bluuebunny/crossref_metadata_2025_split huggingface dataset:
MegaMASLD: An interactive platform for exploring stratified transcriptomic signatures in MASLD progression
Authors: Cheng Hong Sheng , Chua Damien , Chan Sook Teng , Yew Kuo Chao , Wong Sunny Hei , Tan Nguan Soon 
Published: July 2024

AbstractLiver transcriptomic data from patients with metabolic dysfunction-associated steatotic liver disease (MASLD) offers valuable resource for deciphering pathogenic molecular drivers. Here, we performed a Mega-analysis of MASLD Liver Transcriptomes (MegaMASLD) which reanalysed raw RNAseq data of over 800 livers in a standardized and integrative manner, aiming to unravel druggable molecular events in MASLD. Our analysis revealed a progressive transcriptomic shift predominantly associated with immunopathologies during MASLD progression. The differential transcriptomes produced a MASLD gene signature useful for quantitative assessment of MASLD severity but failed to faithfully recapitulate the exact histological staging. Instead, a histologic-independent unsupervised clustering analysis predicted a high-risk group prone to develop metabolic dysfunction-associated steatohepatitis (MASH), characterized by aberrant changes in humoral immune response and antibody repertoires. These findings were supported by another histologic-independent pseudotime analysis, which also identified several potentially targetable molecular switches, including FGFR, PDGFR, PAK, PRKG1 and CAMK kinase families, activated at various transitory phases of MASLD. The robust analysis has enabled risk stratification and deepened our understanding of the dynamic molecular events driving MASLD, thereby offering new options to enhance precision medicine of MASLD. An online web tool featuring MegaMASLD is available athttps://bioanalytics-hs.shinyapps.io/MegaMASLD/.
Conserved signals orchestrate self-organization and symmetry breaking of bi-layered epithelia during development and regeneration
Authors: Journot Robin P. , Huyghe Mathilde , Barthelemy Alexandre , Couto-Moreira Hugo , Sumbal Jakub , Faraldo Marisa M. , Dubail Maxime , Fouillade Charles , Fre Silvia 
Published: July 2024

AbstractOrgan development relies on complex molecular mechanisms that guide initially homogeneous populations of stem cells to differentiate into specialized cell types within defined spatial patterns. While stable during homeostasis, the proper spatial organization of cell types must be re-established in case of tissue injury for successful regeneration of organ shape and function. How cells commit to a differentiation path is a central question in stem cell research; however, the coordination between tissue geometry and cell fate specification remains enigmatic. To elucidate the molecular mechanisms instructing self-organization and symmetry breaking of epithelial stem cells, we developed a multi-faceted approach combiningin vitroorganoids,ex vivoembryonic tissue explants, and single-cell quantitative imaging to investigate the dynamic acquisition of cell fate in four bi-layered epithelia, during embryonic development but also in regeneration. Our findings indicate that tissue architecture is the primary determinant of cell fate decisions in these tissues. Upon the initial cell internalization event, the homogeneous population of stem cell break symmetry. Through genetic and pharmacological perturbations, we have demonstrated that a tightly coordinated interplay between Hippo/YAP and Notch signaling is essential for conveying information from tissue architecture to functional cell differentiation and stem cell potency restriction. Globally, this study uncovers the inherent capacity of stem cells to self-organize into multicellular structures, where the precise position of each differentiated cell is critical to instruct their differentiation choices during embryonic development and regeneration.
Bacillus toyonensisbiovar Thuringiensis: an overlooked entomopathogen?
Authors: Sauka Diego Herman , Del Valle Eleodoro E. , Palma Leopoldo 
Published: July 2024

AbstractHorizontal gene transfer (HGT) significantly influences prokaryotic genome evolution.Bacillus cereusandBacillus thuringiensisare nearly identical genetically, except forB. thuringiensisproducing parasporal crystals. The genes for these crystal proteins (e.g.,cry1A), along with other encoded insecticidal proteins (e.g.,vip3A), are located on megaplasmids and can be horizontally transferred. Recently, Sauka et al. (2022) reported aBacillus toyonensisstrain that produces parasporal crystals with dual insecticidal activity. This strain was classified asBacillus toyonensisbiovar Thuringiensis (NCBI: txid2923195) following Carroll et al.’s (2020) nomenclature. MisclassifiedB. toyonensisstrains, previously identified asB. thuringiensis(e.g., strain MC28), encodecryandcytgenes toxic to lepidopterous and dipterous insects. Advances in genome sequencing and bioinformatics tools now reduce misidentifications, enabling accurate reclassification in databases like GenBank.
Queen number shapes worker longevity, fecundity and gene expression in the invasive, highly polygynous antTapinoma magnum
Authors: Lenhart Anna , Majoe Megha , Selvi Sibel , Colgan Thomas J. , Libbrecht Romain , Foitzik Susanne 
Published: July 2024

AbstractIn social animals, reproductive activity and ageing patterns are influenced by group composition. A well-documented phenomenon in monogynous (one-queen) insect societies is that queen presence affects worker fecundity and longevity. Little is known about whether and how workers respond to queen number variation in polygynous (multi-queen) species and how their queens age. We created queenless, one-queen, and two-queen colonies of the invasive, polygynous antTapinoma magnumto examine worker survival, fecundity, oxidative stress resistance, and fat body gene expression. Additionally, we compared fecundity and brain and fat body transcriptomes of young and old queens. Queenless workers experienced the highest mortality, contrasting with monogynous species where queen removal typically extends lifespan. Workers in single-queen colonies lived longer and were more fertile than in two-queen colonies. Queen number did not directly affect oxidative stress resistance or fat body transcription, though the latter depended on an interaction with worker task. Furthermore, younger nurses demonstrated higher fecundity, oxidative stress resistance and upregulated antioxidant genes compared to older foragers. Absent or minor shifts in fecundity and transcription with queen age, respectively, indicated physiological stability with age. Our research highlights distinct caste- and tissue-specific ageing patterns in this supercolonial species, deviating from typical monogynous ants.
Click-chemistry-aided quantitation and sequencing of oxidized guanines and apurinic sites uncovers their transcription-linked strand bias in human cells
Authors: Takhaveev Vakil , Püllen Nikolai J.L. , Singh Navnit K. , Huber Sabrina M. , Schauer Stefan , Gahlon Hailey L. , Poetsch Anna R. , Sturla Shana J. 
Published: July 2024

AbstractDNA modifications drive aging, neurodegeneration, carcinogenesis, and chemotherapy drug action. To understand the functional genomic roles of DNA modifications, it is critical to accurately map their diverse chemical forms with single-nucleotide precision in complex genomes, but it remains challenging. Click-code-seq is a click-chemistry-aided single-nucleotide-resolution strategy for guanine-oxidation mapping, used in yeast DNA but having poor applicability to human genomes. Here, we upgraded click-code-seq to enable its first application for sequencing DNA oxidation and depurination in human genomes. For this, we developed a companion fluorescence assay, click-fluoro-quant, to rapidly quantify different common DNA modifications, and devised novel adapters to minimize false modification detection and assess modification frequency in cell populations. We uncovered that endogenous DNA oxidation in a human cell line has a highly similar pattern to cancer mutational signatures associated with reactive oxygen species. We established that the DNA-alkylating chemotherapy drug irofulven preferentially induces depurination in ApA dimers and promoter regions. Intriguingly, we revealed that oxidized guanines and apurinic sites, both irofulven-induced and endogenous, are depleted in gene transcribed strands, and the strand bias widens with increasing gene expression. This work substantially advances click-code-seq for deciphering the impacts of key modifications in human DNA on cellular physiology and toxicological responses.
FEHAT: Efficient, Large scale and Automated Heartbeat Detection in Medaka Fish Embryos
Authors: Ferreira Marcio Soares , Stricker Sebastian , Fitzgerald Tomas , Monahan Jack , Defranoux Fanny , Watson Philip , Welz Bettina , Hammouda Omar , Wittbrodt Joachim , Birney Ewan 
Published: July 2024

AbstractHigh resolution imaging of model organisms allows the quantification of important physiological measurements. In the case of fish with transparent embryos, these videos can visualise key physiological processes, such as heartbeat. High throughput systems can provide enough measurements for the robust investigation of developmental processes as well as the impact of system perturbations on physiological state. However, few analytical schemes have been designed to handle thousands of high-resolution videos without the need for some level of human intervention. We developed a software package, named FEHAT, to provide a fully automated solution for the analytics of large numbers of heart rate imaging datasets obtained from developing Medaka fish embryos in 96 well plate format imaged on an Acquifer machine. FEHAT uses image segmentation to define regions of the embryo showing changes in pixel intensity over time, followed by the classification of the most likely position of the heart and Fourier Transformations to estimate the heart rate. Here we describe some important features of the FEHAT software, showcasing its performance across a large set of medaka fish embryos and compare its performance to established, less automated solutions. FEHAT provides reliable heart rate estimates across a range of temperature-based perturbations and can be applied to tens of thousands of embryos without the need for any human intervention.
Feature Importance in Predicting Clinical Outcome: Statistics vs. Explainable Artificial Intelligence
Authors: Amin Parisa 
Published: July 2024

ABSTRACTAt the time of diagnosis for cancer patients, a wide array of data can be gathered, ranging from clinical information to multiple layers of omics data. Determining which of these data are most informative is crucial, not only for advancing biological understanding but also for clinical and economic considerations. This process facilitates the selection of the most significant markers, enhancing patient stratification and informing treatment recommendations. In this paper, we start with 89 features extracted from multiomics and clinical data and aim to identify the most important ones in predicting response to neoadjuvant chemotherapy (NAC) using different explainable Artificial Intelligence (XAI) models and statistics. Our results show that XAI methods consistently recover important features that are missed by statistics and vice versa, hinting towards the need for complementary implementation of these methods. Furthermore, we find that a myriad of features, from mutations to immune infiltration, affect the response to NAC in breast tumors.
Is there a negative trend in abundance of the weedy seadragon (Phyllopteryx taeniolatus) discernible in survey data summarised in Edgar et al. (2023)?
Authors: Schlögl Erik , Booth David J. 
Published: July 2024

AbstractDecadal changes in abundance of marine organisms along the Australian coastline were reported in a recentNaturepaper by Edgar et al. (2023). We reexamine the data used in that paper, and show that the conclusion of a 59% decline in weedy seadragons (Phyllopteryx taeniolatus) cannot be justified based on these data. The data are too sparse, especially for the final survey years of 2020 and 2021, and it is this sparsity in combination with particular modelling choices made by Edgar et al. (2023) that drives their results. While not specifically considered here, it is likely that these issues also affect the results on numerous other species reported in Edgar et al. (2023).
DriverOmicsNet: An Integrated Graph Convolutional Network for Multi-Omics Exploration of Cancer Driver Genes
Authors: Dai Yang-Hong , Chang Chia-Jun , Shen Po-Chien , Jheng Wun-Long , Chen Yu-Guang 
Published: July 2024

AbstractBackgroundCancer is a complex and heterogeneous group of diseases driven by genetic mutations and molecular changes. Identifying and characterizing cancer driver genes (CDgs) is crucial for understanding cancer biology and guiding precision oncology. Integrating multi-omics data can reveal the intricate molecular interactions underlying cancer progression and treatment responses.MethodsWe developed a graph convolutional network (GCN) framework, DriverOmicsNet, that integrates multi-omics data using STRING protein-protein interaction (PPI) networks and correlation-based weighted correlation network analysis (WGCNA). We applied this framework to 15 cancer types, analyzing 5555 tumor samples to predict cancer-related features such as homologous recombination deficiency (HRD), cancer stemness, immune clusters, tumor stage, and survival outcomes.FindingsDriverOmicsNet demonstrated superior predictive accuracy and model performance metrics across all target labels when compared with GCN models based on STRING network alone. Gene expression emerged as the most significant feature, reflecting the dynamic and functional state of cancer cells. The combined use of STRING PPI and WGCNA networks enhanced the identification of key driver genes and their interactions.InterpretationOur study highlights the effectiveness of using GCNs to integrate multi-omics data for precision oncology. The integration of STRING PPI and WGCNA networks provides a comprehensive framework that improves predictive power and facilitates the understanding of cancer biology, paving the way for more tailored treatments.
Recent odor experience selectively modulates olfactory sensitivity across the glomerular output in the mouse olfactory bulb
Authors: Subramanian Narayan , Leong Lee Min , Salemi Mokri Boukani Paria , Storace Douglas A. 
Published: July 2024

AbstractAlthough animals can reliably locate and recognize odorants embedded in complex environments, the neural circuits for accomplishing these tasks remain incompletely understood. Adaptation is likely to be important as it could allow neurons in a brain area to adjust to the broader sensory environment. Adaptive processes must be flexible enough to allow the brain to make dynamic adjustments, while maintaining sufficient stability so that organisms do not forget important olfactory associations. Processing within the mouse olfactory bulb is likely involved in generating adaptation, although there are conflicting models of how it transforms the glomerular output of the mouse olfactory bulb. Here we performed 2-photon Ca2+imaging from mitral/tufted glomeruli in awake mice to determine the time course of recovery from adaptation, and whether it acts broadly or selectively across the glomerular population. Individual glomerular responses, as well as the overall population odor representation was similar across imaging sessions. However, odor-concentration pairings presented with interstimulus intervals upwards of 30-s evoked heterogeneous adaptation that was concentration-dependent. We demonstrate that this form of adaptation is unrelated to variations in respiration, and olfactory receptor neuron glomerular measurements indicate that it is unlikely to be inherited from the periphery. Our results indicate that the olfactory bulb output can reliably transmit stable odor representations, but recent odor experiences can selectively shape neural responsiveness for upwards of 30 seconds. We propose that neural circuits that allow for non-uniform adaptation across mitral/tufted glomerular could be important for making dynamic adjustments in complex odor environments.
The Identification Markers of activated myofibroblast subsets in the Human Lung Fibrosis Ecosystem via integrated omics Analysis
Authors: Zheng Ying , Song Zhihong , Li Shifeng , Cao Bin , Wu Hongping 
Published: July 2024

AbstractBackgroundThe aberrant remodeling of the extracellular matrix (ECM) is closely associated with lung fibrosis. However, the mechanisms underlying ECM remodeling in pulmonary fibrosis (PF) remain unclear. The advent of single-cell RNA sequencing (scRNA-seq) has provided valuable insights into the diverse phenotypic and functional characteristics of human PF. Nevertheless, the dynamic of ECM remodeling in terms of ECM synthesizing and the potential activating markers of myofibroblasts in the human PF microenvironment still needs to be investigated.MethodsWe performed integrative scRNA-seq analyses on high-fidelity PF data from a public platform by filtering out the low-quality counts and doublets using two doublet prediction methods. Next, we investigated the dynamic of the ECM signature in diverse cells in PF and screened the potential markers of myofibroblasts via fitting a successful polynomial regression model. Finally, the markers of activated myofibroblasts were identified using bulk RNA-seq of pulmonary tissue.ResultsFirst, we depicted the pathogenic landscape and demonstrated the heterogeneity of ECM in PF by integratively analyzing single-cell RNA-seq data, and we hypothesized that myofibroblasts played a significant role in ECM formation. Second, our results successfully displayed the biological dynamic changes of ECM and investigated the 73 positive correlated genes of myofibroblasts in PF via a polynomial regression model. Then, the bulk RNA-seq results further identified eight new activating markers of myofibroblasts, such as MFAP2, MXRA5, and LRRC17 via transcriptomic signature, correlation and ROC scores. Finally, the results of cell-cell interaction indicated that myeloid cells may be involved in regulating ECM remodeling through proliferation mediated by myofibroblasts that secrete POSTN, suggesting that ECM remodeling in PF is a complex and multi-participated process.ConclusionsIn summary, we provided insights into the contributions of ECM in human PF by integrative analysis and highlighted potential clinical utilities of myofibroblast subsets as therapeutic targets.
Dual modes of DNA N6-methyladenine maintenance by distinct methyltransferase complexes
Authors: Wang Yuanyuan , Nan Bei , Ye Fei , Zhang Zhe , Yang Wentao , Pan Bo , Niu Junhua , Ju Aili , Liu Yongqiang , Zhang Wenxin , Liu Yifan , Gao Shan 
Published: July 2024

AbstractStable inheritance of DNA N6-methyladenine (6mA) is crucial for its biological functions in eukaryotes. Here, we identify two distinct methyltransferase (MTase) complexes, both sharing the catalytic subunit AMT1, but featuring AMT6 and AMT7 as their unique components, respectively. While the two complexes are jointly responsible for 6mA maintenance methylation, they exhibit distinct enzymology, DNA/chromatin affinity, genomic distribution, and knockout phenotypes. AMT7 complex, featuring high MTase activity and processivity, is connected to transcription-associated epigenetic marks, including H2A.Z and H3K4me3, and is required for the bulk of maintenance methylation. In contrast, AMT6 complex, with reduced activity and processivity, is recruited to initiate maintenance methylation immediately after DNA replication. These two complexes coordinate in maintenance methylation. By integrating signals from both replication and transcription, this mechanism ensures the faithful and efficient transmission of 6mA as an epigenetic mark in eukaryotes.Significance statementDNA N6-methyladenine (6mA) has recently been recognized as an epigenetic mark in eukaryotes. The stable inheritance of 6mA is essential for its biological functions. However, the precise mechanisms by which 6mA patterns are faithfully and efficiently transmitted remain largely unknown. Here, we have identified two distinct 6mA methyltransferase (MTase) complexes and elucidated their coordinated role in maintenance methylation. This dual- complex mechanism ensures rapid and accurate methylation at newly replicated loci with proper transcription-associated epigenetic marks.
Reduced learning rate and E/I imbalance drive Peripersonal Space boundaries expansion in Schizophrenia
Authors: Paredes Renato , Grigoras Vlad , Ferroni Francesca , Ardizzi Martina , Ferri Francesca , Seriès Peggy 
Published: July 2024

AbstractBackground and HypothesisAbnormalities in the encoding of the space close to the body, named peripersonal space (PPS), is thought to play a crucial role in the disruption of the bodily self observed in schizophrenia (SCZ). Empirical evidence indicates a narrower extension of the PPS in SCZ compared to controls but preserved plasticity of the PPS. Computational studies suggest that increased excitation of sensory neurons could explain the smaller PPS observed in SCZ. However, it is unclear why SCZ patients preserve PPS plasticity and how such an excitation imbalance influences learning during the extension of the PPS boundaries.Study DesignWe hypothesise that Hebbian plasticity can account for PPS expansion after active tool use training, which occurs in spite of E/I imbalance and reduced synaptic density. Using simulations in a SCZ network model, we explored the effects of such impairments on PPS plasticity and fitted the model to behavioural data before and after a training routine.Study ResultsWe found that increased excitation of sensory neurons does not impede the expansion of PPS and could explain a sharper demarcation of PPS boundaries after training. In addition, we found that a reduction in the learning rate is required to reproduce the post-training PPS representation of SCZ patients.ConclusionsWe discuss how the neural mechanisms behind the plasticity of PPS in the SCZ spectrum are related to the core pathophysiology of the disease.