bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive endophenotypes in racially- and ethnically-diverse middle-aged adult offspring aggregate with parental magnetic resonance imaging biomarkers of Alzheimer’s disease risk
Authors: Lao Patrick J. , Turney Indira C. , Avila-Reiger Justina , Vonk Jet M.J. , Rentería Miguel Arce , Seblova Dominika , Chesebro Anthony G. , Laing Krystal K. , Amarante Erica , Martinez Michelle , Fleurimont Judes , Gutierrez José , Schupf Nicole , Mayeux Richard , Manly Jennifer J. , Brickman Adam M. 
Published: January 2021

AbstractA family history of Alzheimer’s disease (AD) increases risk for AD in an individual by 1.5-to 3-fold. Heritability of AD risk may be due in part to the aggregation of neurodegeneration and cerebrovascular changes with cognitive endophenotypes within families. The purpose of this study was to determine the extent to which cognitive functioning in middle-aged adults is associated with objectively-measured neurodegenerative and cerebrovascular neuroimaging markers linked to risk for clinical AD in their parents, and the extent to which these associations differ by race/ethnicity and language, as proxy variables for social advantage. Middle-aged children enrolled in the Offspring study (n=356; 53.1±10.1 years old; 13% Non-Hispanic White, 27% Non-Hispanic Black, 26% Latinx tested in English, 34% Latinx tested in Spanish; 65% women; 13.5±3.4 years education) were administered the NIH Toolbox, a computerized neuropsychological battery, in their preferred language. Older adults were a subset of the Washington-Heights Inwood Columbia Aging Project (77.3±6.6 years old; 75% women; 10.0±4.6 years education) who underwent T1w- and T2w-MRI and who had a child enrolled in the Offspring study. We tested the associations of parental MRI measures reflecting neurodegeneration (hippocampal volume, cortical thickness) and cerebrovascular disease (white matter hyperintensity (WMH) volume, presence of infarct) with cognitive tests scores in Offspring participants. We further stratified the models by race/ethnicity. Better offspring cognitive scores aggregated lower parental neurodegeneration and cerebrovascular disease among Non-Hispanic White and Latinx participants, and with lower parental cerebrovascular disease alone among Non-Hispanic Black participants. Associations were generally strongest in Non-Hispanic White participants compared to the other groups. These results suggest a more consistent link between offspring cognitive endophenotype and parental brain health in intergenerational AD transmission among Non-Hispanic White participants compared to racial/ethnic and minority groups in which other social factors may be adding variance.
Simulation of epidemic models with generally distributed sojourn times
Authors: Hernandez-Suarez Carlos , Montesinos-Lopez Osval , Solano-Barajas Ramon 
Published: January 2021

AbstractEpidemic models are used to analyze the progression or outcome of an epidemic under different control policies like vaccinations, quarantines, lockdowns, use of face-masks, pharmaceutical interventions, etc. When these models accurately represent real-life situations, they may become an important tool in the decision-making process. Among these models, compartmental models are very popular and assume individuals move along a series of compartments that describe their current health status. Nevertheless, these models are mostly Markovian, that is, the time in each compartment follows an exponential distribution. Here, we introduce a novel approach to simulate general stochastic epidemic models that accepts any distribution for the sojourn times.
Inactivation of SARS-CoV-2 virus in saliva using a guanidium based transport medium suitable for RT-PCR diagnostic assays
Authors: Banik Sukalyani , Saibire Kaheerman , Suryavanshi Shraddha , Johns Glenn , Chakravorty Soumitesh , Kwiatkowski Robert , Alland David , Banada Padmapriya 
Published: January 2021

AbstractBackgroundUpper respiratory samples used to test for SARS-CoV-2 virus may be infectious and present a hazard during transport and testing. A buffer with the ability to inactivate SARS-CoV-2 at the time of sample collection could simplify and expand testing for COVID-19 to non-conventional settings.MethodsWe evaluated a guanidium thiocyanate-based buffer, eNAT™ (Copan) as a possible transport and inactivation medium for downstream RT-PCR testing to detect SARS-CoV-2. Inactivation of SARS-CoV-2 USA-WA1/2020 in eNAT and in diluted saliva was studied at different incubation times. The stability of viral RNA in eNAT was also evaluated for up to 7 days at room temperature (28°C), refrigerated conditions (4°C) and at 35°C.ResultsSARS-COV-2 virus spiked directly in eNAT could be inactivated at >5.6 log10PFU/ml within a minute of incubation. When saliva was diluted 1:1 in eNAT, no cytopathic effect (CPE) on vero-E6 cell lines was observed, although SARS-CoV-2 RNA could be detected even after 30 min incubation and after two cell culture passages. A 1:2 (saliva:eNAT) dilution abrogated both CPE and detectable viral RNA after as little as 5 min incubation in eNAT. SARS-CoV-2 RNA from virus spiked at 5X the limit of detection remained positive up to 7 days of incubation in all tested conditions.ConclusioneNAT and similar guanidinium thiocyanate-based media may be of value for transport, preservation, and processing of clinical samples for RT-PCR based SARS-CoV-2 detection.
COVID-19 propagation by diffusion - a two-dimensional approach for Germany
Authors: Bärwolff Günter 
Published: January 2021

AbstractDiffusion comes anytime and everywhere. If there is a gradient or a potential difference of a quantity a diffusion process happens and this ends if an equilibrium is reached only. The concentration of a species maybe such quantity, or the voltage. An electric currant will be driven by a voltage difference for example.In this COVID-19 pandemic one observes both regions with low incidence and other ones with high incidence. The local different people density could be a reason for that. In populous areas like big cities or congested urban areas higher COVID-19 incidences could be observed than in rural regions.The aim of this paper consists in the application of a diffusion concept to describe one possible issue of the the COVID-19 propagation.This will be discussed for the German situation based on the quite different incidence data for the different federal states of Germany.With this ansatz some phenomenoms of the actual development of the pandemic could be confirmed. The model gives a possibility to investigate certain scenarios like border-crossings or local spreading events and their influence on the COVID-19 propagation as well.
Native-like SARS-CoV-2 spike glycoprotein expressed by ChAdOx1 nCoV-19/AZD1222 vaccine
Authors: Watanabe Yasunori , Mendonça Luiza , Allen Elizabeth R. , Howe Andrew , Lee Mercede , Allen Joel D. , Chawla Himanshi , Pulido David , Donnellan Francesca , Davies Hannah , Ulaszewska Marta , Belij-Rammerstorfer Sandra , Morris Susan , Krebs Anna-Sophia , Dejnirattisai Wanwisa , Mongkolsapaya Juthathip , Supasa Piyada , Screaton Gavin R. , Green Catherine M. , Lambe Teresa , Zhang Peijun , Gilbert Sarah C. , Crispin Max 
Published: January 2021

AbstractVaccine development against the SARS-CoV-2 virus focuses on the principal target of the neutralizing immune response, the spike (S) glycoprotein. Adenovirus-vectored vaccines offer an effective platform for the delivery of viral antigen, but it is important for the generation of neutralizing antibodies that they produce appropriately processed and assembled viral antigen that mimics that observed on the SARS-CoV-2 virus. Here, we describe the structure, conformation and glycosylation of the S protein derived from the adenovirus-vectored ChAdOx1 nCoV-19/AZD1222 vaccine. We demonstrate native-like post-translational processing and assembly, and reveal the expression of S proteins on the surface of cells adopting the trimeric prefusion conformation. The data presented here confirms the use of ChAdOx1 adenovirus vectors as a leading platform technology for SARS-CoV-2 vaccines.
Metabolomics insights into osteoporosis through association with bone mineral density
Authors: Zhang Xiaoyu , Xu Hanfei , Li Gloria H. Y. , Long Michelle T. , Cheung Ching-Lung , Vasan Ramachandran S. , Hsu Yi-Hsiang , Kiel Douglas P. , Liu Ching-Ti 
Published: January 2021

AbstractOsteoporosis, a disease characterized by low bone mineral density (BMD), increases the risk for fractures. Conventional risk factors alone do not completely explain measured BMD or osteoporotic fracture risk. Metabolomics may provide additional information. We aim to identify BMD-associated metabolomic markers that are predictive of fracture risk. We assessed 209 plasma metabolites by LC-MS/MS in 1,552 Framingham Offspring Study participants, and measured femoral neck (FN) and lumbar spine (LS) BMD 2-10 years later using dual energy x-ray absorptiometry. We assessed osteoporotic fractures up to 27-year follow-up after metabolomic profiling. We identified twenty-seven metabolites associated with FN-BMD or LS-BMD by LASSO regression with internal validation. Incorporating selected metabolites significantly improved the prediction and the classification of osteoporotic fracture risk beyond conventional risk factors (AUC=0.74 for the model with identified metabolites and risk factors vs AUC=0.70 with risk factors alone, p=0.001; Net reclassification index=0.07, p=0.03). We replicated significant improvement in fracture prediction by incorporating selected metabolites in 634 participants from the Hong Kong Osteoporosis Study (HKOS). The glycine, serine, and threonine metabolism pathway (including four identified metabolites: creatine, dimethylglycine, glycine, and serine) was significantly enriched (FDR p-value=0.028). Furthermore, three causally related metabolites (glycine, Phosphatidylcholine [PC], and Triacylglycerol [TAG]) were negatively associated with FN-BMD while PC and TAG were negatively associated with LS-BMD through Mendelian randomization analysis. In summary, metabolites associated with BMD are helpful in osteoporotic fracture risk prediction. Potential causal mechanisms explaining the three metabolites on BMD are worthy of further experimental validation. Our findings may provide novel insights into the pathogenesis of osteoporosis.
Splenic denervation attenuates repeated social defeat stress-induced T-lymphocyte inflammation
Authors: Elkhatib Safwan K. , Moshfegh Cassandra M. , Watson Gabrielle F. , Schwab Aaron D. , Katsurada Kenichi , Patel Kaushik P. , Case Adam J. 
Published: January 2021

AbstractBackgroundPost-traumatic stress disorder (PTSD) is a devastating psychological disorder that significantly increases the risk for inflammatory diseases. While the exact etiology of this predisposition remains unclear, PTSD canonically increases overall sympathetic tone resulting in increased norepinephrine (NE) outflow. Previously, we demonstrated that exogenous NE alters mitochondrial superoxide in T-lymphocytes to produce a pro-inflammatory T-helper 17 (TH17) phenotype. Therefore, we hypothesized sympathetic-driven neuroimmune interactions could mediate psychological trauma-induced T-lymphocyte inflammation.MethodsRepeated social defeat stress (RSDS) is a preclinical murine model that recapitulates the behavioral, autonomic, and inflammatory aspects of PTSD. Targeted splenic denervation (Dnx) was performed to deduce the contribution of splenic sympathetic nerves to RSDS-induced inflammation. Eighty-five C57BL/6J mice underwent Dnx or sham-operation, followed by RSDS or control paradigms. Animals were assessed for behavioral, autonomic, inflammatory, and redox profiles.ResultsDnx did not alter the antisocial or anxiety-like behavior induced by RSDS. In circulation, RSDS Dnx animals exhibited diminished levels of T-lymphocyte-specific cytokines (IL-2, IL-17A, and IL-22) compared to intact animals, whereas other non-specific inflammatory cytokines(e.g.,IL-6, TNF-α, and IL-10) were unaffected by Dnx. Importantly, Dnx specifically ameliorated the increases in RSDS-induced T-lymphocyte mitochondrial superoxide, TH17 polarization, and pro-inflammatory gene expression with minimal impact to non-T-lymphocyte immune populations.ConclusionsOverall, our data suggest that sympathetic nerves regulate RSDS-induced splenic T-lymphocyte inflammation, but play a minimal role in the behavioral and non-T-lymphocyte inflammatory phenotypes induced by this psychological trauma paradigm.
Representation learning for neural population activity with Neural Data Transformers
Authors: Ye Joel , Pandarinath Chethan 
Published: January 2021

AbstractNeural population activity is theorized to reflect an underlying dynamical structure. This structure can be accurately captured using state space models with explicit dynamics, such as those based on recurrent neural networks (RNNs). However, using recurrence to explicitly model dynamics necessitates sequential processing of data, slowing real-time applications such as brain-computer interfaces. Here we introduce the Neural Data Transformer (NDT), a non-recurrent alternative. We test the NDT’s ability to capture autonomous dynamical systems by applying it to synthetic datasets with known dynamics and data from monkey motor cortex during a reaching task well-modeled by RNNs. The NDT models these datasets as well as state-of-the-art recurrent models. Further, its non-recurrence enables 3.9ms inference, well within the loop time of real-time applications and more than 6 times faster than recurrent baselines on the monkey reaching dataset. These results suggest that an explicit dynamics model is not necessary to model autonomous neural population dynamics.Codegithub.com/snel-repo/neural-data-transformers.
Modelling the probability of detecting mass mortality events
Authors: Brunner Jesse L , Calabrese Justin M 
Published: January 2021

AbstractWhile reports of mass mortality events (MMEs) are increasing in the literature, comparing the incidence of MMEs through time, among locations, or taxa is problematic without accounting for detection probabilities. MMEs involving small, cryptic species can be difficult to detect even during the event, and degradation and scavenging of carcasses can make the window for detection very short. As such, the number or occurrence rate of MMEs may often be severely underestimated, especially with infrequent observations. We develop a simple modeling framework to quantify the probability of detecting an MME as a function of the observation frequency relative to the rate at which MMEs become undetectable. This framework facilitates the design of surveillance programs and may be extended to correct estimates of the incidence of MMEs from actual surveillance data for more appropriate analyses of trends through time and among taxa.
A rapid pharmacogenomic assay to detect NAT2 polymorphisms and guide isoniazid dosing for tuberculosis treatment
Authors: Verma Renu , Patil Sunita , Zhang Nan , Moreira Flora M.F. , Vitorio Marize T. , Santos Andrea da S. , Wallace Ellen , Gnanashanmugam Devasena , Persing David , Savic Rada , Croda Julio , Andrews Jason R. 
Published: January 2021

AbstractRationaleStandardized weight-based dose of anti-tubercular drugs contributes to a substantial incidence of toxicities, inadequate treatment response, and relapse, in part due to variable drug levels achieved. Single nucleotide polymorphisms (SNPs) in the N-acetyltransferase-2 (NAT2) gene explain the majority of interindividual pharmacokinetic variability of isoniazid (INH). However, an obstacle to implementing pharmacogenomic-guided dosing is the lack of a point-of-care assay.ObjectivesTo develop and test a NAT2 classification algorithm, validate its performance in predicting isoniazid clearance, and develop a prototype pharmacogenomic assay.MethodsWe trained random forest models to predict NAT2 acetylation genotype from unphased SNP data using a global collection of 8,561 phased genomes. We enrolled 48 pulmonary TB patients, performed sparse pharmacokinetic sampling, and tested the acetylator prediction algorithm accuracy against estimated INH clearance. We then developed a cartridge-based multiplex qPCR assay on the GeneXpert platform and assessed its analytical sensitivity on whole blood samples from healthy individuals.Measurements and Main ResultsWith a 5-SNP model trained on two-thirds of the data (n=5,738), out-of-sample acetylation genotype prediction accuracy on the remaining third (n=2,823) was 100%. Among the 48 TB patients, predicted acetylator types were: 27 (56.2%) slow, 16 (33.3%) intermediate and 5 (10.4%) rapid. INH clearance rates were lowest in predicted slow acetylators (median 19.3 L/hr), moderate in intermediate acetylators (median 41.0 L/hr) and highest in fast acetylators (median 46.7 L/hr). The cartridge-based assay accurately detected all allele patterns directly from 25ul of whole blood.ConclusionsAn automated pharmacogenomic assay on a platform widely used globally for tuberculosis diagnosis could enable personalized dosing of isoniazid.SummaryThis manuscript describes the development and validation of point-of-care multiplex pharmacogenomic assay to guide personalized dosing of isoniazid for treatment or prevention of tuberculosis.
Quantifying nanotherapeutics penetration using hydrogel based microsystem as a new 3Din vitroplatform
Authors: Goodarzi Saba , Prunet Audrey , Rossetti Fabien , Bort Guillaume , Tillement Olivier , Porcel Erika , Lacombe Sandrine , Wu Ting-Di , Guerquin-Kern Jean-Luc , Delanoë-Ayari Hélène , Lux François , Rivière Charlotte 
Published: January 2021

AbstractThe huge gap between 2Din vitroassays used for drug screening, and thein vivo3D-physiological environment hampered reliable predictions for the route and accumulation of nanotherapeuticsin vivo.For such nanotherapeutics, Multi-Cellular Tumour Spheroids (MCTS) is emerging as a good alternativein vitromodel. However, the classical approaches to produce MCTS suffer from low yield, slow process, difficulties in MCTS manipulation and compatibility with high-magnification fluorescent optical microscopy. On the other hand, spheroid-on-chip set-ups developed so far require a microfluidic practical knowledge difficult to transfer to a cell biology laboratory.We present here a simple yet highly flexible 3D-model microsystem consisting of agarose-based microwells. Fully compatible with the multi-well plates format conventionally used in cell biology, our simple process enables the formation of hundreds of reproducible spheroids in a single pipetting. Immunostaining and fluorescent imaging including live high-resolution optical microscopy can be performedin-situ, with no manipulation of spheroids.As a proof-of-principle of the relevance of suchin vitroplatform for nanotherapeutics evaluation, this study investigates the kinetic and localization of nanoparticles within colorectal cancer MCTS cells (HCT-116). The nanoparticles chosen are sub-5 nm ultrasmall nanoparticles made of polysiloxane and gadolinium chelates that can be visualized in MRI (AGuIX®, currently implicated in clinical trials as effective radiosensitizers for radiotherapy) and confocal microscopy after addition of Cy 5.5. We show that the amount of AGuIX®nanoparticles within cells is largely different in 2D and 3D. Using our flexible agarose-based microsystems, we are able to resolve spatially and temporally the penetration and distribution of AGuIX®nanoparticles within MCTS. The nanoparticles are first found in both extracellular and intracellular space of MCTS. While the extracellular part is washed away after few days, we evidenced intracellular localisation of AGuIX®, mainly within lysosomes compartment, but also occasionally within mitochondria. Our agarose-based microsystem appears hence as a promising 3Din vitrouser-friendly platform for investigation of nanotherapeutics transport, ahead ofin vivostudies.Abstract FigureGraphical abstract
Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition
Authors: Nakadai Ryosuke 
Published: January 2021

AbstractBeta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of spatial beta-diversity. The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the “individual-based beta-diversity” concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity. Here, individual-based beta-diversity indices are extended to multiple-unit cases. In addition, a novel type of random permutation criterion related to these multiple-unit indices for detecting patterns of individual persistence is introduced in the present study. To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama. Information regarding “individuals” is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the methods proposed here are expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using traditional individual-tracked forest monitoring data.
FOD-Net: A Deep Learning Method for Fiber Orientation Distribution Angular Super Resolution
Authors: Zeng Rui , Lv Jinglei , Wang He , Zhou Luping , Barnett Michael , Calamante Fernando , Wang Chenyu 
Published: January 2021

ABSTRACTMapping the human connectome using fiber-tracking permits the study of brain connectivity and yields new insights into neuroscience. However, reliable connectome reconstruction using diffusion magnetic resonance imaging (dMRI) data acquired by widely available clinical protocols remains challenging, thus limiting the connectome / tractography clinical applications. Here we develop fiber orientation distribution (FOD) network (FOD-Net), a deep-learning-based framework for FOD angular super-resolution. Our method enhances the angular resolution of FOD images computed from common clinical-quality dMRI data, to obtain FODs with quality comparable to those produced from advanced research scanners. Super-resolved FOD images enable superior tractography and structural connectome reconstruction from clinical protocols. The method was trained and tested with high-quality data from the Human Connectome Project (HCP) and further validated with a local clinical 3.0T scanner. Using this method, we improve the angular resolution of FOD images acquired with typical single-shell low-angular-resolution dMRI data (e.g., 32 directions,b= 1000 s/mm2) to approximate the quality of FODs derived from time-consuming, multi-shell high-angular-resolution dMRI research protocols. We also demonstrate tractography improvement, removing spurious connections and bridging missing connections. We further demonstrate that connectomes reconstructed by super-resolved FODs achieve comparable results to those obtained with more advanced dMRI acquisition protocols, on both HCP and clinical 3.0T data. Advances in deep-learning approaches used in FOD-Net facilitate the generation of high quality tractography / connectome analysis from existing clinical MRI environments. Our code is freely available athttps://github.com/ruizengalways/FOD-Net.