bluuebunny/crossref_metadata_2025_split huggingface dataset:
Divergent east-west lineages in an Australian fruit fly associated with the Carpentaria basin divide
Authors: Manawaduge Chapa G. , Clarke Anthony R. , Hurwood David A. 
Published: October 2022

AbstractBactrocera jarvisi is an endemic Australian fruit fly species (Diptera: Tephritidae). It occurs commonly across tropical and subtropical coastal Australia, from far-northern Western Australia, across the ‘Top End’ of the Northern Territory, and then down the Queensland east coast. Across this range, its distribution crosses several well documented biogeographic barriers. In order to better understand factors leading to the divergence of Australian fruit fly lineages, we carried out a population genetic study of B. jarvisi from across its range using genome-wide SNP analysis, utilising adult specimens gained from trapping and fruit rearing. Populations from the Northern Territory (NT) and Western Australia were genetically similar to each other, but divergent from the genetically uniform east-coast (=Queensland, QLD) population. Phylogenetic analysis demonstrated that the NT population derived from the QLD population. We infer a role for the Carpentaria Basin as a biogeographic barrier restricting east-west gene flow. The QLD populations were largely panmictic and recognised east-coast biogeographic barriers play no part in north-south population structuring. While the NT and QLD populations were genetically distinct, there was evidence for the historically recent translocation of flies from each region to the other. Flies reared from different host fruits collected in the same location showed no genetic divergence. While a role for the Carpentaria Basin as a barrier to gene flow for Australian fruit flies agrees with existing work on the related B. tryoni, the reason(s) for population panmixia for B. jarvisi (and B. tryoni) over the entire Queensland east coast, a linear north-south distance of >2000km, remains unknown.
Diversity-stability relationships become decoupled across spatial scales: a synthesis of organism and ecosystem types
Authors: Wisnoski Nathan I. , Andrade Riley , Castorani Max C.N. , Catano Christopher P. , Compagnoni Aldo , Lamy Thomas , Lany Nina K. , Marazzi Luca , Record Sydne , Smith Annie C. , Swan Christopher M. , Tonkin Jonathan D. , Voelker Nicole M. , Zarnetske Phoebe L. , Sokol Eric R. 
Published: October 2022

ABSTRACTThe relationship between biodiversity and stability, or its inverse, temporal variability, is multidimensional and complex. Temporal variability in aggregate properties, like total biomass or abundance, is typically lower in communities with higher species diversity (i.e., the diversity-stability relationship or DSR). Recent work has shown that, at broader spatial extents, regional-scale aggregate variability is also lower with higher regional diversity (in plant systems) and with lower spatial synchrony. However, it is not yet clear whether regional DSRs hold across a broad range of organisms and ecosystem types. Furthermore, focusing exclusively on aggregate properties of communities may overlook potentially destabilizing compositional shifts. To test these questions, we compiled a large collection of long-term spatial metacommunity data spanning a wide range of taxonomic groups (e.g., birds, fish, plants, invertebrates) and ecosystem types (e.g., deserts, forests, oceans). We applied a newly developed quantitative framework for jointly analyzing aggregate and compositional variability across scales. We quantified DSRs for composition and total abundance in local communities and metacommunities. At the local scale, compositional DSRs suggested that higher local (α) diversity was associated with lower variability in animal populations but higher variability in plant populations, while aggregate DSRs supported the classic stabilizing effects of diversity. Spatial synchrony differed among taxa (birds had the lowest, plants the highest), suggesting differences in stabilization by spatial processes. Spatial synchrony declined with higher diversity among sites (β) for both compositional and aggregate properties. However, at the regional (γ) scale, we found no aggregate DSR, but a positive compositional DSR. Across a broader range of taxa, our results suggest that high γ-diversity does not consistently stabilize aggregate properties at regional scales without sufficient spatial β-diversity to reduce spatial synchrony.Open research statementAll data sets are accessible via the Environmental Data Initiative, and a specific data package of the data sets used in this analysis will be made publicly available (doi: pending). Citations to original sources are included in Appendix S1. Code to reproduce the analyses is found in a Zenodo archive (doi: pending) of the GitHub repository for this project (https://github.com/sokole/ltermetacommunities/tree/master/Manuscripts/MS3).
Integrity of the minor spliceosome in the developing mouse hypothalamus determines neuronal subtype composition regulating energy balance
Authors: White Alisa K. , Drake Kyle D. , Porczak Alexandra E. , Tirado-Mansilla Gabriela , Lee Madisen F. , Hyatt Katery C. , Chow Chrissy , DeQuattro Tava , Mickelsen Laura E. , Sciolino Natale R. , Jackson Alexander C. , Kanadia Rahul N. 
Published: October 2022

AbstractWhile gene regulatory networks underlying hypothalamic development are being characterized, minor intron splicing remains unexplored. Here, we usedNkx2.1-Creto ablateRnu11, encoding the minor spliceosome-specific U11 snRNA, in the progenitors of the ventral diencephalon (VD), to study minor intron splicing in hypothalamic development and control of energy balance in mice. Loss of U11 resulted in aberrant minor intron splicing, mitotic stalling, apoptosis, and altered neurogenesis. Mutant mice exhibited gross dysgenesis of hypothalamic architecture, while single-cell RNA sequencing (scRNAseq) revealed aberrant composition of neuronal subtypes implicated in feeding and energy balance. Mutant weanlings failed to thrive, followed by rapid weight gain, resulting in obesity. Assessment of energy imbalance and pair-feeding demonstrated that hyperphagia in adult mutants initiates weight gain, and is compounded by metabolic dysfunction, ultimately resulting in obesity. Our findings suggest a key role of minor intron splicing in the developmental patterning of hypothalamic neuronal subtypes underlying energy balance.
The Development and Validation of a Portable, Benchtop, Hydrostatic Model to Acquire and Analyze Quantitative Data on Unused and Failed Hydrocephalus Catheters
Authors: Gopalakrishnan Pranav , Faryami Ahmad , Harris Carolyn A. 
Published: October 2022

AbstractIntroductionDespite the prevalence of shunt failure in the treatment of hydrocephalus and the near-constant need for shunt revisions, there are a limited number of methods that yield quick, quantifiable measures of catheter obstruction. We developed and assessed a gravity-driven device that measures flow through ventricular catheters. The model provides neurosurgeons with a quick, simple device that can send useful data to researchers. It can also be used by researchers to quantitatively compare catheter obstruction between different models of catheters. The model was used in this study to quantitatively analyze unused ventricular catheters used in the treatment of hydrocephalus; failed hydrocephalus catheters from our catheter biorepository were also quantitatively analyzed using the same device. The mechanisms of catheter obstruction are still poorly understood, but the literature suggests that resistance to fluid flow plays a significant role.MethodsCatheters of three manufacturing companies were inserted into the benchtop model, which records time, flow rate, and pressure data using sensors. The relative resistances of catheters across six design models were evaluated. Experiments were performed to evaluate changes in the relative resistance of a catheter when the catheter’s holes were progressively closed. Relative resistance of explanted catheters from our catheter biorepository was also measured.ResultsExperimental results showed significant differences (P < 0.05) between the relative resistances of different catheter models just after being removed from their packaging. Furthermore, a trend of increasing resistance was observed in the experiments on catheters with manually plugged ventricular catheter holes. Data from five individual benchtop models were compared, and the differences in measured data between the models were found to be negligible. A significant increase (P < 0.05) in relative resistance was observed in explanted catheters.ConclusionThe current study is meant both to validate the proposed model and to examine data on differences in relative resistance among catheter models. From these experiments, we can rapidly correlate clinical patient cohorts to identify mechanisms of luminal shunt obstruction. Collecting data for predictive analyses of potential patient outcomes is an area of potential future work, assuming sufficient sample size.
The Association of Racial Residential Segregation and Long-Term Outcomes after Out-Of-Hospital Cardiac Arrest Among Medicare Beneficiaries
Authors: Abbott Ethan E , Buckler David G , Hsu Jesse Y , Abella Benjamin S , Richardson Lynne D. , Carr Brendan G , Zebrowski Alexis M 
Published: October 2022

AbstractBackgroundRacial residential segregation in the US is associated with poor health outcomes across multiple chronic conditions including cardiovascular disease. However, the national impact of racial residential segregation on out-of-hospital cardiac arrest (OHCA) outcomes after initial resuscitation remains poorly understood. We sought to characterize the association between measures of racial and economic residential segregation at the ZIP code level and long-term survival after OHCA among Medicare beneficiaries.MethodsIn this retrospective cohort study, utilizing Medicare fee-for-service claims data from 2013-2015, our primary predictor was the index of concentration at the extremes (ICE), a measure of racial and economic segregation. The primary outcomes were death at 1 and 3 years. Using random-effects Cox proportional hazards models, including a shared frailty term to account for clustering at the hospital level, we estimated hazard ratios across all three types of ICE measures for each outcome while adjusting for beneficiary demographics, treating hospital characteristics, and index hospital procedures.ResultsWe identified 29,847 OHCA claims for beneficiaries who survived to discharge after an OHCA. Mean beneficiary age was 75 years (SD 8); 40.1% were female, 80% White and 15.2% Black. Overall crude survival for the cohort was 54% (n=16,129) at 1 year and 40.8% (n= 12,189) at 3 years. In fully adjusted models we found a decreased hazard of death in beneficiaries residing in the most racially and economically privileged ZIP codes (Q5) compared to the least privileged areas (Q1) across all three ICE measures (race: HR:0.84; CI 0.79-0.88, income: HR 0.76; CI 0.73-0.81, race + income: HR 0.78; CI 0.74-0.83)ConclusionWe found a decreased hazard of death for those residing in predominately White and higher income ZIP codes as compared to majority Black and lower income ZIP codes when using validated measures of racial and economic segregation. Future work will need to more closely examine the causal pathways and mechanisms related to disparities in outcomes after OHCA to better understand the impacts of spatial and living environments on long-term outcomes.
Associations between affective/vegetative neuropsychiatric symptoms and brain morphology in aging people with mild cognitive impairment and Alzheimer’s disease
Authors: Cannizzaro Adriana , Ronat Lucas , El Haffaf Lyna Mariam , Hanganu Alexandru ,   the ADNI
Published: October 2022

ObjectivesNeuropsychiatric symptoms (NPS) are common in mild cognitive impairment (MCI) and even more so in Alzheimer’s disease (AD). The affective/vegetative NPS cluster model (sleep disorders, depression, appetite changes, anxiety, and apathy) has been associated with an increased risk of dementia in patients with MCI and these five NPS have common neuroanatomical associations. Hence, in this study, we examined how brain morphology is influenced by the severity of affective/vegetative NPS across different stages of cognitive performance.Participants175 AD, 367 MCI and 223 cognitively normal (CN) participants.SettingParticipants were recruited at multiple centers in North America included in the ADNI project.DesignA GLM was established to test for intergroup differences (CN -MCI, CN-AD, AD-MCI) of the effects of the five NPS on brain structures. A regression model was also performed to show slope directionality of the regions of interest as NPS severity increases.Measurements3T MRI data (cortical volumes, areas and thickness) and severity scores of the five NPS.ResultsAssociations within AD were predominantly stronger compared to MCI. Increased severity of sleep disorders and appetite changes were associated with a decrease in frontal surface areas in AD. Furthermore, increased severity of all NPS (except apathy) were associated with changes in the temporal regions, predominantly with decreased volumes and surface areas.ConclusionThese findings show the implication of fronto-temporal regions with sleep disorders, depression and appetite changes, and contribute to a better understanding of brain morphological differences between CN, MCI and AD with respect to all five NPS.
Machine learning analysis of a digital insole versus clinical standard gait assessments for digital endpoint development
Authors: Wipperman Matthew F. , Lin Allen Z. , Gayvert Kaitlyn M. , Lahner Benjamin , Somersan-Karakaya Selin , Wu Xuefang , Im Joseph , Lee Minji , Koyani Bharatkumar , Setliff Ian , Thakur Malika , Duan Daoyu , Breazna Aurora , Wang Fang , Lim Wei Keat , Halasz Gabor , Urbanek Jacek , Patel Yamini , Atwal Gurinder S. , Hamilton Jennifer D. , Huyghues-Despointes Clotilde , Levy Oren , Avbersek Andreja , Alaj Rinol , Hamon Sara C. , Harari Olivier 
Published: October 2022

AbstractBiomechanical gait analysis informs clinical practice and research by linking characteristics of gait with neurological or musculoskeletal injury or disease. However, there are limitations to analyses conducted at gait labs as they require onerous construction of force plates into laboratories mimicking the lived environment, on-site patient assessments, as well as requiring specialist technicians to operate. Digital insoles may offer patient-centric solutions to these challenges. In this work, we demonstrate how a digital insole measuring osteoarthritis-specific gait signatures yields similar results to the clinical gait-lab standard. To achieve this, we constructed a machine learning model, trained on force plate data collected in participants with knee arthropathy and healthy controls. This model was highly predictive of force plate data from a validation set (area under the receiver operating characteristics curve (auROC) = 0.86; area under the precision-recall curve (auPR) = 0.90) and of a separate, independent digital insole dataset containing control and knee osteoarthritis subjects (auROC = 0.83; auPR = 0.86). After showing that digital insole derived gait characteristics are comparable to traditional gait measurements, we next show that a single stride of raw sensor time series data could be accurately assigned to each subject, highlighting that individuals (even healthy) using digital insoles can be identified by their gait characteristics. This work provides a framework for a promising alternative to traditional clinical gait analysis methods, adds to the growing body of knowledge regarding wearable technology analytical pipelines, and supports clinical development of at-home gait assessments, with the potential to improve the ease, frequency, and depth of patient monitoring.One Sentence SummaryBiosensor data collected by digital insoles is comparable to lab-based clinical assessments and can be used to identify subject-specific gait patterns.
Generative Modeling of Single Cell Gene Expression for Dose-Dependent Chemical Perturbations
Authors: Kana Omar , Nault Rance , Filipovic David , Marri Daniel , Zacharewski Tim , Bhattacharya Sudin 
Published: October 2022

AbstractSingle cell sequencing provides a new opportunity to study the heterogeneity of chemical perturbation within tissues. However, exploring the combinatorial space of all cell type-chemical combinations is experimentally and financially unfeasible. This space is significantly expanded by the dose axis of chemical perturbation. Thus, computational tools are needed to predict responses not only across tissues, but also across doses while capturing the nuances of cell type specific gene expression. Variational autoencoders simplify the single cell expression space allowing cross cell type predictions using simple vector arithmetic. However, differing sensitivities and non-linearities make cell type specific gene expression predictions following treatment at higher doses challenging. Here we introduce single cell Variational Inference of Dose-Response (scVIDR) which achieves high dose and cell type specific predictions better than other state of the art algorithms. scVIDR predicts in vivo and in vitro dose-dependent gene expression across cell types in mouse liver, peripheral blood mononuclear cells, and cancer cell lines. We use regression to interpret the outputs of scVIDR. Additionally, we use scVIDR to order individual cells based on their sensitivities to a particular chemical by assigning a pseudo-dose value to each cell. Taken together, we show that scVIDR can effectively predict the dose and cell state dependent changes associated with chemical perturbations.
Coinfection with Intestinal Parasite Expands Resident Macrophages and Impairs Control of Chronic Herpesvirus Infection
Authors: Zarek Christina M. , Dende Chaitanya , Coronado Jaime , Pendse Mihir , Dryden Phillip , Hooper Lora V. , Reese Tiffany A. 
Published: October 2022

AbstractIn addition to a range of homeostatic functions, resident macrophages are essential for immune surveillance in tissues. Therefore, anything that alters the phenotype or function of these cells potentially impacts their response to infectious challenges. Parasite infections cause proliferation of large peritoneal macrophages (LPMs), which are the resident macrophages of the peritoneal cavity. However, the functional consequences of LPM expansion on the control of secondary infectious challenge is unknown. Using a coinfection model with the intestinal parasite Heligmosomoides polygyrus (HP) and the virus, murine gammaherpesvirus-68 (MHV68), we investigated the impact of LPM expansion on viral infection. We determined that LPM expansion induced by HP required retinoic acid signaling. When we challenged HP-infected mice with MHV68, we observed increased herpesvirus infection and latency. Coinfection of mice with macrophage-specific deletion of GATA6, the retinoic acid-responsive transcription factor that drives LPM transcriptional programming, eradicated the increase in viral infection. In addition to increased MHV68 infection, parasite coinfected mice displayed increased herpesvirus reactivation from latency, indicating impaired control of chronic herpesvirus infection. Elimination of dietary vitamin A, which depletes retinoic acid and LPMs, abolished the increased MHV68 reactivation in parasite coinfected mice. These results indicate that parasite- and retinoic acid-mediated resident macrophage expansion drives increased herpesvirus infection, latency, and reactivation.
A semi-automatic workflow to process camera trap images in R
Authors: Böhner Hanna , Kleiven Eivind Flittie , Ims Rolf Anker , Soininen Eeva M. 
Published: October 2022

AbstractCamera traps have become popular for monitoring biodiversity and animal populations. Artificial intelligence is increasingly used to automatically classify large image data sets produced by camera traps and many tools that incorporate machine-learning models for automatic image classification have been developed over the last years. However, it is still challenging to combine tools for automatic classification with other tools for processing camera trap images and to adapt these tools to a specific study. Therefore, we propose a semi-automatic workflow for processing camera trap images in R. The workflow includes managing raw images, automatic image classification, a quality check of automatic image labels as well as the possibilities to retrain the model with new images and to manually review subsets of images to correct image labels. We illustrate the workflow with a case-study from the small mammal monitoring program of the Climate-ecological Observatory for Arctic Tundra. We first trained a classification model for small mammals and then transferred the model to new images, including images from newly established camera traps. We could show that retraining the original model with a small number of new images increased model performance and therefore highlight the importance of verifying automatic image labels when a model was transferred to new images. Furthermore, retraining the original model also decreased the time needed for manually reviewing images and correcting image labels substantially. Thus, the proposed workflow results in a data set with high accuracy and minimizes time needed for labeling images manually. This is especially useful for long-term monitoring where new images have to be processed continuously and methods have to be adapted over time. We provide all R scripts and the classification model for small mammals to make the workflow accessible to other ecologists.
Nanopore sequencing of human associated methicillin-resistant Staphylococcus aureus RWP1 genome for inferring antibiotic resistant gene, plasmid and prophage information
Authors: Basharat Zarrin 
Published: October 2022

AbstractMethicillin-resistant Staphylococcus aureus (MRSA) is a gram-positive bacterium and responsible for several infections in the human. Here, Oxford nanopore mediated whole genome sequencing is reported for human host associated strain. The genome size obtained was of ~3 MB, while GC content was 32.9%. Approximately 3600 CDSs, 62 tRNAs and 16 rRNAs were identified. Phage segments were present, with two complete intact phages. Type I and type IV restriction elements were also detected, along with five plasmids. Several antibiotic resistance genes were also mined, with a key mutation in the fluoroquinolone resistant gyrA, phosphonic acid resistant murA transferase and fusidic acid resistant fusA genes. Sequence type was determined as 4803. Comparative analysis with MRSA isolates from Pakistan (n=20) revealed an open pan-genome, with 1,934 CDSs forming core genome.