bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of Machine Perfusion in the United States Increases Organ Utilization and Improves DCD Graft Survival in Liver Transplantation
Authors: Wisel Steven A. , Steggerda Justin A. , Kim Irene K.
Published: November 2024

Background.

Adoption of machine perfusion (MP) technology has rapidly expanded in liver transplantation without real-world data on utilization and outcomes, which are critical to understand the appropriate application of MP technology.

Methods.

The Organ Procurement and Transplant Network/Standard Transplant Analysis and Research database was used to identify all deceased donor livers procured with intent for transplant between October 27, 2015 (date of first recorded MP) and June 30, 2023 (n = 67 795). Liver allografts were cohorted by donation after brain death (DBD; n = 59 957) or circulatory death (DCD; n = 7873) and analyzed by static cold storage (SCS) or MP preservation method. Donor demographics, organ utilization, and graft survival were evaluated.

Results.

By 2023, 12.5% of all livers and 37.2% of DCD livers underwent MP preservation (82.6% normothermic, 6.7% hypothermic, and 10.8% other/unknown). Compared with SCS, MP liver donors were older (DBD: 48 versus 40 y [P < 0.001]; DCD: 43 versus 38 y [P < 0.001]) with higher body mass index (DBD: 28.8 versus 26.9 kg/m2 [P < 0.001]; DCD: 27.7 versus 26.9 kg/m2 [P = 0.004]). Donor livers had similar levels of macrosteatosis (median 5%). Graft utilization was higher for MP than SCS after DBD (96.4% versus 93.0%, P < 0.001) and DCD (91.4% versus 70.3%, P < 0.001) donation. Graft survival was similar between MP and SCS livers from DBD donors (P = 0.516), whereas MP-preserved grafts had superior survival from DCD donors at 1 and 3 y posttransplant (P = 0.013 and 0.037). Patient survival was similar across all groups at 3 y (P = 0.322).

Conclusions.

The use of MP in liver transplantation increased rates of liver utilization and improved graft survival after DCD. Further monitoring of MP outcomes is required to understand long-term benefits.
Social and emotional self-perception in people with mild to moderate Alzheimer disease compared to caregiver’s perspective in Brazil
Authors: Rangel da Silva Rogéria Cristina , Neto José Pedro Simões , Belfort Tatiana , Dourado Marcia Cristina Nascimento
Published: November 2024

Introduction:

There was limited evidence on the ability of people with Alzheimer disease (AD) to perceive their own emotions. We aimed to compare socioemotional self-perception in persons with mild and moderate AD to their caregivers’ perspective.

Method:

Cross-sectional assessment of people with mild (n=102) and moderate (n=59) AD and caregivers. Each participant and their caregivers completed the socioemotional questionnaire (SEQ); a 30-item rating scale assessing five dimensions of socioemotional cognition (empathy, emotion recognition, social conformity, antisocial behavior, sociability). We evaluated global cognition, awareness of disease, dementia severity, functionality, neuropsychiatric symptoms, and caregiver burden.

Results:

Participants in the mild and moderate groups showed a similar pattern of socioemotional self-perception. They differed in the anger domain of the emotion recognition subscale, in the antisocial behavior dimension, and in the sociability subscale. In contrast, the caregivers’ perspective of people with mild and moderate AD showed a significant difference in the emotion recognition domain for fear, disgust, and sadness. There were also significant differences in the empathy subscale for disgust and in the sociability subscale. Cognition was correlated with self-reported reduced perception in social conformity, antisocial behavior, and sociability. Awareness was correlated with emotion recognition, antisocial behavior, and sociability. Neuropsychiatric symptoms were correlated with empathy, emotion recognition, and social conformity.

Conclusions:

Significant differences were found between caregivers’ perspectives of socioemotional functioning in people with mild and moderate AD. Meanwhile, there were minimal differences in self-perception between the mild and moderate groups.
Campylobacter fetus subspecies fetus; an unforeseen cause of abortion in Regional Australia.
Authors: Owusu-Ansa Immanuella , Ramadas Manjeera , Jacob Nikhitha , Ayeni Femi E.
Published: November 2024

Campylobacter fetus (C.fetus), a gram-negative bacterium, is an established cause of abortion and infertility in cattle, sheep and goats. Human infections have been rarely reported. In contrast to TORCH infections, this campylobacter species is hardly recognised as a cause of abortion in humans. Since 1947 after the first case report in France, there have only been 11 reported cases in pregnant women worldwide and no published reports in Australia, pregnant or otherwise. In this study, we compare our case to the first reported infection of C.fetus in 1947 to raise awareness and educate doctors and midwives, subsequently impacting prenatal and antenatal counselling in these regions.
devider: long-read reconstruction of many diverse haplotypes
Authors: Shaw Jim , Boucher Christina , Yu Yun William , Noyes Noelle , Li Heng
Published: November 2024

Reconstructing haplotypes is important when sequencing a mixture of similar sequences. Long-read sequencing can connect distant alleles to disentangle similar haplotypes, but handling se-quencing errors requires specialized techniques. We presentdevider, an algorithm for haplotyping small sequences—such as viruses or genes—from long-read sequencing.devideruses a positional de Bruijn graph with sequence-to-graph alignment on an alphabet of informative alleles to provide a fast assembly-inspired approach compatible with various long-read sequencing technologies. On a synthetic Nanopore dataset containing seven HIV strains,deviderrecovered 97% of the haplotype content compared to 86% for the next best method while taking < 4 minutes and 1 GB of memory for > 8000× coverage. Benchmarking on synthetic mixtures of antimicrobial resistance (AMR) genes showed thatdeviderrecovered 83% of haplotypes, 23 percentage points higher than the next best method. On real PacBio and Nanopore datasets,deviderrecapitulates previously known results in seconds, disentan-gling a bacterial community with > 10 strains and an HIV-1 co-infection dataset. We useddeviderto investigate the within-host diversity of a long-read bovine gut metagenome enriched for AMR genes, discovering 13 distinct haplotypes for a tet(Q) tetracycline resistance gene with > 18, 000× coverage and 6 haplotypes for a CfxA2 beta-lactamase gene. We found clear recombination blocks for these AMR gene haplotypes, showcasingdevider’s ability to unveil ecological signals for heterogeneous mixtures.
Machine learning reveals novel targets for both glioblastoma and osteosarcoma
Authors: Li Nan , Ward Max , Bashir Muniba , Cao Yunpeng , Datta Amitava , Li Zhaoyu , Zhang Shuang
Published: November 2024

Glioblastoma and osteosarcoma originate from the same lineage, yet patients with these two tumour types show significant differences in survival outcomes. Transcriptomic analysis comparing these tumours reveals that over 65% genes show similar expression patterns. Principal component analysis further demonstrates substantial similarities between these two tumour types, albeit with discernible differences. Deep learning analysis employing an autoencoder unveils nuanced distinctions and similarities of these two tumours at a high resolution. A classification model, leveraging gradient boosting with eXtreme Gradient Boosting (XGBoost), achieves high accuracy in distinguishing between these two tumour types. Identification of key contributors to the model’s performance is facilitated by SHapley Additive exPlanations (SHAP), yielding two lists of top target genes with and without considering gender. Notably, these SHAP targets tend to cluster within one or two networks of signalling pathways. Remarkably, gene expression levels of many of these SHAP targets alone can recapitulate survival differences solely based on clinical data between glioblastoma and osteosarcoma patients. Of particular interest, C2ORF72 emerges as a common target from both lists, representing an uncharacterised protein with promising potential as a novel target for diagnostic, prognostic, and therapeutic target for both glioblastoma and osteosarcoma.
In vivoengineered quadrivalent CAR-macrophages break tumor barrier, remodel TME and overcome tumor heterogeneity through antigen spreading
Authors: Zhang Shaolong , Lu Hengxing , Zhang Hailing , Ding Xizhong , Wu Qixin , Lei Anhua , Kong Na , Zhang Jin
Published: November 2024

CAR-macrophages have shown promising prospect in treating solid tumors.Ex vivoengineered CAR-macrophages face the challenge of low transfection efficiency, long preparation cycle, and limited cell number. Here, we designed two novel CAR molecules, GPC3-CAR-Super IL-2 and FAP-CAR-△TGFβRII from the perspective of targeting tumor cells and improving tumor microenvironment, and generated quadrivalent CAR-macrophagesin vivofor treating solid tumors by the LNP-mRNA system. We found thatin vivoengineered quadrivalent CAR-macrophages can strongly activate tumor immunity and achieve complete tumor regression without significant side effects. Mechanically,in vivoengineered quadrivalent CAR-macrophages broke down physical barriers around the tumor constructed by CAFs and significantly promoted infiltration and expansion of CD8+T cells. Moreover, the transiently formed CAR-macrophagesin vivoare sufficient to form long-lasting T cell memory which can effectively prevent tumor recurrence. Most importantly,in vivoengineered CAR-macrophages also stimulated T cell memory against antigen-negative tumor cells through antigen spreading, which might effectively prevent the immune escape of heterogeneous tumor cells. Overall, we developed a platform ofin vivoCAR-macrophages with dual roles as a tumor-killing effector cell and a recurrence-preventing vaccine.
Identifying parsimonious pathways of accumulation and convergent evolution from binary data
Authors: Giannakis Konstantinos , Aga Olav N. L. , Moen Marcus T. , Drange Pål G. , Johnston Iain G.
Published: November 2024

How stereotypical, and hence predictable, are evolutionary and accumulation dynamics? Here we consider processes – from genome evolution to cancer progression – involving the irreversible accumulation of binary features (characters), which can be modelled as Markov processes on a hypercubic transition network. We seek subgraphs of such networks that can generate a given set of paired before-after observations and minimize a topological cost function, involving criteria on out-branching which are interpretable in terms of biological parsimony. A transition network supporting a single, deterministic dynamic pathway is maximally simple and lowest cost, and branches (corresponding to possibly different next steps) increase cost, particularly if these branches are “deep”, occurring at early stages in the dynamics. In this sense, the lowest-cost subgraph measures how stereotypical the evolutionary or accumulation process is, and also identifies good start points for likelihood-based inference. The problem is solvable in polynomial time for cross-sectional observations by building on an existing method due to Gutin, and we provide a polynomial-time estimate in the more general case of pairs of observed states. We use this approach to define a “stereotypy index” reflecting the extent of evolutionary predictability. We demonstrate use cases in the evolution of antimicrobial resistance, organelle genomes, and cancer progression, and provide a software implementation athttps://github.com/StochasticBiology/hyperDAGs.
Canadian science graduate stipends lie below the poverty line
Authors: Fraass Andrew Jeffrey , Bailey Thomas J , Karunakumar Kayona , Wishart Andrea E.
Published: November 2024

Despite the critical role of graduate students in the Canadian research ecosystem1, students report high levels of financial stress2. We collected graduate minimum stipends and tuition data from all university graduate programs in Canada in Ecological Sciences/Biology and Physics, along with cost of living measures for the cities in which they reside. This data is heterogeneous, complex, and in many cases simply not publicly available, making it challenging for potential graduate students to understand what support they should expect. We show Canadian minimum stipends are at values almost exclusively below the poverty threshold. Only two of 140 degree programs offered stipends which meet cost of living measures after subtracting tuition and fees. For graduate programs which offered a minimum guaranteed stipend, the average minimum domestic stipend is short ∼Can$9,468 (international ∼Can$16,899) of the poverty threshold after accounting for payment of tuition and fees. On average, approximately 34% of a minimum stipend is returned to the university by a domestic Canadian student and 78% (57% median) by an international student, though there are important caveats with the international student comparison. While international comparison is difficult, the highest Canadian minimum stipend is roughly equivalent or lower than the lowest stipend within the largest dataset of United States of America (US) Biology stipends3, and lower than the United Kingdom (UK) stipend. University endowment correlates with minimum stipend amount but intra- and inter-institutional differences suggest it is not solely institutional wealth which improves graduate pay. Canada is behind comparable countries in funding the next generation of scientists. Canadians who desire higher STEM education have three options: hope for significantly higher guaranteed support from a supervisor, department, or awards; incur substantial debts; or emigrate.
Molecular Simulations Meet Personalized Medicine. The Mechanism of Action of ClC-5 Antiporter and the Origin of Dent’s Disease
Authors: Macaluso Veronica , Pérez Carles , Soliva Robert , Westermaier Yvonne , Díaz Lucía , Wieczór Miłosz , Orozco Modesto
Published: November 2024

ClC-5 is a Cl−/H+ antiporter crucial for the homeostasis of the entire organism, and whose functional deficiencies cause pathologies such as Dent’s disease, a rare genetic disorder that can have lethal consequences. While the clinical aspects of the pathology are known, its molecular basis is elusive, which hampers the development of potential therapies. We present here a systematic study, where we explore the mechanism of transport of ClC-5, deciphering the choreography of structural changes required for the transport of chloride ions and protons in opposing directions. Once the mechanism is determined, we explore how the 523ΔVal deletion linked to Dent’s disease hampers the correct functioning of the transporter, despite having a very minor structural impact. Our study highlights how state-of-the-art simulation methods can provide information on the origin of rare diseases and serve as a tool in personalized medicine.
Benchmarking of T-Cell Receptor - Epitope Predictors with ePytope-TCR
Authors: Drost Felix , Chernysheva Anna , Albahah Mahmoud , Kocher Katharina , Schober Kilian , Schubert Benjamin
Published: November 2024

Understanding the recognition of disease-derived epitopes through T-cell receptors (TCRs) has the potential to serve as a stepping stone for the development of efficient immunotherapies and vaccines. While a plethora of sequence-based prediction methods for TCR-epitope binding exists, their available pre-trained models have not been comparatively evaluated on standardized datasets and evaluation settings. Furthermore, technical problems such as non-standardized input and output formats of these prediction tools hinder interoperability and broad usage in applied research. To alleviate these shortcomings, we introduce ePytope-TCR, an extension of the vaccine design and immuno-prediction framework ePytope. We integrated 18 TCR-epitope prediction methods into this common framework offering interoperable interfaces with standard TCR repertoire data formats. We showcase the applicability of ePytope-TCR by evaluating the performance of the prediction methods on two challenging datasets for annotating single-cell repertoires and predicting TCR cross-reactivity towards mutated epitopes. While novel predictors successfully predicted binding to frequently observed epitopes, all methods failed for less observed epitopes. Further, we detected a strong bias in the prediction scores between different epitope classes. We envision this benchmark to guide researchers in their choice of a predictor for a given setting. Further, we aspire to accelerate the development of novel prediction models by allowing fast benchmarking against existing approaches through common interfaces and defining standardized evaluation settings.
SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data
Authors: Uhl Mathieu , Navascués Miguel , Boitard Simon , Servin Bertrand
Published: November 2024

Genomic samples collected from a single population over several generations provide direct access to the genetic diversity changes occurring within a specific time period. This provides information about both demographic and adaptive processes acting on the population during that period. A common approach to analyze such data is to model observed allele counts in finite samples using a Hidden Markov model (HMM) where hidden states are true allele frequencies over time (i.e. a trajectory). The HMM framework allows to compute the full likelihood of the data, while accounting both for the stochastic evolution of population allele frequencies along time and for the noise arising from sampling a limited number of individuals at possibly spread out generations. Several such HMM methods have been proposed so far, differing mainly in the way they model the transition probabilities of the Markov chain. Following Paris et al. (2019a), we consider here the Beta with Spikes approximation, which avoids the computational issues associated to the Wright-Fisher model while still including fixation probabilities, in contrast to other standard approximations of this model like the Gaussian or Beta distributions. To facilitate the analysis and exploitation of genomic time series data, we present an improved version of Paris et al. (2019a) ‘s approach, denoted SelNeTime, whose computation time is drastically reduced and which accurately estimates effective population size in addition to the selection intensity at each locus. This method is implemented in a user friendly python package, which also allows to easily simulate genomic time series data under a user-defined evolutionary model and sampling design.
Ophiostomatoid fungi associated with bark beetles infestingPinus armandii, with characterizations of seven new species from China
Authors: Chen Minjie , Ran Yutong , Liu Congwang , Liu Kun , Lin Tong , Yin Mingliang
Published: November 2024

Ophiostomatoid fungi mainly refer to the order Ophiostomatales (Ascomycota), which are known to be symbiotic with bark beetles infesting pine trees. These fungi are primarily associated withDendroctonus armandiand other bark beetles, significantly impacting the local pinesPinus armandiiin western China. However, this fungal diversity must be further explored. This study aims to identify Ophiostomatoid fungi associated withP. armandiiin Ningshaan, Shaanxi Province. A total of 225 Ophiostomatalean isolates were obtained from 46 gallery samples, accounting for 77.6 % of the total number of isolated strains. Twenty species were identified based on the phylogenetic analyses of ITS, LSU, β-tubulin, and EF-1α, as well as morphological characteristics. These include seven new taxa,Ceratocystiopsis rugosa,Graphilbum prolificum,G. ramosus,Masuyamyces huoditangensis,Ophiostoma flavescens,O. lenta,O. mediotumida, and thirteen known species. This study laid a theoretical foundation for understanding the relationship between the beetles and the ophiostomatalean fungi in the Ningshan region, China.
Modeling Oncolytic Vaccinia Virus Therapy Highlights Neutrophil Impact on Tumor Suppression∗
Authors: Satani Sahaj , Dobrovolny Hana
Published: November 2024

Abstract

Oncolytic vaccinia viruses (OVVs) present a promising approach for melanoma treatment due to their ability to selectively infect and lyse tumor cells. In this study, we use an ordinary differential equation (ODE) model of tumor growth inhibited by OVV activity to parameterize previous research on the effect of neutrophil depletion in B16-F10 melanoma tumors in mice. We find that the data are best fit by a model that accounts for neutrophil-mediated viral clearance, and that neutrophil depletion provides a mechanism for enhanced OVV efficacy and tumor reduction. We also find that parameter estimates for the most effective OVV regime share characteristics, most notably a low viral clearance rate by neutrophils, that might explain the improved outcomes. Further studies examining the impact of neutrophil modulation across different tumor models may help elucidate the extent to which these findings generalize and inform the design of novel OVV-based cancer therapies.
JOnTADS: a unified caller for TADs and stripes in Hi-C data
Authors: Zeng Qiuhai , Xiang Guanjue , Zhang Yu , Hardison Ross C. , Li Qunhua
Published: November 2024

Topologically associating domains (TADs) and stripes are important architectural structures on Hi-C data that are important for gene regulation. We present Joint Optimized nested TADs and Stripes (JOn-TADS), a unified caller for TADs and stripes in Hi-C data. JOnTADS effectively identifies hierarchical TADs and stripes in population Hi-C and micro-C datasets, and hierarchical TADs in single-cell Hi-C data. It provides robust identifications aligned with known biology and effectively captures interaction frequency variations in contact maps across diverse contexts. When multiple samples are available, JOn-TADS leverages shared information across samples in TAD identification, reducing unwanted variation in TAD boundary identification while preserving biological differences. This approach enables robust identifications in single-cell Hi-C data, effectively addressing challenges posed by data sparsity. JOnTADS is computationally efficient and requires minimal user tuning.
CosinorTest: An R Shiny App for Cosinor-model-based circadian and differential analysis in transcriptomic applications
Authors: Ding Haocheng , Zhang Yutao , Meng Lingsong , Xing Chengguo , Esser Karyn A. , Huo Zhiguang
Published: November 2024

‘CosinorTest’ application is an interactive R Shiny tool designed to facilitate circadian and differential circadian analysis with transcriptomic data using Cosinor-model-based methods. This novel application integrates multiple major statistical algorithms to identify circadian rhythmicity in gene expression data and enables the comparison of differential circadian patterns between two experimental conditions. Key features of the ‘CosinorTest’ app include circadian rhythmicity detection, differential patterns assessment, circadian and differential analyses with repeated measurement, and interactive data visualization, all contributing to a comprehensive understanding of underlying biological mechanisms. As the application doing all comprehensive circadian analysis using the Cosinor model, the ‘CosinorTest’ app fills a crucial gap in the field of circadian biology and transcriptomics, providing a powerful and user-friendly platform for researchers, especially those without profound programming skills to explore the circadian gene expression regulation, and further advance circadian research.

Availability and implementation

CosinorTest is freely available athttps://circadiananalysis.shinyapps.io/circadianapp/.

Contact

hading@augusta.edu

Supplementary information

Supplementary files are available atbioRχivonline.
ENaC contributes to macrophage dysfunction in cystic fibrosis
Authors: Moran John , Pugh Courtney , Brown Nevian , Thomas Ashley , Zhang Shuzhong , McCauley Emily , Cephas Amelia , Shrestha Chandra L. , Partida-Sanchez Santiago , Bai Shasha , Bruscia Emanuela , Kopp Benjamin T.
Published: November 2024

Background

Cystic fibrosis (CF) is a chronic systemic disease caused by dysfunctional or absent cystic fibrosis transmembrane conductance regulator (CFTR). CFTR is expressed in human immune cells and plays a role in regulating innate immunity both directly and indirectly. Besides CFTR, research indicates that the epithelial sodium channel (ENaC) also contributes to dysfunction in CF airway epithelial cells. However, the impact of non-CFTR ion channel dysfunction on CF immune responses is not yet fully understood. A precise understanding of how CF immune function is regulated by ion channels may allow antibiotic-and mutation-agnostic treatment approaches to chronic bacterial infection and inflammation. Therefore, we hypothesized that ENaC is aberrantly expressed in CF macrophages and directly contributes to impaired phagocytic and inflammatory functions.

Methods

ENaC expression was characterized in human immune cells isolated from CF and non-CF blood donors. Monocyte-derived macrophage (MDM) function and bacterial killing was tested in the setting of ENaC modulation.

Results

Baseline expression of ENaC in human CF MDMs, lymphocytes, and granulocytes was increased at both the transcript and protein level relative to non-CF controls and persisted after exposure to bacteria. Inhibition of CFTR in non-CF MDMs resulted in ENaC overexpression.

CFTR modulator treatment reduced but did not eliminate ENaC overexpression in CF MDMs. Interestingly, ENaC inhibition with Amiloride increased CFTR expression. Amiloride-treated CF MDMs also showed normalized ROS production, improved autophagy, and decreased pro-inflammatory cytokine production. Finally, results from an ion channel microarray indicated that sodium channel expression in CF MDMs normalized after Amiloride treatment with minimal effect on other ion channels.

Discussion

ENaC is overexpressed in CF immune cells and is associated with abnormal macrophage function. ENaC modulation in immune cells is a novel potential therapeutic target for infection control in CF, either in combination with CFTR modulators, or as a sole agent for patients not currently eligible for CFTR modulators.
Backward collateral sensitivity can restore antibiotic susceptibility
Authors: Chowdhury Farhan R. , Findlay Brandon L.
Published: November 2024

The prevalence of antibiotic resistance continues to rise, rendering many valuable drugs ineffective. Antibiotic cycling regimens that incorporate collateral sensitivity (CS), the phenomenon where resistance to one antibiotic leads to hypersensitivity to another, are hypothesized to slow the evolution of antibiotic resistance. However, the repeatability of CS interactions and their ability to drive bacterial extinction and resensitizations remain unclear. In this study, we thoroughly investigate four drug pairs proposed for cycling regimens with experimental evolution. We find that reported pairwise CS interactions are not always robust, and even when they are, forward CS (where resistance to drug A leads to hypersensitivity to drug B) does not reliably reduce resistance or promote bacterial extinction. Instead, we find that if evolution of resistance to drug B in naive cells is associated with CS to drug A, a phenomenon we term backward CS, drug A-resistant cells can be rendered more sensitive to A again when resistance to B develops. We describe the mechanism of resistance disruption via backward CS in an aminoglycoside-β-lactam pair, where perturbation of the electron transport chain to inhibit aminoglycoside entry impairs β-lactam efflux. Overall, we highlight the importance of applying antibiotics in the correct order in cycling regimens and identify robust CS interactions that may be used to design treatment regimens less likely to lead to resistance evolution.TOC Graphic
Altered basal forebrain regulation of intrinsic brain networks in depressive and anxiety disorders
Authors: Jamieson Alec J. , Steward Trevor , Davey Christopher G , Ince Sevil , Agathos James A , Moffat Bradford A , Glarin Rebecca K , Felmingham Kim L , Harrison Ben J
Published: November 2024

Altered connectivity both within and between the default mode and salience networks have been observed across depressive and anxiety disorders. Recent work has highlighted the importance of subcortical regions, including subdivisions of the basal forebrain, in coordinating the activity of these networks. However, the precise influence of basal forebrain subregions on intrinsic networks across these disorders remains unknown. Using ultra-high field (7-Tesla) functional magnetic resonance imaging, we examined the resting-state effective connectivity of three basal forebrain subregions in a transdiagnostic sample of 70 individuals with mental health conditions, predominantly depressive and anxiety disorders, compared to 77 healthy controls. We explored connectivity between these subregions and regions of the salience network (anterior insula and dorsal anterior cingulate) and default mode network (ventromedial prefrontal cortex, posterior cingulate cortex, and inferior parietal lobule). Clinical participants showed increased inhibitory connectivity from the nucleus basalis of Meynert to regions of the default mode network and dorsal anterior cingulate. Increased inhibitory connectivity was also observed from the ventral pallidum to regions of the posterior default mode network. These transdiagnostic changes in the basal forebrain’s regulation of large-scale cortical networks across may suggest novel mechanistic avenues for pharmacological treatments, including cholinergic system targeting.
RNApysoforms: Fast rendering interactive visualization of RNA isoform structure and expression in Python
Authors: Heberle Bernardo Aguzzoli , Page Madeline L. , Gustavsson Emil K. , Ryten Mina , Ebbert Mark T. W.
Published: November 2024

Motivation

Alternative splicing generates multiple RNA isoforms from a single gene, enriching genetic diversity and impacting gene function. Effective visualization of these isoforms and their expression patterns is crucial but challenging due to limitations in existing tools. Traditional genome browsers lack programmability, while other tools offer limited customization, produce static plots, or cannot simultaneously display structures and expression levels. RNApysoforms was developed to address these gaps by providing a Python-based package that enables concurrent visualization of RNA isoform structures and expression data. Leveraging plotly and polars libraries, it offers an interactive, customizable, and faster-rendering framework suitable for web applications, enhancing the analysis and dissemination of RNA isoform research.

Availability and implementation

RNApysoforms is a Python package available at (https://github.com/UK-SBCoA-EbbertLab/RNApysoforms) via an open-source MIT license. It can be easily installed using the piip package installer for Python. Thorough documentation and usage vignettes are available at:https://rna-pysoforms.readthedocs.io/en/latest/.
The genome of the sapphire damselfishChrysiptera cyanea: a new resource to support further investigation of the evolution of Pomacentrids
Authors: Gairin Emma , Miura Saori , Takamiyagi Hiroki , Herrera Marcela , Laudet Vincent
Published: November 2024

The number of high-quality genomes is rapidly growing across taxa. However, it remains limited for coral reef fish of the Pomacentrid family, with most research focused on anemonefish. Here, we present the first assembly for a Pomacentrid of the genusChrysiptera. Using PacBio long-read sequencing with a coverage of 94.5x, the genome of the Sapphire Devil,Chrysiptera cyaneawas assembled and annotated. The final assembly consisted of 896 Mb pairs across 91 contigs, with a BUSCO completeness of 97.6%. 28,173 genes were identified. Comparative analyses with available chromosome-scale assemblies for related species identified contig-chromosome correspondences. This genome will be useful to use as a comparison to study the specific adaptations linked to symbiosis life of the closely related anemonefish. Furthermore, this species is present in most tropical coastal areas in the Indo-West Pacific and could become a model for environmental monitoring. This work will allow to expand coral reef research efforts and highlights the power of long-read assemblies to retrieve high quality genomes.
GCTransNet: 3D mitochondrial instance segmentation based on Global Context Vision Transformers
Authors: Chen Chaoyi , Yan Yidan , Wu Jingpeng , Gan Wen-Biao
Published: November 2024

Mitochondria are double membrane-bound organelles essential for generating energy in eukaryotic cells. Mitochondria can be readily visualized in 3D using Volume Electron Microscopy (vEM), and accurate image segmentation is vital for quantitative analysis of mitochondrial morphology and function. To address the challenge of segmenting small mitochondrial compartments in vEM images, we propose an automated mitochondrial segmentation method called GCTransNet. This method employs grayscale migration technology to preprocess images, effectively reducing intensity distribution differences across EM images. By utilizing 3D Global Context Vision Transformers (GC-ViT) combined with global context self-attention modules and local self-attention modules, GCTransNet precisely models long-range and short-range spatial interactions. The long-range interactions enable the model to capture the global structural relationships within the mitochondrial segmentation network, while the short-range interactions refine local details and boundaries. In our approach, the encoder of the 3D U-Net network, a classical multi-scale learning architecture that retains high-resolution features through skip connections and combines multi-scale features for precise segmentation, is replaced by a 3D GC-ViT. The GC-ViT leverages shifted window-based self-attention, capturing long-range dependencies and offering improved segmentation accuracy compared to traditional U-Net encoders. In the MitoEM mitochondrial segmentation challenge, GCTransNet achieved state-of-the-art results, demonstrating its superiority in automated mitochondrial segmentation. The code and its documentation are publicly available athttps://github.com/GanLab123/GCTransNet.
Amyloid signaling in antiphage defense
Authors: Ibarlosa Léa , Dheur Sonia , Sanchez Corinne , Deb Seamoon , Granger-Farbos Alexandra , Coustou Virginie , Berbon Mélanie , Massoni Aurélie , Salin Bénédicte , Blancard Corinne , Saragaglia Claire , Tene Xavière Menatong , Dufour Nicolas , Rossier Ombeline , Habenstein Birgit , Debarbieux Laurent , Kauffmann Brice , Loquet Antoine , Saupe Sven J.
Published: November 2024

Immune regulated cell death (RCD) is a defense strategy common to different domains of life involving purposeful sacrifice of infected cells. In animals and fungi, functional amyloids play a role in the control of RCD as molecular switches activating key cell death effectors, rather than causing direct toxicity as seen with pathological amyloids. Here, we describe a novel amyloid-based signal transduction mechanism in an antiphage defense system inEscherichia coli. This antiphage abortive infection (Abi) system is mediated by two proteins, Bab and Agp which share a common amyloid motif and are encoded by adjacent genes. Upon phage infection, Agp activates Bab through amyloid signaling, leading to cell death. We determined the structure of the Bab cell death execution domain, which is distantly related to pore-forming domains present in fungi, animals and plants. We show that Bab and the fungal HET-S amyloid-controlled cell death execution protein are functionally interchangeable in their respective roles in antiphage defense and allorecognition. These findings add antiphage defense to the functional repertoire of amyloids.
Epigenetic potential and dispersal propensity in a free-living songbird: a spatial and temporal approach
Authors: Jimeno Blanca , Tangili Marianthi , Domínguez Julio C. , Canal David , Camacho Carlos , Potti Jaime , García Jesús T. , Martínez-Padilla Jesús , Ravinet Mark
Published: November 2024

Natal dispersal is a key life-history trait determining fitness and driving population dynamics, genetic structure and species distributions. Despite existing evidence that not all phenotypes are equally likely to successfully establish in new areas, the mechanistic underpinnings of natal dispersal remain poorly understood. The propensity to disperse into a new environment can be favored by a high degree of phenotypic plasticity which facilitates local adaptation and may be achieved via epigenetic mechanisms, which modify gene expression and enable rapid phenotypic changes. Epigenetic processes occur in particular genomic regions - DNA methylation on CpG sites in vertebrates -, and thus individual genomes may differ in their capacity to be modified epigenetically. This “Epigenetic potential” (EP) may represent the range of phenotypic plasticity attainable by an individual, and be a key determinant of successful settlement in novel areas. We investigated the association between EP – quantified as the number of genome-wide CpG variants – and natal dispersal propensity in a long-term study population of Pied flycatchers (Ficedula hypoleuca) monitored since colonization of a new habitat 35 years ago. We tested this association at three levels, comparing EP between: i) individuals dispersing between and within habitat patches; ii) immigrants to the population and locally-born individuals; and iii) individuals from first (comprising colonizers or their direct descendants) and later generations of the population (consisting of locally-born individuals, which did not show natal dispersal). Results show a significant, positive association between EP and dispersal propensity in comparisons i) and iii), but not ii). Furthermore, CpG variants were non-randomly distributed across the genome, suggesting species- and/or population-specific CpGs being more frequent in promoters and exons. Our findings point to EP playing a role in dispersal propensity at spatial and temporal scales, supporting the idea that epigenetically-driven phenotypic plasticity facilitates dispersal and environmental coping in free-living birds.
Pancreatic changes in obese mice supplemented with vitamin D
Authors: da Rocha Guilherme , dos Santos Natália Pereira , Mendonça Juliana Cristina , Baptista Fassis Nathan Oscar , Calsa Bruno , Milanski Marciane , Corezola do Amaral Maria Esméria
Published: November 2024

This study investigates the impact of vitamin D supplementation on insulin secretion and pancreatic islet morphometry in a high-fat diet-induced obese mouse model. Male C57BL/6 mice were randomly assigned to two groups: a control group receiving a standard diet (C) and an obese group receiving a high-fat diet (H). After 12 weeks, the obese group was subdivided, with one subset continuing on the high-fat diet (H) and the other receiving vitamin D supplementation (HD) at 500 IU/kg via oral gavage for four weeks. Glucose tolerance tests, insulin sensitivity assessments, insulin secretion assays, and histological and immunohistochemical analyses for glucagon and PCNA were conducted. Vitamin D supplementation led to a reduction in fasting blood glucose levels and a significant increase in insulin secretion at 20 mM glucose, as indicated by an improved HOMA%B index, suggesting enhanced β-cell protection. Additionally, vitamin D treatment resulted in a β-cell percentage comparable to the control group and a notable increase in α-cell population relative to the untreated obese group. However, elevated circulating cholesterol levels were observed in both obese groups, with a significant rise in hepatic triglycerides in the vitamin D-treated group. These findings highlight the potential of vitamin D to improve pancreatic secretory function in obese mice.
Genetic Variability Analysis of Hot Pepper (Capsicum annuum.L) Landraces at Haramaya University, Eastern Ethiopia.
Authors: Sufiyan Abdurazak
Published: November 2024

Hot pepper is a globally important spice utilized for food flavoring, enhancement, and coloring, with a growing demand over time. In the 2022 cropping season, this study aimed to assess the genetic variability among 19 landrace genotypes and one improved hot pepper genotype under semi-irrigation conditions. Twelve quantitative parameters were evaluated using a randomized complete block design with three replications. Analysis of variance revealed highly significant differences (P less than or equal to 0.01) for all traits except days to harvest and fruit weight, which were non-significant. Coefficients of variation ranged from 2.92 for days to fifty percent flowering to 31.47 for number of fruits per plant, indicating substantial variability among accessions. Fruit length varied from 4.5cm (accession 229694) to 11.17cm (accession 229699), while fruit width ranged from 8.33cm to 31.4cm, and fruit weight from 11.25g to 24.88g. Accession 229697 exhibited the highest fruit number per plant (42.67), while M/fana showed the lowest (12.67), with a mean value of 23.64. Fruit yield per plot ranged from 0.26kg/plot (accession 229696) to 0.91kg/plot (accession 28337), with approximately 40% of genotypes surpassing the population mean (0.5935kg/plot). High phenotypic and genotypic coefficients of variation, along with high genetic advance and heritability, were observed for yield per plot, number of fruits per plant, and fruit width, suggesting potential for improvement through selection. Based on the study results, accession 28337 for yield per plot, accession 229697 for fruit number per plant, and accession 229695 for fruit width are recommended for future selection.
Unlocking the power of gene banks: diversity in base growth temperature provides opportunities for climate-smart agriculture
Authors: Gambart Clara , Wesemael Jelle Van , Swennen Rony , Tardieu François , Carpentier Sebastien
Published: November 2024

Implementation of context-specific solutions, including cultivation of varieties adapted to current and future climatic conditions, were found to be effective in establishing resilient, climate-smart agricultural systems. Gene banks play a pivotal role in this. However, a large fraction of the collections remains neither genotyped nor phenotyped. Hypothesising that significant genotypic diversity inMusatemperature responses exists, this study aimed to assess the diversity in the world’s largest banana gene bank in terms of base temperature (Tbase) and to evaluate its impact on plant performance in the East African highlands during a projected climate scenario. 116 gene bank accessions were evaluated in the BananaTainer, a tailor-made high throughput phenotyping installation. Plant growth was quantified in response to temperature and genotype-specific Tbasewere modelled. Growth response of two genotypes was validated under greenhouse conditions, and gas exchange capacity measurements were made. The model revealed genotype-specific Tbase, with 30 % of the accessions showing a Tbasebelow the reference of 14 °C. The Mutika/Lujugira subgroup, endemic to the East African highlands, appeared to display a low Tbase, although within subgroup diversity was revealed. Greenhouse validation further showed low T sensitivity/tolerance to be related to the photosynthetic capacity. This study, therefore, significantly advances the debate of within species diversity in temperature growth responses, while at the same time unlocking the power of gene banks. Moreover, we provide a high throughput method to reveal the existing genotypic diversity in temperature responses, paving the way for future research to establish climate-smart varieties.
Neural Representation of Time across Complementary Reference Frames
Authors: Xu Yangwen , Sartorato Nicola , Dutriaux Léo , Bottini Roberto
Published: November 2024

Humans conceptualize time in terms of space, allowing flexible time construals from various perspectives. We can travel internally through a timeline to remember the past and imagine the future (i.e., mental time travel) or watch from an external standpoint to have a panoramic view of history (i.e., mental time watching). However, the neural mechanisms that support these flexible temporal construals remain unclear. To investigate this, we asked participants to learn a fictional religious ritual of 15 events. During fMRI scanning, they were guided to consider the event series from either an internal or external perspective in different tasks. Behavioral results confirmed the success of our manipulation, showing the expected symbolic distance effect in the internal-perspective task and the reverse effect in the external-perspective task. We found that the activation level in the posterior partial cortex correlated positively with sequential distance in the external-perspective task but negatively in the internal-perspective task. In contrast, the activation level in the anterior hippocampus positively correlated with sequential distance regardless of the observer’s perspectives. These results suggest that the hippocampus stores the memory of the event sequences allocentrically in a perspective-agnostic manner. Conversely, the posterior parietal cortex retrieves event sequences egocentrically from the optimal perspective for the current task context. Such complementary allocentric and egocentric representations support both the stability of memory storage and the flexibility of time construals.
Gene-scalein vitroreconstitution reveals histone acetylation directly controls chromatin architecture
Authors: Fukai Yohsuke T. , Kujirai Tomoya , Wakamori Masatoshi , Kanamura Setsuko , Yamauchi Lisa , Zeraati Somayeh , Tanegashima Chiharu , Kadota Mitsutaka , Kurumizaka Hitoshi , Umehara Takashi , Kawaguchi Kyogo
Published: November 2024

Chromatin organization plays a crucial role in gene regulation [1, 2, 3], but disentangling the contributions of various epigenetic components to gene-scale chromatin structure remains challenging. Whilein vitrochromatin reconstitution enables controlled studies on the effect of bio-chemical factors on the structure, current methods are either limited to short arrays or lack control over histone modification patterns. Here we directly test how histone modification affects higher-order chromatin architecture by characterizing gene-scale reconstituted chromatin using single-molecule microscopy andin vitroHi-C. We reconstitute 20-kilobase chromatin arrays with histone modification patterns controlled at 12-nucleosome resolution, achieving complete assembly of 96 nucleosomes in the designed order as confirmed by atomic force microscopy and longread sequencing. Observing end-to-end fluctuations of the reconstituted arrays, we find that increasing the density of acetylated nucleosomes leads to larger structural fluctuations with longer relaxation times, consistent with the predictions of a polymer model with hydrodynamic interactions. We demonstrate throughin vitroHi-C how acetylation reduces contact frequency between nucleosomes and induces open conformations. In heterogeneously modified arrays, differential contact probabilities between acetylated and unmodified regions lead to distinct structural domains. The results establish the physical principles by which histone modifications directly modulate chromatin architecture through altered nucleosome-nucleosome interactions, providing a quantitative framework for understanding and engineering genome organization.