bluuebunny/crossref_metadata_2025_split huggingface dataset:
A micro-ChromaDot array with AI integration for the detection of multiple biomarkers in a small portable device
Authors: Lin Zuan-Tao , Peng Yun , Kong Yifei , Zhang Yi , Shou Wan , Jana Biswabandhu , Korupolu Sandeep , Gao Shilin , Li Yongli , Liang Chen , Wang Zhilong , Matusik Wojciech , Wu Mei X. 
Published: January 2025

AbstractWith the rapid growth of digital healthcare, diagnosis, prognosis, and monitoring of chronic and acute diseases at home are increasingly in demand. In light of the intricate biological processes underlying many diseases, a single biomarker is often insufficient for disease diagnosis, whereas multiplexed measurements of biomarkers remain a significant challenge at point-of-care (POC). Herein, we introduce a micro-ChromaDot array (McDa) designed to qualify a panel of biomarkers at POC in a one-biomarker-one-dot fashion. The McDa colorimetric signals were engraved from a 3D microneedle array with chem-spatial signal amplification cascade, which allowed seamless and precise data acquisition and analysis by smartphone. This home-use and cost-effective platform achieved similar specificity and superior sensitivity to conventional enzyme-linked immunoassay (ELISA), a clinic assay that typically requires a fully equipped laboratory, and trained personnel, and is time-consuming. Five biomarkers of clinical sera, collected from a cohort of systemic lupus erythematosus (SLE) patients (n = 42) and healthy controls (n = 34), were measured by McDa and modeled with deep learning. By leveraging the support vector machines (SVM) model combined with 5-fold cross-validation, we demonstrated that a selected panel of three biomarkers effectively discriminated SLE patients from healthy controls with a remarkable 97% specificity, representing an impressive 70% improvement over the clinical standard of the single biomarker antinuclear antibodies (ANA) test, while sustaining the same 93% sensitivity. This platform can easily adapt to assess other biomarkers with a mere drop of blood or any other body liquids and holds great promise to transform POC.
Different functions for the lateral line in schooling behavior in three fish species
Authors: Tidswell Ben K. , Tytell Eric D. 
Published: January 2025

ABSTRACTFish use vision and the lateral line in order to school together. Previous studies suggest that some species rely more than others on the lateral line for schooling, and no clear mechanistic reason for these differences has been identified. To address the question of how species-level differences in the lateral line might impact schooling behavior, we identified three schooling species (giant daniosDevario aequipinnatus, cherry barbsPuntius titteya, and neon tetrasParacheirodon innesi) that come from different environments and have differently structured lateral line systems. We expected to see larger changes in schooling behavior in species of fish with more neuromasts. To test this hypothesis we imaged the lateral lines of these fishes, then quantified schooling behavior before and after lateral line ablation. Giant danios had the lowest density of neuromasts and, as expected, showed little response to ablation. Cherry barbs and neon tetras both had higher densities of neuromasts and schooled differently after ablation, but in opposite ways. Cherry barbs became a less cohesive school while neon tetras formed a more cohesive school. Both of these species had a greater density of neuromasts than giant danios, but the cherry barbs had a greater number of canal neuromasts. This difference in canal neuromasts in cherry barbs may explain the differences in schooling behavior after ablation if they depended more on them for schooling. Overall, these results shed light on the importance of the lateral line, and the diversity of roles it plays in fish schooling.
Optimized antibody with W32I mutation enhances antiviral efficacy against influenza
Authors: Guan Shanshan , Wang Qingyu , Nie Jiaojiao , Yao Xin , Xie Kunpeng , Zhao Weihao , Chang Yaotian , Zhu Lvzhou , Hui Jiaru , Yin Tieyan , Liu Xiaopan , Shan Yaming 
Published: January 2025

ABSTRACTThe influenza virus has caused a global pandemic with significant morbidity and mortality, highlighting the need to optimize antibodies for improved antiviral efficacy. The 3E1 antibody effectively neutralizes influenza subtypes H1 and H5 by inhibiting acid-induced conformational changes of hemagglutinin (HA). This study aimed to optimize the antibody’s bioactivity by modifying amino acid residues, resulting in single-point mutants (3E1-L [W32I], 3E1-H [F103I]) and a double mutant (3E1-H+L [F103I, W32I]). The binding affinity, neutralizing activity, and antiviral mechanisms of the mutants were evaluated. Notably, the 3E1-L mutant showed significantly enhanced antiviral activity against H1N1 and H3N2 compared to wild-type 3E1, inhibiting both viral entry and release. The prophylactic and therapeutic efficacy of the 3E1-L mutant was validated. Molecular dynamics simulations of the 3E1-L/HA complex showed that the W32I mutation reduces steric hindrance between tryptophan at position 32 and the complementarity-determining region (CDR) L1 loop of HA. In conclusion, the W32I substitution enhances the antiviral activity of wild-type 3E1, making the optimization of 3E1-L a promising strategy for developing more effective influenza therapies.
High short tandem repeat mutation recurrence in heat-stressedArabidopsis thalianalines
Authors: Reinar William B. , Greulich Anne , Lalun Vilde O. , Butenko Melinka A. , Jakobsen Kjetill S. 
Published: January 2025

SummaryThe rise of the annual average temperature presents a strong selection pressure for many species. Sessile organisms, such as the plantArabidopsis thaliana(A. thaliana), need to adapt to elevated temperatures. Here, we conducted a mutation accumulation experiment inA. thalianaunder high temperature to monitor genetic changes over nine generations in three parallel lines compared to three lines under normal growth conditions. Whole-genome sequencing of every sample allowed us to accurately capture mutations in troublesome regions by utilizing the genotypes of both parent and offspring. Our approach revealed that high temperature treatment disproportionally increased the rate of insertions and deletions in dimeric short tandem repeats (STRs) compared to the rate of single nucleotide variants. Recurrent mutations appeared more often than expected, indicating a mutation bias along the genome sequence. Our study sheds light on the mutational landscape of a plant genome when exposed to high temperature stress and points to STRs as key genomic elements that rapidly increase the standing genetic variation available for natural selection.
A serotonergic mechanism is involved in the pro-cognitive effect of AM6545 treatment in a mouse model of fragile X syndrome
Authors: de los Reyes-Ramírez Lucía , Bergadà-Martínez Araceli , Martínez-Torres Sara , Martínez-Gallego Irene , Losada-Ruiz Pilar , Arboleya Silvia , Gueimonde Miguel , Maldonado Rafael , Rodríguez-Moreno Antonio , Ozaita Andrés 
Published: January 2025

AbstractFragile X syndrome (FXS) is the principal monogenic syndrome leading to inherited intellectual disability and autism. It is caused by the silencing ofFMR1gene that leads to the loss in the expression of its encoded protein, the fragile X messenger ribonucleoprotein 1 (FMRP). In synapses, FMRP has a key role in local mRNA modulation to maintain synaptic plasticity. TheFmr1KO (FX) mouse model shows cognitive impairment and some of the synaptic traits present in individuals with FXS together with alterations in gut microbiota. Previous studies revealed that pharmacological and genetic cannabinoid type-1 receptor (CB1R) inhibition significantly prevented central key alterations in FX mice. Here, we aimed to evaluate the effect of a sub-chronic treatment with the largely peripherally-restricted CB1R antagonist AM6545. We found that AM6545 reduced memory deficits and restored enhanced hippocampal mGluR5-dependent long-term depression and aberrant dendritic spine density in FX mice. At the peripheral level, AM6545 modified altered FX mice fecal microbiota composition, while in the hippocampus AM6545 treatment upregulated hippocampalHtr4, the gene encoding for serotonin receptor 4 (5-HT4R) This upregulation positively correlated with memory performance. Notably, acute pharmacological blockade of 5-HT4R abolished the pro-cognitive effect produced by AM6545. Together, our results suggest that peripheral CB1R inhibition ameliorates key alterations in FX mouse model and modifies the expression of serotonergic receptors important for cognitive performance.
Lipidomic Analysis Reveals Drug-Induced Lipoxins in Glaucoma Treatment
Authors: Mathew DJ , Maurya S , Ho J , Livne-Bar I , Chan D , Buys Y , Sit M , Trope G , Flanagan JG , Gronert K , Sivak JM 
Published: January 2025

ABSTRACTSynthetic prostaglandin analogues, such as latanoprost, are first-line treatments to reduce intraocular pressure (IOP) in the management of glaucoma, treating millions of patients daily. Glaucoma is a leading cause of blindness, characterized by progressive optic neuropathy, with elevated IOP being the sole modifiable risk factor. Despite this importance, the underlying latanoprost mechanism is still not well defined, being associated with both acute and long term activities, and ocular side effects. Prostaglandins are eicosanoid lipid mediators. Yet, there has not been a comprehensive assessment of small lipid mediators in glaucomatous eyes. Here we performed a lipidomic screen of aqueous humour sampled from glaucoma patients or healthy control eyes. The resulting signature was surprisingly focused on significantly elevated levels of arachidonic acid (AA) and the potent proresolving mediator, lipoxin A4(LXA4) in glaucoma eyes. Subsequent experiments revealed that this response is due to latanoprost actions, rather than a consequence of elevated IOP. We demonstrated that increased LXA4inhibits pro-inflammatory cues and promotes TGF-β3mediated tissue remodeling in the anterior chamber. In concert, an autocrine prostaglandin circuit mediates rapid IOP-lowering. This work reveals parallel mechanisms underlying acute and long-term latanoprost activities during the treatment of glaucoma.
ECLARE: multi-teacher contrastive learning via ensemble distillation for diagonal integration of single-cell multi-omic data
Authors: Mann-Krzisnik Dylan , Li Yue 
Published: January 2025

AbstractIntegrating multimodal single-cell data, such as scRNA-seq and scATAC-seq, is key for decoding gene regulatory networks but remains challenging due to issues like feature harmonization and limited quantity of paired data. To address these challenges, we introduceECLARE, a novel framework combining multi-teacher ensemble knowledge distillation with contrastive learning for diagonal integration of single-cell multi-omic data.ECLAREtrains teacher models on paired datasets to guide a student model for unpaired data, leveraging a refined contrastive objective and transport-based loss for precise cross-modality alignment. Experiments demonstrateECLARE’s competitive performance in cell pairing accuracy, multimodal integration and biological structure preservation, indicating that multi-teacher knowledge distillation provides an effective mean to improve a diagonal integration model beyond its zero-shot capabilities. Additionally, we validateECLARE’s applicability through a case study on major depressive disorder (MDD) data, illustrating its capability to reveal gene regulatory insights from unpaired nuclei. While current results highlight the potential of ensemble distillation in multi-omic analyses, future work will focus on optimizing model complexity, dataset scalability, and exploring applications in diverse multi-omic contexts.ECLAREestablishes a robust foundation for biologically informed single-cell data integration, facilitating advanced downstream analyses and scaling multi-omic data for training advanced machine learning models.
Molecular Mechanisms of Drug Resistance and Compensation in SARS-CoV-2 Main Protease: The Interplay Between E166 and L50
Authors: Zvornicanin Sarah N. , Shaqra Ala M. , Flynn Julia , Carias Martinez Heidi , Jia Weiping , Moquin Stephanie , Dovala Dustin , Bolon Daniel N. , Kurt Yilmaz Nese , Schiffer Celia A. 
Published: January 2025

AbstractThe SARS-CoV-2 main protease (Mpro) is essential for viral replication, and a primary target for COVID-19 antivirals. Direct-acting antivirals such as nirmatrelvir, the active component of Paxlovid, target the Mproactive site to block viral polyprotein cleavage and thus replication. However, drug resistance mutations at the active site residue Glu166 (E166) have emerged inin vitroselection studies, raising concerns about the durability of current antiviral strategies. Here, we investigate the molecular basis of drug resistance conferred by E166A and E166V mutations against nirmatrelvir and the related PF-00835231, individually and in combination with the distal mutation L50F. We found that E166 mutations reduce nirmatrelvir potency by up to 3000-fold while preserving substrate cleavage, with catalytic efficiency reduced by only up to 2- fold. This loss of catalytic efficiency was compensated for by the addition of L50F in the double- mutant variants. We have determined three cocrystal structures of the E166 variants (E166A, E166V, and E166V/L50F) bound to PF-00835231. Comparison of these structures with wild- type demonstrated that E166 is crucial for dimerization and for shaping the substrate-binding S1 pocket. Our findings highlight the mutability of E166, a prime site for resistance for inhibitors that leverage direct interactions with this position, and the potential emergence of highly resistant and active variants in combination with the compensatory mutation L50F. These insights support the design of inhibitors that target conserved protease features and avoid E166 side- chain interactions to minimize susceptibility to resistance.
Toti: an integrated multi-omics database to decipher the epigenetic regulation of gene expression in totipotent stem cells
Authors: Chai Yi , Zhang Ruiying , Jia Shunze , Zhu Danfei , Chen Siyi , Fu Xudong , Sheng Xin 
Published: January 2025

AbstractTotipotent cells (TSCs), the origin of mammalian life and foundation to early mammalian embryogenesis, are characterized by the highest differentiation capacity and extensive developmental potential. However, none of the existing embryonic databases have provided epigenetic and transcriptomic resources on totipotency, greatly limiting our understanding of the mechanisms governing the establishment and exit of totipotency. Here, we present Toti, a pioneering multi-omics database exclusively developed for totipotency, coveringin vivo,in vitroand genome-edited human and mouse embryonic TSCs, TSC-like cells, pluripotent cells (PSCs), and embryos spanning preimplantation stages, with a total of 8,265 samples. Toti facilitates an in-depth exploration of the molecular mechanisms underlying totipotency by offering Search, Browse and Analysis modules available athttp://toti.zju.edu.cn/.
Unveiling Cognitive Processes Underlying Depression-like Behaviors in the Force Swim and Tail Suspension Tests
Authors: Li Zhihan , Lu Tianyu , Yan Jiaozhao , Zhang Xiang , Li Yun-Feng 
Published: January 2025

AbstractThe forced swim test (FST) and tail suspension test (TST) are widely used to assess depression-like behaviors in rodents, with immobility time serving as a primary metric. However, this measure oversimplifies the complex cognitive processes involved, obscuring the relationship between immobility and cognitive biases. Here, we employ a custom-developed tool to capture complete behavioral trajectories in mice and apply reinforcement learning models for systematic analysis. Our findings indicate that behaviors in both tests can be interpreted as reinforcement learning processes that encompass learning, consequence perceiving, and decision-making. Notably, the underlying cognitive processes differ between the two tests, challenging the assumption that the FST and TST are interchangeable for cross-validation. Additionally, we exam two methods for inducing depression-like behavior: chronic restraint stress and medial prefrontal cortex inhibition. Both approaches increase immobility by altering learning dynamics and consequence sensitivity. Regression analyses further reveal two distinct behavior phases: an early phase dominated by learning-related factors and a later phase influenced by consequence sensitivity. These results suggests that conventional metrics focus solely on the final minutes of testing may underestimate learning processes while overemphasize sensitivity to consequences. Our study underscores the importance of computational modeling in revealing the complex cognitive mechanisms underlying animal behavior.
Dietary protein source mediates colitis pathogenesis through bacterial modulation of bile acids
Authors: Gray Simon M. , Wood Michael C. , Mulkeen Samantha C. , Ahmed Sunjida , Thaker Shrey D. , Chen Bo , Sander William R. , Bibeva Vladimira , Zhang Xiaoyue , Yang Jie , Herzog Jeremy W. , Zhang Shiying , Dogan Belgin , Simpson Kenneth W. , Sartor R. Balfour , Montrose David C. 
Published: January 2025

Introductory paragraphEvidence-based dietary recommendations for individuals with inflammatory bowel diseases (IBD) are limited. Red meat consumption is associated with increased IBD incidence and relapse in patients, suggesting that switching to a plant-based diet may limit gut inflammation. However, the mechanisms underlying the differential effects of these diets remain poorly understood. Feeding diets containing plant- or animal-derived proteins to murine colitis models revealed that mice given a beef protein (BP) diet exhibited the most severe colitis, while mice fed pea protein (PP) developed mild inflammation. The colitis-promoting effects of BP were microbially-mediated as determined by bacterial elimination or depletion and microbiota transplant studies. In the absence of colitis, BP-feeding reduced abundance ofLactobacillus johnsoniiandTuricibacter sanguinisand expandedAkkermansia muciniphila, which localized to the mucus in association with decreased mucus thickness and quality. BP-fed mice had elevated primary and conjugated fecal bile acids (BAs), and taurocholic acid administration to PP-fed mice worsened colitis. Dietary psyllium protected against BP-mediated inflammation, restored BA-modulating commensals and normalized BA ratios. Collectively, these data suggest that the protein component of red meat may be responsible, in part, for the colitis-promoting effects of this food source and provide insight into dietary factors that may influence IBD severity.
PathX-CNN: An Enhanced Explainable Convolutional Neural Network for Survival Prediction and Pathway Analysis in Glioblastoma
Authors: Sobhan Masrur , Islam Md Mezbahul , Mondal Ananda Mohan 
Published: January 2025

AbstractMotivationConvolutional neural networks (CNNs) offer potential for analyzing non-grid structured data, such as biological array data, by converting it into image-like formats using principal component analysis (PCA) of pathway genes. However, PCA-derived principal components (PCs) from the entire dataset capture global variance but fail to extract sub-cohort (class-specific) variances. Consequently, CNNs trained on global PCs perform poorly in survival prediction of glioblastoma multiforme (GBM), and the corresponding explanation of CNN outcomes may not align with disease-relevant pathways.ResultsWe present PathX-CNN, an explainable CNN framework that addresses these limitations by integrating multi-omics data through pathway-based images derived from sub-cohort-specific PCs. PathX-CNN outperformed existing pathway-based methods in predicting long-term survival (LTS) versus non-LTS in GBM. By leveraging SHAP (SHapley Additive exPlanations), a cooperative game theory-based explainable AI method, PathX-CNN identified biologically plausible pathways associated with GBM survival. Additionally, experiments on other cancer types demonstrated superior performance compared to traditional approaches. PathX-CNN demonstrates the potential of CNNs for multiomics integration, offering both improved prediction accuracy and pathway-specific insights into disease mechanisms.Code Availabilityhttps://github.com/codebysobhan/PathX-CNNContactamondal@fiu.eduSupplementary informationSupplementary data are available atBioinformaticsonline.
YTHDF3 promotes the progression of gastric cancer by activating Wnt/β-catenin signaling pathway via targeting NEK7
Authors: Sun Xiaoran , Han Shuangshuang , Liu Kunyi , Si Yi , Xuan Mingda , Zhang Rui , Jiao Jiao , Liu Ting , Yu Weifang , Wang Jia 
Published: January 2025

AbstractGastric cancer is a widespread and deadly malignancy among global digestive tract tumors, alarmingly ranking as the fifth most common cancer in terms of incidence and mortality. Our research, utilizing immunohistochemistry and qRT-PCR, revealed a significant upregulation of YTHDF3 in gastric cancer tissues compared to adjacent non-cancerous tissues. This increased expression of YTHDF3 was found to be closely associated with the incidence of lymph node metastasis and the progression to more advanced TNM stages in patients.In vitroexperiments demonstrated that YTHDF3 is crucial in promoting the aggressive characteristics of gastric cancer cells by enhancing their ability to proliferate, migrate, and invade, while simultaneously inhibiting apoptosis. The role of YTHDF3 in the progression of gastric cancer was further confirmed by nude mouse subcutaneous tumor model, which showed slowed tumor growth upon YTHDF3 knockdown. This study further confirms through a series of experiments including Co-IP, Co-IF, Western blot, and rescue studies that YTHDF3 promotes the progression of gastric cancer by targeting NEK7 to regulate the Wnt/β-catenin signaling pathway. These pivotal findings highlight the YTHDF3/NEK7/Wnt/β-catenin axis as a promising and accessible therapeutic target for developing new treatments aimed at enhancing the outcomes for gastric cancer patients.
Decoy-seq unlocks scalable genetic screening for regulatory small noncoding RNAs
Authors: Choi Benedict , Sobti Sushil , Soto Larisa M. , Charbonneau Trey , Sababi Aiden , Navickas Albertas , Najafabadi Hamed S. , Goodarzi Hani 
Published: January 2025

AbstractSmall noncoding RNAs (smRNAs) play critical roles in regulating various cellular processes, including development, stress response, and disease pathogenesis. However, functional characterization of smRNAs remains limited by the scale and simplicity of phenotypic readouts. Recently, single-cell perturbation screening methods, which link CRISPR-mediated genetic perturbations to rich transcriptomic profiling, have emerged as foundational and scalable approaches for understanding gene functions, mapping regulatory networks, and revealing genetic interactions. However, a comparable approach for probing the regulatory consequences of smRNA perturbations is lacking. Here, we present Decoy-seq as an extension of this approach for high-content, single-cell perturbation screening of smRNAs. This method leverages U6-driven tough decoys (TuD), which form stable duplexes with their target smRNAs, for inhibition in the cell. Lentiviral-encoded TuDs are compatible with conventional single-cell RNA-sequencing (scRNA-seq) technologies, allowing joint identification of the smRNA perturbation in each cell and its associated transcriptomic profile. We applied Decoy-seq to 336 microRNAs (miRNAs) and 196 tRNA-derived fragments (tRFs) in a human breast cancer cell line, demonstrating its ability to uncover complex regulatory pathways and novel functions of these smRNAs. Notably, we show that tRFs influence mRNA polyadenylation and regulate key cancer-associated processes, such as cell cycle progression and proliferation. Therefore, Decoy-seq provides a powerful framework for exploring the functional roles of smRNAs in normal physiology and disease, and holds promise for accelerating future discoveries.