bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mitochondrial networks of microglia adapt in a sex-specific manner upon injury-induced stress and UCP2 knockout
Authors: Maes Margaret E , Colombo Gloria , Schoot Uiterkamp Florianne E. , Sternberg Felix , Venturino Alessandro , Pohl Elena E , Siegert Sandra 
Published: August 2022

AbstractBalanced and dynamic mitochondrial networks are essential for cell survival and function. Mitochondrial networks remodel their connectivity, content and subcellular localization to support optimized energy production under conditions of increased stress.In vivo, stressors can arise from the environment, such as in neuronal injury, or from mutation-induced cellular dysfunction. Cells programmed to identify and respond to these stress signals, like microglia, rely on optimized mitochondrial function, however we know very little about mitochondrial networks of microgliain vivoor their adaptation to environmental or cellular stressors.Here, we define the mitochondrial networks of retinal microglia in physiological conditionsin vivoand evaluate network alterations by taking advantage of a microglia-selective mitochondria-labeled mouse model. First, we demonstrate significant differences in the mitochondrial networks of microgliain vivoandin vitro.Then, we induced neuronal injury in thein vivoenvironment using optic nerve crush, where responsive microglia exhibit more fragmented mitochondrial networks with increased content and perinuclear localization, supporting a state of increased cellular stress. Surprisingly, when we selectively increase cellular stress by knocking out the mitochondria-associated gene uncoupling protein 2 (UCP2), only male UCP2KOmicroglia establish a hyperfused mitochondrial network after injury, indicating sex differences in microglial stress mitigation. Ovariectomy in UCP2KOfemales elicits a shift toward the male hyperfused mitochondrial phenotype suggesting that circulating estrogens are a contributing factor to the differences in microglial stress mitigation.
The absence of gastrointestinal redox dyshomeostasis in the brain-first rat model of Parkinson’s disease induced by bilateral intrastriatal 6-hydroxydopamine
Authors: Homolak Jan , Joja Mihovil , Grabaric Gracia , Schiatti Emiliano , Virag Davor , Perhoc Ana Babic , Knezovic Ana , Barilar Jelena Osmanovic , Salkovic-Petrisic Melita 
Published: August 2022

AbstractThe gut-brain axis plays an important role in Parkinson’s disease (PD) by acting as a route for vagal propagation of aggregated α-synuclein in the gut-first endophenotype and as a mediator of gastrointestinal dyshomeostasis via the nigro-vagal pathway in the brain-first endophenotype of the disease. One important mechanism by which the gut-brain axis may promote PD is by regulating gastrointestinal redox homeostasis as overwhelming evidence suggests that oxidative stress plays a key role in the etiopathogenesis and progression of PD and the gastrointestinal tract maintains redox homeostasis of the organism by acting as a critical barrier to environmental and microbiological electrophilic challenges. The present aim was to utilize the bilateral intrastriatal 6-hydroxydopamine (6-OHDA) brain-first PD model to study the effects of isolated central pathology on redox homeostasis of the gastrointestinal tract. Three-month-old male Wistar rats were either not treated (intact controls; CTR) or treated bilaterally intrastriatally with vehicle (CIS) or 6-OHDA (6-OHDA). Motor deficits were assessed with the rotarod performance test and the duodenum, ileum, and colon were dissected for biochemical analyses 12 weeks after the treatment. Lipid peroxidation, total antioxidant capacity, low-molecular thiols, and protein sulfhydryls, the activity of total and Mn/Fe superoxide dismutases, and total and azide-insensitive catalase/peroxidase were measured. Univariate and multivariate models of redox biomarkers provide solid evidence against the existence of pronounced gastrointestinal redox dyshomeostasis. The results indicate that the dysfunction of the nigro-vagal system and not motor deficit may be a key mediator of gastrointestinal dyshomeostasis in brain-first 6-OHDA-induced rodent models of PD.
Global maps of lake surface water temperatures reveal pitfalls of air-for-water substitutions in ecological prediction
Authors: Armitage David W. 
Published: August 2022

AbstractIn modeling species distributions and population dynamics, spatially-interpolated climatic data are often used as proxies for real, on-the-ground measurements. For shallow freshwater systems, this practice may be problematic as interpolations used for surface waters are generated from terrestrial sensor networks measuring air temperatures. Using these may therefore bias statistical estimates of species’ environmental tolerances or population projections – particularly among pleustonic and epilimnetic organisms. Using a global database of millions of daily satellite-derived lake surface water temperatures (LSWT), I trained machine learning models to correct for the correspondence between air and LSWT as a function of atmospheric and topographic predictors, resulting in the creation of monthly high-resolution global maps of air-LSWT offsets, corresponding uncertainty measures, and derived LSWT-based bioclimatic layers for use by the scientific community. I then compared the performance of these LSWT layers and air temperature-based layers in population dynamic and ecological niche models (ENM). While generally high, the correspondence between air temperature and LSWT was quite variable and often nonlinear depending on the spatial context. These LSWT predictions were better able to capture the modeled population dynamics and geographic distributions of two common aquatic plant species. Further, ENM models trained with LSWT predictors more accurately captured lab-measured thermal response curves. I conclude that these predicted LSWT temperatures perform better than raw air temperatures when used for population projections and environmental niche modeling, and should be used by practitioners to derive more biologically-meaningful results. These global LSWT predictions and corresponding error estimates and bioclimatic layers have been made freely available to all researchers in a permanent archive.
Effective Matrix Designs for COVID-19 Group Testing
Authors: Brust David , Brust Johannes J. 
Published: August 2022

AbstractBackgroundGrouping samples with low prevalence of positives into pools and testing these pools can achieve considerable savings in testing resources compared with individual testing in the context of COVID-19. We review published pooling matrices, which encode the assignment of samples into pools and describe decoding algorithms, which decode individual samples from pools. Based on the findings we propose new one-round pooling designs with high compression that can efficiently be decoded by combinatorial algorithms. This expands the admissible parameter space for the construction of pooling matrices compared to current methods.ResultsBy arranging samples in a grid and using polynomials to construct pools, we develop direct formulas for an Algorithm (Polynomial Pools (PP)) to generate assignments of samples into pools. Designs from PP guarantee to correctly decode all samples with up to a specified number of positive samples. PP includes recent combinatorial methods for COVID-19, and enables new constructions that can result in more effective designs.ConclusionFor low prevalences of COVID-19, group tests can save resources when compared to individual testing. Constructions from the recent literature on combinatorial methods have gaps with respect to the designs that are available. We develop a method (PP), which generalizes previous constructions and enables new designs that can be advantageous in various situations.
Mapping of genomic regions linked to stemphylium blight (Stemphylium botryosum Wallr.) resistance in lentil using linkage mapping and marker-trait association analysis
Authors: Adobor Stanley , Gela Tadesse S. , Banniza Sabine , Vandenberg Albert 
Published: August 2022

AbstractStemphylium blight caused by Stemphylium botryosum, is a foliar disease of lentil. It affects the productivity and milling quality of lentil crops, mainly in South Asia and Canada. Development of stemphylium blight resistant cultivars by introgression of resistance alleles from crop wild relatives of lentil, such as Lens ervoides, is one strategy of disease control. The objective of this study was to identify genomic regions associated with stemphylium blight resistance by combining linkage mapping and marker-trait association analysis. A total of 182 genotypes of a lentil advanced backcross population (LABC-01) developed from the backcross of the interspecific L. culinaris × L. ervoides line LR-59-81 (donor) and cultivar CDC Redberry (recurrent) and 101 diverse lentil accessions selected by stratified random sampling from a lentil diversity panel were genotyped and evaluated for stemphylium blight reactions. Quantitative trait locus (QTL) analysis identified four loci contributing to stemphylium blight resistance on lentil chromosomes 2, 4 and 5. Marker trait association analysis detected five significant single nucleotide polymorphism (SNP) markers associated with stemphylium blight resistance within QTLs regions and seven SNP markers outside the QTLs regions on chromosomes 1, 2, 3, 5, and 7. The markers associated with stemphylium blight resistance may be useful for marker-assisted selection of resistant cultivars after validation.
Valproic acid exposure affects social visual lateralization and asymmetric gene expression in zebrafish larvae
Authors: Messina Andrea , Sovrano Valeria Anna , Baratti Greta , Musa Alessia , Adiletta Alice , Sgadò Paola 
Published: August 2022

AbstractCerebral asymmetry is critical for typical brain function and development, at the same time altered brain lateralization seems to be associated with neuropsychiatric disorders. In autism spectrum disorders (ASD) studies have suggested reduced functional and structural cerebral asymmetry, reporting changes in asymmetric activation of brain structures involved in language and social processing, and increased prevalence of left-handedness. Zebrafish are increasingly emerging as model species to study brain lateralization, using asymmetric development of the habenula, a phylogenetically old brain structure associated with social and emotional processing, to investigate the relationship between brain asymmetry and social behavior. We exposed 5-hour post-fertilization zebrafish embryos to valproic acid (VPA), a compound used to model the core signs of ASD in many vertebrate species, and assessed social interaction, visual lateralization and gene expression in the thalamus and the telencephalon. VPA-exposed zebrafish exhibit social deficits and a deconstruction of social visual laterality to the mirror. We also observe changes in the asymmetric expression of the epithalamic markerleftoverand in telencephalic gene expression in adult zebrafish. Our data indicate that VPA exposure neutralizes the animals’ visual field bias, with a complete loss of the left-eye use bias in front of their own mirror image, and alters brain asymmetric gene expression, opening new perspectives to investigate brain lateralization and its link to atypical social cognitive development, considering zebrafish as an animal model for the autistic syndrome.
PyWGCNA: A Python package for weighted gene co-expression network analysis
Authors: Rezaie Narges , Reese Fairlie , Mortazavi Ali 
Published: August 2022

ABSTRACTMotivationWeighted gene co-expression network analysis (WGCNA) is frequently used to identify modules of genes that are co-expressed across many RNA-seq samples. However, the current R implementation is slow, not designed to compare modules between multiple WGCNA networks, and results are hard to interpret and visualize. We introduce the PyWGCNA Python package designed to identify and compare co-expression modules from RNA-seq data.ResultsWe apply PyWGCNA to two distinct datasets of brain bulk RNA-seq from MODEL-AD to identify modules associated with the genotypes. We compare the resulting modules to each other to find modules with significant overlap across the datasets.AvailabilityThe PyWGCNA library for Python 3 is available on PyPi at https://pypi.org/project/PyWGCNA and on GitHub at https://github.com/mortazavilab/PyWGCNA.
DeepGenePrior: A deep learning model to prioritize genes affected by copy number variants
Authors: Rahaie Zahra , Rabiee Hamid R. , Alinejad-Rokny Hamid 
Published: August 2022

AbstractThe genetic etiology of neurodevelopmental disorders is highly heterogeneous. They are characterized by abnormalities in the development of the central nervous system, which lead to diminished physical or intellectual capabilities. Determining which gene is the driver of disease (not just a passenger), termed ‘gene prioritization,’ is not entirely known. In terms of disease-gene associations, genome-wide explorations are still underdeveloped due to the reliance on previous discoveries when spotting new genes and other evidence sources with false positive or false negative relations. This paper introduces DeepGenePrior, a model based on deep neural networks that prioritizes candidate genes in Copy Number Variant (CNV) mediated diseases. Based on the well-studied Variational AutoEncoder (VAE), we developed a score to measure the impact of the genes on the target diseases.Unlike other methods that use prior data on gene-disease associations to prioritize candidate genes (using the guilt by association principle), the current study exclusively relies on copy number variants. Therefore, the procedure can identify disease-associated genes regardless of prior knowledge or auxiliary data sources. We identified genes that distinguish cases from disorders (autism, schizophrenia, and developmental delay). A 12% increase in fold enrichment was observed in brain-expressed genes compared to previous studies, while 15% more fold enrichment was found in genes associated with mouse nervous system phenotypes. We also explored sex dimorphism for the disorders and discovered genes that overexpress more in one gender than the other. Additionally, we investigated the gene ontology of the putative genes with WebGestalt and the associations between the causative genes and the other phenotypes in the DECIPHER dataset. Furthermore, some genes were jointly present in the top genes associated with the three disorders in this study (i.e., autism spectrum disorder, schizophrenia, and developmental delay); namely, deletions in ZDHHC8, DGCR5, and CATG00000022283 were common between them. These findings suggest the common etiology of these clinically distinct conditions.With DeepGenePrior, we address the obstacles in existing gene prioritization studies. This study identified promising candidate genes without prior knowledge of diseases or phenotypes using deep learning.
Genome-wide analysis of Structural Variants in Parkinson’s Disease using Short-Read Sequencing data
Authors: Billingsley Kimberley J. , Ding Jinhui , Jerez Pilar Alvarez , Illarionova Anastasia , Grenn Francis P. , Makarious Mary B. , Moore Anni , Vitale Daniel , Reed Xylena , Hernandez Dena , Torkamani Ali , Ryten Mina , Hardy John ,   UK Brain Expression Consortium (UKBEC), Chia Ruth , Scholz Sonja W. , Traynor Bryan J. , Dalgard Clifton L. , Ehrlich Debra J. , Tanaka Toshiko , Ferrucci Luigi , Beach Thomas.G. , Serrano Geidy E. , Quinn John P. , Bubb Vivien J. , Collins Ryan L , Zhao Xuefang , Walker Mark , Pierce-Hoffman Emma , Brand Harrison , Talkowski Michael , Casey Bradford , Cookson Mark R , Markham Androo , Nalls Mike , Mahmoud Medhat , Sedlazeck Fritz J , Blauwendraat Cornelis , Gibbs J. Raphael , Singleton Andrew B. 
Published: August 2022

AbstractParkinson’s disease is a complex neurodegenerative disorder, affecting approximately one million individuals in the USA alone. A significant proportion of risk for Parkinson’s disease is driven by genetics. Despite this, the majority of the common genetic variation that contributes to disease risk is unknown, in-part because previous genetic studies have focussed solely on the contribution of single nucleotide variants. Structural variants represent a significant source of genetic variation in the human genome. However, because assay of this variability is challenging, structural variants have not been cataloged on a genome-wide scale, and their contribution to the risk of Parkinson’s disease remains unknown. In this study, we 1) leveraged the GATK-SV pipeline to detect and genotype structural variants in 7,772 short-read sequencing data and 2) generated a subset of matched whole-genome Oxford Nanopore Technologies long-read sequencing data from the PPMI cohort to allow for comprehensive structural variant confirmation. We detected, genotyped, and tested 3,154 “high-confidence” common structural variant loci, representing over 412 million nucleotides of non-reference genetic variation. Using the long-read sequencing data, we validated three structural variants that may drive the association signals at known Parkinson’s disease risk loci, including a 2kb intronic deletion within the gene LRRN4. Further, we confirm that the majority of structural variants in the human genome cannot be detected using short-read sequencing alone, encompassing on average around 4 million nucleotides of inaccessible sequence per genome. Therefore, although these data provide the most comprehensive survey of the contribution of structural variants to the genetic risk of Parkinson’s disease to date, this study highlights the need for large-scale long-read datasets to fully elucidate the role of structural variants in Parkinson’s disease.
Isolation and characterization of SARS-CoV-2 in Kenya
Authors: Makio Albina , Irekwa Robinson Mugasiali , Munyao Matthew Mutinda , Njoroge Caroline Wangui , Rotich Peter Kipkemboi , Nyandwaro Tonny Teya , Yego Joanne Jepkemei , Mwangi Anne Wanjiru , Kimotho James Hungo , Tanui Ronald , Rutto Vincent , Nzou Samson Muuo 
Published: August 2022

AbstractThe emergence of Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) from Wuhan, China, in December 2019 raised a global health concern that eventually became a pandemic affecting almost all countries worldwide. The respiratory disease has infected over 530 million people worldwide, with over 950,000 deaths recorded. This has led scientists to focus their efforts on understanding the virus to develop effective means to diagnose, treat, prevent, and control this pandemic. One of the areas of focus is isolation of this virus, which plays a crucial role in understanding the viral dynamics in the laboratory. In this study, we report the isolation and detection of locally circulating SARS-CoV-2 in Kenya. The isolates were cultured on Vero Cercopithecus cell line (CCL-81) cells, RNA extraction conducted from the supernatants, and reverse transcriptase-polymerase chain reaction (RT-PCR). Genome sequencing was done to profile the strains phylogenetically and identify novel and previously reported mutations. Vero CCL-81 cells were able to support the growth of SARS-CoV-2 in vitro, and mutations were detected from the two isolates sequenced (001 and 002). These virus isolates will be expanded and made available to the Kenya Ministry of Health and other research institutions to advance SARS-CoV-2 research in Kenya and the region.Author SummaryThe Coronavirus disease 2019 (COVID-19) pandemic is caused by a type of coronavirus that emerged in Wuhan, China in December 2019 and later spread to almost all countries. Many countries are still finding ways to contain it. The virus has been studied in many ways to investigate its origin, infectivity, and evolution. Different variants of the virus have emerged and spread, causing a lot of concern as to whether the pandemic will end soon. Significant studies have proven the ability of the virus to grow in the laboratory using cell lines that offer the necessary conditions. Therefore, this study sought to find out the growth of the virus in specific monkey cell line and the variant circulating within the Kenyan population. We found that the selected cell lines supported viral growth outside a human host system. In addition, the circulating virus was found to have evolved to enhance its survival mechanism. This is the first study in Kenya to report this virus’s isolation, culture, and identification in monkey kidney cells. These cells supported the growth of the virus in the laboratory and analysing the genome of the growth products showed the virus was related to previously reported strains with multiple changes in its whole DNA sequence.
Mind the Gap! Developing Patient Responsive Information for Epilepsy
Authors: Jones Sarah , Angus-Leppan Heather 
Published: August 2022

AbstractTechnology must adapt to changing expectations about shifting patient needs and accessing health services. Standardised websites provide information often in the “frequently asked questions” format. There is little research about how much these answer the questions of people with epilepsy (PWE).This study used social media data to analyse the questions PWE have relating to “what would you ask a neurologist/epileptologist” and “do you have any questions relating to your epilepsy”. The study resulted in 2752 questions from PWE in Europe, North America and Australia, presented in the raw data format of natural language. Questions were themed using an unsupervised topic modelling algorithm to process and categorise the data into an aggregated question set.Many of the questions are not currently answered by Epilepsy charity and medical websites, and many centre on restrictions and fears about lifestyle. This study acts as the first stage toward the supervised topic classification: providing a list of questions to be submitted for answering by healthcare professionals required for a Virtual Assistant.The ultimate aim of the project is to generate a Virtual Assistant/Chatbot for the use of PWE to provide accurate and interactive responses to their real questions.
The divergent effects of neat food presentation on purchase likelihood: the moderating role of time-related positioning
Authors: Quach Sara , Septianto Felix , Thaichon Park 
Published: August 2022

PurposeUnderpinned by the fit-fluency framework, this research aims to explore the effect of visual entropy (i.e. the neatness or disorder of food presentation) on the likelihood to purchase under different time-related positioning conditions.Design/methodology/approachTwo experiments were conducted with customers who are located in the USA via Amazon Mechanical Turk. Study 1 employed a 2 (visual entropy: neat vs non-neat) × 2 (time-related positioning: traditional vs modern) between-subjects design using four advertisements for a fictitious ice cream brand. Study 2 employed a 2 (visual entropy: neat vs non-neat) × 2 (time-related positioning: traditional vs modern) between-subjects design using four book covers for fruit salad recipes.FindingsThe findings demonstrate low entropy (i.e. neatness) increases purchase likelihood when being paired with modern positioning, whilst high entropy (i.e. non-neat presentation) positively influences the propensity to purchase a traditional product on account of temporal fit. These relationships are mediated by perceived quality and nostalgia.Originality/valueThis research extends the understanding of visual entropy and addresses the inconclusive evidence of the impact of the neatness of product presentation on consumer behavior. The authors elucidate the mechanisms behind which neatness and non-neatness of food presentation affect purchase likelihood when different types of time-related positioning are featured.