bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phylogenetic tree statistics: a systematic overview using the new R package ‘treestats’
Authors: Janzen Thijs , Etienne Rampal S. 
Published: January 2024

AbstractPhylogenetic trees are believed to contain a wealth of information on diversification processes. Comparing phylogenetic trees is not straightforward due to their high dimensionality. Researchers have therefore defined a wide range of one-dimensional summary statistics. However, it remains unexplored to what extent these summary statistics cover the same underlying information and what summary statistics best explain observed variation across phylogenies. Furthermore, a large subset of available summary statistics focusses on measuring the topological features of a phylogenetic tree, but are often only explored at the extreme edge cases of the fully balanced or unbalanced tree and not for trees of intermediate balance.Here, we introduce a new R package that provides speed optimized code to compute 54 summary statistics. We study correlations between summary statistics on empirical trees and on trees simulated using several diversification models. Furthermore, we introduce an algorithm to create intermediately balanced trees in a well-defined manner, in order to explore variation in summary statistics across a balance gradient.We find that almost all summary statistics are correlated with tree size, and it is difficult if not impossible to correct for tree size, unless the tree generating model is known. Furthermore, we find that across empirical and simulated trees, at least two large clusters of correlated summary statistics can be found, where statistics group together based on information used (topology or branching times). However, the finer grained correlation structure appears to depend strongly on either the taxonomic group studied (in empirical studies) or the diversification model (in simulation studies). Nevertheless, we can identify multiple groups of summary statistics that are strongly and consistently correlated, indicating that these statistics measure the same underlying property of a tree. Lastly, we find that almost all topological summary statistics vary non-linearly and sometimes even non-monotonically with our intuitive balance gradient.Therefore, in order to avoid introducing biases and missing underlying information, we advocate for selecting as many summary statistics as possible in phylogenetic analyses. With the introduction of the treestats package, which provides fast and reliable calculations, such an approach is now routinely possible.
They all rock: A systematic comparison of conformational movements in LeuT-fold transporters
Authors: Licht Jacob A. , Berry Samuel P. , Gutierrez Michael A. , Gaudet Rachelle 
Published: January 2024

SUMMARYMany membrane transporters share the LeuT fold—two five-helix repeats inverted across the membrane plane. Despite hundreds of structures, whether distinct conformational mechanisms are supported by the LeuT fold has not been systematically determined. After annotating published LeuT-fold structures, we analyzed distance difference matrices (DDMs) for nine proteins with multiple available conformations. We identified rigid bodies and relative movements of transmembrane helices (TMs) during distinct steps of the transport cycle. In all transporters the bundle (first two TMs of each repeat) rotates relative to the hash (third and fourth TMs). Motions of the arms (fifth TM) to close or open the intracellular and outer vestibules are common, as is a TM1a swing, with notable variations in the opening-closing motions of the outer vestibule. Our analyses suggest that LeuT-fold transporters layer distinct motions on a common bundle-hash rock and demonstrate that systematic analyses can provide new insights into large structural datasets.
scATAcat: Cell-type annotation for scATAC-seq data
Authors: Altay Aybuge , Vingron Martin 
Published: January 2024

ABSTRACTCells whose accessibility landscape has been profiled with scATAC-seq cannot readily be annotated to a particular cell type. In fact, annotating cell-types in scATAC-seq data is a challenging task since, unlike in scRNA-seq data, we lack knowledge of “marker regions” which could be used for cell-type annotation. Current annotation methods typically translate accessibility to expression space and rely on gene expression patterns. We propose a novel approach, scATAcat, that leverages characterized bulk ATAC-seq data as prototypes to annotate scATAC-seq data. To mitigate the inherent sparsity of single-cell data, we aggregate cells that belong to the same cluster and create pseudobulk. To demonstrate the feasibility of our approach we collected a number of datasets with respective annotations to quantify the results and evaluate performance for scATAcat. scATAcat is available as a python package athttps://github.com/aybugealtay/scATAcat.
Viral antigen mismatch affects antiviral T-cell response and may impair immunotherapeutic efficacy against ATL
Authors: Sugata Kenji , Takatori Mitsuyoshi , Reda Omnia , Yang Tan Benjy Jek , Tokunaga Masahito , Sato Tomoo , Ueda Mitsuharu , Yamano Yoshihisa , Utsunomiya Atae , Satou Yorifumi 
Published: January 2024

AbstractHuman T-cell leukemia virus type 1 (HTLV-1) has the potential to transform primary CD4+T cellsin vitrowithin a short time; however, the majority of infected individuals maintain an asymptomatic and disease-free condition, suggesting the existence of an equilibrium between the proliferation of infected cells and host immunity. The decline in anti-viral immunity contributes to the transformation of the infected cells, leading to the development of adult T-cell leukemia/lymphoma (ATL). This study identified a variation in a major viral antigen, HTLV-1 Tax, in human leukocyte antigen-A24 (HLA-A24) positive individuals. Two variants of Tax301-309peptides, SFHNLHLLF (Tax301-309A) and SFHSLHLLF (Tax301-309B) were found to induce distinct T-cell immune responses in HLA-A24 positive individuals. There was a disparity between two Tax301-309peptides in the detection of anti-Tax301-309cytotoxic T-lymphocytes (CTLs) binding to A24/peptide multimers by flow cytometry analysis. More importantly, over half of the anti-Tax TCRs of anti-Tax CTLs from infected individuals did not recognize mismatched Tax301-309peptides by Enzyme-Linked Immunospot (ELISpot) assay using Jurkat T cells expressing the anti-Tax301-309specific TCR. These findings underscore the importance of matching the viral antigen epitope type in T-cell-based immunotherapy against ATL by using viral antigen Tax.Key pointsEpitope heterogeneity in the major viral antigen in HTLV-1 infection causes different T-cell responses in infected individuals.Recommended guideline; performing virus typing to obtain optimal efficacy in T-cell-mediated immunotherapy against the viral antigen Tax
Comparative Analysis of Biomarkers in Type 2 Diabetes Patients with and without Comorbidities: Insights into the Role of Hypertension and Cardiovascular Disease
Authors: Savvopoulos Symeon , Hatzikirou Haralampos , Jelinek Herbert F. 
Published: January 2024

AbstractBackgroundType 2 diabetes mellitus (T2DM) are 90% of diabetes cases, and its prevalence and incidence, including comorbidities, are rising worldwide. Clinically, diabetes and associated comorbidities are identified by biochemical and physical characteristics including glycaemia, glycated hemoglobin (HbA1c), and tests for cardiovascular, eye and kidney disease.ObjectivesDiabetes may have a common etiology based on inflammation and oxidative stress that may provide additional information about disease progression and treatment options. Thus, identifying high-risk individuals can delay or prevent diabetes and its complications.DesignIn patients with or without hypertension and cardiovascular disease, as part of progression from no diabetes to T2DM, this research studied the changes in biomarkers between control and prediabetes, prediabetes to T2DM, and control to T2DM, and classified patients based on first-attendance data. Control patients and patients with hypertension, cardiovascular, and with both hypertension and cardiovascular diseases are 156, 148, 61, and 216, respectively.MethodsLinear discriminant analysis is used for classification method and feature importance, This study examined the relationship between Humanin and mitochondrial protein (MOTSc), mitochondrial peptides associated with oxidative stress, diabetes progression, and associated complications.ResultsMOTSc, reduced glutathione and glutathione disulfide ratio (GSH/GSSG), interleukin-1β (IL-1β), and 8-isoprostane were significant (p<0.05) for the transition from prediabetes to T2DM, highlighting the importance of mitochondrial involvement. Complement component 5a (C5a) is a biomarker associated with disease progression and comorbidities, with GSH/GSSG, monocyte chemoattractant protein-1 (MCP-1), and 8-isoprostane being the most important biomarkers.ConclusionsComorbidities affect the hypothesized biomarkers as diabetes progresses. Mitochondrial oxidative stress indicators, coagulation, and inflammatory markers help assess diabetes disease development and provide appropriate medications. Future studies will examine longitudinal biomarker evolution.
Establishment of an easy-to-construct liver injury mouse model for longitudinal analysis by drinking-water administration of MDA
Authors: Iwasaka Takumi , Mizuno Tadahaya , Morita Katsuhisa , Azuma Iori , Nakagawa Tomoka , Nakashima Eri , Kusuhara Hiroyuki 
Published: January 2024

AbstractCompound actions are diverse, capable of inducing various biological responses, making them a valuable exploratory tool for understanding biological mechanisms. While widely employed in liver dysfunction research, models requiring continuous administration for longitudinal studies come with high construction costs. Although drinking water models are useful, currently utilized compounds are limited, with thioacetamide being one of the few examples. Is it possible to expand drinking water models for liver dysfunction research? Addressing this question, our study focused on constructing a novel drinking water-induced liver injury model. Through data mining and literature research, 4,4’-methylenedianiline (MDA) was identified, whose drinking water administration consistently exhibited elevated ALT levels over 28 days. To evaluate differences in pathophysiological profiles compared to existing thioacetamide models, we acquired multi-view data of early biochemical test values, immune cell trafficking, and transcriptome over time. The analysis revealed unique features such as elevated total bilirubin in serum, increased monocyte-derived macrophages in the liver, and enhanced fibrinolysis in the liver, suggesting a model of cholestatic liver injury. This study proposes the first cholestatic liver injury model for compound drinking water administration, expanding the scope of longitudinal analysis in liver dysfunction research.
Learning predictive signatures of HLA type from T-cell repertoires
Authors: Ortega Maria Ruiz , Pogorelyy Mikhail V. , Minervina Anastasia A. , Thomas Paul G. , Walczak Aleksandra M. , Mora Thierry 
Published: January 2024

AbstractT cells recognize a wide range of pathogens using surface receptors that interact directly with pep-tides presented on major histocompatibility complexes (MHC) encoded by the HLA loci in humans. Understanding the association between T cell receptors (TCR) and HLA alleles is an important step towards predicting TCR-antigen specificity from sequences. Here we analyze the TCR alpha and beta repertoires of large cohorts of HLA-typed donors to systematically infer such associations, by looking for overrepresentation of TCRs in individuals with a common allele.TCRs, associated with a specific HLA allele, exhibit sequence similarities that suggest prior antigen exposure. Immune repertoire sequencing has produced large numbers of datasets, however the HLA type of the corresponding donors is rarely available. Using our TCR-HLA associations, we trained a computational model to predict the HLA type of individuals from their TCR repertoire alone. We propose an iterative procedure to refine this model by using data from large cohorts of untyped individuals, by recursively typing them using the model itself. The resulting model shows good predictive performance, even for relatively rare HLA alleles.
SignalingProfiler2.0: a network-based approach to bridge multi-omics data to phenotypic hallmarks
Authors: Venafra Veronica , Sacco Francesca , Perfetto Livia 
Published: January 2024

AbstractUnraveling the cellular signaling remodeling upon a perturbation is a fundamental challenge to understand disease mechanisms and to identify potential drug targets. In this pursuit, computational tools that generate mechanistic hypotheses from multi-omics data have invaluable potential. Here we presentSignalingProfiler2.0, a multi-step pipeline to systematically derive context-specific signaling models by integrating proteogenomic data with prior knowledge-causal networks. This is a freely accessible and flexible tool that incorporates statistical, footprint-based, and graph algorithms to accelerate the integration and interpretation of multi-omics data. Through benchmarking and rigorous parameter selection on a proof-of-concept study, performed in metformin-treated breast cancer cells, we demonstrate the tool’s ability to generate a hierarchical mechanistic network that recapitulates novel and known drug-perturbed signaling and phenotypic outcomes. In summary, SignalingProfiler2.0 addresses the emergent need to derive biologically relevant information from complex multi-omics data by extracting interpretable networks.
Hexose transporters CsHT3/16 involved in post-phloem transport and affected cucumber fruit development
Authors: Cheng Jintao , Wen Suying , Li Kexin , Zhou Yixuan , Zhu Mengtian , Neuhaus H. Ekkehard , Bie Zhilong 
Published: January 2024

AbstractHexoses are crucial for plant growth and fruit development. However, the role of hexose transporters in post-phloem sugar transport and maintenance of cellular sugar homeostasis in rapidly growing fruits, such as cucumber, is not yet fully understood. To clarify the impact of hexose transporters in cucumber fruits, we conducted systematic analyses of their tissue expression, localization, transport characteristics and physiological functions. The study revealed thatCsHT3,CsHT12 andCsHT16 are the primary hexose transporter genes expressed in cucumber fruit. During the ovary and young fruit stages,CsHT3 andCsHT16 were located in the SE/CC system, but as the cucumber fruit developed and expanded, both transporters shifted to phloem parenchyma cells. The knock-out mutants ofCsHT16display shorter fruits with a larger circumference, likely due to impaired homeostasis of sugars and hormones. Simultaneously reducing the expression ofCsHT3,CsHT12andCsHT16leads to decreased fruit size. Conversely, overexpression ofCsHT3results in increased fruit size and higher fruit sugar levels. Our data suggest thatCsHT16 plays an important role in maintaining sugar homeostasis to shape the fruit, whileCsHT3,CsHT12 andCsHT16 together determine the carbohydrates requirement of the enlarged cucumber fruit.
Performance of GPT-4V(ision) in Ophthalmology: Use of Images in Clinical Questions
Authors: Tomita Kosei , Nishida Takashi , Kitaguchi Yoshiyuki , Miyake Masahiro , Kitazawa Koji 
Published: January 2024

AbstractBackground/aimsTo compare the diagnostic accuracy of Generative Pre-trained Transformer with Vision (GPT)-4 and GPT-4 with Vision (GPT-4V) for clinical questions in ophthalmology.MethodsThe questions were collected from the “Diagnosis This” section on the American Academy of Ophthalmology website. We tested 580 questions and presented GPT-4V with the same questions under two conditions: 1) multimodal model, incorporating both the question text and associated images, and 2) text-only model. We then compared the difference in accuracy between the two conditions using the chi-square test. The percentage of general correct answers was also collected from the website.ResultsThe GPT-4V model demonstrated higher accuracy with images (71.7%) than without images (66.7%, p<0.001). Both GPT-4 models showed higher accuracy than the general correct answers on the website [64.6 (95%CI, 62.9 to 66.3)].ConclusionsThe addition of information from images enhances the performance of GPT-4V in diagnosing clinical questions in ophthalmology. This suggests that integrating multimodal data could be crucial in developing more effective and reliable diagnostic tools in medical fields.SYNOPSISThe study compared the diagnostic accuracy of GPT-4 and GPT-4 with Vision for clinical questions in ophthalmology, finding that the performance improved when it analyzed both text and images.WHAT IS ALREADY KNOWN ON THIS TOPICText-based large language models (LLMs) have demonstrated significant potential in enhancing medical interpretation and diagnosis. Generative Pretrained Transformer 4 with Vision (GPT-4V) can address image-related questions, but the use of GPT-4V in ophthalmology has not yet been validated.WHAT THIS STUDY ADDSOur study reports the answer accuracy on ‘Diagnose This,’ provided by the American Academy of Ophthalmology, using GPT-4V. The integration of image data with GPT-4V enhances diagnostic accuracy in addressing ophthalmic clinical questions.HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYOur study indicates that combining image data with GPT-4 can enhance diagnostic accuracy in ophthalmic clinical questions. The development of LLMs trained on medical-specific datasets could further increase accuracy, advancing towards practical clinical applications.
Limited genomic signatures of population collapse in the critically endangered black abalone (Haliotis cracherodii)
Authors: Wooldridge Brock , Orland Chloé , Enbody Erik , Escalona Merly , Mirchandani Cade , Corbett-Detig Russell , Kapp Joshua D. , Fletcher Nathaniel , Ammann Karah , Raimondi Peter , Shapiro Beth 
Published: January 2024

AbstractThe black abalone,Haliotis cracherodii, is a large, long-lived marine mollusc that inhabits rocky intertidal habitats along the coast of California and Mexico. In 1985, populations were impacted by a bacterial disease known as withering syndrome (WS) that wiped out >90% of individuals, leading to the species’ designation as critically endangered. Current conservation strategies include restoring diminished populations by translocating healthy individuals. However, population collapse on this scale may have dramatically lowered genetic diversity and strengthened geographic differentiation, making translocation-based recovery contentious. Additionally, the current prevalence of WS is unknown. To address these uncertainties, we sequenced and analyzed the genomes of 133 black abalone individuals from across their present range. We observed no spatial genetic structure among black abalone, with the exception of a single chromosomal inversion that increases in frequency with latitude. Genetic divergence between sites is minimal, and does not scale with either geographic distance or environmental dissimilarity. Genetic diversity appears uniformly high across the range. Despite this, however, demographic inference confirms a severe population bottleneck beginning around the time of WS onset, highlighting the temporal offset that may occur between a population collapse and its potential impact on genetic diversity. Finally, we find the bacterial agent of WS is equally present across the sampled range, but only in 10% of individuals. The lack of genetic structure, uniform diversity, and prevalence of WS bacteria indicates that translocation could be a valid and low-risk means of population restoration for black abalone species’ recovery.
Prolactin-mediates a lactation-induced suppression of arcuate kisspeptin neuronal activity necessary for lactational infertility in mice
Authors: Hackwell Eleni C.R. , Ladyman Sharon R. , Clarkson Jenny , McQuillan H. James , Boehm Ulrich , Herbison Allan E. , Brown Rosemary S.E. , Grattan David R. 
Published: January 2024

AbstractThe specific role that prolactin plays in lactational infertility, as distinct from other suckling or metabolic cues, remains unresolved. Here, deletion of the prolactin receptor (Prlr) from forebrain neurons or arcuate kisspeptin neurons resulted in failure to maintain normal lactation-induced suppression of estrous cycles. Kisspeptin immunoreactivity and pulsatile LH secretion were increased in these mice, even in the presence of ongoing suckling stimulation and lactation. GCaMP fibre photometry of arcuate kisspeptin neurons revealed that the normal episodic activity of these neurons is rapidly suppressed in pregnancy and this was maintained throughout early lactation. Deletion of Prlr from arcuate kisspeptin neurons resulted in early reactivation of episodic activity of kisspeptin neurons prior to a premature return of reproductive cycles in early lactation. These observations show dynamic variation in arcuate kisspeptin neuronal activity associated with the hormonal changes of pregnancy and lactation, and provide direct evidence that prolactin action on arcuate kisspeptin neurons is necessary for suppressing fertility during lactation in mice.
Islands of genomic stability in the face of genetically unstable metastatic cancer
Authors: Bowland Kirsten , Lai Jiaying , Skaist Alyza , Zhang Yan , Teh Selina Shiqing K , Roberts Nicholas J. , Thompson Elizabeth , Wheelan Sarah J. , Hruban Ralph H. , Karchin Rachel , Iacobuzio-Donahue Christine A. , Eshleman James R. 
Published: January 2024

AbstractIntroductionMetastatic cancer affects millions of people worldwide annually and is the leading cause of cancer-related deaths. Most patients with metastatic disease are not eligible for surgical resection, and current therapeutic regimens have varying success rates, some with 5-year survival rates below 5%. Here we test the hypothesis that metastatic cancer can be genetically targeted by exploiting single base substitution mutations unique to individual cells that occur as part of normal aging prior to transformation. These mutations are targetable because ∼10% of them form novel tumor-specific “NGG” protospacer adjacent motif (PAM) sites targetable by CRISPR-Cas9.MethodsWhole genome sequencing was performed on five rapid autopsy cases of patient-matched primary tumor, normal and metastatic tissue from pancreatic ductal adenocarcinoma decedents. CRISPR-Cas9 PAM targets were determined by bioinformatic tumor-normal subtraction for each patient and verified in metastatic samples by high-depth capture-based sequencing.ResultsWe found that 90% of PAM targets were maintained between primary carcinomas and metastases overall. We identified rules that predict PAM loss or retention, where PAMs located in heterozygous regions in the primary tumor can be lost in metastases (private LOH), but PAMs occurring in regions of loss of heterozygosity (LOH) in the primary tumor were universally conserved in metastases.ConclusionsRegions of truncal LOH are strongly retained in the presence of genetic instability, and therefore represent genetic vulnerabilities in pancreatic adenocarcinomas. A CRISPR-based gene therapy approach targeting these regions may be a novel way to genetically target metastatic cancer.