bluuebunny/crossref_metadata_2025_split huggingface dataset:
HumanIslets: An integrated platform for human islet data access and analysis
Authors: Ewald Jessica D. , Lu Yao , Ellis Cara E. , Worton Jessica , Kolic Jelena , Sasaki Shugo , Zhang Dahai , dos Santos Theodore , Spigelman Aliya F. , Bautista Austin , Dai Xiao-Qing , Lyon James G. , Smith Nancy P. , Wong Jordan M. , Rajesh Varsha , Sun Han , Sharp Seth A. , Rogalski Jason C. , Moravcova Renata , Cen Haoning H , Manning Fox Jocelyn E. , Consortium HI-DAS , Atlas Ella , Bruin Jennifer E. , Mulvihill Erin E. , Verchere C. Bruce , Foster Leonard J. , Gloyn Anna L. , Johnson James D. , Pepper Andrew R. , Lynn Francis C. , Xia Jianguo , MacDonald Patrick E. 
Published: June 2024

SUMMARYComprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduceHumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes.HumanIslets.comprovides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.
Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization
Authors: Vardaman Donald , Ali Md Akkas , Bolding Chase , Tidwell Harrison , Stephens Holly , Tyrrell Daniel J. 
Published: June 2024

AbstractFlow cytometry is a widely used technique for immune cell analysis, offering insights into cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large antibody panels can be challenging using traditional bi-axial gating strategies. Here, we present a novel analysis pipeline designed to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2–3 months) and aged (18–19 months) female mice then stained these with a panel of 20 fluorescently labeled antibodies. Spectral flow cytometry was performed, followed by data processing and analysis using Python within a Jupyter Notebook environment to perform batch correction, unsupervised clustering, dimensionality reduction, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 34 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with certain clusters enriched in one age group over the other. Naïve, effector memory, and central memory CD8+and CD4+T cell subsets exhibited age-associated changes in abundance and marker expression. Additionally, γδ T cell clusters showed differential abundance between age groups. By leveraging high-dimensional analysis methods borrowed from single-cell RNA sequencing analysis, we identified age-related differences in T cell subsets, providing insights into the immune aging process. This approach offers a robust, free, and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.
Bisphenol AF induces overactivation of primordial follicles via Hippo signaling and causes premature ovarian insufficiency in mice
Authors: Liu Xiaoyang , Yu Mingxi , Wang Tiancheng , Hu Xiangdong , Zhong Rui , Xiao Yuan , Xu Yan , Zhang Mei , Tang Shuang 
Published: June 2024

AbstractPremature depletion of ovarian reserve is a cause of female infertility. Plasticizer Bisphenol AF (BPAF) residues have been found in human reproductive-related samples. However, little is known about its influence on the ovarian reserve. Here, we demonstrate that BPAF exposure causes excessive activation of primordial follicles through Hippo signaling in young females, resulting in rapid exhaustion of the ovarian reserve and, ultimately, premature ovarian insufficiency. We found that oral ingestion of BPAF disrupts normal estrous cyclicity and induces constant estrus in a dose-dependent manner. BPAF can upregulate the expression of YAP transcriptional coactivator. Intriguingly, only the high dose of BPAF inhibits Hippo signaling by eliciting a substantial decrease in phospho-YAP levels. Through such regulatory effects, BPAF causes YAP translocation into the nucleus and triggers the overactivation of primordial follicles. Collectively, this study proposes a novel toxicological mechanism explaining the negative impact of BPAF on the ovarian health of young females.
cryoSPHERE: Single-particle heterogeneous reconstruction from cryo EM
Authors: Ducrocq Gabriel , Grunewald Lukas , Westenhoff Sebastian , Lindsten Fredrik 
Published: June 2024

AbstractThe three-dimensional structure of a protein plays a key role in determining its function. Methods like AlphaFold have revolutionized protein structure prediction based only on the amino-acid sequence. However, proteins often appear in multiple different conformations, and it is highly relevant to resolve the full conformational distribution. Single-particle cryo-electron microscopy (cryo EM) is a powerful tool for capturing a large number of images of a given protein, frequently in different conformations (referred to asparticles). The images are, however, very noisy projections of the protein, and traditional methods for cryo EM reconstruction are limited to recovering a single, or a few, conformations. In this paper, we introduce cryoSPHERE, a deep learning method that takes as input a nominal protein structure, e.g. from AlphaFold, learns how to divide it into segments, and how to move these as approximately rigid bodies to fit the different conformations present in the cryo EM dataset. This formulation is shown to provide enough constraints to recover meaningful reconstructions of single protein structures. This is illustrated in three examples where we show consistent improvements over the current state-of-the-art for heterogeneous reconstruction.
Identification of a global gene expression signature associated with the genetic risk of catastrophic fracture in iPSC-derived osteoblasts from Thoroughbred horses
Authors: Palomino Lago Esther , Ross Amy K. C. , McClellan Alyce , Guest Deborah J. 
Published: June 2024

AbstractBone fractures are a significant problem in Thoroughbred racehorses. The risk of fracture is influenced by both genetic and environmental factors. To determine the biological processes that are affected in genetically susceptible horses, we utilised polygenic risk scoring to establish induced pluripotent stem cells (iPSCs) from horses at high and low genetic risk. RNA-sequencing on iPSC-derived osteoblasts revealed 112 genes that were significantly differentially expressed. 43 of these genes have known roles in bone, 27 are not yet annotated in the equine genome and 42 currently have no described role in bone. However, many of the proteins encoded by the known and unknown genes have reported interactions. Functional enrichment analyses revealed that the differentially expressed genes were overrepresented in processes regulating the extracellular matrix and pathways known to be involved in bone remodelling and bone diseases. Gene set enrichment analysis also detected numerous biological processes and pathways involved in glycolysis with the associated genes having a higher expression in the iPSC-osteoblasts from horses with low polygenic risk scores for fracture.Therefore, the differentially expressed genes may be relevant for maintaining bone homeostasis and contribute to fracture risk. A deeper understanding of the consequences of mis-regulation of these genes and the identification of the DNA variants which underpin their differential expression may reveal more about the molecular mechanisms which are involved in equine bone health and fracture risk.
Decoding in the fourth dimension: Classification of temporal patterns and their generalization across locations
Authors: Santos-Mayo Alejandro , Gilbert Faith , Ahumada Laura , Traiser Caitlin , Engle Hannah , Panitz Christian , Ding Mingzhou , Keil Andreas 
Published: June 2024

AbstractNeuroscience research has increasingly used decoding techniques, in which multivariate statistical methods identify patterns in neural data that allow the classification of experimental conditions or participant groups. Typically, the features used for decoding are spatial in nature, including voxel patterns and electrode locations. However, the strength of many neurophysiological recording techniques such as electroencephalography or magnetoencephalography is in their rich temporal, rather than spatial, content. The present report proposes a new decoding method that relies on the time information contained in neural time series. This information is then used in a subsequent step, generalization across location (GAL), which characterizes the relationship between sensor locations based on their ability to cross-decode. Two datasets are used to demonstrate usage of this method, referred to as time-GAL, involving (1) event-related potentials in response to affective pictures and (2) steady-state visual evoked potentials in response to aversively conditioned grating stimuli. In both cases, experimental conditions were successfully decoded based on the temporal features contained in the neural time series. Cross-decoding occurred in regions known to be involved in visual and affective processing. We conclude that the time-GAL approach holds promise for analyzing neural time series from a wide range of paradigms and measurement domains providing an assumption-free method to quantifying differences in temporal patterns of neural information processing and whether these patterns are shared across sensor locations.Author summaryDecoding and classification approaches are widely used in computational biology. In the field of neuroscience, pattern classification approaches typically use spatial information. In many instances, neural time series however are best defined by the their temporal, rather than spatial, features. Here, we propose a novel decoding approach taking advantage of the temporal information. Specifically, we utilize the waveform of neural time series as features for decoding experimental conditions and quantify each decoder’s generalization across locations (GAL) in multi-channel recordings. We illustrate the usage of our open source toolbox using two datasets, showing the sensitivity of the method to systematic condition differences in temporal dynamics along with its ability to capture and quantify spatial dependencies between recording locations.
Toxicogenomic Assessment of In Vitro Macrophages Exposed to Profibrotic Challenge Reveals a Sustained Transcriptomic Immune Signature
Authors: Morikka Jack , Federico Antonio , Möbus Lena , Inkala Simo , Pavel Alisa , Sani Saara , Vaani Maaret , Peltola Sanna , Serra Angela , Greco Dario 
Published: June 2024

AbstractImmune signalling is a crucial component in the progression of fibrosis. However, approaches for the safety assessment of potentially profibrotic substances, providing information on mechanistic immune responses, are underdeveloped. This study utilises a comprehensive analysis of RNA sequencing data from macrophages exposed in vitro to multiple sublethal concentrations of the profibrotic agent bleomycin, over multiple timepoints. Using a toxicogenomic framework, we performed dose-dependent analysis to filter genes truly altered by bleomycin exposure from noise and identified a subset of immune genes with a sustained dose-dependent and differential expression response to profibrotic challenge. We performed an immunoassay and revealed cytokines and proteinases responding to bleomycin exposure that closely correlate to transcriptomic alterations, underscoring the integration between transcriptional immune response and external immune signalling activity. This study not only increases our understanding of the immunological mechanisms of fibrosis, but also offers an innovative framework for the toxicological evaluation of substances with potential fibrogenic effects on macrophage signalling. Our work brings a new immunotoxicogenomic direction for hazard assessment of fibrotic compounds, through implementation of a time and resource efficient in vitro methodology.
Enhancing Cytoplasmic Expression of Exogenous mRNA through Dynamic Mechanical Stimulation
Authors: Chen Jiawen , Patel Aneri , Mir Mohammad , Hudock Maria R. , Pinezich Meghan R. , Guenthart Brandon , Bacchetta Matthew , Vunjak-Novakovic Gordana , Kim Jinho 
Published: June 2024

AbstractIonizable lipid nanoparticles (LNPs) have been pivotal in combating COVID-19, and numerous preclinical and clinical studies have highlighted their potential in nucleic acid-based therapies and vaccines. However, the effectiveness of endosomal escape for the nucleic acid cargos encapsulated in LNPs is still low, leading to suboptimal treatment outcomes and side effects. Hence, improving endosomal escape is crucial for enhancing the efficacy of nucleic acid delivery using LNPs. Here, a mechanical oscillation (frequency: 65 Hz) is utilized to prompt the LNP-mediated endosomal escape. The results reveal this mechanical oscillation can induce the combination and fusion between LNPs with opposite surface charges, enhance endosomal escape of mRNA, and increase the transfection efficiency of mRNA. Additionally, cell viability remains high at 99.3% after treatment with oscillation, which is comparable to that of untreated cells. Furthermore, there is no obvious damage to mitochondrial membrane potential and Golgi apparatus integrity. Thus, this work presents a user-friendly and safe approach to enhancing endosomal escape of mRNA and boosting gene expression. As a result, our work can be potentially utilized in both research and clinical fields to facilitate LNP-based delivery by enabling more effective release of LNP-encapsulated cargos from endosomes.
sORFdb – A database for sORFs, small proteins, and small protein families in bacteria
Authors: Hahnfeld Julian M. , Schwengers Oliver , Jelonek Lukas , Diedrich Sonja , Cemič Franz , Goesmann Alexander 
Published: June 2024

AbstractSmall proteins with fewer than 100, particularly fewer than 50, amino acids are still largely unexplored. Nonetheless, they represent an essential part of bacteria’s often neglected genetic repertoire. In recent years, the development of ribosome profiling protocols has led to the detection of an increasing number of previously unknown small proteins. Despite this, they are overlooked in many cases by automated genome annotation pipelines, and often, no functional descriptions can be assigned due to a lack of known homologs. To understand and overcome these limitations, the current abundance of small proteins in existing databases was evaluated, and a new dedicated database for small proteins and their potential functions, called ‘sORFdb’, was created. To this end, small proteins were extracted from annotated bacterial genomes in the GenBank database. Subsequently, they were quality-filtered, compared, and complemented with proteins from Swiss-Prot, UniProt, and SmProt to ensure reliable identification and characterization of small proteins. Families of similar small proteins were created using bidirectional best BLAST hits followed by Markov clustering. Analysis of small proteins in public databases revealed that their number is still limited due to historical and technical constraints. Additionally, functional descriptions were often missing despite the presence of potential homologs. As expected, a taxonomic bias was evident in over-represented clinically relevant bacteria.This new and comprehensive database is accessible via a feature-rich website providing specialized search features for sORFs and small proteins of high quality. Additionally, small protein families with Hidden Markov Models and information on taxonomic distribution and other physicochemical properties are available. In conclusion, the novel small protein database sORFdb is a specialized, taxonomy-independent database that improves the findability and classification of sORFs, small proteins, and their functions in bacteria, thereby supporting their future detection and consistent annotation. All sORFdb data is freely accessible viahttps://sorfdb.computational.bio.
Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning
Authors: Gray Callum , Chitnavis Samir , Buja Tamara Lucy , Duffy Christopher D. P. 
Published: June 2024

AbstractOxygenic photosynthesis is responsible for nearly all biomass production on Earth, and may have been a prerequisite for establishing a complex biosphere rich in multicellular life. Life on Earth has evolved to perform photosynthesis in a wide range of light environments, but with a common basic architecture of a light-harvestingantennasystem coupled to a photochemical reaction centre. Using a generalized thermodynamic model of light-harvesting, coupled with an evolutionary algorithm, we predict the type of light-harvesting structures that might evolve in light of different intensities and spectral profiles. We reproduce qualitatively the pigment composition, linear absorption profile and structural topology of the antenna systems of multiple types of oxygenic photoautotrophs, suggesting that the same physical principles underlie the development of distinct antenna structures in various light environments. Finally we apply our model to representative light environments that would exist on Earth-like exoplanets, predicting that both oxygenic and anoxygenic photosynthesis could evolve around low mass stars, though the latter would seem to work better around the coolest M-dwarfs. We see this as an interesting first step toward a general evolutionary model of basic biological processes and proof that it is meaningful to hypothesize on the nature of biology beyond Earth.
Mouse models of non-dystrophic and dystrophic myotonia exhibit nociplastic pain-like behaviors
Authors: Nelson Tyler S. , Duran Paz , Calderon-Rivera Aida , Gomez Kimberly , Loya-Lopez Santiago , Khanna Rajesh 
Published: June 2024

AbstractPain is a prominent and debilitating symptom in myotonic disorders, yet its physiological mechanisms remain poorly understood. This study assessed preclinical pain-like behavior in murine models of pharmacologically induced myotonia and myotonic dystrophy type 1 (DM1). In both myotonia congenita and DM1, impairment of theCLCN1gene, which encodes skeletal muscle voltage-gated CLC-1 chloride channels, reduces chloride ion conductance in skeletal muscle cells, leading to prolonged muscle excitability and delayed relaxation after contraction. We used the CLC-1 antagonist anthracene-9- carboxylic acid (9-AC) at intraperitoneal doses of 30 or 60 mg/kg and HSA LR20b DM1 mice to model CLC-1-induced myotonia. Our experimental approach includedin vivopain behavioral testing,ex vivocalcium imaging, and whole-cell current-clamp electrophysiology in mouse dorsal root ganglion (DRG) neurons. A single injection of 9-AC induced myotonia in mice, which persisted for several hours and resulted in long-lasting allodynic pain-like behavior. Similarly, HSA LR20b mice exhibited both allodynia and hyperalgesia. Despite these pain-like behaviors, DRG neurons did not show signs of hyperexcitability in either myotonic model. These findings suggest that myotonia induces nociplastic pain-like behavior in preclinical rodents, likely through central sensitization mechanisms rather than peripheral sensitization. This study provides insights into the pathophysiology of pain in myotonic disorders and highlights the potential of using myotonic mouse models to explore pain mechanisms and assess novel analgesics. Future research should focus on the central mechanisms involved in myotonia-induced pain and develop targeted therapies to alleviate this significant clinical burden.
Notch Signaling in regulating Bone-derived Nanoparticles (BNPs) enhanced Osteogenic Differentiation
Authors: Stellpflug Austin , Caron Justin , Fasciano Samantha , Wang Bo , Wang Shue 
Published: June 2024

AbstractMesenchymal stem cells (MSCs)-based bone tissue regeneration has gained significant attention due to their excellent differentiation capacity and immunomodulatory activity. Enhancing osteogenesis regulation is crucial for improving the therapeutic efficacy of MSC- based regeneration. By utilizing the regenerative capacity of bone ECM and the functionality of nanoparticles, we recently engineered bone-based nanoparticles (BNPs) from decellularized porcine bone. The effects of internalization of BNPs on MSCs viability, proliferation, and osteogenic differentiation were first investigated and compared at different time points. The phenotypic behaviors, including cell number, proliferation, and differentiation were characterized and compared. By incorporating this LNA/DNA nanobiosensor and MSCs live cell imaging, we monitored and compared Notch ligand delta-like 4 (Dll4) expression dynamics in cytoplasm and nucleus during osteogenic differentiation. Pharmacological interventions are used to inhibit Notch signaling to examine the mechanisms involved. The results suggest Notch inhibition mediates osteogenic process, with reduced expression of early and late stage of differentiation markers (ALP, calcium mineralization). The internalization of BNPs led to an increase in Dll4 expression, exhibiting a time-dependent pattern that aligned with enhanced cell proliferation and differentiation. Our findings indicate that the observed changes in BNP-treated cells during osteogenic differentiation could be associated with the elevated levels of Dll4 mRNA expression. In summary, this study provides new insights into MSCs osteogenic differentiation and the molecular mechanisms through which BNPs stimulate this process. The results indicate that BNPs influence osteogenesis by modulating Notch ligand Dll4 expression, demonstrating a potential link between Notch signaling and the proteins present in BNPs.