bluuebunny/crossref_metadata_2025 huggingface dataset:
A Multinational Cohort Study Examining Sex Differences in Excess Risk of Death With Graft Function After Kidney Transplant
Authors: Vinson Amanda Jean , Zhang Xun , Dahhou Mourad , Süsal Caner , Döhler Bernd , Sapir-Pichhadze Ruth , Cardinal Heloise , Melk Anette , Wong Germaine , Francis Anna , Pilmore Helen , Foster Bethany J.
Published: January 2024

Background.

Kidney transplant recipients show sex differences in excess overall mortality risk that vary by donor sex and recipient age. However, whether the excess risk of death with graft function (DWGF) differs by recipient sex is unknown.

Methods.

In this study, we combined data from 3 of the largest transplant registries worldwide (Scientific Registry of Transplant Recipient, Australia and New Zealand Dialysis and Transplant Registry, and Collaborative Transplant Study) using individual patient data meta-analysis to compare the excess risk of DWGF between male and female recipients of a first deceased donor kidney transplant (1988–2019), conditional on donor sex and recipient age.

Results.

Among 463 895 individuals examined, when the donor was male, female recipients aged 0 to 12 y experienced a higher excess risk of DWGF than male recipients (relative excess risk 1.68; 95% confidence interval, 1.24-2.29); there were no significant differences in other age intervals or at any age when the donor was female. There was no statistically significant between-cohort heterogeneity.

Conclusions.

Given the lack of sex differences in the excess risk of DWGF (other than in prepubertal recipients of a male donor kidney) and the known greater excess overall mortality risk for female recipients compared with male recipients in the setting of a male donor, future study is required to characterize potential sex-specific causes of death after graft loss.
Delirium Severity and Physical Function in Hospitalized Persons Living With Dementia
Authors: Kuzmik Ashley , Boltz Marie , Resnick Barbara , McPherson Rachel , Rodriguez Marleny , Drazich Brittany F. , Galik Elizabeth
Published: January 2024

Objective:

This study investigated whether demographic characteristics (age, sex, and race) moderated delirium severity as a predictor of physical function in hospitalized persons living with dementia.

Methods:

The sample consisted of 351 patients enrolled in a randomized controlled trial (Function Focused Care for Acute Care Using the Evidence Integration Triangle). Preliminary analysis was conducted to assess the main effect, and multiple linear regression was used to examine the moderating effect of demographic characteristics between delirium severity and physical function.

Results:

Both age and sex were found to have significant moderating effects on the relationship between delirium severity and physical function (β = 2.22; P = 0.02 and β = 1.34; P = 0.04, respectively). Older adults aged 85 years or older with higher levels of delirium severity reported lower levels of physical function compared with older adults aged 65 to 84 years. Males with higher levels of delirium severity reported lower levels of physical function compared with females. Race did not significantly moderate the association between delirium severity and physical function (β = 0.22; P = 0.90).

Conclusions:

Our findings suggest that age and sex may have differential effects on physical function across different levels of delirium severity in hospitalized persons living with dementia.
The Technology in Caring Questionnaire
Authors: Kiselica Andrew M. , Lin Shayne S.H. , Ranum Rylea , Mikula Cynthia M. , Hermann Greta , Boone Anna , Scullin Michael , Mechanic-Hamilton Dawn , Wolf Timothy , Stevens Alan , Benge Jared F.
Published: January 2024

Objective:

We developed the Technology in Caring Questionnaire (TCQ) to assess the use of technology-based strategies by dementia caregivers.

Methods:

One hundred caregivers completed a survey that included TCQ items along with measures of technology proficiency and patient and caregiver-centered outcomes.

Results:

The final 34-item TCQ scale had adequate to excellent internal consistency (raw Cronbach alpha = 0.75; standardized Cronbach alpha = 0.95; Guttman lambda-6 = 0.97). TCQ scores demonstrated modest convergent associations with scores from measures of smartphone (r = 0.265, P < 0.01) and computer proficiency (r = 0.230, P < 0.05) but a strong association with overall technology experience scores (r = 0.578, P < 0.001). Elevated TCQ scores were associated with reduced informant-reported cognitive symptoms (B = −0.003, P < 0.05), increased ability of caregivers to find support and information (B = 0.03, P < 0.001), and increased direct care strain (B = 0.03, P < 0.05), after controlling for dementia severity and demographics.

Conclusion:

The TCQ has good psychometric properties for the assessment of technology-based care strategies among dementia caregivers. Findings imply that the use of technologies may aid in symptom management and finding support and information but may also increase caregiver strain.
Citizen Science Data on Urban Forageable Plants: A Case Study in Brazil
Authors: Soares Filipi Miranda , Pires LuÍs Ferreira , Garcia Maria Carolina , Coradin Lidio , Ghilardi-Lopes Natalia Pirani , Silva Rubens Rangel , de Carvalho Aline Martins , Gavai Anand , Bouzembrak Yamine , dos Santos Maculan Benildes Coura Moreira , Koffler Sheina , Montedo Uiara Bandineli , Drucker Debora Pignatari , Santiago Raquel , de Carvalho Maria Clara Peres , Silva Lima Ana Carolina da , Elias Gabriel Hillary Dandara , de França Stephanie Gabriele Mendonça , de Almeida Karoline Reis , dos Santos Bárbara Junqueira , Saraiva Antonio Mauro
Published: January 2024

This paper presents two key data sets derived from thePomar Urbanoproject. The first data set is a comprehensive catalog of edible fruit-bearing plant species, native or introduced in Brazil. The second data set, sourced from the iNaturalist platform, tracks the distribution and monitoring of these plants within urban landscapes across Brazil. The study encompasses data from all 27 Brazilian state capitals, focusing on the ten cities that contributed the most observations as of August 2023. The research emphasizes the significance of citizen science in urban biodiversity monitoring and its potential to contribute to various fields, including food and nutrition, creative industry, study of plant phenology, and machine learning applications. We expect the data sets to serve as a resource for further studies in urban foraging, food security, cultural ecosystem services, and environmental sustainability.
Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks
Authors: Deng Chao , Li Hong-Dong , Zhang Li-Shen , Liu Yi-Wei , Li Yaohang , Wang Jianxin
Published: January 2024

Motivation

Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited.

Results

Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes.

Availability

DISHyper is freely available for download athttps://github.com/genemine/DISHyper.

Contact

jxwang@mail.csu.edu.cn
Quantifying Unbiased Conformational Ensembles from Biased Simulations Using ShapeGMM
Authors: Sasmal Subarna , Pal Triasha , Hocky Glen M. , McCullagh Martin
Published: January 2024

Quantifying the conformational ensembles of biomolecules is fundamental to describing mechanisms of processes such as ligand binding and allosteric regulation. Accurate quantification of these ensembles remains a challenge for all but the simplest molecules. One such challenge is insufficient sampling which enhanced sampling approaches, such as metadynamics, were designed to overcome; however, the non-uniform frame weights that result from many of these approaches present an additional challenge to ensemble quantification techniques such as Markov State Modeling or structural clustering. Here, we present rigorous inclusion of non-uniform frame weights into a structural clustering method entitled shapeGMM. The shapeGMM method fits a Gaussian mixture model to particle positions, and here we advance that approach by incorporating nonuniform frame weights in the estimates of all parameters of the model. The resulting models are high dimensional probability densities for the unbiased systems from which we can compute important thermodynamic properties such as relative free energies and configurational entropy. The accuracy of this approach is demonstrated by the quantitative agreement between GMMs computed by Hamiltonian reweighting and direct simulation of a coarse-grained helix model system. Furthermore, the relative free energy computed from a high dimensional probability density of alanine dipeptide reweighted from a metadynamics simulation quantitatively reproduces the metadynamics free energy in the basins. Finally, the method identifies hidden structures along the actin globular to filamentous-like structural transition from a metadynamics simulation on a linear discriminant analysis coordinate trained on GMM states, demonstrating the broad applicability of combining our prior and new methods, and illustrating how structural clustering of biased data can lead to biophysical insight. Combined, these results demonstrate that frame-weighted shapeGMM is a powerful approach to quantify biomolecular ensembles from biased simulations.
Comprehensive epitope mutational scan database enables accurate T cell receptor cross-reactivity prediction
Authors: Banerjee Amitava , Pattinson David J , Wincek Cornelia L. , Bunk Paul , Axhemi Armend , Chapin Sarah R. , Navlakha Saket , Meyer Hannah V.
Published: January 2024

Predicting T cell receptor (TCR) activation is challenging due to the lack of both unbiased benchmarking datasets and computational methods that are sensitive to small mutations to a peptide. To address these challenges, we curated a comprehensive database, called BATCAVE, encompassing complete single amino acid mutational assays of more than 22,000 TCR-peptide pairs, centered around 25 immunogenic human and mouse epitopes, across both major histocompatibility complex classes, against 151 TCRs. We then present an interpretable Bayesian model, called BATMAN, that can predict the set of peptides that activates a TCR. We also developed an active learning version of BATMAN, which can efficiently learn the binding profile of a novel TCR by selecting an informative yet small number of peptides to assay. When validated on our database, BATMAN outperforms existing methods and reveals important biochemical predictors of TCR-peptide interactions. Finally, we demonstrate the broad applicability of BATMAN, including for predicting off-target effects for TCR-based therapies and polyclonal T cell responses.
Genetic network analysis uncovers spatial variation in diversity and connectivity of a species presenting a continuous distribution
Authors: Fournier Cory , Manseau Micheline , Redquest Bridget , Andrew Leon , Kelly Allicia , Hervieux Dave , Hegel Troy , Pittoello Gigi , Trim Vicki , Brannen Dennis , Wilson Paul
Published: January 2024

The conservation of genetic diversity and connectivity is essential for the long-term persistence and adaptive ability of a species. Recent calls have been made for the inclusion of genetic diversity and differentiation measures in the assessment, management, and conservation of species. However, the literature often lacks direction on how to do so for species with continuous distributions or no distinct breaks in genetic connectivity. There are many considerations to overcome when investigating genetic diversity and connectivity of such species. We combine multiple genetic network methodologies with more traditional population genetic analyses within a single framework to address the challenges of investigating population structure and quantifying variation in genetic diversity and connectivity of wide-ranging species with continuous distributions. We demonstrate the efficacy and applicability of our framework through a study on woodland caribou (Rangifer tarandus) occupying the boreal forest of Canada; a species of significant conservation concern. The dataset consisted of 4911 unique individuals genotyped at 9 microsatellite loci, which were subsequently partitioned into 103 spatial nodes to create a population-based genetic network. The Walktrap community detection algorithm was used to detect hierarchical population genetic structure within the study area and node-based network metrics such as mean inverse edge weight and clustering coefficient were used to quantify the variation in genetic connectivity across the range. Lastly, genetic diversity was assessed by calculating allelic richness and heterozygosity of the nodes making up the network. The community detection analysis identified two communities at the coarsest scale to nine communities at the optimal partition. A strong pattern of Isolation by Distance (IBD) was found across the range at multiple scales. Furthermore, signs of genetic erosion along the study area’s southern boundaries were depicted by nodes presenting low genetic diversity and low centrality values. These results are important to the species status assessments in providing previously unavailable information on connectivity and diversity within and beyond the current local population units used in management. Our approach to quantify the patterns and extent of connectivity across the boreal range is comprehensive and could easily be adapted to other species. The results are robust and provide a solid foundation for the continued monitoring and recovery of the species.
Mitochondrial uncoupler and retinoic acid synergistically induce differentiation and inhibit proliferation in neuroblastoma
Authors: Jiang Haowen , Tiche Sarah Jane , He Clifford JiaJun , Jedoui Mohamed , Forgo Balint , Zhao Meng , He Bo , Li Yang , Li Albert M. , Truong Anh T. , Ho Jestine , Simmermaker Cathyrin , Yang Yanan , Zhou Meng-Ning , Hu Zhen , Cuthbertson Daniel J. , Svensson Katrin J. , Hazard Florette K. , Shimada Hiroyuki , Chiu Bill , Ye Jiangbin
Published: January 2024

Neuroblastoma is a leading cause of death in childhood cancer cases. Unlike adult malignancies, which typically develop from aged cells through accumulated damage and mutagenesis, neuroblastoma originates from neural crest cells with disrupted differentiation. This distinct feature provides novel therapeutic opportunities beyond conventional cytotoxic methods. Previously, we reported that the mitochondrial uncoupler NEN (niclosamide ethanolamine) activated mitochondria respiration to reprogram the epigenome, promoting neuronal differentiation. In the current study, we further combine NEN with retinoic acid (RA) to promote neural differentiation bothin vitroandin vivo. The treatment increased the expression of RA signaling and neuron differentiation-related genes, resulting in a global shift in the transcriptome towards a more favorable prognosis. Overall, these results suggest that the combination of a mitochondrial uncoupler and the differentiation agent RA is a promising therapeutic strategy for neuroblastoma.
Right-to-Left Shunt-associated Brain Functional Changes in Migraine: Evidences from a Resting-state FMRI Study
Authors: Cao Wenfei , Jiao Lei , Zhou Huizhong , Zhong Jiaqi , Wang Nizhuan , Yang Jiajun
Published: January 2024

Background

Migraine, a neurological disorder under perpetual investigation, has an elusive etiology. An potential association with Right-to-Left Shunt (RLS) exists, yet the precise nature of this connection remains unclear. This study employs the resting-state functional magnetic resonance imaging (rs-fMRI) technique to examine brain functional differences between the migraine patients with and without RLS, aiming at exploring RLS associated alterations in functional segregation and integration.

Methods

This study included 32 migraine patients (14 patients with RLS and 18 without RLS), each undergoing rs-fMRI data acquisition. The amplitude of low-frequency fluctuation (ALFF) was employed to investigate functional segregation. Functional connectivity (FC) analysis was conducted to explore the functional integration across distinct brain regions. Graph theory-based network analysis was utilized to assess functional networks in migraine patients with RLS. Pearson correlation analysis further explored the relationship between RLS severity and various functional metrics..

Results

Compared with migraine patients without RLS, migraine patients with RLS exhibited a significant increase in the ALFF in the left middle occipital and superior occipital gyrus; As to FC, the reduced connectivity between the left rolandic operculum and the right middle cingulate gyrus was observed in migraine patients with RLS; Based on the brain networks analysis, migraine patients with RLS displayed higher values of the normalized clustering coefficient and greater betweenness centrality in specific regions, including the left precuneus, right insula, and right inferior temporal gyrus. Further, the study found positive correlations between ALFF values in the temporal lobes, thalamus, left middle occipital, and superior occipital gyrus and RLS severity. Conversely, negative correlations emerged between ALFF values in the right inferior frontal gyrus, middle frontal gyrus, and insula and RLS grading. Finally, the study identified a positive correlation between angular gyrus betweenness centrality and RLS severity.

Conclusion

RLS-associated brain functional alterations in migraine consisted of local brain regions, connectivity, and networks involved in pain conduction and regulation did exist in migraine with RLS.
High-performing Multi-task Model of Urinary Tract Dilation (UTD) Classification for Neonatal Ultrasound Reports Through Natural Language Processing
Authors: Hua Yining , Mukkamala Anudeep , Estrada Carlos , Li Michael Lingzhi , Wang Hsin-Hsiao Scott
Published: January 2024

Objective

The urinary tract dilation (UTD) classification system provides objective assessment relevant to hydronephrosis management for children. However, the lack of uniform language regarding UTD in radiology reports leads to significant difficulty in both clinical management and research. We seek to develop a unified multi-task/multi-class model that can effectively extract UTD components and classifications from early postnatal ultrasound (US) reports.

Methods

Radiology records from our institution were reviewed to identify infants aged 0-90 days undergoing early ultrasound for antenatal UTD. The report and images were reviewed by the study team to create the ground truth of UTD classification and components (primary outcome). Bio_ClinicalBERT, a variant of the Bidirectional Encoder Representations from Transformers (BERT) model, was used as the embedding layers of the classification model. The model was fine-tuned with 11 linear classification layers. All but the last BERT layer were frozen during the fine-tuning process. The model performance was evaluated with five-fold cross-validation with an 80:20 train-test ratio.

Results

2460 early (0-90 days) US reports were included. The five-fold cross-validated model performance is satisfactory (Weighted F1 > 0.9 for all UTD components). We report the weighted F1 scores, accuracies, and standard deviations for all 11 tasks and their average performance.

Conclusions

By applying deep state-of-the-art NLP neural networks, we developed a high-performing, efficient, and scalable solution to extract UTD components from unstructured ultrasound reports using one single multi-task model. This can potentially help standardize and facilitate large-scale computer vision research for pediatric hydronephrosis. Key Words: machine learning, efficiency, ambulatory care, forecasting
The Validation of Non-Invasive Pressure-Volume Loop Indices in Severe Aortic Stenosis
Authors: Aldalati Omar , Eskandari Mehdi , Ali Montasir H , Cabaco Rita , Byrne Jonathan , Monaghan Mark , Lukban Bobit , Kennedy Nicola , Shah Ajay , Dworakowski Rafal , MacCarthy Philip
Published: January 2024

Background

Studies utilizing invasive pressure-volume loops offer valuable insights into left ventricular (LV) contractility, yet their availability remains limited. Conversely, non-invasive indices are accessible and reproducible; however, their validation in aortic stenosis (AS) is lacking. We sought to validate the non-invasive indices of PVL studies in a group of symptomatic severe AS.

Methods

We recruited patients with symptomatic severe AS admitted for trans-catheter aortic valve replacement (TAVR) to undergo invasive PVL studies. Non-invasive PVL indices were measured with three-dimensional (3D) echocardiography with a pre-specified protocol. The agreement between invasive and non-invasive calculation methods were assessed.

Results

Eleven patients (11) were recruited for this pilot study. The non-invasive end-systolic pressure-volume relationship (ESPVR) Kelly’s method (Ees(sb)= 0.9 × systolic blood pressure/end-systolic volume (ESV)) had the best agreement with invasive ESPVR (limits of agreement - 1.7 to 2.1 with a percentage error of 24%, one sample T-test p =0.504). Systolic blood pressure, as measured by the brachial blood pressure cuff, had the best agreement with end-systolic pressure in severe aortic stenosis (limits of agreement −60 to 60 with a percentage error of 3%, one sample T-test p =0.959).

Conclusion

Measurement of the single-beat estimate of ventricular elastance (Ees(sb)) is possible in patients with severe aortic stenosis. Kelly’s method (Ees(sb)= 0.9 × SBP /ESV) has the best agreement with the invasive measurement of left ventricular elastance (Ees). Systolic blood pressure, as measured by the brachial blood pressure cuff, has the best agreement with end-systolic pressure in severe aortic stenosis.
Instability of excitatory synapses in experimental autoimmune encephalomyelitis and the outcome for excitatory circuit inputs to individual cortical neurons
Authors: Gillani Rebecca L. , Kironde Eseza N. , Whiteman Sara , Zwang Theodore J. , Bacskai Brian J.
Published: January 2024

Synapses are lost on a massive scale in the brain and spinal cord of people living with multiple sclerosis (PwMS), and this synaptic loss extends far beyond demyelinating lesions. Post-mortem studies show the long-term consequences of multiple sclerosis (MS) on synapses but do not inform on the early impacts of neuroinflammation on synapses that subsequently lead to synapse loss. How excitatory circuit inputs are altered across the dendritic tree of individual neurons under neuroinflammatory stress is not well understood. Here, we directly assessed the structural dynamics of labeled excitatory synapses in experimental autoimmune encephalomyelitis (EAE) as a model of immune-mediated cortical neuronal damage. We used in vivo two-photon imaging and a synthetic tissue-hydrogel super-resolution imaging technique to reveal the dynamics of excitatory synapses, map their location across the dendritic tree of individual neurons, and examine neurons at super-resolution for synaptic loss. We found that excitatory synapses are destabilized but not lost from dendritic spines in EAE, starting with the earliest imaging session before symptom onset. This led to dramatic changes in excitatory circuit inputs to individual cells. In EAE, stable synapses are replaced by synapses that appear or disappear across the imaging sessions or repeatedly change at the same location. These unstable excitatory inputs occur closer to one another in EAE than in healthy controls and are distributed across the dendritic tree. When imaged at super-resolution, we found that a small proportion of dendritic protrusions lost their presynapse and/or postsynapse. Our finding of diffuse destabilizing effects of neuroinflammation on excitatory synapses across cortical neurons may have significant functional consequences since normal dendritic spine dynamics and clustering are essential for learning and memory.
Reduced Capsaicin-Induced Mechanical Allodynia and Neuronal Responses in the DRG in the Presence ofShp1Overexpression
Authors: Vroman Robin , Ishihara Shingo , Fullam Spencer , Wood Matthew J. , Adamczyk Natalie S. , Lomeli Nolan , Malfait Fransiska , Malfait Anne-Marie , Miller Rachel E. , Markovics Adrienn
Published: January 2024

Transient Receptor Potential Vanilloid 1 (TRPV1) is a nonselective cation channel expressed by pain-sensing neurons and has been an attractive target for the development of drugs to treat pain. Recently, Src homology region 2 domain-containing phosphatase-1 (SHP-1) was shown to dephosphorylate TRPV1 in dorsal root ganglia (DRG) neurons, which was linked with alleviating different pain phenotypes. These previous studies were performed in male rodents only and did not directly investigate the role of SHP-1 in TRPV-1 mediated sensitization. Therefore, our goal was to determine the impact ofShp1overexpression on TRPV1-mediated neuronal responses and capsaicin-induced pain behavior in mice of both sexes. Twelve-week-old male and female mice overexpressingShp1(Shp1-Tg) and their wild type (WT) littermates were used.

Shp1overexpression was confirmed in the DRG of Shp1-Tg mice by RNAin situhybridization and RT-qPCR.Trpv1andShp1were found to be co-expressed in DRG sensory neurons in both genotypes. Functionally, this overexpression resulted in lower magnitude intracellular calcium responses to 200 nM capsaicin stimulation in DRG cultures from Shp1-Tg mice compared to WTs.In vivo, we tested the effects ofShp1overexpression on capsaicin-induced pain through a model of capsaicin footpad injection. While capsaicin injection evoked nocifensive behavior (paw licking) and paw swelling in both genotypes and sexes, only WT mice developed mechanical allodynia after capsaicin injection. We observed similar level of TRPV1 protein expression in the DRG of both genotypes, however, a higher amount of tyrosine phosphorylated TRPV1 was detected in WT DRG. These experiments suggest that, while SHP-1 does not mediate the acute swelling and nocifensive behavior induced by capsaicin, it does mediate a protective effect against capsaicin-induced mechanical allodynia in both sexes. The protective effect of SHP-1 might be mediated by TRPV1 dephosphorylation in capsaicin-sensitive sensory neurons of the DRG.
GTDrift: A resource for exploring the interplay between genetic drift, genomic and transcriptomic characteristics in eukaryotes
Authors: Bénitière Florian , Duret Laurent , Necsulea Anamaria
Published: January 2024

We present GTDrift, a comprehensive data resource that enables explorations of genomic and transcriptomic characteristics alongside proxies of the intensity of genetic drift in individual species. This resource encompasses data for 1,506 eukaryotic species, including 1,413 animals and 93 green plants, and is organized in three components. The first two components contain approximations of the effective population size, which serve as indicators of the extent of random genetic drift within each species. In the first component, we meticulously investigated public databases to assemble data on life history traits such as longevity, adult body length and body mass for a set of 979 species. The second component includes estimations of the ratio between the rate of non-synonymous substitutions and the rate of synonymous substitutions (dN/dS) in protein-coding sequences for 1,324 species. This ratio provides an estimate of the efficiency of natural selection in purging deleterious substitutions. Additionally, we present polymorphism-derivedNeestimates for 66 species. The third component encompasses various genomic and transcriptomic characteristics. With this component, we aim to facilitate comparative transcriptomics analyses across species, by providing easy-to-use processed data for more than 16,000 RNA-seq samples across 491 species. These data include intron-centered alternative splicing frequencies, gene expression levels and sequencing depth statistics for each species, obtained with a homogeneous analysis protocol. To enable cross-species comparisons, we provide orthology predictions for conserved single-copy genes based on BUSCO gene sets. To illustrate the possible uses of this database, we identify the most frequently used introns for each gene and we assess how the sequencing depth available for each species affects our power to identify major and minor splice variants.
Sertraline modulates hippocampal plasticity and learning via sigma 1 receptors, cellular stress and neurosteroids
Authors: Izumi Yukitoshi , Reiersen Angela M. , Lenze Eric J. , Mennerick Steven J. , Zorumski Charles F.
Published: January 2024

In addition to modulating serotonin transport, selective serotonin reuptake inhibitors (SSRIs) have multiple other effects that may contribute to clinical effects, and some of these latter actions prompt repurposing of SSRIs for non-psychiatric indications. We recently observed that the SSRIs fluvoxamine and fluoxetine prevent the acute adverse effects of pro-inflammatory stimulation on long-term potentiation (LTP) in the CA1 hippocampal region. Sertraline showed markedly different effects, acutely inhibiting LTP at a low micromolar concentration through inverse agonism of sigma 1 receptors (S1Rs). In the present studies, we pursued mechanisms contributing to sertraline modulation of LTP in rat hippocampal slices. We found that sertraline partially inhibits synaptic responses mediated by N-methyl-D-aspartate receptors (NMDARs) via effects on NMDARs that express GluN2B subunits. A selective S1R antagonist (NE-100), but not an S1R agonist (PRE-084) blocked effects on NMDARs, despite the fact that both S1R ligands were previously shown to prevent LTP inhibition. Both NE-100 and PRE-084, however, prevented adverse effects of sertraline on one-trial learning. Because of the important role that S1Rs play in modulating endoplasmic reticulum stress, we examined whether inhibitors of cellular stress alter effects of sertraline. We found that two stress inhibitors, ISRIB and quercetin, prevented LTP inhibition, as did inhibitors of the synthesis of endogenous neurosteroids, which are homeostatic regulators of cellular stress. These studies highlight complex effects of sertraline, S1Rs and neurosteroids on hippocampal function and have relevance for understanding therapeutic and adverse drug actions.
Diagnostically distinct resting state fMRI energy distributions: A subject-specific maximum entropy modeling study
Authors: Theis Nicholas , Bahuguna Jyotika , Rubin Jonathan E , Cape Joshua R , IYENGAR SATISH , Prasad Konasale M
Published: January 2024

Objective Existing neuroimaging studies of psychotic and mood disorders have reported brain activation differences (first-order properties) and altered pairwise correlation based functional connectivity (second-order properties). However, both approaches have certain limitations that can be overcome by integrating them in a pairwise maximum entropy model (MEM) that better represents a comprehensive picture of fMRI signal patterns and provides a system-wide summary measure called energy. This study examines the applicability of individual-level MEM for psychiatry and identifies image-derived model coefficients related to model parameters. Method MEMs are fit to resting state fMRI data from each individual with schizophrenia/schizoaffective disorder, bipolar disorder, and major depression (n=132) and demographically matched healthy controls (n=132) from the UK Biobank to different subsets of the default mode network (DMN) regions. Results The model satisfactorily explained observed brain energy state occurrence probabilities across all participants, and model parameters were significantly correlated with image-derived coefficients for all groups. Within clinical groups, averaged energy level distributions were higher in schizophrenia/schizoaffective disorder but lower in bipolar disorder compared to controls for both bilateral and unilateral DMN. Major depression energy distributions were higher compared to controls only in the right hemisphere DMN. Conclusions Diagnostically distinct energy states suggest that probability distributions of temporal changes in synchronously active nodes may underlie each diagnostic entity. Subject-specific MEMs allow for factoring in the individual variations compared to traditional group-level inferences, offering an improved measure of biologically meaningful correlates of brain activity that may have potential clinical utility.
Automatic Geometry-based Estimation of the Locus Coeruleus Region on T1-Weighted Magnetic Resonance Images
Authors: Aganj Iman , Mora Jocelyn , Fischl Bruce , Augustinack Jean C.
Published: January 2024

The locus coeruleus (LC) is a key brain structure implicated in cognitive function and neurodegenerative disease. Automatic segmentation of the LC is a crucial step in quantitative non-invasive analysis of the LC in large MRI cohorts. Most publicly available imaging databases for training automatic LC segmentation models take advantage of specialized contrast-enhancing (e.g., neuromelanin-sensitive) MRI. Segmentation models developed with such image contrasts, however, are not readily applicable to existing datasets with conventional MRI sequences. In this work, we evaluate the feasibility of using non-contrast neuroanatomical information to geometrically approximate the LC region from standard 3-Tesla T1-weighted images of 20 subjects from the Human Connectome Project (HCP). We employ this dataset to train and internally/externally evaluate two automatic localization methods, the Expected Label Value and the U-Net. We also test the hypothesis that using thephaseimage as input can improve the robustness of out-of-sample segmentation. We then apply our trained models to a larger subset of HCP, while exploratorily correlating LC imaging variables and structural connectivity with demographic and clinical data. This report contributes and provides an evaluation of two computational methods estimating neural structure.
Large ungulates will be present in most of Japan by 2050 owing to natural expansion and human population shrinkage
Authors: Morosawa Takahiro , Iijima Hayato , Kawamoto Tomonori , Kanno Takahisa , Araki Ryota , Oka Teruki
Published: January 2024

The aims of this study were to elucidate factors contributing to the expansion of the distributions of sika deer and wild boar in Japan and to predict the expansion of their distributions by 2025, 2050, and 2100. A site occupancy model was constructed using information on species distribution collected by the Ministry of the Environment in 1978, 2003, 2014, and 2018, days of snow cover, forested and road areas, elevation, human population, and distance from occupied grid cells as covariates to calculate the probability of distribution change. Factors contributing to distribution expansion were elucidated and distribution expansion was predicted. Distance from occupied grid cells had the strongest influence on distribution expansion, followed by the inherent ability of each species to expand its distribution. For sika deer, human population had a strong negative effect and elevation and number of days of snow cover were important. For wild boar, forest area and elevation had high importance. Predictions of future distribution showed that both species will be distributed over 90% of Japan by 2050 and over 100% by 2100.
Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases
Authors: Li Celine Man Ying , Briggs Matthew T , Lee Yea-Rin , Tin Teresa , Young Clifford , Pierides John , Kaur Gurjeet , Drew Paul , Maddern Guy J , Hoffmann Peter , Klingler-Hoffmann Manuela , Fenix Kevin
Published: January 2024

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentifiedm/zvalues (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Tenm/zvalues were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Hemoglobin subunit alpha, and Inosine-5’-monophosphate dehydrogenase 2) and two unidentifiedm/zvalues (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.
Investigating Sensitivity, Specificity and Accuracy of Variant Calling Pipelines for Analyzing SARS-CoV-2 Data
Authors: Krishna Aadi C. , Choi Judy S.
Published: January 2024

The rapidly increasing popularity of Next Generation Sequencing and analysis methods in clinical and research settings necessitates an understanding of ideal combinations in identifying genomic variants. Especially with the importance of detecting accurate variants for the development of targeted SARS-CoV-2 vaccines. This research compares the results of two ‘Mapping Algorithms ‘, BWA-MEM and Bowtie2, and two ‘Variant Calling Algorithms ‘, LoFreq and FreeBayes, and their combinatory Variant Calling Pipelines on the analyses of Next Generation Sequencing (NGS) data of five SARS-CoV-2 samples collected from patients in the USA, India, Italy, and Malawi and sourced for this research from the publicly available NCBI SRA database. Our analysis of mapping algorithms found that BWA-MEM likely has higher sensitivity and specificity than Bowtie2 for mapping reads, and their specificity and sensitivity vary with read length. Furthermore, the accuracy of variant calling algorithms increases with the number of reads, while higher read length possibly leads to divergence in accuracy and sensitivity. Overall, FreeBayes was found to likely be more sensitive to detecting variants when used with Bowtie2 rather than BWA-MEM for analyzing SARS-CoV-2 data.
Comparative genomics reveals intra and inter species variation in the pathogenic fungusBatrachochytrium dendrobatidis
Authors: Yacoub Mark N. , Stajich Jason E.
Published: January 2024

The Global Pandemic Lineage (GPL) of the amphibian pathogenBatrachochytrium dendrobatidis(Bd) has been described as a main driver of amphibian extinctions on nearly every continent. Near complete genome of threeBd-GPL strains have enabled studies of the pathogen but the genomic features that setBd-GPL apart from otherBdlineages is not well understood due to a lack of high-quality genome assemblies and annotations from other lineages. We used long-read DNA sequencing to assemble high-quality genomes of threeBd-BRAZIL isolates and one non-pathogen outgroup speciesPolyrhizophydium stewartii(Ps) strain JEL0888, and compared these to genomes of previously sequencedBd-GPL strains. TheBd-BRAZIL assemblies range in size between 22.0 and 26.1 Mb and encode 8495-8620 protein-coding genes for each strain. Our pan-genome analysis provided insight into shared and lineage-specific gene content. The core genome ofBdconsists of 6278 conserved gene families, with 202Bd-BRAZIL and 172Bd-GPL specific gene families. We discovered gene copy number variation in pathogenicity gene families betweenBd-BRAZIL andBd-GPL strains though none were consistently expanded inBd-GPL orBd-BRAZIL strains. Comparison within the Batrachochytrium genus and two closely related non-pathogenic saprophytic chytrids identified variation in sequence and protein domain counts. We further test these new Bd-BRAZIL genomes to assess their utility as reference genomes for transcriptome alignment and analysis. Our analysis examines the genomic variation between strains inBd-BRAZIL andBd-GPL and offers insights into the application of these genomes as reference genomes for future studies.
Unravelling the ancient fungal DNA from the Iceman’s gut
Authors: Oskolkov Nikolay , Sandionigi Anna , Göterström Anders , Canini Fabiana , Turchetti Benedetta , Zucconi Laura , Mimmo Tanja , Buzzini Pietro , Borruso Luigimaria
Published: January 2024

Here, we explore the possible ancient fungal species in the gut of Ötzi, the Iceman, a naturally mummified human found in the Tyrolean Alps (border between Italy and Austria). While ancient DNA (aDNA) has been extensively used to study human, animal, and plant evolution, this research focuses on ancient microbial diversity, specifically fungi. Fungal DNA is often underestimated in metagenomic samples, however here we hypothesise the possibility of retrieving ancient fungal sequences from Ötzi’s gut. A robust bioinformatic pipeline has been developed to detect and authenticate fungal aDNA from stomach, small intestine, and large intestine samples. We revealed the presence ofPseudogymnoascusgenus, withP. destructansandP. verrucosusas possible species, that were particularly abundant in the stomach and small intestine. We suggest that Ötzi may have consumed these fungi accidentally, likely in association with other elements of his diet, and they thrived in his gut after his death due to their adaptability to harsh and cold environments. This research provides insight into the coexistence of ancient humans with specific fungal species and proposes and validates a conservative bioinformatic approach for detecting fungal aDNA in historical metagenomic samples.

Significance statement

Despite their essential interactions with all kingdoms of life, limited molecular studies have focused on ancient fungi. Here, we developed a thorough bioinformatic pipeline that allowed us to detect the presence of ancient DNA likely belonging toPseudogymnoascus destructansandP. verrucosusin the gut of Ötzi, a human naturally mummified over 3,000 years ago in the Tyrolean Alps. Both species can survive harsh environmental conditions, andP. destructansis known for its pathogenicity, suggesting that Ötzi may have accidentally ingested them and providing valuable insights into how ancient humans coexisted with specific fungal species. We propose a highly reliable methodology for detecting ancient fungal DNA in metagenomic studies of historical samples that can have broader applications to understand ancient ecosystems and their interactions.
Adaptation to complex environments reveals pervasive trade-offs and genomic targets with large pleiotropic effects
Authors: Rêgo Alexandre , Stajic Dragan , Bautista Carla , Rouot Sofia , de la Paz Celorio-Mancera Maria , Stelkens Rike
Published: January 2024

Populations in nature rarely adapt to a single stress at a time. Various biotic and abiotic factors come together to produce a complex environment to which populations must adapt. How populations adapt to multiple stressors simultaneously, and how trade-offs evolve between these stressors has been of interest to evolutionary biologists for decades. But natural populations often present logistical challenges to understanding the dynamics of evolution and isolating the genetic basis of adaptation. Here we use methods in experimental evolution to test how adaptation proceeds in the presence of co-occurring stressors, and to quantify the evolution of trade-offs between stressors in a complex environment. We adapted populations of the yeast Saccharomyces cerevisiae to a full-factorial combination of four stressors over the course of 15 serial transfers. We observed rapid increases in fitness paired with the accumulation of mutations related to specific stressors. Trade-offs evolved rapidly and dynamics of trade-off evolution varied between stressors, likely due to the inherent physiological and genetic basis of resistance to each stressor. The degree of parallelism at the phenotypic level showed evidence of being modified by the degree of environmental complexity, while parallelism at the genic level was apparent between populations which shared stressors.
Occurrence of non-apical mitoses at the primitive streak, induced by relaxation of actomyosin and acceleration of the cell cycle, contributes to cell delamination during mouse gastrulation
Authors: Despin-Guitard Evangéline , Plunder Steffen , Mathiah Navrita , Theveneau Eric , Migeotte Isabelle
Published: January 2024

During the epithelial-mesenchymal transition driving mouse embryo gastrulation, cells at the primitive streak divide more frequently that in the rest of the epiblast, and half of those divisions happen away from the apical pole. These observations suggests that non-apical mitoses might play a role in cell delamination and/or mesoderm specification. We aimed to uncover and challenge the molecular determinants of mitosis position in the different regions of the epiblast through a combination of computational modeling and pharmacological treatments of embryos.

Blocking basement membrane degradation at the streak had no impact on the asymmetry in mitosis frequency and position. By contrast disturbance of actomyosin cytoskeleton or cell cycle dynamics elicited ectopic non-apical mitosis and showed that the streak region is characterized by local relaxation of the actomyosin cytoskeleton and less stringent regulation of cell division. These factors are essential for normal dynamics at the streak but are not sufficient to promote acquisition of mesoderm identity or ectopic cell delamination in the epiblast. Exit from the epithelium requires additional events, such as detachment from the basement membrane.

Altogether, our data indicate that cell delamination at the streak is a morphogenetic process which results from a cooperation between EMT events and the local occurrence of non-apical mitoses driven by specific cell cycle and contractility parameters.