bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative analysis of waterlogging and drought stress regulatory networks in barley (Hordeum vulgare)
Authors: Panahi Bahman 
Published: February 2025

We applied a systems biology approach to gain a deep insight into the regulatory mechanisms of barley (Hordeum vulgare) under drought and waterlogging stress conditions. To identify informative models related to stress conditions, we constructed meta-analysis and two distinct weighted gene co-expression networks. We then performed module trait association analyses. Additionally, we conducted functional enrichment analysis of significant modules to shed light on the biological performance of underlying genes in the two contrasting stresses. In the next step, we inferred the gene regulatory networks between top hub genes of significant modules, kinases, and transcription factors (TFs) using a machine learning algorithm. Our results showed that at power = 10, the scale-free topology fitting index (R2) was higher than 0.8 and the connectivity mean became stable. We identified 31 co-expressed gene modules in barley, with 13 and 14 modules demonstrating significant associations with drought and waterlogging stress, respectively. Functional enrichment analysis indicated that these stress-responsive modules are involved in critical processes, including ADP-rybosylation factors (ARF) protein signal transduction, ethylene-induced autophagy, and phosphoric ester hydrolase activity. Specific TFs and kinases, such as C2C2-GATA, HB-BELL, and MADS-MIKC, were identified as key regulators under these stress conditions. Furthermore, certain TFs and kinases established unique connections with hub genes in response to waterlogging and drought conditions. These findings enhance our understanding of the molecular networks that modulate barley’s response to drought and waterlogging stresses, offering insights into the regulatory mechanisms essential for stress adaptation.
Kin-discriminating partner choice promotes the evolution of helping
Authors: Scott Thomas W , Wild Geoff , Gardner Andy 
Published: February 2025

Abstract
Kin selection theory predicts that individuals should evolve to help relatives, either by helping indiscriminately in a population where they do not move very far from their relatives, or by discriminating kin and conditionally helping them. It has been argued that, because kin discrimination enables individuals to reduce how helpful they are with some social partners as well increase how helpful they are with others, this could lead to an increase or a decrease in the overall level of helping. Specifically, it was argued that kin discrimination would increase the overall level of helping if the function relating the optimal level of help and genetic relatedness is convex, but kin discrimination would decrease the overall level of helping if the function relating the optimal level of help and genetic relatedness is concave. However, this prediction was based on a model in which individuals were not able to choose their social partners but only adjust how helpful they should be towards those social partners they have been allocated. Here, we perform a mathematical analysis showing that being able to choose social partners increases the overall level of helping. Consequently, if kin discriminators are allowed to choose whom they help, kin discrimination is more likely to increase the overall level of helping than previously anticipated. We obtained these results in two complementary theoretical settings: one more general, which makes few demographic assumptions, and the other more specific and concrete, which assumes a patch-structured population with complete dispersal.
The addition of partially Pregelatinized sago starch and red Rice-sago fibre mixture on the functional properties of sago Analog Rice produced through extrusion
Authors: Sabirin  , Sitanggang Azis Boing , Budijanto Slamet , Kusarpoko Mardonius Budi , Pramana Yanuar Sigit , Darussalam Abdullah , Purwoto Ahmad Safrudin , Triwiyono Bambang , Kuswardani Novi , Yassaroh  , Pangesti Anggun , Ratri Laila Widya 
Published: February 2025

Abstract
Partially pregelatinized sago starch (PPSS) and a red rice-sago fibre mixture were investigated for their effects on the functional properties of sago analog rice. Five PPSS:sago starch ratios were tested, each mixed with 33% red rice and 7% sago fibre. Extrusion was performed without precooking using specific process conditions. The addition of 15% PPSS resulted in the lowest cooking loss and improved texture. Sago analog rice had higher crude fibre content than red and white rice due to the sago fibre. X-ray diffraction revealed the formation of intrahelical V-type complexes between sago analog rice and red rice via non-covalent bonds. Various properties were analysed and compared with those of red and white rice.
Microbial ecology of Serpentinite-hosted ecosystems
Authors: Colman Daniel R , Templeton Alexis S , Spear John R , Boyd Eric S 
Published: February 2025

Abstract
Serpentinization, the collective set of geochemical reactions initiated by the hydration of ultramafic rock, has occurred throughout Earth history and is inferred to occur on several planets and moons in our solar system. These reactions generate highly reducing conditions that can drive organic synthesis reactions potentially conducive to the emergence of life, while concomitantly generating fluids that challenge life owing to hyperalkalinity and limited inorganic carbon (and oxidant) availability. Consequently, the serpentinite-hosted biosphere offers insights into the earliest life, the habitable limits for life, and the potential for life on other planets. However, the support of abundant microbial communities by serpentinites was only recognized ~20 years ago with the discovery of deep-sea hydrothermal vents emanating serpentinized fluids. Here, we review the microbial ecology of both marine and continental serpentinization-influenced ecosystems in conjunction with a comparison of publicly available metagenomic sequence data from these communities to provide a global perspective of serpentinite microbial ecology. Synthesis of observations across global systems reveal consistent themes in the diversity, ecology, and functioning of communities. Nevertheless, individual systems exhibit nuances due to local geology, hydrology, and input of oxidized, near-surface/seawater fluids. Further, several new (and old) questions remain including the provenance of carbon to support biomass synthesis, the physical and chemical limits of life in serpentinites, the mode and tempo of in situ evolution, and the extent that modern serpentinites serve as analogs for those on early Earth. These topics are explored from a microbial perspective to outline key knowledge-gaps for future research.
Biphasic bone loss in experimental autoimmune encephalomyelitis
Authors: Schmidt Constantin , Woo Marcel S , Alimy Assil-Ramin , Baranowsky Anke , Krasemann Susanne , Yorgan Timur A , Beil Frank Timo , Schinke Thorsten , Keller Johannes , Friese Manuel A , Amling Michael , Rolvien Tim 
Published: February 2025

Abstract
Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system (CNS) and a common cause for neurological disabilities in young adults. Although it is known that the peripheral immune landscape is altered in people with MS (pwMS), the impact on other organ systems than the CNS is frequently overlooked. In addition to neurological deficits, pwMS suffer from impaired bone health and increased fracture risk. However, the mechanisms underlying bone loss in pwMS are poorly understood. Here, we investigated the compartment-specific bone microarchitecture as well as cellular and molecular mechanisms of altered bone remodeling in pwMS and the corresponding mouse model of experimental autoimmune encephalomyelitis (EAE). We show that pwMS and EAE mice have reduced bone mineral density characterized by a combined loss of trabecular and cortical bone. Intriguingly, bone loss in EAE followed a biphasic dynamic defined by increased osteocyte apoptosis associated with decreased bone formation in acute EAE and increased bone resorption in the chronic phase, which could be explained by increased CXCL13/CXCR5 signaling. In conclusion, the identified stage-dependent mechanism for bone loss in EAE may help to develop improved strategies for osteoporosis treatment in pwMS.
Distinct Gut Microbiota Composition in Pediatric Patients with Central Nervous System (CNS) Tumors: A Comparative Study
Authors: Dossena Chiara , Bergamaschi Luca , Rossignoli Federico , Licata Armando Giuseppe , Gasparini Patrizia , Venturini Lara Veronica , Marra Manuela , Oriani Matilde , Biassoni Veronica , Schiavello Elisabetta , Nigro Olga , Chiaravalli Stefano , Massimino Maura , De Cecco Loris 
Published: February 2025

Abstract

Background
Central nervous system (CNS) tumors are the leading cause of cancer-related deaths in children aged 0–14 years. Despite significant efforts, targeted therapies based on identified pathways have not improved survival rates. Research has shown that the gut microbiota (GM) can influence brain tumor cell proliferation, suggesting that the microbiota-gut-brain axis plays a role in CNS cancer. Our study aims to assess whether the GM composition in pediatric CNS tumors exhibits specific characteristics.

Methods
The study included 18 pediatric patients, 9 diagnosed with CNS tumors (CNS tumors group) and 9 with other tumor types (extra-CNS tumors group). Microbial DNA was extracted from stool samples, and 16S DNA libraries were generated and sequenced. Gut microbiota composition was analyzed using Amplicon Sequence Variant (ASV) tables.

Results
Alpha diversity analysis, represented by the number of observed features, was lower in CNS tumors group (p = 0.0054), while Pielou’s evenness index was similar between groups. LEfSe analysis revealed a significantly reduced abundance of the Firmicutes phylum in CNS tumors group, along with other taxa within this phylum, such as the Clostridia class, Clostridiales order, and Lachnospiraceae family, compared to extra-CNS tumors group. Further analysis using sPLS-DA showed a distinct pattern in GM composition in CNS tumors group, with lower levels of several taxa, particularly the Firmicutes phylum, Lachnospiraceae family, Clostridiales order, Clostridia class, Ruminococcaceae and Coriobacteriaceae families, and Blautia genus..

Conclusions
Pediatric patients with CNS tumors have a distinct gut microbiota composition. The reduction of specific beneficial microbial taxa may contribute to tumor growth through the microbiota-gut-brain axis.
Integration of New Approach Methods for the Assessment of Data Poor Chemicals
Authors: Paul Friedman Katie , Thomas Russell S , Wambaugh John F , Harrill Joshua A , Judson Richard S , Shafer Timothy J , Williams Antony J , Lee Jia-Ying Joey , Loo Lit-Hsin , Gagné Matthew , Long Alexandra S , Barton-Maclaren Tara S , Whelan Maurice , Bouhifd Mounir , Rasenberg Mike , Simanainen Ulla , Sobanski Tomasz 
Published: February 2025

Abstract
Use of new approach methods (NAMs), including high-throughput, in vitro bioactivity data, in setting a point-of-departure (POD) will accelerate the pace of human health hazard assessments. Combining hazard and exposure predictions into a bioactivity: Exposure ratio (BER) for use in risk-based prioritization and utilizing NAM-based bioactivity flags to indicate potential hazards of interest for further prediction or mechanism-based screening together comprise a prospective approach for management of substances with limited traditional toxicity testing data. In this work we demonstrate a NAM-based assessment case study conducted via the Accelerating the Pace of Chemical Risk Assessment (APCRA) initiative, a consortium of international research and regulatory scientists. The primary objective was to develop a reusable and adaptable approach for addressing chemicals with limited traditional toxicity data using a NAM-based POD, BER, and bioactivity-based flags for indication of putative endocrine, developmental, neurological, and immunosuppressive effects via data generation and interpretation for 200 substances. Multiple data streams, including in silico and in vitro NAMs, were used. High-throughput transcriptomics and phenotypic profiling data, as well as targeted biochemical and cell-based assays, were combined with generic high-throughput toxicokinetic models parameterized with chemical-specific data to estimate dose for comparison to exposure predictions. This case study further enables regulatory scientists from different international purviews to utilize efficient approaches for prospective chemical management, addressing hazard and risk-based data needs, while reducing the need for animal studies. This work demonstrates the feasibility of using a battery of toxicodynamic and toxicokinetic NAMs to provide a NAM-based POD for screening-level assessment.
Museums and Zoos: Rapid genetic identification of rare species and practical applications for conservation and systematics in a biodiverse country
Authors: Chavez Daniel E. , Carrión-Olmedo Julio C. , Cabezas María B. , Reyes-Barriga Daniela , Lojan Pamela , Mora David , Bustamante Martin , Pinto C. Miguel , Jarrin-V Pablo 
Published: February 2025

AbstractObtaining genetic information from rare species is challenging for scientists, but it is crucial for understanding animal evolutionary history and informing conservation management initiatives. We present the first example of a collaborative local network that includes zoos and natural history collections to investigate the evolution, systematics, and conservation concerns of olingos (genusBassaricyon, Procyonidae, Carnivora, Mammalia). We sequenced the entire (1,146 base pairs) cytochromebgene to phylogenetically identify individuals that have been victims of wildlife trafficking. Unexpectedly, we detected an individual specimen belonging toBassaricyon medius orinomus(western lowland olingo), which may represent a new geographical record for this taxon in Ecuador. Through our practical experiences, we describe how local collaboration is possible and crucial for promoting wildlife genetic research in the Global South and contributing to protecting the last populations of rare mammals. We also discuss the significance of wild animals under human care as a valuable genetic resource for scientific research, conservation strategies, and informed wildlife management decisions.
A Study of Calibration as a Measurement of Trustworthiness of Large Language Models in Biomedical Research
Authors: de Oliveira Rodrigo , Garber Matthew , Gwinnutt James M , Rashidi Emaan , Hwang Jwu-Hsuan (Shantina) , Gilmour William , Nanavati Jay , El Abidine Khaldoun Zine , Mack Christina DeFilippo 
Published: February 2025

ABSTRACTObjectivesTo assess the calibration of 9 large language models (LLMs) within biomedical natural language processing (BioNLP) tasks, furthering understanding of trustworthiness and reliability in real-world settings.Materials and MethodsFor each LLM, we collected responses and corresponding confidence scores for all 13 datasets (grouped into 6 tasks) of the Biomedical Language Understanding & Reasoning Benchmark (BLURB). Confidence scores were assigned using 3 strategies: Verbal, Self-consistency, Hybrid. For evaluation, we introduced Flex-ECE (Flexible Expected Calibration Error): a novel adaptation of ECE that accounts for partial correctness in model responses, allowing for a more realistic assessment of calibration in language-based settings. Two post-hoc calibration techniques—isotonic regression and histogram binning—were evaluated.ResultsAcross tasks, mean calibration ranged from 23.9% (Population-Intervention-Comparison-Outcome extraction) to 46.6% (Relation Extraction). Across LLMs, Medicine-Llama3-8B had the best mean overall calibration (29.8%); Flan-T5-XXL had the highest ranking on 5/13 datasets. Across strategies, self-consistency (mean: 27.3%) had better calibration than Verbal (mean: 42.0%) and Hybrid (mean: 44.2%). Post-hoc methods substantially improved calibration, with best mean calibrated Flex-ECEs ranging from 0.1% to 4.1%.DiscussionThe poor out-of-the-box calibration of LLMs poses a risk to trustworthy deployment of such models in real-world BioNLP applications. Calibration can be improved post-hoc and is a recommended practice. Non-binary metrics for LLM evaluation such as Flex-ECE provide a more realistic assessment of trustworthiness of LLMs, and indeed any model that can be partially right/wrong.ConclusionThis study shows that out-of-the-box calibration of LLMs is very poor, but traditional post-hoc calibration techniques are useful to calibrate LLMs.
In vivovalidation of kinematic relationships for epithelial morphogenesis
Authors: Namba Toshinori , Sugimura Kaoru , Ishihara Shuji 
Published: February 2025

AbstractTissue growth and deformation result from the combined effects of various cellular events, including cell shape change, cell rearrangement, cell division, and cell death. Resolving and integrating these cellular events is essential for understanding the coordination of tissue-scale growth and deformation by individual cellular behaviors that are critical for morphogenesis, wound healing, and other collective cellular phenomena. For epithelial tissues composed of tightly connected cells, the texture tensor method provides a unified framework for quantifying tissue and cell strains by tracking individual cells in live imaging data. The corresponding kinematic relationships have been introduced in a continuum model that we previously reported. In this study, we validated the kinematic equations proposed in the continuum model using experimental data from a growingDrosophilawing. To accomplish this, we introduced modified definitions of the texture tensor and validated that one of these modifications more accurately represents approximated cellular shapes without relying onad hocscaling factors. By utilizing the modified tensor, we demonstrated the compatibility of the strain rate tensors and validated both the kinematic and cell number density equations. These results crossvalidate the modified texture analysis and continuum model. Further, the precision in the kinematic relationships achieved in this study provide a robust and solid foundation for more advanced integration of modeling and experiments.
Heterogeneous T cell responses across Hepatitis B virus clinical phases revealed by rapid whole-blood HBV T cell analysis
Authors: Le Bert Nina , Koffas Apostolos , Kumar Rajneesh , Facchetti Floriana , Tan Anthony T , Gill Upkar S , Mak Lung-Yi , Stretch Sophie W , Miao Tizong , Hariharaputran Smrithi , Hang Shou Kit , Guo Yifei , Chen Qi , Degasperi Elisabetta , Lampertico Pietro , Chow Wan Cheng , Bertoletti Antonio , Kennedy Patrick TF 
Published: February 2025

AbstractBackground & AimsThere is an unmet need for immunological biomarkers in chronic hepatitis B (CHB), where patient management relies on virological and biochemical markers despite the crucial role of virus-specific T cells in controlling viral replication and disease progression. To address this, we developed the HBV-cytokine release assay (HBV-CRA), a rapid, point-of-care test that measures multiple cytokines in whole blood after HBV-peptide stimulation.MethodsWe first assessed the assay’s sensitivity by spiking whole blood with engineered HBV-specific T cells. Next, we compared sensitivity and consistency of HBV-CRA to ex vivo IFN-γ ELISpot assays. We then applied the assay in a cross-sectional study of 235 CHB patients and longitudinally in acute HBV patients during HBsAg sero-clearance.ResultsThe HBV-CRA detected T cell function in 80% of CHB cases and showed that elevated IL-2 and IFN-γ levels after Core peptide stimulation were associated with HBsAg clearance. Importantly, unsupervised clustering identified distinct immune response patterns independent of established clinical and virological classifications. The assay also demonstrated the functional impact of NUC treatment on HBV-specific T cell responses.ConclusionsThe HBV-CRA is a rapid and easy-to-use assay that identifies immune profiles associated with HBsAg clearance and differentiates CHB patients based on antiviral T cell function. Its application in a large CHB cohort revealed that traditional disease phase classifications, based on viral and clinical parameters, cannot predict HBV-specific T cell profiles. The HBV-CRA has the potential to guide patient stratification for immunotherapeutic interventions.
cfDecon: Accurate and Interpretable methylation-based cell type deconvolution for cell-free DNA
Authors: Wang Yixuan , Li Jiayi , Li Jingqi , Yang Shen , Huang Yuhan , Liu Xinyuan , Fan Yimin , King Irwin , Li Yumei , Li Yu 
Published: February 2025

AbstractCell-free DNA (cfDNA) analysis has emerged as a powerful tool for noninvasive diagnostics and monitoring of aberrant methylation. However, computational deconvolution of cfDNA remains challenging due to the complexity of methylation data, the diverse cellular compositions in cfDNA mixtures, and the limited interpretability of current methods. We present cfDecon, an efficient deep-learning framework for cfDNA deconvolution at the resolution of individual reads. cfDecon employs a multichannel autoencoder core module and an iterative refinement process to estimate cell-type proportions and generate condition-aware cell-type-specific methylation profiles. We rigorously evaluate cfDecon through comprehensive simulation experiments, including scenarios with normal cellular compositions, rare cell types, and unknown cell types, where cfDecon consistently outperforms previous state-of-the-art methods in deconvolution. Using strict data separation and careful control for potential data leakage, cfDecon shows scalability and applicability to large-scale studies by raising Lin’s Concordance Correlation Coefficient (CCC) over 33% on an atlas-level reference dataset. We further validate cfDecon’s utility in disease diagnosis on two clinical datasets, Amyotrophic Lateral Sclerosis (ALS) and Hepatocellular Carcinoma (HCC). cfDecon raises the performance of disease detection from 0.53 to 0.79 compared to existing methods on the ALS dataset and 0.55 to 0.77 on the HCC dataset. The capacity of cfDecon to predict condition-specific DNA methylation patterns across cell types offers a valuable framework for studying differentially methylated CpGs. Furthermore, integrating cfDecon with enrichment analysis facilitates the exploration of functional variations in CpGs across different conditions. cfDecon represents a significant advancement in cfDNA analysis, offering improved accuracy, interpretability, and potential for personalized medicine applications. The codebase is available athttps://github.com/Susanxuan/cfDecon.