bluuebunny/crossref_metadata_2025 huggingface dataset:
Community engagement through “student-led science” for dengue prevention during the COVID-19 pandemic in Córdoba, Argentina
Authors: Estallo Elizabet L. , Madelon Magali , Benitez Elisabet M. , Stewart-Ibarra Anna M. , Ludueña-Almeida Francisco F.
Published: October 2022

Background

During 2019-2020 while COVID-19 pandemic, the Americas were facing the biggest dengue fever epidemic in recent history. Traditional vector control programs, based on insecticide application have been insufficient to control the spread of dengue fever. Several studies suggest refocusing on education with the aim of an integrated vector management strategy within the local ecological-community context. We aim to assess community perceptions, knowledge, attitude, preventive practice, and action through student-led science assignments regarding dengue fever, prevention, and socio-ecological factors in temperate Córdoba, Argentina.

Methods

The study was conducted during the COVID-19 quarantine when schools switched to online education for the first time. Several activities through Google Classroom platform included a survey to one student’s family member, and an outdoor activity to assess their attitudes and to clean the backyard and gardens.

Results

Significant number of respondents developed good preventive practices and increased their knowledge about the vector and disease highlighting that 75% of responders knew that dengue fever was transmitted by a mosquito, 81.96% declared having obtained knowledge regarding dengue and vector through television, 56% affirm that dengue is a severe illness, 67% of respondents admitted that individuals play an important role in the prevention of dengue. Regarding mosquito control activities, 90% of respondents reported turning containers.

Conclusions

This highlights the need for school programs with curricula to address vector biology and the prevention of vector-borne diseases not only during activity periods when mosquitoes batter people but all year long to do real prevention.
Perioral secretions enable complex social signaling in African mole-rats (genus Fukomys)
Authors: Caspar Kai R. , Stopka Pavel , Issel Daniel , Katschak Kristin , Zöllner Till , Zupanc Sina , Žáček Petr , Begall Sabine
Published: October 2022

Subterranean common mole-rats of the genus Fukomys (family Bathyergidae) live in large cooperatively-breeding families. Odor cues have been hypothesized to importantly mediate social behaviors in the underground ecotope, but only little is known about the role of olfactory signaling in burrowing mammals. Here we characterize the so far neglected perioral glands of Fukomys and other African mole-rats as an important source of olfactory social information. Histology demonstrates these structures to be derived sebaceous glands that are developed regardless of sex and reproductive status. However, gland activity is higher in Fukomys males, leading to sexually dimorphic patterns of stain and clotting of the facial pelage. Behavioral assays revealed that conspecifics prefer male but not female perioral swabs over scent samples from the back fur and that male sebum causes similar attraction as anogenital scent, a known source of social information in Fukomys. Finally, we assessed volatile compounds in the perioral sebum of the giant mole-rat (Fukomys mechowii) via GCxGC-MS-based metabolomic profiling. Volatiles displayed pronounced sex-specific signatures but also allowed to differentiate between intrasexual reproductive status groups. These different lines of evidence suggest that mole-rat perioral glands provide complex odor signals that play a crucial role in social communication.
A guide to the manufacture of sustainable, ready to use in vitro platforms for the electric-field pacing of cellularised 3D porous scaffolds
Authors: Solazzo Matteo , Monaghan Michael G.
Published: October 2022

Electrical activity is a key feature of most native tissues, with the most notable examples being the nervous and the cardiac systems. Modern medicine has moved towards the mimicking and regenerations of such systems both with in vitro models and therapies. Although researchers have now an increased repertoire of cell types and bio-physical cues to generate increasingly complex in vitro models, the inclusion of novel biomaterials in such systems has been negligible, with most approaches relying on scaffold-free self-assembling strategies. However, the rapid development of functional biomaterials and fabrication technologies - such as electroconductive scaffolds – warrants consideration and inclusion of materials, with recent evidence supporting the benefit of incorporating electrically active materials and their influence on the maturation of cardiac cells and tissues. In order to be manipulated in bioreactor systems, scaffold-based in vitro models require bespoke rig and bioreactors that vary from those commonly used for scaffold-free systems. In this work, we detail methods to rapid prototype an electrical pacing bioreactor and R3S - a Rig for Stimulation of Sponge-like Scaffolds. As a proof of concept and validation we demonstrate that these systems are compatible with isotropic and anisotropic porous scaffolds composed of collagen or poly(3,4-ethylene dioxythiophene):polystyrene sulfonate (PEDOT:PSS). External pacing of C3H10 cells on anisotropic porous scaffolds led to a metabolic increase and enhanced cell alignment. This setup has been designed for pacing and simultaneously live tracking of in vitro models. This platform has wide suitability for the study of electrical pacing of cellularized scaffolds in 3D in vitro cultures.
Nature portrayed in images in Dutch Brazil: Tracing the sources of the plant woodcuts in theHistoria Naturalis Brasiliae(1648)
Authors: Alcantara-Rodriguez Mireia , Van Andel Tinde , Françozo Mariana
Published: October 2022

By the mid-seventeenth century, images of natural elements that originated in Dutch Brazil circulated in Europe. These were often included in art collections (theLibri Picturati), and natural history treatises (theHistoria Naturalis Brasiliaeand theIndia Utriesque re Naturale et Medica). The plant woodcut images in these books constituted (icono) type specimens and played a significant role in the transmission of (botanical) knowledge. We present a systematic analysis of their origins by cross-referencing the visual and textual sources related to Dutch Brazil. To do so, we used the scientific identifications of the portrayed plants and digital archival material. The plant woodcuts accounted for 529 images, which correspond to 426 taxa. We created a PDF booklet to visualize the correlations of the woodcuts with theLibri Picturatiand other visual sources. Substantial differences in the visual-making methodology exist between the two treatises (1648, 1658). Overall, availability, economy, and the Indigenous Tupi-based plant names that accompanied the images were crucial when arranging the sources, as well as portraying as much botanical information as possible.

Freshly picked, living plants, and dried branches, fruits, and seeds were used to represent the megadiverse Brazilian flora, even when these belonged to species originating from other regions. Despite not being recognized for their contribution, Indigenous Brazilians and enslaved Africans were essential in the visual knowledge-making processes that later resulted in these natural history collections. As several sources remain lost and many histories yet untold, further archival studies and collaborative projects are pertinent to reveal the missing pieces of this conundrum.
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

Bactrocera 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

The 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 statement

All 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

While 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

Introduction

Despite 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.

Methods

Catheters 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.

Results

Experimental 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.

Conclusion

The 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

Background

Racial 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.

Methods

In 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.

Results

We 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)

Conclusion

We 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

Objectives

Neuropsychiatric 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.

Participants

175 AD, 367 MCI and 223 cognitively normal (CN) participants.

Setting

Participants were recruited at multiple centers in North America included in the ADNI project.

Design

A 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.

Measurements

3T MRI data (cortical volumes, areas and thickness) and severity scores of the five NPS.

Results

Associations 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.

Conclusion

These 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

Biomechanical 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 Summary

Biosensor 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

Single 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

In 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

Camera 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

Methicillin-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.
Biomechanical Stimulation of Muscles Influences Bone Phenotype by Modulating Myokine Secretion
Authors: Suresh Kumar Harshini , Barnett Edwina N. , Kalaitzoglou Evangelia , Fowlkes John L. , Annamalai Ramkumar T.
Published: October 2022

Diabetes is a chronic metabolic disorder that affects 422 million people worldwide and can lead to diabetic myopathy and bone diseases. The etiology of musculoskeletal complications in diabetes and the interplay between the muscular and osseous systems are poorly understood. Exercise training promises to prevent diabetic myopathy and diabetic bone disease and offer protective effects on muscle and bone. Although the muscle-bone interaction is largely biomechanical, the muscle secretome, specifically the myokines, has significant implications for bone biology. Here, we have developed an in vitro model to elucidate the effects of mechanical strain on myokine secretion and its impact on bone metabolism decoupled from physical stimuli. We developed modular bone constructs using crosslinked gelatin hydrogels which facilitated osteogenic differentiation of osteoprogenitor cells. Then muscle constructs were made from fibrin hydrogel, which enabled myoblast differentiation and formed mature myotubes. We investigated the myokine expression by the muscle constructs under strain regimens replicating endurance (END) and high-intensity interval training (HIIT) in hyperglycemic conditions. In monocultures, both regimens induced higher expression of Il15 and Igf1, while END supported more myoblasts differentiation and myotube maturation than HIIT. When cocultured with bone constructs, the HIIT regimen increased Glut4 expression in muscle contructs that END supporting higher glucose uptake. Likewise, the muscle constructs under the HIIT regimen promoted a healthier and matured bone phenotype than END. Interestingly, under static conditions, myostatin (Mstn) expression was significantly downregulated in muscle constructs cocultured with bone constructs compared to monocultures. Our in vivo analysis of the role of myostatin on bone structure and function also showed that myostatin knockout (GDF8-/-) enhanced muscle mass and moderately influenced bone phenotype in adult mice. Together, our in vitro coculture system allowed orthogonal manipulation of mechanical strain on muscle constructs while facilitating biochemical crosstalk between bone and muscle constructs. Such systems can provide an individualized microenvironment and allow decoupled biomechanical manipulation, which is unachievable using traditional models. In the long-term, these in-vitro systems will help identify molecular targets and develop engineered therapies for diabetic bone disease.
Iron Chelation Improves Ineffective Erythropoiesis and Iron Overload in Myelodysplastic Syndrome Mice
Authors: An Wenbin , Feola Maria , Aluri Srinivas , Ruiz-Martinez Marc , Shridharan Ashwin , Levy Maayan , Fibach Eitan , Zhu Xiaofan , Verma Amit , Ginzburg Yelena Z.
Published: October 2022

Myelodysplastic syndrome (MDS) is a heterogeneous group of bone marrow stem cell disorders characterized by ineffective hematopoiesis and cytopenias, most commonly anemia. Red cell transfusion therapy for anemia in MDS results in iron overload, correlating with reduced overall survival. Whether treatment of iron overload benefits MDS patients remains controversial. We evaluate underlying iron-related pathophysiology and the effect of iron chelation using deferiprone on erythropoiesis inNUP98-HOXD13transgenic mice, a highly penetrant well-established MDS mouse model. Our results characterize an iron overload phenotype with aberrant erythropoiesis in these mice which was reversed by deferiprone-treatment. Serum erythropoietin level decreased while erythroblast erythropoietin receptor expression increased in deferiprone-treated MDS mice. We demonstrate, for the first time, normalized expression of the iron chaperonesPcbp1andNco4and increased ferritin stores in late stage erythroblasts from deferiprone-treated MDS mice, evidence of aberrant iron trafficking in MDS erythroblasts. Importantly, erythroblast ferritin is increased in response to deferiprone, correlating with decreased erythroblast ROS. Finally, we confirmed increased expression of genes involved in iron uptake, sensing, and trafficking in stem and progenitor cells from MDS patients. Taken together, our findings provide evidence that erythroblast-specific iron metabolism is a novel potential therapeutic target to reverse ineffective erythropoiesis in MDS.

BRIEF SUMMARY

Ineffective erythropoiesis in MDS mice correlates with aberrant iron trafficking within bone marrow erythroblasts, consistent with findings in MDS patient progenitors, reversed after iron chelation.
A Synthetic ERRα Agonist Induces an Acute Aerobic Exercise Response and Enhances Exercise Capacity
Authors: Billon Cyrielle , Sitaula Sadichha , Banerjee Subhashis , Welch Ryan , Elgendy Bahaa , Hegazy Lamees , Oh Tae Gyu , Kazantzis Melissa , Chatterjee Arindam , Chrivia John , Hayes Matthew E. , Xu Weiyi , Hamilton Angelica , Huss Janice M. , Zhang Lilei , Walker John K , Downes Michael , Evans Ronald M. , Burris Thomas P.
Published: October 2022

Repetitive physical exercise induces physiological adaptations in skeletal muscle that improves exercise performance and is effective for the prevention and treatment of several diseases. Here we report the identification of a synthetic agonist for the orphan nuclear receptor ERRα (estrogen receptor-related receptor α), SLU-PP-332, that activates an acute aerobic exercise genetic program in skeletal muscle in an ERRα-dependent manner. SLU-PP-332 increases mitochondrial function and cellular respiration consistent with induction of this genetic program. When administered to mice, SLU-PP-332 increased the type IIa oxidative skeletal muscle fibers and enhanced exercise endurance. These data indicate the feasibility of targeting ERRα for development of compounds that act as exercise mimetics that may be effective in treatment of numerous metabolic disorders and to improve muscle function in the aging.
Artificial Intelligence Guided Discovery of Gastric Cancer Continuum
Authors: Vo Daniella , Ghosh Pradipta , Sahoo Debashis
Published: October 2022

Background

Detailed understanding of pre, early and late neoplastic states in gastric cancer helps develop better models of risk of progression to Gastric Cancers (GCs) and medical treatment to intercept such progression.

Methods

We built a Boolean Implication network of gastric cancer and deployed machine learning algorithms to develop predictive models of known pre-neoplastic states, e.g., atrophic gastritis, intestinal metaplasia (IM) and low-to high-grade intestinal neoplasia (L/HGIN), and GC. Our approach exploits the presence of asymmetric Boolean Implication relationships that are likely to be invariant across almost all gastric cancer datasets. Invariant asymmetric Boolean Implication relationships can decipher fundamental time series underlying the biological data. Pursuing this method, we developed a healthy mucosa →GC continuum model based on this approach.

Results

Our model performed better against publicly available models for distinguishing healthy versus GC samples. Although not trained on IM and L/HGIN datasets, the model could identify the risk of progression to GC via the metaplasia →dysplasia →neoplasia cascade in patient samples. The model could rank all publicly available mouse models for their ability to best recapitulate the gene expression patterns during human GC initiation and progression.

Conclusions

A Boolean implication network enabled the identification of hitherto undefined continuum states during GC initiation. The developed model could now serve as a starting point for rationalizing candidate therapeutic targets to intercept GC progression.

MINI-ABSTRACT

We developed predictive models of early and late neoplastic states in gastric cancer and identified gene clusters that are up/down-regulated at various points along the gastric cancer disease continuum.
Non-Gaussian Normative Modelling With Hierarchical Bayesian Regression
Authors: de Boer Augustijn A.A. , Bayer Johanna M. M. , Kia Seyed Mostafa , Rutherford Saige , Zabihi Mariam , Fraza Charlotte , Barkema Pieter , Westlye Lars T. , Andreassen Ole A. , Hinne Max , Beckmann Christian F. , Marquand Andre
Published: October 2022

Normative modelling is an emerging technique for parsing heterogeneity in clinical cohorts. This can be implemented in practice using hierarchical Bayesian regression, which provides an elegant probabilistic solution to handle site variation in a federated learning framework. However, applications of this method to date have employed a Gaussian assumption, which may be restrictive in some applications. We have extended the hierarchical Bayesian regression framework to flexibly model non-Gaussian data with heteroskdastic skewness and kurtosis. To this end, we employ a flexible distribution from the sinh-arcsinh (SHASH) family, and introduce a novel reparameterisation and a Markov chain Monte Carlo sampling approach to perform inference in this model. Using a large neuroimaging dataset collected at 82 different sites, we show that the results achieved with this extension are equivalent or better than a warped Bayesian linear regression baseline model on most datasets, whilst providing better control over the parameters governing the shape of distributions that approach is able to model. We also demonstrate that the attained flexibility is useful for accurately modelling highly nonlinear relationships between aging and imaging derived phenotypes, which shows that the extension is important for pushing the field of normative modelling forward. All methods described here are available in the open-sourcepcntoolkit.

Highlights

We extended the Hierarchical Bayesian Regression framework for normative modelling

Our extension allows modelling data with heteroskedastic skewness and kurtosis

We developed a reparameterization of the SHASH distribution, suitable for sampling

We provide the first implementation of the SHASH distribution in a fully Bayesian framework

Results show that the extension outperforms current methods on various measures
Zebrafish screen of high-confidence effector genes at insomnia GWAS loci implicates conserved regulators of sleep-wake behaviors
Authors: Zimmerman Amber J. , Doldur-Balli Fusun , Keenan Brendan T. , Shetty Zoe Y. , Palermo Justin , Chesi Alessandra , Sonti Shilpa , Pahl Matthew C. , Brown Elizabeth B. , Pippin James A. , Wells Andrew D. , Veatch Olivia J. , Mazzotti Diego R. , Krishnan Anitra , Gehrman Phillip R. , Keene Alex C. , Grant Struan F.A. , Pack Allan I.
Published: October 2022

Recent large-scale human genome-wide association studies (GWAS) for insomnia have identified more than 200 significant loci. The functional relevance of these loci to the pathogenesis of insomnia is largely unknown. GWAS signals are typically non-coding variants, which are often arbitrarily annotated to the nearest protein-coding gene; however, due to 3D chromatin structure, variants can interact with more distal genes driving their function. The distal gene may, therefore, represent the true causal gene influencing the phenotype. By integrating our high-resolution chromatin interaction maps from neural progenitor cells with phenotypic data from aDrosophilaRNAi screen, we prioritized candidate genes that we hypothesized would have deep phylogenetic conservation of sleep function. To determine the conservation of these candidate genes in the context of vertebrate sleep and their relevance to insomnia-like behaviors, we performed CRISPR-Cas9 mutagenesis in larval zebrafish for six highly conserved candidate genes and examined sleep-wake behaviors using automated video-tracking. CRISPR mutation of zebrafish orthologs ofMEIS1andSKIV2Lproduced insomnia-like behaviors, while mutation ofARFGAP2impaired activity and development in our larval zebrafish model, demonstrating the importance of performing functional validation of GWAS-implicated effector genes to reveal genes influencing disease-relevant mechanisms.
Plant–hummingbird pollination networks exhibit minimal rewiring after experimental removal of a locally abundant plant species
Authors: Leimberger Kara G. , Hadley Adam S. , Betts Matthew G.
Published: October 2022

Mutualistic relationships, such as those between plants and pollinators, may be vulnerable to the local extinctions predicted under global environmental change. However, network theory predicts that plant–pollinator networks can withstand species loss if pollinators switch to alternative floral resources (rewiring). Whether rewiring occurs following species loss in natural communities is poorly known because replicated species exclusions are difficult to implement at appropriate spatial scales.

We experimentally removed a hummingbird-pollinated plant,Heliconia tortuosa, from within tropical forest fragments to investigate how hummingbirds respond to temporary loss of an abundant resource. Under therewiring hypothesis, we expected that niche expansions would decrease ecological specialization and reorganize the network structure (i.e., pairwise interactions).

We employed a replicated Before-After-Control-Impact experimental design and quantified plant–hummingbird interactions using two parallel sampling methods: observations of hummingbirds visiting focal plants (‘camera networks’, created from >19,000 observation hours) and pollen collected from individual hummingbirds (‘pollen networks’, created from >300 pollen samples). To assess hummingbird rewiring, we quantified ecological specialization at the individual, species, and network levels and calculated the amount of network-level interaction turnover (i.e., gain/loss of pairwise interactions). Leveraging our parallel network datasets, we also explored how sampling method influences apparent specialization.

H. tortuosaremoval caused some reorganization of pairwise interactions but did not prompt large changes in specialization, despite the large magnitude of our manipulation (on average, >100 inflorescences removed in treatment areas of >1 ha). Although some individual hummingbirds sampled through time showed modest increases in niche breadth followingHeliconiaremoval (relative to birds that did not experience resource loss), these changes were not reflected in species- and network-level specialization metrics. We also found that camera networks were more specialized than pollen networks, and that correlation between sampling methods was low.

Our results suggest that animals may not necessarily shift to alternative resources after losing an abundant food resource, even in species thought to be highly opportunistic foragers such as hummingbirds. Given that rewiring contributes to theoretical predictions of network stability, future studies should investigate why pollinators might not expand their diets after a local resource extinction.
Predicting Anti-Cancer Drug Combination Responses with a Temporal Cell State Network Model
Authors: Sarmah Deepraj , Meredith Wesley O , Weber Ian , Price Madison R , Birtwistle Marc R
Published: October 2022

Cancer chemotherapy combines multiple drugs, but predicting the effects of drug combinations on cancer cell proliferation remains challenging. We hypothesized that by combining knowledge of single drug dose responses and cell state transition network dynamics, we could predict how a population of cancer cells will respond to drug combinations. We tested this hypothesis here using three targeted inhibitors of different cell cycle states in two different cell lines. We formulated a Markov model to capture temporal cell state transitions between different cell cycle phases, with single drug data constraining how drug doses affect transition rates. This model was able to predict the landscape of all three different pairwise drug combinations across all dose ranges for both cell lines with no additional data. This work shows how currently available or attainable information could be combined to predict how cancer cell populations respond to drug combinations.
Spatial metabolomics for symbiotic marine invertebrates
Authors: Chan Wing Yan , Rudd David , van Oppen Madeleine J. H.
Published: October 2022

Microbial symbionts frequently localize within specific body structures or cell types of their multicellular hosts. This spatiotemporal niche is critical to host health, nutrient exchange and fitness. Measuring host-microbe metabolite exchange has conventionally relied on tissue homogenates, eliminating dimensionality and dampening analytical sensitivity. We have developed a mass spectrometry imaging (MSI) workflow for a soft- and hard-bodied cnidarian animal capable of revealing the host and symbiont metabolome in situ, without the need for a priori isotopic labelling or skeleton decalcification. The MSI method provides critical functional insights that cannot be gleaned from bulk tissue analyses or other presently available spatial methods. We show that cnidarian hosts may regulate microalgal symbionts acquisition and rejection through specific ceramides distributed throughout the tissue lining the gastrovascular cavity; once resident, symbionts reside in light-exposed tentacles to generate photosynthate. These spatial patterns reveal how symbiont identity can drive host metabolism.