bluuebunny/crossref_metadata_2025_split huggingface dataset:
The accuracy of species tree inference under gene tree dependence
Authors: He Wanting , Scornavacca Celine , Chan Yao-ban 
Published: June 2024

AbstractWhen inferring the evolutionary history of species and the genes they contain, the phylogenetic trees of the genes can be different to that of the species and to each other, due to a variety of causes including incomplete lineage sorting. We often wish to infer the species tree, but only reconstruct the gene trees from sequences. We then combine the gene trees to produce a species tree; methods to do this are known as summary methods, of which ASTRAL is the currently among the most popular. ASTRAL has been shown to be practically accurate in many scenarios through extensive simulations. However, these simulations generally assume that the input gene trees are independent of each other. This is known to be unrealistic, as genes that are close to each other on the chromosome (or are related by function) have dependent phylogenies, due to the absence of unlimited recombination between the genes.In this paper, we develop a model for generating dependent gene trees within a species tree, based on the coalescent with recombination. We then use these trees as input to ASTRAL to reassess its accuracy for dependent gene trees. Our results show that ASTRAL performs more poorly with greater dependence, both when gene trees are known and estimated from sequences. Indeed, the effect of dependence between gene trees is comparable to (if not larger than) the effect of gene tree estimation error. We then re-analyse a 37-taxon mammalian data set; under a realistic recombination rate, the estimated accuracy of ASTRAL decreases substantially (the Robinson-Foulds distance increases by a factor of 4.7) relative to the accuracy previously estimated with independent gene trees, and the effective sample size for this dataset is about one-third of the actual sample size. This shows that the impact of gene tree dependence on the accuracy of ASTRAL (and other summary methods) can be extensive.Author summaryThe study of the evolutionary history of species is important for understanding and reconstructing the history of life on Earth. These evolutionary histories are represented in the form of species trees, which can be reconstructed from the evolutionary histories of the genes contained in the species using so-called species tree inference methods. This is complicated by the fact that the histories of the genes (gene trees) can be related to each other, depending on their placement in the genome or their functions. Gene tree dependence is not taken into account in almost all studies of the accuracy of species tree inference. In this paper, we develop a statistical model to include gene tree dependence, and show that it can significantly affect the accuracy of species tree inference. This effect is at least as large as the impact of incorrect reconstruction of the gene trees themselves, a well-known issue in species tree inference.
Chromatin remodeling with combined FACT and BET inhibition disrupts oncogenic transcription in Diffuse Midline Glioma
Authors: Holliday Holly , Khan Aaminah , Ehteda Anahid , Ross Samuel E. , Jayatilleke Nisitha , Gopalakrishnan Anjana , Guo Xinyi , Liu Jie , Nguyen Hieu , Lee Alvin , Sanguino Yolanda Colino , Dinger Marcel E. , Mayoh Chelsea , Rayner Benjamin S. , Tsoli Maria , Ziegler David S. 
Published: June 2024

AbstractAberrant epigenetic regulation is a hallmark of Diffuse Midline Glioma (DMG), an incurable pediatric brain tumor. The H3K27M driver histone mutation leads to transcriptional dysregulation, indicating that targeting the epigenome and transcription may be key therapeutic strategies against this highly aggressive cancer. One such target is the Facilitates Chromatin Transcription (FACT) histone chaperone. We found FACT to be enriched at developmental gene promoters, coinciding with regions of open chromatin and binding motifs of core DMG regulatory transcription factors. Furthermore, FACT interacted and co-localized with the Bromodomain and Extra-Terminal Domain (BET) protein BRD4 at promoters and enhancers, suggesting functional cooperation between FACT and BRD4 in DMG.In vitro, a combinatorial therapeutic approach using the FACT inhibitor CBL0137, coupled with BET inhibition revealed potent and synergistic cytotoxicity across a range of DMG cultures, with H3K27M-mutant cells demonstrating heightened sensitivity. These results were recapitulatedin vivo, significantly extending survival in three independent orthotopic PDX models of DMG. Mechanistically, we show that CBL0137 treatment decreased chromatin accessibility, synergizing with BET inhibition to disrupt transcription, silencing several key oncogenes includingMYC, PDGFRAandMDM4, as well as causing alterations to the splicing landscape. Combined, these data highlight the therapeutic promise of simultaneously targeting FACT and BRD4 in DMG, proposing a novel strategy for combating this devastating pediatric brain tumor.
Training Compute-Optimal Protein Language Models
Authors: Cheng Xingyi , Chen Bo , Li Pan , Gong Jing , Tang Jie , Song Le 
Published: June 2024

AbstractWe explore optimally training protein language models, an area of significant interest in biological research where guidance on best practices is limited. Most models are trained with extensive compute resources until performance gains plateau, focusing primarily on increasing model sizes rather than optimizing the efficient compute frontier that balances performance and compute budgets. Our investigation is grounded in a massive dataset consisting of 939 million protein sequences. We trained over 300 models ranging from 3.5 million to 10.7 billion parameters on 5 to 200 billion unique tokens, to investigate the relations between model sizes, training token numbers, and objectives. First, we observed the effect of diminishing returns for the Causal Language Model (CLM) and that of overfitting for the Masked Language Model (MLM) when repeating the commonly used Uniref database. To address this, we included metagenomic protein sequences in the training set to increase the diversity and avoid the plateau or overfitting effects. Second, we obtained the scaling laws of CLM and MLM on Transformer, tailored to the specific characteristics of protein sequence data. Third, we observe a transfer scaling phenomenon from CLM to MLM, further demonstrating the effectiveness of transfer through scaling behaviors based on estimated Effectively Transferred Tokens. Finally, to validate our scaling laws, we compare the large-scale versions of ESM-2 and PROGEN2 on downstream tasks, encompassing evaluations of protein generation as well as structure- and function-related tasks, all within less or equivalent pre-training compute budgets.
The role of eye movements in the process of silicone oil emulsification after vitreoretinal surgery
Authors: Nepita Irene , Brusati Camilla , Liggieri Libero , Ravera Francesca , Ferrara Mariantonia , Stocchino Alessandro , Romano Mario R. , Santini Eva , Repetto Rodolfo 
Published: June 2024

AbstractBackgroundEmulsification of silicone oil (SO) is a feared and common complication of SO tamponade as potentially associated with significant risks to ocular health, including elevated intraocular pressure (IOP), glaucoma, corneal and retinal changes. The aim of this study was to investigate the role and interplay of major factors on the formation of SO emulsion, such as eye rotations and albumin, a blood serum protein known to affect interfacial properties.MethodsExperiments were conducted in a realistic model of the vitreous chamber, filled with SO and an aqueous solution containing different concentrations of albumin. The model was subjected to harmonic and saccadic rotations, at body temperature.ResultsNo emulsions were detected in the absence of endogenous proteins in the aqueous solution. The presence of albumin significantly influenced emulsion formation, acting as a surfactant. Mechanical energy from eye movements was also found to contribute to emulsification, with higher mechanical energy provided to the system leading to smaller droplet sizes. The emulsions formed were stable over extended times.ConclusionsThis study highlights the complex interplay of factors influencing SO emulsification in the vitreous chamber. A better understanding of the mechanisms underlying SO emulsification is crucial for developing strategies to mitigate SO emulsion and the related complications.
Impairment of brain function in a mouse model of Alzheimer’s disease during the pre-depositing phase: the role of α7 nicotinic acetylcholine receptors
Authors: Lykhmus Olena , Tzeng Wen-Yu , Koval Lyudmyla , Uspenska Kateryna , Zirdum Elizabeta , Kalashnyk Olena , Garaschuk Olga , Skok Maryna 
Published: June 2024

AbstractAlzheimer’s disease (AD) is an age-dependent incurable neurodegenerative disorder accompanied by neuroinflammation, amyloid accumulation and memory impairment. It begins decades before the first clinical symptoms appear, and identifying early biomarkers is key for developing disease-modifying therapies. We show now in a mouse model of AD that before any amyloid deposition the brains of 1.5-month-old mice contain increased levels of pro-inflammatory cytokines IL-1β and IL-6, decreased levels of nicotinic acetylcholine receptors (nAChRs) in the brain and brain mitochondria and increased amounts of α7 nAChR-bound Aβ1-42, along with impaired episodic memory and increased risk of apoptosis. Both acute (1-week-long) and chronic (4-month-long) treatments with α7-selective agonist PNU282987, starting at 1.5 months of age, were well tolerated. The acute treatment did not affect the levels of soluble Aβ1-42but consistently upregulated the α7 nAChR expression, decreased the level of α7- Aβ1-42complexes and improved episodic memory of 1.5-month-old mice. The chronic treatment, covering the disease development phase, strongly upregulated the expression of all abundant brain nAChRs, reduced both free and α7-coupled Aβ1-42within the brain, had anti-inflammatory and antiapoptotic effects, and potently upregulated cognition, thus identifying α7 nAChRs as both early biomarker and potent therapeutic target for fighting this devastating disease.
Endurance rivalry in capelin: insights from semen quality and regeneration
Authors: Wagle Ranjan , Hanley Connor P. , Purchase Craig F. 
Published: June 2024

AbstractMale-biased adult sexual size dimorphism is often the result of intra-sex sexual selection driven by male-male competition. Capelin (Mallotus villosus) exhibit male-biased sexual size dimorphism but lack contests/fighting, and female mate choice, if present, is unrelated to male size. Consequently, it is hypothesized that adult sexual size dimorphism in capelin is due to a mating system that favours larger males with greater energy reserves, allowing them to compete for prolonged access to mating opportunities through endurance rivalry. To enable this, males need a continual supply of semen through the spawning season. However, they have unusually small testes and are predicted to deplete stored semen rapidly, and their unique sperm physiology (i.e. the only known external fertilizing vertebrate to release pre-activated semen) may constrain the ability to regenerate it. We found that the majority of capelin sampled on beaches in 2023 had adequate semen, but towards the end of the spawning season some fish had none. Capelin held in laboratory tanks could regenerate semen within two days, maintaining their ability to seize continual mating opportunities. These results support the endurance rivalry hypothesis.
AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia
Authors: Sikirzhytskaya Aliaksandra , Tyagin Ilya , Sutton S. Scott , Wyatt Michael D. , Safro Ilya , Shtutman Michael 
Published: June 2024

AbstractNeurodegenerative pathologies such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, Amyotrophic lateral sclerosis, Multiple sclerosis, HIV-associated neurocognitive disorder, and others significantly affect individuals, their families, caregivers, and healthcare systems. While there are no cures yet, researchers worldwide are actively working on the development of novel treatments that have the potential to slow disease progression, alleviate symptoms, and ultimately improve the overall health of patients. Huge volumes of new scientific information necessitate new analytical approaches for meaningful hypothesis generation. To enable the automatic analysis of biomedical data we introduced AGATHA, an effective AI-based literature mining tool that can navigate massive scientific literature databases, such as PubMed. The overarching goal of this effort is to adapt AGATHA for drug repurposing by revealing hidden connections between FDA-approved medications and a health condition of interest. Our tool converts the abstracts of peer-reviewed papers from PubMed into multidimensional space where each gene and health condition are represented by specific metrics. We implemented advanced statistical analysis to reveal distinct clusters of scientific terms within the virtual space created using AGATHA-calculated parameters for selected health conditions and genes. Partial Least Squares Discriminant Analysis was employed for categorizing and predicting samples (122 diseases and 20889 genes) fitted to specific classes. Advanced statistics were employed to build a discrimination model and extract lists of genes specific to each disease class. Here we focus on drugs that can be repurposed for dementia treatment as an outcome of neurodegenerative diseases. Therefore, we determined dementia-associated genes statistically highly ranked in other disease classes. Additionally, we report a mechanism for detecting genes common to multiple health conditions. These sets of genes were classified based on their presence in biological pathways, aiding in selecting candidates and biological processes that are exploitable with drug repurposing.Author SummaryThis manuscript outlines our project involving the application of AGATHA, an AI-based literature mining tool, to discover drugs with the potential for repurposing in the context of neurocognitive disorders. The primary objective is to identify connections between approved medications and specific health conditions through advanced statistical analysis, including techniques like Partial Least Squares Discriminant Analysis (PLSDA) and unsupervised clustering. The methodology involves grouping scientific terms related to different health conditions and genes, followed by building discrimination models to extract lists of disease-specific genes. These genes are then analyzed through pathway analysis to select candidates for drug repurposing.
Drivers ofIxodes ricinuspopulation dynamics in Northeast France: a Bayesian modelling approach
Authors: Kim Younjung , Jaulhac Benoît , Vesga Juan F , Zilliox Laurence , Boulanger Nathalie , Edmunds W John , Métras Raphaëlle 
Published: June 2024

AbstractIxodes ricinusis the primary vector for Lyme disease and tick-borne encephalitis across Europe. To better understand the environmental and ecological drivers of its population dynamics, we collected monthly tick density data over ten years (2013–2022) in four sites in Northeast France, whereI. ricinushas established, and developed and fitted a mathematical model using a Bayesian approach. Our model estimated oviposition, hatching, and moulting rates across a range of temperature or saturation deficit, as well as questing and vertebrate host contact rates. Furthermore, we showed the importance of diapause in reproducing the observed seasonal population dynamics. Finally, model projections indicated a significant decrease inI. ricinusabundance over the next 20 years under several climate change scenarios. This study elucidatesI. ricinuspopulation dynamics in Northeast France, provides foundations for developing models ofI. ricinus-borne pathogen transmission, and is adaptable to otherIxodidaepopulations of public health significance.
Lestaurtinib’s antineoplastic activity converges on JAK/STAT signaling to inhibit advanced forms of therapy resistant ovarian cancer
Authors: Rodman Esther P.B. , Emch Michael J. , Hou Xiaonan , Bajaj Archit , Pearson Nicole A. , John August J. , Ortiz Yamillie , Bass Adam D. , Singh Saloni , Baldassarre Gustavo , Kaufmann Scott H. , Weroha S. John , Hawse John R. 
Published: June 2024

AbstractOvarian cancer is the deadliest gynecological malignancy, owing to its late-stage diagnosis and high rates of recurrence and resistance following standard-of-care treatment, highlighting the need for novel treatment approaches. Through an unbiased drug screen, we identified the kinase inhibitor, lestaurtinib, as a potent antineoplastic agent for chemotherapy- and PARP-inhibitor (PARPi)-sensitive and -resistant ovarian cancer cells and patient derived xenografts (PDXs). RNA-sequencing revealed that lestaurtinib potently suppressed JAK/STAT signaling and lestaurtinib efficacy was shown to be directly related to JAK/STAT pathway activity in cell lines and PDX models. Most ovarian cancer cells exhibited constitutive JAK/STAT pathway activation and genetic loss of STAT1 and STAT3 resulted in growth inhibition. Lestaurtinib also displayed synergy when combined with cisplatin and olaparib, including in a model of PARPi resistance. In contrast, the most well-known JAK/STAT inhibitor, ruxolitinib, lacked antineoplastic activity against all ovarian cancer cell lines and PDX models tested. This divergent behavior was reflected in the ability of lestaurtinib to block both Y701/705 and S727 phosphorylation of STAT1 and STAT3, whereas ruxolitinib failed to block S727. Consistent with these findings, lestaurtinib additionally inhibited JNK and ERK activity, leading to more complete suppression of STAT phosphorylation. Concordantly, combinatorial treatment with ruxolitinib and a JNK or ERK inhibitor resulted in synergistic antineoplastic effects at dose levels where single agents were ineffective. Taken together, these findings indicate that lestaurtinib, and other treatments that converge on JAK/STAT signaling, are worthy of further pre-clinical and clinical exploration for the treatment of highly aggressive and advanced forms of ovarian cancer.Statement of significanceLestaurtinib is a novel inhibitor of ovarian cancer, including chemotherapy- and PARPi-resistant models, that acts through robust inhibition of the JAK/STAT pathway and synergizes with standard-of-care agents at clinically relevant concentrations.
Lag3 and PD-1 pathways regulate NFAT-dependent TCR signalling programmes during early CD4+T cell activation
Authors: Sheriff Lozan , Copland Alastair , Lecky David A.J. , Done Reygn , George Lorna S , Jennings Emma K. , Rouvray Sophie , Elliot Thomas A.E. , Jinks Elizabeth S. , Pallan Lalit , Bending David 
Published: June 2024

SummaryLag3 and PD-1 are immune checkpoints that regulate T cell responses and are current immunotherapy targets. Yet how they function to control early CD4+T cell activation remains unclear. Here, we show that the PD-1 and Lag3 pathways exhibit layered control of the early CD4+T cell activation process, with the effects of Lag3 more pronounced in the presence of PD-1 pathway co-blockade (CB). RNA-sequencing revealed that CB drove an early NFAT-dependent transcriptional profile, including promotion of ICOShiT follicular helper (Tfh) cell differentiation. NFAT pathway inhibition abolished CB-induced upregulation of NFAT-dependent co-receptors ICOS and OX40, whilst unaffecting the NFAT-independent geneNr4a1. Mechanistically, Lag3 and PD-1 pathways functioned additively to regulate the duration of T cell receptor (TCR) signals during CD4+T cell re-activation. Our data therefore reveal that PD-1 and Lag3 pathways converge to additively regulate TCR signal duration and NFAT-dependent transcriptional activity during early CD4+T cell re-activation.HighlightsPD-1 and Lag3 pathways exhibit layered control of early CD4+T cell activationTheir co-blockade enhances NFAT-dependent TCR transcriptional programmesInhibition of NFAT signalling reverses the functional effects of PD-1 and Lag3 co-blockadeMechanistically, PD-1 and Lag3 function to additively regulate TCR signal duration during re-activation of CD4+T cells
SpotSweeper: spatially-aware quality control for spatial transcriptomics
Authors: Totty Michael , Hicks Stephanie C. , Guo Boyi 
Published: June 2024

AbstractQuality control (QC) is a crucial step to ensure the reliability and accuracy of the data obtained from RNA sequencing experiments, including spatially-resolved transcriptomics (SRT). Existing QC approaches for SRT that have been adopted from single-nucleus RNA sequencing (snRNA-seq) methods are confounded by spatial biology and are inappropriate for SRT data. In addition, no methods currently exist for identifying histological tissue artifacts unique to SRT. Here, we introduce SpotSweeper, spatially-aware QC methods for identifying local outliers and regional artifacts in SRT. SpotSweeper evaluates the quality of individual spots relative to their local neighborhood, thus minimizing bias due to biological heterogeneity, and uses multiscale methods to detect regional artifacts. Using SpotSweeper on publicly available data, we identified a consistent set of Visium barcodes/spots as systematically low quality and demonstrate that SpotSweeper accurately identifies two distinct types of regional artifacts, resulting in improved downstream clustering and marker gene detection for spatial domains.
Does force depression resulting from shortening against series elasticity contribute to the activation dependence of optimum length?
Authors: Mayfield Dean L , Holt Natalie C 
Published: June 2024

ABSTRACTThe optimum length for force generation (L0) increases as activation is reduced, challenging classic theories of muscle contraction. Although the activation dependence ofL0is seemingly consistent with length-dependent Ca2+sensitivity, this mechanism can’t explain the apparent force dependence ofL0, or the effect of series compliance on activation-related shifts inL0. We have tested a theory proposing that the activation dependence ofL0relates to force depression resulting from shortening against series elasticity. This theory predicts that significant series compliance would cause tetanicL0to be shorter than the length corresponding to optimal filament overlap, thereby increasing the activation dependence ofL0. We tested this prediction by determiningL0and maximum tetanic force (P0) with (L0_spring,P0_spring) and without added compliance in bullfrog semitendinosus muscles. The activation dependence ofL0was characterised with the addition of twitch and doublet contractions. Springs attached to muscles gave added fixed-end compliances of 11-39%, and this added compliance induced force depression for tetanic fixed-end contractions (P0_spring/P0< 1). We found strong, negative correlations between spring compliance and bothP0_spring(r2= 0.89-91) andL0_spring(r2= 0.60-63;P< 0.001), while the activation dependence ofL0was positively correlated to added compliance (r2= 0.45,P= 0.011). However, since the compliance-mediated reduction inL0was modest relative to the activation-related shift reported for the bullfrog plantaris muscle, additional factors must be considered. Our demonstration of force depression under novel conditions adds support to the involvement of a stress-induced inhibition of cross-bridge binding.