bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comprehensive knowledgebase of known and predicted human genetic variants associated with COVID-19 susceptibility and severity
Authors: Kars Meltem Ece , Stein David , Sevim Bayrak Çiğdem , Stenson Peter D , Cooper David N , Itan Yuval 
Published: November 2022

AbstractHost genetic susceptibility is a key risk factor for severe illness associated with COVID-19. Despite numerous studies of COVID-19 host genetics, our knowledge of COVID-19-associated variants is still limited, and there is no resource comprising all the published variants and categorizing them based on their confidence level. Also, there are currently no computational tools available to predict novel COVID-19 severity variants. Therefore, we collated 820 host genetic variants reported to affect COVID-19 susceptibility by means of a systematic literature search and confidence evaluation, and obtained 196 high-confidence variants. We then developed the first machine learning classifier of severe COVID-19 variants to perform a genome-wide prediction of COVID-19 severity for 82,468,698 missense variants in the human genome. We further evaluated the classifier’s predictions using feature importance analyses to investigate the biological properties of COVID-19 susceptibility variants, which identified conservation scores as the most impactful predictive features. The results of enrichment analyses revealed that genes carrying high-confidence COVID-19 susceptibility variants shared pathways, networks, diseases and biological functions, with the immune system and infectious disease being the most significant categories. Additionally, we investigated the pleiotropic effects of COVID-19-associated variants using phenome-wide association studies (PheWAS) in ∼40,000 BioMe BioBank genotyped individuals, revealing pre-existing conditions that could serve to increase the risk of severe COVID-19 such as chronic liver disease and thromboembolism. Lastly, we generated a web-based interface for exploring, downloading and submitting genetic variants associated with COVID-19 susceptibility for use in both research and clinical settings (https://itanlab.shinyapps.io/COVID19webpage/). Taken together, our work provides the most comprehensive COVID-19 host genetics knowledgebase to date for the known and predicted genetic determinants of severe COVID-19, a resource that should further contribute to our understanding of the biology underlying COVID-19 susceptibility and facilitate the identification of individuals at high risk for severe COVID-19.
The mode effect of web-based surveying on the 2018 HRS measure of cognitive functioning
Authors: Domingue Benjamin W. , McCammon Ryan , West Brady T. , Langa Ken , Weir David , Faul Jessica 
Published: November 2022

AbstractMeasuring cognition in an aging population is a public health priority. A move towards survey measurement via the web (as opposed to phone or in-person) is cost effective but challenging as it may induce bias in cognitive measures. We examine this possibility using an experiment embedded in the 2018 wave of data collection for the US Health and Retirement Study (HRS). We find evidence of an increase in scores for HRS respondents who are randomly assigned to the web-based mode of data collection in 2018. Web-based respondents score higher in 2018 than do phone-based respondents, and they show much larger gains relative to 2016 performance and subsequently larger declines in 2020. The bias in favor of web-based responding is observed across all item types, but most pronounced for the serial 7 and items on financial literacy. These results imply a larger threshold for web-based respondents in applications requiring an indicator of cognitive impairment. Implications for both use of HRS data and future survey work on cognition are discussed.
Continuous automated analysis workflow for MRS studies
Authors: Zöllner Helge J. , Davies-Jenkins Christopher W. , Lee Erik G. , Hendrickson Timothy J. , Clarke William T. , Edden Richard A. E. , Wisnowski Jessica L. , Gudmundson Aaron T. , Oeltzschner Georg 
Published: November 2022

AbstractBackgroundMagnetic resonance spectroscopy (MRS) can non-invasively measure levels of endogenous metabolites in living tissue and is of great interest to neuroscience and clinical research. To this day, MRS data analysis workflows differ substantially between groups, frequently requiring many manual steps to be performed on individual datasets, e.g., data renaming/sorting, manual execution of analysis scripts, and manual assessment of success/failure. Manual analysis practices are a substantial barrier to wider uptake of MRS. They also increase the likelihood of human error and prevent deployment of MRS at large scale. Here, we demonstrate an end-to-end workflow for fully automated data uptake, processing, and quality review.New MethodThe proposed continuous automated MRS analysis workflow integrates several recent innovations in MRS data and file storage conventions. They are efficiently deployed by a directory monitoring service that automatically triggers the following steps upon arrival of a new raw MRS dataset in a project folder: (1) conversion from proprietary manufacturer file formats into the universal format NIfTI-MRS; (2) consistent file system organization according to the data accumulation logic standard BIDS-MRS; (3) executing a command-line executable of our open-source end-to-end analysis software Osprey; (4) e-mail delivery of a quality control summary report for all analysis steps.ResultsThe automated architecture successfully completed for a demonstration dataset. The only manual step required was to copy a raw data folder into a monitored directory.Comparison with Existing Method(s)The workflow presented here is the first implementation of a continuous automated MRS analysis ecosystem based on NIfTI-MRS and BIDS-MRS standards. Traditional MRS workflows are non-standardized, often require manual input, and frequently noy compatible with established neuroimaging workflows. This workflow should therefore facilitate integration of MRS into large-scale and multi-center studies.ConclusionsContinuous automated analysis of MRS data can reduce the burden of manual data analysis and quality control, particularly for non-expert users and multi-center or large-scale studies.
Weighing psychosocial factors in relatives for the risk of depressive and anxious psychopathology: A sibling-pair comparison study
Authors: van Sprang Eleonore D. , Maciejewski Dominique F. , Milaneschi Yuri , Kullberg Marie-Louise J. , Elzinga Bernet M. , van Hemert Albert M. , Hartman Catharina A. , Penninx Brenda W. J. H. 
Published: November 2022

AbstractPurposeSiblings of probands with depressive and anxiety disorders are at increased risk for psychopathology, but little is known about how risk factors operate within families to increase psychopathology for siblings. We examined the additional impact of psychosocial risk factors in probands – on top of or in combination with those in siblings – on depressive/anxious psychopathology in siblings.MethodsThe sample included 636 participants (Mage= 49.7; 62.4% female) from 256 families, each including a proband with lifetime depressive and/or anxiety disorders and their sibling(s) (N=380 proband-sibling pairs). Sixteen psychosocial risk factors were tested. In siblings, depressive and anxiety disorders were determined with standardized psychiatric interviews; symptom severity was measured using self-report questionnaires. Analyses were performed with mixed-effects models accounting for familial structure.ResultsIn siblings, various psychosocial risk factors (female gender, low income, childhood trauma, poor parental bonding, being single, smoking, hazardous alcohol use) were associated with higher symptomatology and likelihood of disorder. The presence of the same risk factor in probands was independently associated (low income, being single) with higher symptomatology in siblings or moderated (low education, childhood trauma, hazardous alcohol use) – by reducing its strength – the association between the risk factor and symptomatology in siblings. There was no additional impact of risk factors in probands on likelihood of disorder in siblings.ConclusionOur findings demonstrate the importance of weighing psychosocial risk factors within a family context, as it may provide relevant information on the risk of affective psychopathology for individuals.
A personal, reference quality, fully annotated genome from a Saudi individual
Authors: Kulmanov Maxat , Tawfiq Rund , Al Ali Hatoon , Abdelhakim Marwa , Alarawi Mohammed , Aldakhil Hind , Alhattab Dana , Alsolme Ebtehal A. , Althagafi Azza , Angelov Angel , Bougouffa Salim , Driguez Patrick , Liu Yang , Park Changsook , Putra Alexander , Reyes-Ramos Ana M. , Hauser Charlotte A. E. , Cheung Ming Sin , Abedalthagafi Malak S , Hoehndorf Robert 
Published: November 2022

AbstractWe have used multiple sequencing approaches to sequence the genome of a volunteer from Saudi Arabia. We use the resulting data to generate ade novoassembly of the genome, and use different computational approaches to refine the assembly. As a consequence, we provide a contiguous assembly of the complete genome of an individual from Saudi Arabia for all chromosomes except chromosome Y, and label this assemblyKSA001. We transferred genome annotations from reference genomes and predicted genome features using methods from Artificial Intelligence to fully annotateKSA001, and we make all primary sequencing data, the assembly, and the genome annotations freely available in public databases using the FAIR data principles.
Dose-response relationships of LSD-induced subjective experiences in humans
Authors: Hirschfeld Tim , Prugger Johanna , Majić Tomislav , Schmidt Timo T. 
Published: November 2022

AbstractLysergic acid diethylamide (LSD) is a potent classic serotonergic psychedelic, which facilitates a variety of altered states of consciousness. Here we present the first meta-analysis establishing dose-response relationship estimates of the altered experience induced by LSD. Data extracted from articles identified by a systematic literature review following PRISMA guidelines were obtained from the Altered States Database. The psychometric data comprised ratings of subjective effects from standardized and validated questionnaires: the Altered States of Consciousness Rating Scale (5D-ASC, 11-ASC) and the Mystical Experience Questionnaire (MEQ30). We performed meta-regression analyses using restricted cubic splines for data from studies with LSD doses of up to 200 μg base. Most scales revealed a sigmoid-like increase of effects with a plateauing at around 100 μg. The most strongly modulated factors referred to changes in perception and illusory imagination, followed by positively experienced ego-dissolution, while only small effects were found forAnxietyandDread of Ego Dissolution. The partly observed considerable variability of effects points to the importance of non-pharmacological effects on subjective experiences. The established dose-response relationships may be used as general references for future experimental and clinical research on LSD to relate observed with expected subjective effects and to elucidate phenomenological differences between psychedelics.
Symbiotic diazotrophic UCYN-A strains co-occurred with El Niño, relaxed upwelling, and varied eukaryotes over 10 years off Southern California Bight
Authors: Fletcher-Hoppe Colette , Yeh Yi-Chun , Raut Yubin , Weissman J.L. , Fuhrman Jed A. 
Published: November 2022

AbstractBiological nitrogen fixation, the conversion of N2 gas into a more bioavailable form, is vital to sustaining marine primary production. Studies have shifted beyond traditionally studied tropical diazotrophs.CandidatusAtelocyanobacterium thalassa (or UCYN-A) has emerged as a research focal point due to its streamlined metabolism, intimate partnership with a haptophyte host, and broad distribution. Here, we explore the abiotic factors that govern UCYN-A’s presence at the San Pedro Ocean Time-series (SPOT), its partner fidelity, and statistical interactions with non-symbiotic eukaryotes. 16S and 18S rRNA sequences were amplified by “universal primers” from monthly samples and resolved into Amplicon Sequence Variants, allowing us to observe multiple UCYN-A symbioses. UCYN-A1 relative abundances increased following the 2015-2016 El Niño event. When this “open ocean ecotype” was present, coastal upwelling ceased, and Ekman transport brought tropical waters into the region. Network analyses reveal all strains of UCYN-A co-occur with dinoflagellates includingLepidodinium, a potential predator, and parasiticSyndiniales. UCYN-A2 appeared to pair with multiple hosts and was not tightly coupled to its predominate host, while UCYN-A1 maintained a strong host-symbiont relationship. These biological relationships are particularly important to study in the context of climate change, which will alter UCYN-A distribution patterns both locally and globally.
Laser ablation tomography (LATscan) as a new tool for anatomical studies of woody plants
Authors: Cunha Neto Israel L. , Hall Benjamin , Lanba Asheesh , Blosenski Joshua , Onyenedum Joyce G. 
Published: November 2022

SummaryTraditionally, botanists study the anatomy of plants by carefully sectioning samples, histological staining to highlight tissues of interests, then imaging slides under light microscopy. This approach generates significant details; however, this traditional workflow is laborious and time consuming, and ultimately yields two-dimensional (2D) images. Laser Ablation Tomography (LATscan) is a high-throughput imaging system that yields hundreds of images per minute. This method has proven useful for studying the structure of delicate plant tissues, however its utility in understanding the structure of tougher woody tissues is underexplored.We report LATscan-derived anatomical data from several woody stems (ca. 20 mm) of eight species and compare these results to those obtained through traditional anatomical techniques.LATscan successfully allows the description of tissue composition by differentiating cell type, size, and shape, but also permits the recognition of distinct cell wall composition (e.g., lignin, suberin, cellulose) based on differential fluorescent signals on unstained samples.LATscan generate high-resolution 2D images and 3D reconstructions of woody plant samples, therefore this new technology is useful for both qualitative and quantitative analyses. This high-throughput imaging technology has the potential to bolster phenotyping of vegetative and reproductive anatomy, wood anatomy, and other biological systems such as plant-pathogen and parasitic plant associations.
Dynamics of organelle DNA segregation inArabidopsisdevelopment and reproduction revealed with tissue-specific heteroplasmy profiling and stochastic modelling
Authors: Broz Amanda K , Sloan Daniel B , Johnston Iain G 
Published: November 2022

AbstractOrganelle DNA (oDNA) in mitochondria and plastids is vital for plant (and eukaryotic) life. Selection against damaged oDNA is mediated in part by segregation – the sorting of different oDNA types into different cells in the germline. Plants segregate oDNA very rapidly, with oDNA recombination protein MutS Homolog 1 (MSH1), a key driver of this segregation, but in contrast to mammals, we have very limited knowledge of the dynamics of this segregation within plants and between generations. Here, we combine stochastic modelling with tissue-specific heteroplasmy measurements to reveal the trajectories of oDNA segregation inArabidopsis thalianadevelopment and reproduction. We obtain and use new experimental observations of oDNA through development to confirm and refine the predictions of the theory inferred from existing measurements. Ongoing segregation proceeds gradually but continually during plant development, with a more rapid increase between inflorescence formation and the establishment of the next generation. When MSH1 is compromised, we show that the majority of observed segregation could be achieved through partitioning at cell divisions. When MSH1 is functional, mtDNA segregation is far more rapid than can be achieved through cell divisions; we show that increased oDNA gene conversion is a plausible mechanism quantitatively explaining this acceleration. We also discuss the support for different models of the plant germline provided by these observations.
Effective design and inference for cell sorting and sequencing based massively parallel reporter assays
Authors: Gilliot Pierre-Aurélien , Gorochowski Thomas E. 
Published: November 2022

AbstractThe ability to measure the phenotype of millions of different genetic designs using Massively Parallel Reporter Assays (MPRAs) has revolutionised our understanding of genotype-to-phenotype relationships and opened avenues for data-centric approaches to biological design. However, our knowledge of how best to design these costly experiments and the effect that our choices have on the quality of the data produced is lacking. Here, we tackle this issue by developing FORE-CAST, a Python package that supports the accurate simulation of cell-sorting and sequencing based MPRAs and robust maximum like-lihood based inference of genetic design function from MPRA data. We use FORECAST’s capabilities to reveal rules for MPRA experimental design that help ensure accurate genotype-to-phenotype links and show how the simulation of MPRA experiments can help us better understand the limits of prediction accuracy when this data is used for training deep learning based classifiers. As the scale and scope of MPRAs grows, tools like FORECAST will help ensure we make informed decisions during their development and the most of the data produced.
Proteomic mapping reveals dysregulated angiogenesis in the cerebral arteries of rats with early-onset hypertension
Authors: Bastrup Joakim A. , Jepps Thomas A. 
Published: November 2022

AbstractHypertension is associated with presence of vascular abnormalities, such as remodeling and rarefaction. These processes play an important role in cerebrovascular disease development, however, the mechanistic changes leading to these diseases are not well characterized. Using data-independent acquisition-based mass spectrometry analysis, we determined the protein changes in cerebral arteries in pre- and early-onset hypertension from the spontaneously hypertensive rat (SHR), a model that resembles essential hypertension. Our analysis identified 125 proteins with expression levels that were significantly up- or downregulated in 12-week old SHRs compared to normotensive Wistar Kyoto rats. Using an angiogenesis enrichment analysis, we identified a critical imbalance in angiogenic proteins, promoting an anti-angiogenic profile in cerebral arteries at the early-onset of hypertension. In a comparison to previously published data, we demonstrate that this angiogenic imbalance is not present in mesenteric and renal arteries from age-matched SHRs. Finally, we identified two proteins (Fbln5 and Cdh13), whose expression levels were critically altered in cerebral arteries compared to the other arterial beds. The observation of an angiogenic imbalance in cerebral arteries from the SHR reveals critical protein changes in the cerebrovasculature at the early-onset of hypertension and provides novel insight into the early pathology of cerebrovascular disease.
SOX9-positive pituitary stem cells differ according to their position in the gland and maintenance of their progeny depends on context
Authors: Rizzoti Karine , Chakravarty Probir , Sheridan Daniel , Lovell-Badge Robin 
Published: November 2022

ABSTRACTStem cell (SC) differentiation and maintenance of resultant progeny underlie cell-turnover in many organs, but it is difficult to pinpoint the contribution of either process. In the pituitary, a central regulator of endocrine axes, adult SCs undergo activation following target organ ablation, providing a well-characterized paradigm to study an adaptative response in a multi-organ system. Here we used single cell technologies to characterize SC heterogeneity and mobilization together with lineage tracing. We show that SC differentiation occurs more frequently than thought previously. In adaptative conditions, differentiation increases and is more diverse than demonstrated by the lineage tracing experiments. Detailed examination of SC progeny suggests that maintenance of selected nascent cells underlies SC output, highlighting a trophic role for the microenvironment. Analyses of cell trajectories further predict pathways and potential new regulators. Our model provides a valuable system to study the influence of evolving states on the mechanisms of SC mobilization.Teaser: Pituitary stem cells are diverse and differentiate more than thought but only selected progeny persist according to need.
Steady state visual evoked potentials reveal a signature of the pitch-size crossmodal association in visual cortex
Authors: Sciortino Placido , Kayser Christoph 
Published: November 2022

AbstractCrossmodal correspondences describe our tendency to associate sensory features from different modalities with each other, such as the pitch of a sound with the size of a visual object. While such crossmodal correspondences (or associations) are described in many behavioural studies their neurophysiological correlates remain unclear. Under the current working model of multisensory perception both a low- and a high-level account seem plausible. That is, the neurophysiological processes shaping these associations could commence in low-level sensory regions, or may predominantly emerge in high-level association regions of semantic and object identification networks. We exploited steady-state visual evoked potentials (SSVEP) to directly probe this question, focusing on the associations between pitch and the visual features of size, hue or chromatic saturation. We found that SSVEPs over occipital regions are sensitive to the congruency between pitch and size, and a source analysis pointed to an origin around primary visual cortices. We speculate that this signature of the pitch-size association in low-level visual cortices reflects the successful pairing of congruent visual and acoustic object properties and may contribute to establishing causal relations between multisensory objects.
Screening of metabolism-disrupting chemicals on pancreatic α-cells using in vitro methods
Authors: Dos Santos Reinaldo Sousa , Babiloni-Chust Ignacio , Marroqui Laura , Nadal Angel 
Published: November 2022

AbstractMetabolism-disrupting chemicals (MDCs) are endocrine disruptors with obesogenic and/or diabetogenic action. There is mounting evidence linking exposure to MDCs to increased susceptibility to diabetes. Despite the important role of glucagon in glucose homeostasis, there is little information on the effects of MDCs on α-cells. Furthermore, there are no methods to identify and test MDCs with the potential to alter α-cell viability and function. Here we used the mouse α-cell line αTC1-9 to evaluate the effects of MDCs on cell viability and glucagon secretion. We tested six chemicals at concentrations within human exposure (from 0.1 pM to 1 μM): bisphenol-A (BPA), tributyltin (TBT), perfluorooctanoic acid (PFOA), triphenylphosphate (TPP), triclosan (TCS), and dichlorodiphenyldichloroethylene (DDE). Using two different approaches, MTT assay and DNA-binding dyes, we observed that BPA and TBT decreased α-cell viability via a mechanism that depends on the activation of estrogen receptors and PPARγ, respectively. These two chemicals induced ROS production, but barely altered the expression of endoplasmic reticulum (ER) stress markers. Although PFOA, TPP, TCS, and DDE did not alter cell viability nor induced ROS generation or ER stress, all four compounds negatively affected glucagon secretion. Our findings suggest that αTC1-9 cells seem an appropriate model to test chemicals with metabolism-disrupting activity and that the improvement of the test methods proposed herein could be incorporated into protocols for the screening of diabetogenic MDCs.