bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of single housing on innate immune activation in SIV-infected pigtail macaques (Macaca nemestrina) as a model of psychosocial stress in acute HIV infection
Authors: Castell Natalie , Guerrero-Martin Selena M. , Rubin Leah H. , Shirk Erin N. , Brockhurst Jacqueline K. , Lyons Claire E. , Najarro Kevin M. , Queen Suzanne E. , Carlson Bess W. , Adams Robert J. , Morrell Craig N. , Gama Lucio , Graham David R. , Zink Christine , Mankowski Joseph L. , Clements Janice E. , Metcalf Pate Kelly A. 
Published: September 2022

Abstract

Objective
Simian immunodeficiency virus (SIV) infection of macaques recapitulates many aspects of HIV pathogenesis and is similarly affected by both genetic and environmental factors. Psychosocial stress is associated with immune system dysregulation and worse clinical outcomes in people with HIV (PWH). This study assessed the impact of single housing, as a model of psychosocial stress, on innate immune responses of pigtailed macaques (Macaca nemestrina) during acute SIV infection.

Methods
A retrospective analysis of acute SIV infection of two- to six-year-old male pigtailed macaques was performed to compare the innate immune responses of socially (n = 41) and singly (n = 35) housed animals. Measures included absolute monocyte count and subsets, and in a subset (n ≤ 18) platelet counts and activation data.

Results
SIV infection resulted in the expected innate immune parameter changes with a modulating effect from housing condition. Monocyte number increased post-infection for both groups, driven by classical monocytes (CD14+ CD16-), with a greater increase in socially housed animals (227%, p < 0.001, by day 14 compared to pre-inoculation timepoints). Platelet numbers recovered more quickly in the socially housed animals. Platelet activation (P-selectin) increased 65% (p = 0.004) and MHC-I surface expression 40% (p = 0.009) from pre-inoculation only in socially housed animals, while no change in these measures occurred in singly housed animals.

Conclusions
Chronic psychosocial stress produced by single housing may play an immunomodulatory role in the innate immune response to acute retroviral infection. Dysregulated innate immunity could be one of the pathways by which psychosocial stress contributes to immune suppression and increased disease severity in PWH.
MECHANISMS OF CARDIAC DYSFUNCTION IN SEPSIS
Authors: Hobai Ion A. 
Published: September 2022

ABSTRACT
Studies in animal models of sepsis have elucidated an intricate network of signaling pathways that lead to the dysregulation of myocardial Ca2+ handling and subsequently to a decrease in cardiac contractile force, in a sex- and model-dependent manner. After challenge with a lethal dose of LPS, male animals show a decrease in cellular Ca2+ transients (ΔCai), with intact myofilament function, whereas female animals show myofilament dysfunction, with intact ΔCai. Male mice challenged with a low, nonlethal dose of LPS also develop myofilament desensitization, with intact ΔCai. In the cecal ligation and puncture (CLP) model, the causative mechanisms seem similar to those in the LPS model in male mice and are unknown in female subjects. ΔCai decrease in male mice is primarily due to redox-dependent inhibition of sarco/endoplasmic reticulum Ca2+ ATP-ase (SERCA). Reactive oxygen species (ROS) are overproduced by dysregulated mitochondria and the enzymes NADPH/NADH oxidase, cyclooxygenase, and xanthine oxidase. In addition to inhibiting SERCA, ROS amplify cardiomyocyte cytokine production and mitochondrial dysfunction, making the process self-propagating. In contrast, female animals may exhibit a natural redox resilience. Myofilament dysfunction is due to hyperphosphorylation of troponin I, troponin T cleavage by caspase-3, and overproduction of cGMP by NO-activated soluble guanylate cyclase. Depleted, dysfunctional, or uncoupled mitochondria likely synthesize less ATP in both sexes, but the role of energy deficit is not clear. NO produced by NO synthase (NOS)-3 and mitochondrial NOSs, protein kinases and phosphatases, the processes of autophagy and sarco/endoplasmic reticulum stress, and β-adrenergic insensitivity may also play currently uncertain roles.
Immune Cell Deformability in Depressive Disorders: Longitudinal Associations Between Depression, Glucocorticoids and Cell Deformability
Authors: Walther Andreas , Kräter Martin , Kirschbaum Clemens , Gao Wei , Wekenborg Magdalena , Penz Marlene , Rothe Nicole , Guck Jochen , Wittwer Lucas Daniel , Eder Julian 
Published: September 2022

AbstractBackgroundCell deformability of all major blood cell types is increased in depressive disorders (DD). Furthermore, impaired glucocorticoid secretion is causally related to DD. Nevertheless, there are no longitudinal studies examining changes in glucocorticoid output and depressive symptoms regarding cell deformability in DD.AimTo investigate, whether changes in depressive symptoms or hair glucocorticoids predict cell deformability in DD.MethodsIn 136 individuals, depressive symptoms (PHQ-9) and hair glucocorticoids (cortisol and cortisone) were measured at timepoint one (T1), while one year later (T2) depressive symptoms and hair glucocorticoids were remeasured and additionally cell deformability of peripheral blood cells was assessed and DD status was determined by clinical interview.ResultsDepression severity at T1 predicted higher cell deformability in monocytes and lymphocytes over the entire sample. Subjects with continuously high depressive symptoms at T1 and T2 showed elevated monocyte deformability as compared to subjects with low depressive symptoms. Depression severity at T1 of subjects with a lifetime persistent depressive disorder (PDD) was associated with elevated monocyte, neutrophil, and granulo-monocyte deformability. Depression severity at T1 of subjects with a 12-month PDD was positively associated with monocyte deformability. Furthermore, increases in glucocorticoid concentrations from T1 to T2 tended to be associated with higher immune cell deformability, while strongest associations emerged for the increase in cortisone with elevated neutrophil and granulo-monocyte deformability in the 12-month PDD group.ConclusionContinuously elevated depressive symptomatology as well as an increase in glucocorticoid levels over one year are associated with higher immune cell deformability, particularly in PDD. These findings suggest, that persistent depressive symptomatology associated with increased glucocorticoid secretion may lead to increased immune cell deformability thereby compromising immune cell function and likely contributing to the perpetuation of PDD.
Exploration of cortical ß-Amyloid load in Alzheimer’s disease using quantitative susceptibility mapping at 9.4T
Authors: Tuzzi Elisa , Loktyushin Alexander , Zeller Anja , Pohmann Rolf , Laske Christoph , Scheffler Klaus , Hagberg Gisela E. 
Published: September 2022

ABSTRACTEarly detection of β-Amyloid (Aβ) deposits in Alzheimer’s disease (AD) patients may enable treatment in the early stages of the disease. To date, there are no validated, specific, and non-invasive routines for early Aβ detection which are suitable for clinical practice. Ultra-high resolution quantitative susceptibility mapping (QSM) at 14.1T has previously shown different contrasts in cortical areas of an AD sample that resembled distinct Aβ spatial patterns in histological sections of the same specimen. These contrasts appeared different in the QSM from a healthy control (HC) sample where, instead, no plaques were detected. In a few cases, this distinction in the cortical magnetic effects (para- and diamagnetic) between AD and HC was also observed in vivo using ultra- high resolution single-echo Acquisition Weighted (AW) gradient echo MRI at 9.4T. Based on this evidence, a method to quantify the paramagnetic and diamagnetic effects of Aβ to possibly distinguish between AD and HC was developed. In this study, we extended those results and explored the ability to use QSM to estimate β-Amyloid plaque load in the cortex of 7 elderly patients with early AD and 7 healthy age-matched HC. Besides ultra-high resolution AW images, we acquired lower resolution multi-echo (MTE) data and compared the previously used RESHARP- based method for background removal (“AW-filter”, with a high Tikhonov term and a small kernel size) with a method widely used in the literature (“mild-filter”, with a low-regularization term and a large kernel size) for the MTE processing. Paramagnetic and diamagnetic QSM changes were assessed in 16 cortical areas. All methods enabled the detection of regions with high QSM values (up to 45 ppb in AD and up to 25 ppb in HC) and known as early Aβ accumulation areas in AD progression. A distinct cortical pattern was observed at both spatial resolutions using the AW-filter. This was not the case with the mild-filter at the lower resolution. AW-QSM outperformed MTE maps with the AW-filter for the detection of areas with prominent cortical paramagnetic effects, including regions where Aβ accumulation happens in the earliest AD stages, such as the precuneus and posterior cingulate cortex. Diamagnetic changes were more prominent than the paramagnetic effects regardless of the spatial resolution used and this difference was further enhanced with the mild-filter. This explorative study points toward the development of more accessible clinical methods to non-invasively detect effects of Aβ accumulation in AD patients by exploring cortical features that can be detected by ultra-high field QSM at different spatial resolutions.
Pharmacokinetics and pharmacogenomics of clozapine in an ancestrally diverse sample: A longitudinal analysis and GWAS using clinical monitoring data from the UK
Authors: Pardiñas Antonio F. , Kappel Djenifer B. , Roberts Milly , Tipple Francesca , Shitomi-Jones Lisa M. , King Adrian , Jansen John , Helthuis Marinka , Owen Michael J. , O’Donovan Michael C. , Walters James T.R. 
Published: September 2022

BackgroundThe antipsychotic clozapine is the only drug with proven effectiveness against the treatment-resistant symptoms that affect 20-30% of those with schizophrenia. Despite this, clozapine is markedly under-prescribed, partly due to concerns about its narrow therapeutic range and adverse drug reaction profile. Both concerns are linked to drug metabolism, which varies across worldwide populations and is partially genetically determined. There is, however, a lack of clozapine pharmacogenomic data based on study participants of multiple ancestries.MethodsWe analysed data from 4,495 individuals linked to 16,068 assays from a clozapine monitoring service in the UK. Genomic information was used to identify five biogeographical ancestries (European, Sub-Saharan African, North African, Southwest Asian and East Asian) as well as admixed individuals. Pharmacokinetic modelling, GWAS, and a polygenic score association analysis were conducted on this longitudinal dataset using three outcome variables: two metabolite plasma concentrations (clozapine and norclozapine) and their ratio.FindingsA faster average clozapine metabolism was seen in those of Sub-Saharan African ancestry compared to Europeans. In contrast, East and Southwest Asians were more likely to be slow clozapine metabolisers. Eight pharmacogenomic loci were identified in the GWAS, with consistent cross-ancestral effects. Polygenic scores generated from these loci led to significant associations with clozapine outcome variables in the whole sample and within individual ancestries, with variances explained between 0.61%-7.26%.InterpretationLongitudinal cross-ancestry GWAS can discover pharmacogenomic markers of clozapine metabolism that, individually or as polygenic scores, have consistent effects across ancestries. While the potential clinical role of these predictors is evaluated, we provide strong evidence that ancestral differences in clozapine metabolism should be incorporated into clozapine dosing and managing protocols to optimise their utility for diverse populations.FundingMedical Research Council (MRC).
Global observation of plankton communities from space
Authors: Kaneko Hiroto , Endo Hisashi , Henry Nicolas , Berney Cédric , Mahé Frédéric , Poulain Julie , Labadie Karine , Beluche Odette , El Hourany Roy ,   Tara Oceans Coordinators, Chaffron Samuel , Wincker Patrick , Nakamura Ryosuke , Karp-Boss Lee , Boss Emmanuel , Bowler Chris , de Vargas Colomban , Tomii Kentaro , Ogata Hiroyuki 
Published: September 2022

AbstractSatellite remote sensing from space is a powerful way to monitor the global dynamics of marine plankton. Previous research has focused on developing models to predict the size or taxonomic groups of phytoplankton. Here we present an approach to identify representative communities from a global plankton network that included both zooplankton and phytoplankton and using global satellite observations to predict their biogeography. Six representative plankton communities were identified from a global co-occurrence network inferred using a novel rDNA 18S V4 planetary-scale eukaryotic metabarcoding dataset. Machine learning techniques were then applied to train a model that predicted these representative communities from satellite data. The model showed an overall 67% accuracy in the prediction of the representative communities. The prediction based on 17 satellite-derived parameters showed better performance than based only on temperature and/or the concentration of chlorophylla. The trained model allowed to predict the global spatiotemporal distribution of communities over 19-years. Our model exhibited strong seasonal changes in the community compositions in the subarctic-subtropical boundary regions, which were consistent with previous field observations. This network-oriented approach can easily be extended to more comprehensive models including prokaryotes as well as viruses.
Elevated genetic risk for multiple sclerosis originated in Steppe Pastoralist populations
Authors: Barrie William , Yang Yaoling , Irving-Pease Evan K. , Attfield Kathrine E. , Scorrano Gabriele , Jensen Lise Torp , Armen Angelos P. , Dimopoulos Evangelos Antonios , Stern Aaron , Refoyo-Martinez Alba , Ramsøe Abigail , Gaunitz Charleen , Demeter Fabrice , Jørkov Marie Louise S. , Møller Stig Bermann , Springborg Bente , Klassen Lutz , Hyldgård Inger Marie , Wickmann Niels , Vinner Lasse , Korneliussen Thorfinn Sand , Allentoft Morten E. , Sikora Martin , Kristiansen Kristian , Rodriguez Santiago , Nielsen Rasmus , Iversen Astrid K. N. , Lawson Daniel J. , Fugger Lars , Willerslev Eske 
Published: September 2022

SUMMARYMultiple sclerosis (MS) is a modern neuro-inflammatory and -degenerative disease, which is most prevalent in Northern Europe. Whilst it is known that inherited risk to MS is located within or within close proximity to immune genes, it is unknown when, where and how this genetic risk originated1. By using the largest ancient genome dataset from the Stone Age2, along with new Medieval and post-Medieval genomes, we show that many of the genetic risk variants for MS rose to higher frequency among pastoralists located on the Pontic Steppe, and were brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the Steppe population, and later in Europe, likely driven by pathogenic challenges coinciding with dietary, lifestyle, and population density changes. This study highlights the critical importance of this period as a determinant of modern immune responses and its subsequent impact on the risk of developing MS in a changing environment.
Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale
Authors: Latrille T. , Rodrigue N. , Lartillot N. 
Published: September 2022

AbstractAdaptation in protein-coding sequences can be detected from multiple sequence alignments across species, or alternatively by leveraging polymorphism data inside a population. Across species, quantification of the adaptive rate relies on phylogenetic codon models, classically formulated in terms of the ratio of non-synonymous over synonymous substitution rates. Evidence of an accelerated non-synonymous substitution rate is considered a signature of pervasive adaptation. However, because of the background of purifying selection, these models are potentially limited in their sensitivity. Recent developments have led to more sophisticated mutation-selection codon models aimed at making a more detailed quantitative assessment of the interplay between mutation, purifying and positive selection. In this study, we conducted a large-scale exome-wide analysis of placental mammals with mutation-selection models, assessing their performance at detecting proteins and sites under adaptation. Importantly, mutation-selection codon models are based on a population-genetic formalism and thus are directly comparable to McDonald & Kreitman tests at the population level to quantify adaptation. Taking advantage of this relationship between phylogenetic and population genetics, we integrated divergence and polymorphism data across the entire exome for 29 populations across 7 genera, and showed that proteins and sites detected to be under adaptation at the phylogenetic scale are also under adaptation at the population-genetic scale. Altogether, our exome-wide analysis shows that phylogenetic mutation-selection codon models and population-genetic test of adaptation can be reconciled and are congruent, paving the way for integrative models and analyses across individuals and populations.Significance StatementDetecting genes under adaptation represents a key step in the decoding of genomes. Several methods have been proposed, focussing either on the short time scale (population genetics, e.g. human populations), or on the long time scale (phylogenetics, e.g. across mammals). However, the accuracy of these methods is still under debate, and it is still unclear whether the signatures of adaptation are congruent across evolutionary scales. In this study, using novel phylogenetic methods and gathering genome data across and within species, we show that the signatures of adaptation at the phylogenetic and population-genetic scales can be reconciled. While providing a mutual confirmation of the two approaches, our work paves the way for further methodological integration between micro- and macro-evolutionary genomics.
MegaFeed: Global database of megaherbivores’ feeding preferences
Authors: Berzaghi Fabio , Awasthi Balram 
Published: September 2022

AbstractTerrestrial mammalian herbivores heavier than ~1000 kg, also known as megaherbivores, perform unique ecological functions due to their combination of heavy body mass, extended home ranges, abundant biomass consumption, and highly diverse diet. Megaherbivores can have substantial effects on ecosystem functioning, vegetation structure, and biogeochemical cycles. Elephants (family Elephantidae) and rhinoceros (family Rhinocerotidae) are two of the remaining megaherbivores that survived the late Pleistocene extinctions, but their populations have been globally declining in the last century. Feeding preferences are a key factor determining the influence of megaherbivores on ecosystems and plant communities; however, comprehensive and centralized data on megaherbivores food preferences are lacking. Here we present MegaFeed, an extensive dataset of megaherbivores’ feeding preferences across their distribution. This first version of MegaFeed here described contains more than 12,000 records of feeding preferences for the extant elephant species: Loxodonta africana (African savanna elephant), Loxodonta cyclotis (African Forest elephant), and Elephas maximus (Asian elephant). MegaFeed will contribute to a better understanding of the ecological functions of megaherbivores, evaluate the consequences of their decline, and guide rewilding and conservation initiatives such as habitat restoration and reduction of human–wildlife conflicts.
Bioinformatic-based identification of 3 immune-related genes for prognostic in breast invasive carcinoma
Authors: Cui Xiaoying , Song Shuang , Zhang Wenjuan , Wang Dawei , Fang Zhijun 
Published: September 2022

AbstractBreast invasive carcinoma (BRCA) is the leading cause of cancer deaths in female worldwide. Immune cell infiltration is considered to be crucial factor for the success or failure of BRCA therapy. As we all known, early diagnosis of breast cancer can greatly improve the survival rate of patients. Hence, to screen effective biomarkers for breast cancer immunotherapy might be extremely important. In this research, we identified an immune-related, three-gene biomarkers for prognosis of BRCA. We obtained altogether 192 differentially expressed genes (DEGs) from GEO datasets (GSE22820, GSE36295) and GEPIA database, followed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. We screened 3 immune-related candidate biomarkers composing by CXCL2, CXCL9 and RBP7 that improves survival prediction outcome in BRCA. Kaplan–Meier analysis was conducted to analyze the patient survival based on 3 genes. In addition, we found that selected biomarkers were closely connected with infiltration levels of different tumor immune cells. Moreover, principal component analysis showed three biomarkers could effectively distinguish tumor samples from normal samples. In summary, these findings suggested that CXCL2, CXCL9 and RBP7 are viable prognostic and diagnostic biomarkers and provide new ideas for immunotherapy solutions of BRCA in the future.
HaploCart: Human mtDNA Haplogroup Classification Using a Pangenomic Reference Graph
Authors: Rubin Joshua Daniel , Vogel Nicola Alexandra , Gopalakrishnan Shyam , Sackett Peter Wad , Renaud Gabriel 
Published: September 2022

AbstractCurrent mitochondrial DNA (mtDNA) haplogroup classification tools map reads to a single reference genome and perform inference based on the detected mutations to this reference. This approach biases haplogroup assignments towards the reference and prohibits accurate calculations of the uncertainty in assignment. We presentHaploCart, an mtDNA haplogroup classifier which usesVG’s pangenomic reference graph framework together with principles of Bayesian inference. We demonstrate that our approach significantly outperforms available tools by being more robust to lower coverage or incomplete consensus sequences and producing phylogenetically-aware confidence scores that are unbiased towards any haplogroup.HaploCartis available both as a command-line tool and through a user-friendly web interface. The program written inC++accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments along with confidence estimates. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment.HaploCartis available as a command-line tool athttps://github.com/grenaud/vganand as a web server athttps://services.healthtech.dtu.dk/service. php?HaploCart.
Comparing Long Read Fusion Callers using Simulated Read Data
Authors: Van Twisk Daniel , Vincent Benjamin , Rubinsteyn Alex 
Published: September 2022

AbstractThe advent of single-molecule third generation sequencing technologies provide new possibilities for the detection of fusion transcripts in sequencing data. Here, we test three long-read fusions detection tools on simulated data, compare various tooling parameters and compare the performance between long-read and short-read fusion detection tools. We also use our fusion transcript detection pipeline to describe fusions transcripts detected in U87 and U937 glioblastoma cell lines. We find that LongGF is the most capable of the long-read fusion detection tools at identifying the most simulated fusion transcripts. While the short read fusion transcript detection tool, Arriba, had similar recall to some of the long-read tools, its precision was found to be much lower. Several fusions with ample evidence were found in U87 and U937 cell lines.