributes (disease, cell type, tissue, and treatment). scCompare also provides three modules enabling several comparative analysis and visualization options. geneQuery supports comparisons of queried genes across differential gene lists identified from multiple scRNA-seq datasets. DEGEnricher performs cell-type-specific enrichment analysis across studies based on a user-input gene list. DEGCompare allows interactive comparisons of multiple differential gene lists of many studies and performs pathway enrichment analyses. Using two case studies as examples, we demonstrated that scCompare represents a unique platform for biologists to identify, compare and validate the pathogenesis at the single-cell levels among auto-immune diseases.Availability and implementationscCompare is freely available athttps://sccompare.shinyapps.io/main/. The source code is available athttps://github.com/abbviegrc/scCompare.
NMR Spectroscopy for the Validation of AlphaFold2 Structures
Authors: Williams Jake , Gagnon Isabelle A. , Sachleben Joseph R. 
Published: February 2025

AbstractThe introduction of AlphaFold has fundamentally changed our ability to predict the structure of proteins from their primary sequence of amino acids. As machine learning (ML) and artificial intelligence (AI) based protein prediction continues to advance, we examine the potential of hybrid techniques that combine experiment and computation that may yield more accurate structures than AI alone with significantly reduced experimental burden. We have developed heuristics comparing N-edited NOESY spectra and AlphaFold predicted structures that seek to determine whether the predicted structure reasonably describes the structure of the protein which generated the NOESY. We present a large collection of data connecting entries across the BMRB, PDB and AlphaFold Database that includes experimentally derived structures and corresponding spectra, establishing it as a means to develop and test hybrid methods utilizing AlphaFold and NMR spectra to perform structure determination. These data test the new heuristics’ ability to identify inaccurate AlphaFold structures. A support vector machine was developed to test the consistency of NMR data with predicted structure and we show its application to the structure of an unsolved engineered protein, LoTOP.
A Multi-Model Ensemble Reveals Soil Carbon Gains from Regenerative Practices in the U.S. Midwest Cropland
Authors: Basso Bruno , Tadiello Tommaso , Millar Neville , Robertson G. Philip , Paustian Keith , Maureira Fidel S. , Albarenque Susana , Baer Brian , Price Lydia , Sharma Prateek , Villalobos Chris , Fowler Ames , Delandmeter Mathieu , Acutis Marco , Archontoulis Sotirios , Covey Kristofer R. , Doro Luca , Dumont Benjamin , Grace Peter R. , Hoogenboom Gerrit , Jones James W. , Perego Alessia , Ruane Alexander , Stöckle Claudio O. , Zhang Yao 
Published: February 2025

AbstractProcess-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification (MMRV) frameworks of carbon markets, but their application suffers from model-specific differences that keep any one model from working well across all combinations of soils, climates, crops, and agronomic practices at varying scales. Multi-model ensemble (MME), successfully used to quantify soil, management and climate impact on crop productivity, provide an opportunity to better estimate changes in soil organic carbon (SOC) outcomes for agronomic practices that have the potential to mitigate SOC loss at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4- km2to assess the aggregate ability of different regenerative practices to sequester SOC at this scale compared to their dynamic baselines. MME was validated with long-term experimental data and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 ± 0.12 Mg ha-1yr-1aggregated across the entire U.S. Midwest cropland. At the regional scale, this corresponds to a net SOC gain of 16.4 Tg C yr-1compared to business-as-usual baselines. These benefits are approximately halved when each management change is practiced individually, and the modest gains are only fully realized when continued over the long-term in soils with low initial carbon stock. Results demonstrate the power of MMEs run at high resolution for providing robust estimates of environmental outcomes following agricultural practice change, and for pinpointing locations for most effective intervention. This approach can alleviate many producer carbon market participation barriers and help address market issues while ultimately supporting large-scale regenerative agriculture initiatives.