bluuebunny/crossref_metadata_2025_split huggingface dataset:
In vitro neuroendocrine differentiation of BPH-1 cells under β2 adrenergic receptor stimulation
Authors: Pigat Natascha , Garrido Castillo Laura Nalleli , Lefevre Coline , Baures Manon , Goffin Vincent , Anract Julien , Armand Anne-Sophie , Capiod Thierry 
Published: December 2024

AbstractEpidemiologic and experimental animal studies have shown that stress can alter tumor growth and that adrenergic fibers from the sympathetic nervous system, acting through stromal β2 adrenergic receptors, promote tumor cell survival during the initial phases of cancer development. Recent epidemiological data suggest that beta blocker intake improves survival of prostate cancer patients. Hypertension and high blood pressure have been suggested to increase likelihood of prostate cancer development, suggesting that the use of beta blockers in these patients could reduce prostate cancer risk. Signaling mediated by β adrenergic receptors promotes neuroendocrine differentiation in the LNCaP prostate cancer cell line. Although neuroendocrine cells are a minor population in the epithelial compartment of normal prostate glands, the population of neuroendocrine-like cells that express markers such as SYN, Bcl-2, Dll-3, and AMACR correlates with cancer progression, androgen-independent state, and poor prognosis in prostate cancer patients. As recent studies show that an increase in neuroendocrine cell density occurs before development of benign prostatic hyperplasia, a non-lethal disease affecting the transition zone, in hypertensive rats, we investigated whether neuroendocrine differentiation is associated with benign prostatic hyperplasia. Our results showed that isobutyl-methyl-xanthine, which blocks cAMP degradation, and forskolin, an adenylate cyclase activator, triggered sustained activation of the cAMP/PKA pathway and led to an increase in neuroendocrine differentiation markers in BPH-1 cells, which are a benign prostatic hyperplasia cell line. Similar results were observed by combining the β adrenergic receptors agonist isoproterenol with forskolin. The same treatments reduced BPH-1 cell proliferation rates by 40% and 60%, respectively. Effects on AMACR and SYN expression and cell proliferation were fully reversed by the β2 blocker carvedilol. These data suggest that β adrenergic receptors are linked to the development of neuroendocrine-like cells and benign prostatic hyperplasia. As 20% of the prostate cancer tumors occur in this zone, this observation warrants further investigation.
Snake venom metalloproteinases are predominantly responsible for the cytotoxic effects of certain African viper venoms
Authors: Bartlett Keirah E. , Westhorpe Adam , Wilkinson Mark C. , Casewell Nicholas R. 
Published: December 2024

AbstractSnakebite envenoming is a neglected tropical disease that causes substantial mortality and morbidity globally. The puff adder (Bitis arietans) and saw-scaled viper (Echis romani) have cytotoxic venoms that cause permanent injury via tissue-destructive dermonecrosis around the bite site. Identification of cytotoxic toxins within these venoms will allow development of targeted treatments, such as small molecule inhibitors or monoclonal antibodies to prevent snakebite morbidity. Venoms from both species were fractionated using gel filtration chromatography, and a combination of cell-based cytotoxicity approaches, SDS-PAGE gel electrophoresis, and enzymatic assays were applied to identify venom cytotoxins in the resulting fractions. Our results indicated that snake venom metalloproteinase (SVMP) toxins are predominately responsible for causing cytotoxic effects across both venoms, but that the PII subclass of SVMPs are likely the main driver of cytotoxicity following envenoming byB. arietans, whilst the structurally distinct PIII subclass of SVMPs are responsible for conveying this effect inE. romanivenom. Identification of distinct SVMPs as the primary cytotoxicity-causing toxins in these two African viper venoms will facilitate the future design and development of novel therapeutics targeting these medically important venoms, which in turn could help to mitigate the severe life and limb threatening consequences of tropical snakebite.Key ContributionSVMP toxins were identified as the primary cytotoxicity-causing toxins in the venoms of the puff adder (Bitis arietans) and saw-scaled viper (Echis romani); PII and PIII SVMPs, respectively. This cytotoxicity can be prevented using the metalloproteinase-inhibiting chelator EDTA, suggesting targeted drugs/antibodies may be a viable option for future treatment.
Comparative analysis of CRISPR/Cas9-targeted nanopore sequencing approaches in repeat expansion disorders
Authors: Benarroch Louise , Boëlle Pierre-Yves , Madry Hélène , Mohand Oumoussa Badreddine , Eura Noboyuki , Nishino Ichizo , Labrèche Karim , Bassez Guillaume , Stojkovic Tanya , Gourdon Geneviève , Bonne Gisèle , Tomé Stéphanie 
Published: December 2024

ABSTRACTMore than 50 repeat expansion disorders have been identified, with long-read sequencing marking a new milestone in the diagnosis of these disorders. Despite these major achievements, the comprehensive characterization of short tandem repeats in a pathological context remains challenging, primarily due to their inherent characteristics such as motif complexity, high GC content, and variable length.In this study, our aim was to thoroughly characterize repeat expansions in two neuromuscular diseases: myotonic dystrophy type 1 (DM1) and oculopharyngodistal myopathy (OPDM) using CRISPR/Cas9-targeted long-read sequencing (Oxford Nanopore Technologies, ONT). We conducted precise analyses of the DM1 and OPDM loci, determining repeat size, repeat length distribution, expansion architecture and DNA methylation, using three different basecallers (Guppy, Bonito and Dorado). We demonstrated the importance of the basecalling strategy in repeat expansion characterization. We proposed guidelines to perform CRISPR-Cas9 targeted long-read sequencing (no longer supported by ONT), from library preparation to bioinformatical analyses. Finally, we showed, for the first time, somatic mosaicism, hypermethylation ofLRP12loci in symptomatic patients and changes in the repeat tract structure of OPDM patients.We propose a strategy based on CRISPR/Cas9-enrichment long-read sequencing for repeat expansion diseases, which could be readily applicable in research but also in diagnostic settings.
Adrenocortical Cancer Cell uptake of Iron Oxide Nanoparticles
Authors: Challapalli Ritihaas Surya , Hong Cong , Sorushanova Anna , Covarrubias-Zambrano Obdulia , Mullen Nathan , Feely Sarah , Covarrubias Jose , Varghese Sunita N. , Hantel Constanze , Owens Peter , O’Halloran Martin , Prakash Punit , Bossmann Stefan H. , Dennedy Michael Conall 
Published: December 2024

AbstractAdrenocortical carcinoma (ACC) is a rare cancer with poor prognosis, treated primarily through surgery and chemotherapy. Other treatments like radiation or thermal ablation for metastases have limited success, and recurrence is common. More effective management options are needed. Magnetic iron oxide nanoparticles (IONP) show promise in cancer treatment due to their ability to be modified for selective uptake by cancer cells. This study investigated IONP uptake in ACC cell lines (H295R, HAC-15, MUC-1) using a multicellular model with endothelial cells (HUVEC) and monocytes. IONP uptake was concentration- and time-dependent, with optimal uptake at 10 µg/mL. IONP were found in the cytoplasm and intracellular vesicles of ACC cells. However, endothelial cells and monocytes also absorbed IONP, reducing uptake by ACC cells. These findings suggest ACC cells actively take up IONP, but better targeting is needed to enhance uptake specificity and efficiency.
Cell Type Differentiation Using Network Clustering Algorithms
Authors: Nasrollahi Fatemeh Sadat Fatemi , Silva Filipi Nascimento , Liu Shiwei , Chaudhuri Soumilee , Yu Meichen , Wang Juexin , Nho Kwangsik , Saykin Andrew J. , Bennett David A. , Sporns Olaf , Fortunato Santo 
Published: December 2024

AbstractSingle cell RNA-seq (scRNA-seq) technologies provide unprecedented resolution representing transcriptomics at the level of single cell. One of the biggest challenges in scRNA-seq data analysis is the cell type annotation, which is usually inferred by cell separation approaches. In-silico algorithms that accurately identify individual cell types in ongoing single-cell sequencing studies are crucial for unlocking cellular heterogeneity and understanding the biological basis of diseases. In this study, we focus on robustly identifying cell types in single-cell RNA sequencing data; we conduct a comparative analysis using methods established in biology, like Seurat, Leiden, and WGCNA, as well as Infomap, statistical inference via Stochastic Block Models (SBM), and single-cell Graph Neural Networks (scGNN). We also analyze preprocessing pipelines to identify and optimize key components in the process. Leveraging two independent datasets, PBMC and ROSMAP, we employ clustering algorithms on cell-cell networks derived from gene expression data. Our findings reveal that while clusters detected by WGCNA exhibit limited correspondence with cell types, those identified by multiresolution Infomap and Leiden, and SBM show a closer alignment, with Infomap standing out as a particularly effective approach. Infomap notably offers valuable insights for the precise characterization of cellular landscapes related to neurodegenration and immunology in scRNA-seq.
Diverging transposon activity among polar bear sub-populations inhabiting different climate zones
Authors: Godden Alice M. , Rix Benjamin T. , Immler Simone 
Published: December 2024

AbstractA new subpopulation of polar bears (Ursus maritimus) was recently discovered in the South-East of Greenland (SEG). This isolated colony inhabits a warmer climate zone, akin to the predicted future environments of polar bears with vastly reduced sea ice habitats, rendering this population of bears particularly important. Over two-thirds of polar bears will be extinct by 2050 with total extinction predicted by the end of this century and understanding possible mechanisms of adaptation via genomic analyses and preservation are critical. Transposable elements (TEs) are parasitic mobile elements that may play a role in an adaptive response to environmental challenges. We analysed transcriptome data from polar bear sub-populations in North-East and South-East Greenland (NEG, SEG), who reside in cooler and warmer habitats respectively, to identify differentially expressed, divergent TE species, TE families and linked changes in gene expression with some overlapping significantly differentially expressed TEs and genes. We identified activity hotspots in the genome of regions with significantly differentially expressed TEs. LINE family TEs were the most abundant, and most differentially expressed and divergent in the SEG population compared to reference TEs. Our results provide insights into how a genomic response at the TE level may allow the SEG subpopulations adapt and survive to climate change and provides a useful resource for conservation in polar bears.
At-RS31 orchestrates hierarchical cross-regulation of splicing factors and integrates alternative splicing with TOR-ABA pathways
Authors: Köster Tino , Venhuizen Peter , Lewinski Martin , Petrillo Ezequiel , Marquez Yamile , Fuchs Armin , Ray Debashish , Nimeth Barbara A. , Riegler Stefan , Franzmeier Sophie , Zheng Hong , Hughes Timothy , Morris Quaid , Barta Andrea , Staiger Dorothee , Kalyna Maria 
Published: December 2024

SUMMARYAlternative splicing is essential for plants, enabling a single gene to produce multiple transcript variants to boost functional diversity and fine-tune responses to environmental and developmental cues. At-RS31, a plant-specific splicing factor in the Serine/Arginine (SR)-rich protein family, responds to light and the Target of Rapamycin (TOR) signaling pathway, yet its downstream targets and regulatory impact remain unknown.To identify At-RS31 targets, we applied individual-nucleotide resolution crosslinking and immunoprecipitation (iCLIP) and RNAcompete assays. Transcriptomic analyses of At-RS31 mutant and overexpressing plants further revealed its effects on alternative splicing.iCLIP identified 4,034 At-RS31 binding sites across 1,421 genes, enriched in CU-rich and CAGA RNA motifs. Comparative iCLIP and RNAcompete data indicate that the RS domain of At-RS31 may influence its binding specificityin planta, underscoring the value of combiningin vivoandin vitroapproaches. Transcriptomic analysis showed that At-RS31 modulates diverse splicing events, particularly intron retention and exitron splicing, and influences other splicing modulators, acting as a hierarchical regulator.By regulating stress-response genes and genes in both TOR and abscisic acid (ABA) signaling pathways, At-RS31 may help integrate these signals, balancing plant growth with environmental adaptability through alternative splicing.
Spike sorting biases and information loss in a detailed cortical model
Authors: Laquitaine Steeve , Imbeni Milo , Tharayil Joseph , Isbister James B. , Reimann Michael W. 
Published: December 2024

AbstractSorting electrical signals (spikes) from extracellular recordings of large groups of connected neurons is essential to understanding brain function. Despite transformative advances in dense extracellular recordings, the activity of most cortical neurons remains undetected. Small simulations with known neuron spike times offer critical ground truth data to improve spike sorting. Yet, current simulations underestimate neuronal heterogeneity and connectivity, which can potentially make spike sorting more challenging. We simulated recordings in a detailed large-scale cortical microcircuit model to link spike sorting accuracy to neuronal heterogeneity, evaluate the performance of state-of-the-art spike sorters and examine how spike sorting impacts the retrieval of information encoded in the cortical circuit. We found that modern spike sorters accurately isolated about 15% of neurons within 50 µm of the electrode shank, which contrasts with previous simulated yields but agrees with experiments. Neurons were unresolved because their spike trains were either missed (undersampling) or, when detected, incomplete or merged with other units’ (assignment biases). Neuron isolation quality was influenced by both anatomical and physiological factors (selection bias), improving with increased neuron firing rate, spike spatial extent, for neurons in layer 5, and excitatory neurons. We exposed the network to various stimuli to dissociate the impact of these biases on its stimulus discrimination ability. Surprisingly, undersampling did not affect discrimination capacity, but selection and assignment biases nearly reduced it by half. These findings posit realistic models as a complementary method to evaluate and improve spike sorting and, hence, brain activity representations.
Mapping of Multilineage Tumor Cell Populations in Mouse Bladder Cancer
Authors: Schrode Nadine , Hu Yang , Yu Haocheng , Galsky Matthew , Sfakianos John , Sebra Robert , Beaumont Kristin G. , Mulholland David J 
Published: December 2024

ABSTRACTIn bladder cancer (BLCA), the cellular expression of lineage markers with predictive biomarker function can have important implications for tumor progression, treatment response, and survival. However, tumor heterogeneity and the coexistence of distinct tumor subpopulations can complicate the utility of using a primary, clinically assigned tumor signature. In this report, we have applied the reference atlas,Tabula Sapiens,and deep learning model, UniCell, to conduct in-depth transcriptional analysis of unique lineage marker-defined cell clusters in a carcinogen (BBN) induced bladder cancer model. UniCell deconvolution has identified tumor populations, including urothelial, adenocarcinoma, squamous cell carcinoma, and mesenchymal tumor populations, each with cell-intrinsic gene expression signatures relevant to human BLCA progression. The identified tumor clusters contain uniquely basal, luminal, stromal, or hybrid cells in cell lineage marker expression. To understand the significance of these populations during progression, we used trajectory and pseudo-time analysis to show that cells uniquely basal are plastic in lineage identity and can evolve to form tumor populations composed of other lineage marker-defined signatures. Finally, pathway and drug enrichment analysis of tumor cell clusters were used to identify therapeutics that may preferentially target the identified tumor cell populations.These data collectively define a molecular template that may uniquely profile molecular plasticity occurring during progression and response to therapy with important implications for human disease.SignificanceTumor heterogeneity is a mechanism for treatment resistance. Our study defines unique tumor subpopulations having differential therapeutic sensitivities and potential for lineage plasticity. Our modeling may impact the treatment of BLCA patients.
Pigmentation and retinal pigment epithelium thickness: a study of the phenotypic and genotypic relationships between ocular and extraocular pigmented tissues
Authors: Julian Thomas , Fitzgerald Tomas ,   UK Biobank Eye and Vision Consortium, Birney Ewan , Sergouniotis Panagiotis I. 
Published: December 2024

AbstractThe retinal pigment epithelium (RPE) is a specialised monolayer of pigmented epithelial cells in the outer retina. The embryology and biology of pigmentation in the RPE differs from other pigmented tissues such as the hair, skin and iris. The extent to which RPE pigmentation is related to that of other tissues remains unclear, and this study aims to address this knowledge gap. Here, we utilised RPE thickness measured using optical coherence tomography (OCT) imaging as a surrogate phenotype for RPE melanin content. We used UK Biobank data to assess the phenotypic relationships between RPE thickness and fundus pigmentation (principally a measure of choroidal pigmentation), hair colour, skin colour, and ability to tan. We subsequently performed a genome-wide association study (GWAS) to identify genetic loci associated with RPE thickness. We utilised the obtained genetic data to explore the global and local genetic correlation between RPE thickness and other pigmentation-related traits. We found that RPE thickness is not phenotypically or globally genetically correlated with hair colour, skin colour or ability to tan. Whilst RPE thickness was phenotypically correlated with retinal pigmentation score, there was not significant global genetic correlation. Despite this, variants in key pigmentation loci includingTYR, andOCA2-HERC2were found to be significant in our GWAS of RPE thickness. Furthermore, we identified four genetic regions in which RPE thickness is locally genetically correlated with other pigmentation-related traits, all of which contain protein-coding genes that are central to melanogenesis and melanosome transport. In conclusion, our study supports our assertion that pigmentation plays a role in RPE thickness, and highlights both shared and divergent features of RPE and other pigmentation-related traits.
Integration of diverse bioactivity data into the Chemical Checker compound universe
Authors: Comajuncosa-Creus Arnau , Bertoni Martino , Duran-Frigola Miquel , Fernández-Torras Adrià , Guitart-Pla Oriol , Kurzawa Nils , Locatelli Martina , Martins Yasmmin , Pareja-Lorente Elena , Rojas-Granado Gema , Soler Nicolas , Viesi Eva , Aloy Patrick 
Published: December 2024

AbstractChemical signatures encode the physicochemical and structural properties of small molecules into numerical descriptors, forming the basis for chemical comparisons and search algorithms. The increasing availability of bioactivity data has improved compound representations to include biological effects, although bioactivity descriptors are often limited to a few well-documented molecules. To address this issue, we implemented a collection of deep neural networks able to leverage the experimentally determined bioactivity data associated to small molecules and infer the missing bioactivity signatures for any compound of interest. However, unlike static chemical descriptors, these bioactivity signatures dynamically evolve with new data and processing strategies. Here, we present a computational protocol to modify or generate novel bioactivity spaces and signatures, describing the main steps needed to leverage diverse bioactivity data with the current knowledge, as catalogued in the Chemical Checker (CC), using the predefined data curation pipeline. We illustrate the functioning of the protocol through four specific examples, including the incorporation of new compounds to an already existing bioactivity space, a change in the data pre-processing without altering the underlying experimental data, and the creation of two novel bioactivity spaces from scratch, which are completed in under 9 hours using GPU computing. Overall, this protocol offers a guideline for installing, testing and running the CC data integration approach on user-provided data, with the aim of extending the annotation presented for a limited number of small molecules to a larger chemical landscape.Key pointsThe Chemical Checker is a large collection of processed, harmonized and integrated bioactivity signatures for over 1 million small molecules. Data are organized into 5 levels of increasing biological complexity and curation degrees: from chemical properties to clinical outcomes and from raw data representing explicit knowledge to embedded signatures inferred from observed bioactivity patterns.The Chemical Checker package provides a predefined and versatile framework to integrate user-provided data to the Chemical Checker universe of small molecules and generate novel customized bioactivity signatures.Key referencesDuran-Frigolaet al. “Extending the small-molecule similarity principle to all levels of biology with the Chemical Checker.” Nature Biotechnology 38.9 (2020): 1087-1096.Bertoniet al. “Bioactivity descriptors for uncharacterized chemical compounds.” Nature Communications 12.1 (2021): 3932.