bluuebunny/crossref_metadata_2025_split huggingface dataset:
Human Immunodeficiency Virus
Authors: Das Pankaj , Singh Neelam , Kharayat Veena , Vasudevan Biju , Priya Krishnan Lekshmi , Mukhida Sahjid , Das Nikunja Kumar , Sutar Anupama 
Published: January 2025

ABSTRACT
Often overlooked or misdiagnosed, cutaneous symptoms are common in chronic human immunodeficiency virus (HIV) disease and can serve as early signs of the disease. These cutaneous signs prompted to test for HIV on the three patients, which all were found to be positive. In this article, we are attempting to highlight the importance of recognizing cutaneous manifestations of HIV for early diagnosis and timely initiation of antiretroviral therapy. Three cases of cutaneous symptoms are presented: (a) generalized hyperpigmentation; (b) generalized hyperpigmentation with oral hairy leukoplakia; and (c) seborrheic dermatitis, xerosis, oral hairy leukoplakia, multiple foci of furuncles, and linear gingival erythema. Studies have shown that various cutaneous symptoms are common in chronic HIV disease. The most common are seborrheic dermatitis, xerosis, oral candidiasis, and folliculitis. Recognition of these skin findings is crucial, as it can lead to early diagnosis and treatment of HIV infection, thereby reducing morbidity and mortality associated with HIV infection and improving quality of life for patients.
Dermoscopy 101
Authors: Davis Kyleen E. 
Published: January 2025

ABSTRACT
Dermoscopy is a noninvasive diagnostic technique that allows dermatology clinicians to evaluate suspicious skin lesions and determine the need for biopsy. Basal cell carcinomas (BCCs) exhibit distinct dermoscopic features that when accurately identified help aid in diagnosis. This article focuses on the most pathognomonic dermoscopic feature of BCC—arborizing vessels.
Cerebellar infarction due to atlantoaxial subluxation in spondyloepimetaphyseal dysplasia-joint laxity type 1 case
Authors: Bilgeç Nagehan , Çalişkan Burcu , Eravci Saliha Yavuz , Güven Ahmet Sami , Çaksen Hüseyin 
Published: January 2025

Introduction
Spondyloepimetaphyseal dysplasia with joint laxity type 1 (SEMD-JL1) is an extremely rare skeletal dysplasia belonging to a group of disorders called linkeropathies. It is characterized by skeletal and connective tissue abnormalities. Biallelic variants in genes encoding enzymes that synthesize the tetrasaccharide linker region of glycosaminoglycans lead to linkeropathies, which exhibit clinical and phenotypic features that overlap with each other. SEMD-JL1 results in impaired growth and short stature, along with increased joint flexibility leading to limb joint dislocations and progressive spinal deformity.

Methods and Result
Whole exome sequencing was performed on the patient’s genomic DNA. A novel variant in the B3GALT6 gene was detected as homozygous. During the patient’s follow-up, signs of cerebellar infarction was observed due to atlantoaxial subluxation. Posterior circulation ischemic strokes have not been described with SEMD-JL1 and it was the second case in the skeletal dysplasia group to develop posterior circulation ischemic stroke due to atlantoaxial luxation.

Conclusion
Linkeropathies present with varying clinical manifestations and necessitate comprehensive genetic testing for accurate diagnosis of this complex patient group. Skeletal dysplasias, such as spondyloepimetaphyseal dysplasia, may be accompanied by atlantoaxial instability that can lead to serious spinal symptoms and even sudden death.
Biallelic variants in AGRN with recurrent pregnancy losses in a family with a fetal akinesia deformation sequence
Authors: Shravya Mangalore S. , Chaurasia Ankur , Girisha Katta M. , Nayak Shalini S. 
Published: January 2025

Introduction
Agrin, encoded by AGRN, plays a vital role in the acetylcholine receptor clustering pathway, and any defects in this pathway are known to cause congenital myasthenic syndrome (CMS) 8 in early childhood with variable fatigable muscle weakness. The most severe or lethal form of CMS manifests as a fetal akinesia deformation sequence (FADS). To date, only one family has been reported with an association of null variants in AGRN and a lethal FADS.

Methods
We identified a nonconsanguineous couple with recurrent pregnancy loss. Detailed phenotyping of fetuses was performed via perinatal autopsy. Genetic evaluation was performed along with split-read analysis to identify variants.

Results
Perinatal phenotyping revealed an FADS in the family, and genomic testing identified novel null variants in AGRN. First, whole-exome sequencing revealed the maternally inherited heterozygous variant c.952+1_952+3del in AGRN in fetuses. Split-read analysis of the exome led to the identification of the paternally inherited second variant, a heterozygous deletion of 41.33 kb, encompassing exons 1 and 2 of AGRN.

Conclusion
This study highlights the importance of incorporating split-read analysis in clinical practice and emphasizes the association of null variants in AGRN with the FADS. To the best of our knowledge, this is the second report explaining FADS and null variants in AGRN.
Developing ERAF-AI: An Early-stage Research Assessment Framework for Artificial Intelligence
Authors: Falvo David , Weidener Lukas , Karlsson Martin 
Published: January 2025

AbstractToday, most research evaluation frameworks are designed to assess mature projects with well-defined data and clearly articulated outcomes. Yet, few, if any, are equipped to evaluate the promise of early-stage research, which is inherently characterized by limited evidence, high uncertainty, and evolving objectives. These early-stage projects require nuanced assessments that can adapt to incomplete information, project maturity, and shifting research questions. Compounding these challenges is the difficulty of systematically scaling evaluations with the increasing volume of research projects. As a step toward addressing this gap, we introduce the Early-Stage Research Assessment Framework for Artificial Intelligence (ERAF-AI), a systematic approach to evaluate research at Technology Readiness Levels (TRLs) 1 to 3 – maturity levels where ideas are more conceptual and only preliminary evidence exists to indicate potential viability. By leveraging AI-driven methodologies and platforms such as Lateral’s Coordination.Network, ERAF-AI ensures transparent, scalable, and context-sensitive evaluations that integrate research maturity classification, adaptive scoring, and strategic decision-making. Importantly, ERAF-AI aligns criteria with the unique demands of early-stage research, guiding evaluation through the 4P framework (Promote, Pause, Pivot, Perish) to inform next steps. As an initial demonstration of its potential, we apply ERAF-AI to a high-impact early-stage project, providing actionable insights and measurable improvement over conventional practices. Although ERAF-AI shows significant promise in improving the prioritization of early-stage research, further refinement and validation across a wider range of disciplines and datasets is required to refine its scalability and adaptability. Overall, we expect this framework to serve as a valuable tool for empowering researchers to make informed decisions and to prioritize high-potential initiatives in the face of uncertainty and limited data.
Autoantibody-Driven Monocyte Dysfunction in Post-COVID Syndrome with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome
Authors: Hackel Alexander , Sotzny Franziska , Mennenga Elise , Heidecke Harald , Schulze-Foster Kai , Fourlakis Konstantinos , Lüders Susanne , Grasshoff Hanna , Rubarth Kerstin , Konietschke Frank , Lange Tanja , Scheibenbogen Carmen , Akbarzadeh Reza , Riemekasten Gabriela 
Published: January 2025

AbstractPost-COVID syndrome (PCS) has emerged as a significant health concern with persisting symptoms. A subset of PCS patients develops severe myalgic encephalomyelitis/chronic fatigue syndrome (pcME/CFS). Dysregulated autoantibodies (AABs) have been implicated in PCS, contributing to immune dysregulation, impairment of autonomous nerve and vascular function. As recently shown in autoimmune diseases, IgG fractions translate disease-specific pathways into various cells. Therefore, we asked whether IgG fractions from PCS patients could be applied in-vitro to identify specific cytokine responses for PCS patients without (nPCS) and with pcME/CSF. To assess this, we have stimulated monocyte cell lines with IgG fractions from PCS patients. Our findings reveal distinct cytokine responses induced by patient derived AABs which are suggested in vascular and immune dysfunction. In contrast to nPCS, pcME/CSF AABs induced enhanced neurotrophic responses, characterized by significant cytokine correlations involving brain-derived neurotrophic factor (BDNF), glial cell-derived neurotrophic factor (GDNF) and tumor necrosis factor superfamily member 14(LIGHT). Further, AAB-induced cytokine levels correlate with clinical symptoms. This study emphasizes a contribution of AABs in PCS, in mitigating long-term immune dysregulation, and a need for therapies modulating IgG-induced signaling pathways.
Characterizing Oligodendrocyte-Lineage Cells and Myelination in the Basolateral Amygdala: Insights from a Novel Methodology in Postmortem Human Brain
Authors: Perlman Kelly , Curto Emanuel , Barnett-Burns Sarah , Davoli Maria-Antonietta , Yerko Volodymyr , Merza Reem , Papadakis Andreas I , Spatz Alan , Pryce Christopher R , Turecki Gustavo , Mechawar Naguib 
Published: January 2025

AbstractThe basolateral amygdala (BLA) plays a key role in the pathophysiology of depressive disorders and trauma, yet oligodendrocyte-lineage cells and myelin in this brain region remain understudied in humans. This might be due, at least in part, to the lack of a cost-effective, antibody-based method to isolate oligodendrocytes (OL) and OL precursor cells (OPC) from postmortem brain tissue that is compatible with molecular biology applications. This study aimed to: 1) create and validate a method for isolating OPC and OL nuclei from frozen postmortem grey matter; 2) compare OPC and OL gene expression in the BLA between subjects having died with depression and matched controls; and 3) provide histological characterizations of OPC, OL, and myelin in the BLA. Frozen left-hemisphere BLA samples were obtained from brain donors with well-characterized phenotypic information. Immunolabeled nuclei were sorted into OPC (SOX10+/CRYAB-) and OL (SOX10+/CRYAB+) populations, and RNA was measured using a custom Nanostring codeset. Fluorescence in situ hybridization was used to determine OPC (PDGFRα+) and OL (MYRF+) densities, and immunofluorescence was used to label axons (NF-H) and myelin (MBP) for myelin area fraction. The method successfully isolated OPC and OL nuclei with correct transcriptomic profiles. While no significant group differences were observed in gene expression, cell densities, or myelin coverage, we did observe significant age-related patterns. Moreover, a strong significant correlation between OL density and myelin area fraction was identified. This study provides a novel sorting method and a comprehensive characterization of OL-lineage gene expression, cell densities, and myelin in the human BLA.
Docking 14 million virtual isoquinuclidines against the mu and kappa opioid receptors reveals dual antagonists-inverse agonists with reduced withdrawal effects
Authors: Vigneron Seth F. , Ohno Shohei , Braz Joao , Kim Joseph Y. , Kweon Oh Sang , Webb Chase , Billesbølle Christian , Bhardwaj Karnika , Irwin John , Manglik Aashish , Basbaum Allan I. , Ellman Jonathan A. , Shoichet Brian K. 
Published: January 2025

AbstractLarge library docking of tangible molecules has revealed potent ligands across many targets. While make-on-demand libraries now exceed 75 billion enumerated molecules, their synthetic routes are dominated by a few reaction types, reducing diversity and inevitably leaving many interesting bioactive-like chemotypes unexplored. Here, we investigate the large-scale enumeration and targeted docking of isoquinuclidines. These “natural-product-like” molecules are rare in the current libraries and are functionally congested, making them interesting as receptor probes. Using a modular, four-component reaction scheme, we built and docked a virtual library of over 14.6 million isoquinuclidines against both the µ- andκ-opioid receptors (MOR and KOR, respectively). Synthesis and experimental testing of 18 prioritized compounds found nine ligands with low µM affinities. Structure-based optimization revealed low- and sub- nM antagonists and inverse agonists targeting both receptors. Cryo-electron microscopy (cryoEM) structures illuminate the origins of activity on each target. In mouse behavioral studies, a potent member of the series with joint MOR-antagonist and KOR-inverse-agonist activity reversed morphine-induced analgesia, phenocopying the MOR-selective anti-overdose agent naloxone. Encouragingly, the new molecule induced less severe opioid-induced withdrawal symptoms compared to naloxone during withdrawal precipitation, and did not induce conditioned-place aversion, likely reflecting a reduction of dysphoria due to the compound’s KOR-inverse agonism. The strengths and weaknesses of bespoke library docking, and of docking for opioid receptor polypharmacology, will be considered.
A Vascularized Liver Microphysiological System Captures Key Features of Hepatic Insulin Resistance and Monocyte Infiltration
Authors: Tevonian Erin N. , Kan Ellen L. , Maniar Kairav K. , Wang Alex J. , Datta Anisha , Kamm Roger D. , Lauffenburger Douglas A. , Griffith Linda G. 
Published: January 2025

AbstractThree-dimensionalin vitroliver models are a promising means to recapitulate key aspects of human liver disease pathologies, thereby aiding therapeutic development. Spheroidal aggregates of hepatocytes, sometimes including non-parenchymal cells, are an established approach for modeling facets of metabolism and drug responses, yet these models often lack dynamic interactions with vascular and immune cells that also contribute to disease development and progression. To address this, we developed a microphysiological system (MPS) that integrates multicellular human hepatic spheroids with self-organized microvascular networks. We show extensive interaction between primary human spheroids and functional vasculature while maintaining key hepatic functions. We demonstrate the utility of this MPS by modeling an insulin resistance state through chronic exposure to disease-mimetic media conditions. This disease model displays altered hepatocyte metabolism, dysregulated vascular features, and increased inflammation state. Enabled by the functional vasculature, we further extend this disease model to capture changes in immune cell recruitment. When culturing CD14+ monocytes in our liver MPS, a subset of monocytes extravasate, localize to hepatic spheroids, and begin differentiating into CD163+ macrophages. These cells infiltrate with greater frequency in insulin resistant samples, consistent with known clinical findings. All together, this vascularized MPS model captures disease-relevant liver biology including inflammatory features.
Noise Correlations in Balanced Networks with Unreliable Synapses
Authors: Leone Michael J. , Huang Chengcheng , Doiron Brent 
Published: January 2025

AbstractSynaptic physiology is highly stochastic in the neocortex: immediately following an action potential, individual synapses release neurotransmitter unreliably, sometimes even failing to release any vesicles. However, theoretical models of neuronal networks typically neglect this well-established feature of biology, especially recurrent networks. In this work, to better understand the effects of synaptic unreliability in recurrent networks, we describe neuronal variability in a balanced network model of non-leaky integrate-and-fire neurons incorporating a Bernoulli model of synaptic release. For arbitrary network size, synaptic unreliability contributes non-negligibly to spike count variability. Most notably, this additional noise is overshadowed by effects on noise correlations. In particular, we find that feedforward and recurrent synaptic reliability have opposite influences on noise correlations: while increased reliability of synaptic input from neurons outside of the network increase correlations, reliability of recurrent synapses de-correlates population activity. We explain this dichotomy by examining the average input currents to cell pairs, and verify this effect with simulations of exponential integrate-and-fire neurons with adaptation and conductance-based synapses. Overall, our results emphasize the importance of synaptic unreliability in the study of noise correlations.
Evaluating Genetic Regulators of MicroRNAs Using Machine Learning Models
Authors: Cihan Mert , Anyaegbunam Uchenna Alex , Albrecht Steffen , Andrade-Navarro Miguel A , Sprang Maximilian 
Published: January 2025

AbstractThis study explores the genetic regulators of microRNAs (miRNAs) using an ensemble of machine learning models to predict miRNA expression levels from gene expression data. Employing ridge regression, we accurately predicted the expression of 353 human miRNAs (R2> 0.5), revealing robust miRNA-gene regulatory relationships. By analyzing the coefficients of these predictive models, we identified genetic regulators for each miRNA and highlighted the multifactorial nature of miRNA regulation.Further network analysis uncovered that miRNAs with higher predictive accuracy are more densely connected to their top predictive genes, reflecting strong regulatory control within miRNA-gene networks. To refine these insights, we filtered the gene-miRNA interaction networks to identify miRNAs specifically associated with enriched pathways, such as synaptic function and cardiovascular processes. From this pathway-centric analysis, we present a curated list of miRNAs and their genetic regulators, pinpointing their activity within distinct biological contexts.Additionally, our study provides a comprehensive set of metrics and coefficients for the genes most predictive of miRNA expression, along with a filtered subnetwork of miRNAs linked to specific pathways and phenotypes. By integrating miRNA expression predictors with network analysis and pathway enrichment, this work advances our understanding of miRNA regulatory mechanisms and their roles across distinct biological systems.
Self-supervision deep learning models are better models of human high-level visual cortex: The roles of multi-modality and dataset training size
Authors: Grosbard Idan Daniel , Yovel Galit 
Published: January 2025

AbstractWith the rapid development of Artificial Neural Network based visual models, many studies have shown that these models show unprecedented potence in predicting neural responses to images in visual cortex. Lately, advances in computer vision have introduced self-supervised models, where a model is trained using supervision from natural properties of the training set. This has led to examination of their neural prediction performance, which revealed better prediction of self-supervised than supervised models for models trained with language supervision or with image-only supervision. In this work, we delve deeper into the models’ ability to explain neural representations of object categories. We compare models that differed in their training objectives to examine where they diverge in their ability to predict fMRI and MEG recordings while participants are presented with images of different object categories. Results from both fMRI and MEG show that self-supervision was advantageous in comparison to classification training. In addition, language supervision is a better predictor for later stages of visual perception, while image-only supervision shows a consistent advantage over a longer duration, beginning from 80ms after exposure. Examination of the effect of data size training revealed that large dataset did not necessarily improve neural predictions, in particular in visual self-supervised models. Finally, examination of the correspondence of the hierarchy of each model to visual cortex showed that image-only self-supervision led to better correspondence than image only models. We conclude that while self-supervision shows consistently better prediction of fMRI and MEG recordings, each type of supervision reveals a different property of neural activity, with language-supervision explaining later onsets, while image-only self-supervision explains long and very early latencies of the neural response, with the model hierarchy naturally sharing corresponding hierarchical structure as the brain.
MiRNA-501-3p and MiRNA-502-3p: A Promising Biomarker Panel for Alzheimer’s Disease
Authors: Devara Davin , Sharma Bhupender , Goyal Gunjan , Rodarte Daniela , Kulkarni Aditi , Tinu Nathan , Pai Ayana , Kumar Subodh 
Published: January 2025

ABSTRACTINTRODUCTIONAlzheimer’s disease (AD) lacks a less invasive and early detectable biomarker. Here, we investigated the biomarker potential of miR-501-3p and miR-502-3p using different AD sources.METHODSMiR-501-3p and miR-502-3p expressions were evaluated in AD CSF exosomes, serum exosomes, familial and sporadic AD fibroblasts and B-lymphocytes by qRT-PCR analysis. Further, miR-501-3p and miR-502-3p expressions were analyzed in APP, Tau cells and media exosomes.RESULTSMiR-501-3p and miR-502-3p expressions were significantly upregulated in AD CSF exosomes relative to controls. MiRNA levels were high in accordance with amyloid plaque and NFT density in multiple brain regions. Similarly, both miRNAs were elevated in AD and MCI serum exosomes compared to controls. MiR-502-3p expression was high in fAD and sAD B-lymphocytes. Finally, miR-501-3p and miR-502-3p expression were elevated intracellularly and secreted extracellularly in response to APP and Tau pathology.DISCUSSIONThese results suggest that miR-501-3p and miR-502-3p could be promising biomarkers for AD.
Dimerization and dynamics of angiotensin-I converting enzyme revealed by cryoEM and MD simulations
Authors: Mancl Jordan M. , Wu Xiaoyang , Zhao Minglei , Tang Wei-Jen 
Published: January 2025

AbstractAngiotensin-I converting enzyme (ACE) regulates the levels of disparate bioactive peptides, notably converting angiotensin-I to angiotensin-II and degrading amyloid beta. ACE is a heavily glycosylated dimer, containing 4 analogous catalytic sites, and exists in membrane bound and soluble (sACE) forms. ACE inhibition is a frontline, FDA-approved, therapy for cardiovascular diseases yet is associated with significant side effects, including higher rates of lung cancer. To date, structural studies have been confined to individual domains or partially denatured cryoEM structures. Here we report the cryoEM structure of the full-length, glycosylated, sACE dimer. We resolved four structural states at 2.99 to 3.65 Å resolution which are primarily differentiated by varying degrees of solvent accessibility to the active sites and reveal the full dimerization interface. We also employed all-atom molecular dynamics (MD) simulations and heterogeneity analysis in cryoSPARC, cryoDRGN, and RECOVAR to elucidate the conformational dynamics of sACE and identify key regions mediating conformational change. We identify differences in the mechanisms governing the conformational dynamics of individual domains that have implications for the design of domain-specific sACE modulators.