bluuebunny/crossref_metadata_2025_split huggingface dataset:
Merging conformational landscapes in a single consensus space with FlexConsensus algorithm
Authors: Herreros D. , Mata C.P. , Sorzano C.O.S. , Carazo J.M. 
Published: January 2025

AbstractThe analysis of structural heterogeneity in CryoEM is experimenting a significant breakthrough toward estimating more accurate, richer, and interpretable conformational landscapes directly derived from experimental data. The increasing number of new methods designed to tackle the heterogeneity challenge reflects these new paradigms, allowing users to understand protein dynamics better. However, a question remains on how the estimation of different heterogeneity algorithms compare, which is essential to properly determine the reliability, stability, and correctness of the conformational landscapes and the structural transitions extracted from the CryoEM images. The intrinsic differences arising from the approximation and implementation of every heterogeneity algorithm make the definition of a consensus complex, a problem that remains unsolved. To overcome the challenges of comparing heterogeneity algorithms, we introduce our new FlexConsenus algorithm in this work. FlexConsensus relies on a multi-autoencoder architecture to learn the commonalities and differences of several conformational landscapes, allowing one to place them in a shared consensus space with enhanced reliability. In addition, FlexConsensus enables the derivation of error metrics from the consensus space to measure the reproducibility of the heterogeneity estimations. Thanks to the previous consensus metrics, it is possible to clean the original particle datasets further based on the differences in the estimation of their structural variability among different algorithms and/or different runs, allowing users to focus their analysis only on those particles with a stable estimation of their structural variability.
The research trends and hotspots of NLRP3 inflammasome in Alzheimer’s disease: a bibliometric and visualization analysis
Authors: Wen Xuanwei , Yang Huiye , Chen Shuangxi , Xiao Zijian 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) is the most common neurodegenerative disorder, the NLRP3 inflammasome has been shown to play a pivotal role in the pathogenesis of AD, and with increasing attention to its involvement in AD. Therefore, we applied bibliometric methods to describe the current research status of the NLRP3 inflammasome in AD. This study aims to analyze the research trends and hotspots in this field from 2013 to 2024, providing valuable insights for AD research.MethodsWe have selected research on the NLRP3 inflammasome in Alzheimer’s disease from the Web of Science Core Collection, with the time range from January 1, 2013, to November 30, 2024, and exported all publications in plain text format. Visualization analysis was performed using CiteSpace 6.4.R1, VOSviewer 1.6.20, and Scimago Graphica 1.0.46.ResultsA total of 759 publications related to the NLRP3 inflammasome in Alzheimer’s disease were included in this study. The number of annual publications showed a general upward trend. The top three countries in terms of publication volume were China, the United States, and Italy. The University of Manchester was the institution with the highest number of publications. The author with the most publications was Michael Heneka, while the most cited author was Eicke Latz. The International Journal of Molecular Sciences published the highest number of articles and was also the most frequently cited journal. The most common keywords included Alzheimer’s disease, NLRP3 inflammasome, neuroinflammation, Aβ, and microglia.ConclusionThe primary research hotspots in this field focus on the role of NLRP3 in AD pathology, its potential as a therapeutic target, and strategies to modulate neuroinflammation through targeting the NLRP3 inflammasome. Future research should further investigate the interactions between NLRP3 and other molecular pathways, assess its clinical therapeutic potential, and provide new insights and strategies for the early diagnosis and treatment of AD.
Structural and functional characterization of integrin α5-targeting antibodies for anti-angiogenic therapy
Authors: Nguyen Adam , Heim Joel B. , Cordara Gabriele , Chan Matthew C. , Johannesen Hedda , Charlesworth Cristine , Li Ming , Azumaya Caleigh M. , Madden Benjamin , Krengel Ute , Meves Alexander , Campbell Melody G. 
Published: January 2025

AbstractIntegrins are a large family of heterodimeric receptors important for cell adhesion and signaling. Integrin α5β1, also known as the fibronectin receptor, is a key mediator of angiogenesis and its dysregulation is associated with tumor proliferation, progression, and metastasis. Despite numerous efforts, α5β1-targeting therapeutics have been unsuccessful in large part due to efficacy and off-target effects. To mediate activation and signaling, integrins undergo drastic conformational changes. However, how therapeutics influence or are affected by integrin conformation remains incompletely characterized. Using cell biology, biophysics, and electron microscopy, we shed light on these relationships by characterizing two potentially therapeutic anti-α5β1 antibodies, BIIG2 and MINT1526A. We show that both antibodies bind α5β1 with nanomolar affinity and reduce angiogenesisin vitro. We demonstrate BIIG2 reduces tumor growth in two human xenograft mouse models and exhibits a strong specificity for connective tissue-resident fibroblasts and melanoma cells. Using electron microscopy, we map out the molecular interfaces mediating the integrin-antibody interactions and reveal that although both antibodies have overlapping epitopes and block fibronectin binding via steric hindrance, the effect on the conformational equilibrium is drastically different. While MINT1526A constricts α5β1’s range of flexibility, BIIG2 binds without restricting the available conformational states. These mechanistic insights, coupled with the functional analysis, guide which aspects should be prioritized to avoid off-target effects or partial agonism in the design of future integrin-targeted therapeutics.
ERGA-BGE genome ofErebia palaricaChapman, 1905: a montane butterfly endemic to North-West Iberia
Authors: Vila Marta , Torrado-Blanco Laura , Ryrholm Nils , Romero-Pedreira David , Conejero María , Böhne Astrid , Monteiro Rita , Marcussen Thomas , Oomen Rebekah , Struck Torsten Hugo , Aguilera Laura , Gut Marta , Ferreira Francisco Câmara , Rodriguez Fernando Cruz , Gómez-Garrido Jèssica , Alioto Tyler S. , Bortoluzzi Chiara 
Published: January 2025

AbstractThe reference genome ofErebia palaricawill provide valuable insights into evolutionary and conservation genomics. On one hand, the reference genome paves the way to unravel the speciation process, reproductive barriers, and putative hybridisation ofE. palaricawith its closely related sister species:Erebica meolans. On the other hand, the reference genome will play an important role in the genetic monitoring of this endemic species, facilitating the use of genomics to estimate population genomics parameters. The genome was assembled into 14 contiguous chromosomal pseudomolecules (Z chromosome included). This chromosome-level assembly encompasses 0.49 Gb, composed of 38 contigs and 17 scaffolds, with contig and scaffold N50 values of 34.2 Mb and 38.4 Mb, respectively.
ERGA-BGE genome of the Spanish Moon MothGraellsia isabellaeGraells, 1849: a nocturnal lepidopteran protected by the Habitats Directive
Authors: Vila Marta , Marí-Mena Neus , Vila Roger , Riesgo Ana , García-Souto Daniel , Lopez-Vaamonde Carlos , Böhne Astrid , Monteiro Rita , Marcussen Thomas , Oomen Rebekah , Struck Torsten Hugo , Gut Marta , Aguilera Laura , Ferreira Francisco Câmara , Rodriguez Fernando Cruz , Gómez-Garrido Jèssica , Alioto Tyler S. , Bortoluzzi Chiara 
Published: January 2025

AbstractThe reference genome of the Spanish Moon Moth,Graellsia isabellae, will be of great importance for evolutionary and conservation genomics. Firstly, this reference genome, alongside phylogenomic analyses, may finally resolve the longstanding debate regarding the scientific name of this iconic species—whether it should beGraellsia isabellae(Graells, 1849) orActias isabellae(Graells, 1849). Secondly, the reference genome will be instrumental in the genetic monitoring of this protected species, enabling advanced methods to calculate contemporary population genomics estimates. The genome was assembled into 31 contiguous chromosomal pseudomolecules (Z chromosome included). The mitochondrial genome has also been assembled and is 15,247 bp in length. This chromosome-level assembly encompasses 0.56 Gb, composed of 38 contigs and 32 scaffolds, with contig and scaffold N50 values of 18.9 Mb and 20.4 Mb, respectively.
PARAS: high-accuracy machine-learning of substrate specificities in nonribosomal peptide synthetases
Authors: Terlouw Barbara R. , Huang Chuan , Meijer David , Cediel-Becerra José D. D. , Rothe Marlene L. , Jenner Matthew , Zhou Shanshan , Zhang Yu , Fage Christopher D. , Tsunematsu Yuta , van Wezel Gilles P. , Robinson Serina L. , Alberti Fabrizio , Alkhalaf Lona M. , Chevrette Marc G. , Challis Gregory L. , Medema Marnix H. 
Published: January 2025

AbstractNonribosomal peptides are chemically and functionally diverse natural products with important applications in medicine and agriculture. Bacterial and fungal genomes contain thousands of nonribosomal peptide biosynthetic gene clusters (BGCs) of unknown function, providing a promising resource for peptide discovery. Core structural features of such peptides can be inferred by predicting the substrate(s) of adenylation (A) domains in nonribosomal peptide synthetases (NRPSs). However, existing approaches to A domain prediction rely on limited datasets and often struggle with domains selecting large substrates or from less-studied taxa. Here, we systematically curate and computationally analyse 3,254 A domains and present two new high-accuracy specificity predictors, PARAS and PARASECT. A new type of A domain with unusually high L-tryptophan specificity was identified through the application of PARAS, and intact protein mass spectrometry to the corresponding NRPS showed it to direct the production of tryptopeptin-related metabolites inStreptomycesspecies. Together, these technologies will accelerate the characterisation of novel NRPSs and their metabolic products.PARAS and PARASECT are available athttps://paras.bioinformatics.nl.
Sinusoidal regulation denoises circadian machinery
Authors: Kaji Hotaka , Mori Fumito , Maruyama Osamu , Ito Hiroshi 
Published: January 2025

AbstractThe rhythms transmitted from the circadian clock inevitably fluctuate because of molecular noise. The level of period fluctuations, observed not in the circadian clock, but in the output system that receives the transmitted rhythm, varies according to the organism and cell type, ranging from 0.5% to 10%. However, it remains unclear how the signal transduction involved in this transmission affects the fluctuations in the oscillation period of the output system. To address this, we investigated a coupled system consisting of a circadian clock and its output. We numerically and analytically demonstrated that the rhythmic regulation through which the clock controls downstream gene expression affects the level of fluctuations in the output system. Moreover, Gibbs sampling based on the analytically obtained fluctuation formula confirmed that the sine-wave-like regulatory functions effectively minimized the fluctuation of the output system. These theoretical insights provide new perspectives on signal transduction as a denoising mechanism embodied in the circadian system.Author summaryRecent single-cell observations have revealed that individual cells exhibit circadian rhythms with intrinsic variability. In particular, the period fluctuation, evaluated using the coefficient of variation (CV), was studied. In this study, we investigated how signal transduction from the central clock affects period fluctuations in the output system. We identified a key factor influencing these fluctuations: the waveform of the regulatory function by which the circadian clock governs the downstream output. We numerically demonstrated that the fluctuations vary widely depending on the regulatory function and that the sinusoidal function significantly reduced fluctuations in the output system. Furthermore, Gibbs sampling revealed that sine-like regulatory functions effectively minimized fluctuations. These findings suggest a preference for near-sinusoidal waveforms in the regulation of circadian rhythms.
A hermetically closed sample chamber enables time-lapse nano-characterization of pathogenic microorganismsin-vitro
Authors: Braun Esther , Andany Santiago H. , Kangül Mustafa , Asmari Navid S. , McKinney John D. , Fantner Georg E. 
Published: January 2025

AbstractPathogenic microorganisms, such as pathogenic mycobacteria, pose a global health burden. Studying these organisms is crucial for gaining detailed knowledge about the pathogens and the diseases they cause. To handle pathogenic organisms, specific biosafety measures appropriate to the virulence of the organism must be fulfilled, most importantly ensuring that all manipulations of pathogenic material are performed within a confined environment. Atomic force microscopy (AFM) is a powerful technique to study biological samples at nanometer-scale resolution, yielding also mechanical properties, all while maintaining physiological conditions. However, standard AFM sample holders do not meet stringent biosafety requirements since they do not constitute a confined system. AFM imaging relies on direct contact between the cantilever and the sample and is sensitive to mechanical interference, rendering conventional containment systems for handling infectious substances inapplicable. Here, we introduce a hermetically sealed AFM sample chamber that meets biosafety demands while satisfying the mechanical and optical constraints of correlated optical microscopy and AFM. We imaged various pathogenic mycobacteria to demonstrate the chamber’s versatility and effectiveness in containing biohazardous materials. This sample chamber enables high-resolution, time-lapse correlated imaging and biomechanical characterization of pathogenic microorganismsin-vitro. It broadens the scope of research with pathogenic microorganisms under safe and controlled conditions.
Phosphorylation patterns modulate the transient secondary structure of RNA polymerase II CTD without altering its global conformation
Authors: Chen (陳瑋) Wei , Laremore Tatiana N. , Yennawar Neela H. , Showalter Scott A. 
Published: January 2025

AbstractThe intrinsically disordered C-terminal domain (CTD) of RNA polymerase II coordinates transcription and co-transcriptional events through dynamic phosphorylation patterns. While it has been long hypothesized that phosphorylation induces structural changes in the CTD, a direct comparison of how different phosphorylation patterns modulate the CTD conformation has been limited. Here, we generated two distinct phosphorylation patterns in an essentialDrosophilaCTD region with the kinase Dyrk1a: one where Ser2 are primarily phosphorylated, mimicking the state near transcription termination, and a hyperphosphorylation state where most Ser2, Ser5, and Thr4 residues are phosphorylated, expanding on our work on Ser5 phosphorylation, which mimics early transcription elongation. Using13C Direct-Detect NMR, we show that the CTD has a tendency to form transient beta strands and beta turns, which is altered differently by Ser2 and Ser5 phosphorylation. Small angle x-ray scattering (SAXS) revealed no significant changes in the CTD global dimensions even at high levels of phosphorylation, contradicting the common assumption of phosphorylation-induced chain expansion. Our findings support a transient beta model in which unphosphorylated CTD adopts transient beta strands at Ser2 during transcription pre-initiation. These transient structures are disrupted by Ser5 phosphorylation in early elongation, and later restored by Ser2 phosphorylation near termination for recruiting beta turn-recognizing termination factors.
APMAT analysis reveals the association between CD8 T cell receptors, cognate antigen, and T cell phenotype and persistence
Authors: Xie Jingyi , Chen Daniel G. , Chour William , Ng Rachel H. , Zhang Rongyu , Yuan Dan , Choi Jongchan , McKasson Michaela , Troisch Pamela , Smith Brett , Jones Lesley , Webster Andrew , Rasheed Yusuf , Li Sarah , Edmark Rick , Hong Sunga , Murray Kim M. , Logue Jennifer K. , Franko Nicholas M. , Lausted Christopher G. , Piening Brian , Algren Heather , Wallick Julie , Magis Andrew T. , Watanabe Kino , Mease Phil , Greenberg Philip D. , Chu Helen , Goldman Jason D. , Su Yapeng , Heath James R. 
Published: January 2025

AbstractElucidating the relationships between a class I peptide antigen, a CD8 T cell receptor (TCR) specific to that antigen, and the T cell phenotype that emerges following antigen stimulation, remains a mostly unsolved problem, largely due to the lack of large data sets that can be mined to resolve such relationships. Here, we describe Antigen-TCR Pairing and Multiomic Analysis of T-cells (APMAT), an integrated experimental-computational framework designed for the high-throughput capture and analysis of CD8 T cells, with paired antigen, TCR sequence, and single-cell transcriptome. Starting with 951 putative antigens representing a comprehensive survey of the SARS-CoV-2 viral proteome, we utilize APMAT for the capture and single cell analysis of CD8 T cells from 62 HLA A*02:01 COVID-19 participants. We leverage this unique, comprehensive dataset to integrate with peptide antigen properties, TCR CDR3 sequences, and T cell phenotypes to show that distinct physicochemical features of the antigen-TCR pairs strongly associate with both T cell phenotype and T cell persistence. This analysis suggests that CD8+ T cell phenotype following antigen stimulation is at least partially deterministic, rather than the result of stochastic biological properties.
A diagnostic support system based on interpretable machine learning and oscillometry for accurate diagnosis of respiratory dysfunction in silicosis
Authors: Machado do Amaral Jorge Luís , Moraes de Sá Sousa Cíntia , de Oliveira Ribeiro Caroline , Morisco de Sá Paula , Lopes Agnaldo José , Lopes de Melo Pedro 
Published: January 2025

ABSTRACTSilicosis, the most dangerous and common lung illness associated with breathing in mineral dust, is a significant health concern. Spirometry, the traditional method for evaluating pulmonary functions, requires high patient compliance. Respiratory Oscillometry and electrical models are being studied to evaluate the respiratory system. This study aims to harness the power of machine learning (ML) to enhance the accuracy and interpretability of oscillometric parameters in silicosis. The data was obtained from 109 volunteers (60 in the training and 49 in the validation groups). Some supervised ML algorithms were selected for tests: K-Nearest Neighbors, Logistic Regression, Random Forest, CatBoost (CAT), Explainable Boosting Machines (EBM), and a deep learning algorithm. Two synthetic data generation algorithms were also applied. Initially, this study revealed the most accurate oscillometric parameter: the resonant frequency (fr, AUC=0.86), indicating a moderate accuracy (0.70-0.90). Next, original oscillometric parameters were used as input in the selected algorithms. EBM (AUC=0.93) and HyperTab (AUC=0.95) demonstrated the best performance. When feature selection was applied, HyperTab (AUC=0.94), EBM (AUC=0.94), and Catboost (AUC=0.93) emerged as the most accurate results. Finally, external validation resulted in a high diagnostic accuracy (AUC=0.96). Machine learning algorithms introduced enhanced accuracy in diagnosing respiratory changes associated with silicosis. The HyperTab and EBM achieved a high diagnostic accuracy range, and EBM explains the importance of the features and their interactions. This AI-assisted workflow has the potential to serve as a valuable decision support tool for clinicians, which can enhance their decision-making process, ultimately leading to improved accuracy and efficiency.
Global dissection of the impact of Alzheimer’s disease on brain architecture and behavior: High resolution MRH resolves robust regional effects
Authors: Johnson G. Allan , Tian Yuqi , Hornburg Kathryn , Cook James J. , Qi Yi , White Leonard E. , Killmar John T. , Kaczorowski Catherine , Ashbrook David G. , Williams Robert W. 
Published: January 2025

ABSTRACTAlzheimer’s disease (AD) affects brain regions with remarkable heterogeneity, but the precise impact of this disease on hundreds of small cortical, subcortical, and brainstem regions remains poorly defined. Here, as a prelude to testing preclinical models to prevent AD, we systematically quantified effects of human AD mutations inAPPandPSEN1on 231 regions and comprehensively evaluated changes in volume with unprecedented resolution in genetically diverse mice as a function of sex and genetic background. We studied 34 5XFAD F1 hybrids and 23 sibling controls at 14 months, evaluating learning and memory behaviors, followed byex vivodiffusion tensor images (DTI) at 25 µm resolution. We delineated 231 regions of interest (ROIs) bilaterally with high precision. Remarkably, we found bidirectional changes: marked volume increases (up to 10%) in neocortex, hippocampus, amygdala, and sensory nuclei, contrasted with decreases in striatum, pallidum, thalamus, hypothalamus, and most fiber tracts. These opposing effects are unrelated to amyloid load and are likely to reflect temporal gradients in susceptibility of ROIs. Effects are similar in both sexes but far more prominent in females. Genetic background strongly modulates penetrance of the human mutations with the AD-BXD77 F1 type having the greatest sensitivity. Light sheet microscopy and stereological analysis of NeuN+ neurons and amyloid β aggregates in 22 regions revealed up to 20% loss of cells in CA3 and in anterior and intralaminar parts of the thalamus. Volumetric changes correlated with impaired fear acquisition and memory, with cases and controls often showing opposite relations between performance and regional volumes. These findings reveal unprecedented regional heterogeneity in AD progression and suggest therapeutic efficacy may vary substantially across genetic backgrounds and between sexes.