bluuebunny/crossref_metadata_2025_split huggingface dataset:
Depth Dataset Using Microsoft Kinect-v2
Authors: Heravi Hamed , Delgarmi Masumeh , Jounghani Ali Rahimpour , shahrezaie Abdollah , Ebrahimi Afshin , Shamsi Mousa 
Published: February 2021

AbstractIn biomedical imaging studies, numerous methods have been used to capture human data, mostly by using magnetic resonance imaging (MRI) and computed tomography (CT). However, due to being inexpensive and accessibility of Microsoft Kinect, its usage has been significantly increased in recent years. In this study, we aimed to represent the procedure of data acquisition, which includes a set of depth images from individuals’ back surfaces. The goal of image acquisition is to investigate spinal deformities and landmark detection of the back surface. Traditional imaging systems are challenging, most notably because of ionized beams in the data acquisition process, which has not been solved yet. Indeed, noninvasiveness is the most crucial advantage of our study. Our imaging system was set in a dim laboratory, and the University approved the ethical letter of Medical Sciences before data acquisition. After that, the subjects (total 105; 50 women and 55 men) were recruited, and data images were captured from the back surface. Then, we increased the imaging data size by using the augmentation method to use deep learning methods in future works. Finally, this Dataset leads us to the desired output in our study procedure.
High-resolution portability of 245 polygenic scores when derived and applied in the same cohort
Authors: Privé Florian , Aschard Hugues , Carmi Shai , Folkersen Lasse , Hoggart Clive , O’Reilly Paul F. , Vilhjálmsson Bjarni J. 
Published: February 2021

AbstractThe low portability of polygenic scores (PGS) across global populations is a major concern that must be addressed before PGS can be used for everyone in the clinic. Indeed, prediction accuracy has been shown to decay as a function of the genetic distance between the training and test cohorts. However, such cohorts differ not only in their genetic distance but also in their geographical distance and their data collection and assaying, conflating multiple factors. In this study, we examine the extent to which PGS are transferable between ancestries by deriving polygenic scores for 245 curated traits from the UK Biobank data and applying them in nine ancestry groups from the same cohort. By restricting both training and testing to the UK Biobank data, we reduce the risk of environmental and genotyping confounding from using different cohorts. We define the nine ancestry groups at a high-resolution, country-specific level, based on a simple, robust and effective method that we introduce here. We then apply two different predictive methods to derive polygenic scores for all 245 phenotypes, and show a systematic and dramatic reduction in portability of PGS trained in the inferred ancestral UK population and applied to the inferred ancestral Polish - Italian - Iranian - Indian - Chinese - Caribbean - Nigerian - Ashkenazi populations, respectively. These analyses, performed at a finer scale than the usual continental scale, demonstrate that prediction already drops off within European ancestries and reduces globally in proportion to PC distance, even when all individuals reside in the same country and are genotyped and phenotyped as part of the same cohort. Our study provides high-resolution and robust insights into the PGS portability problem.
Endometrial microbiota composition is associated with reproductive outcome in infertile patients
Authors: Moreno Inmaculada , Garcia-Grau Iolanda , Perez-Villaroya David , Gonzalez-Monfort Marta , Bahçeci Mustafa , Barrionuevo Marcelo J. , Taguchi Sagiri , Puente Elena , Dimattina Michael , Lim Mei Wei , Meneghini Georgina , Aubuchon Mira , Leondires Mark , Izquierdo Alexandra , Perez-Olgiati Martina , Chavez Alejandro , Seethram Ken , Bau Davide , Gomez Carlos , Valbuena Diana , Vilella Felipe , Simon Carlos 
Published: February 2021

ABSTRACTBackgroundPrevious evidence indicates associations between the female reproductive tract microbiome composition and reproductive outcome in infertile patients undergoing assisted reproduction. We aimed to determine whether the endometrial microbiota composition is associated with reproductive outcomes of live birth, biochemical pregnancy, clinical miscarriage, or no pregnancy.MethodsHere we present a multicentre prospective observational study using 16S rRNA gene sequencing to analyse endometrial fluid and biopsy samples before embryo transfer in a cohort of 342 infertile patients asymptomatic for infection undergoing assisted reproductive treatments.ResultsA dysbiotic endometrial microbiota profile composed of Atopobium, Bifidobacterium, Chryseobacterium, Gardnerella, Haemophilus, Klebsiella, Neisseria, Staphylococcus and Streptococcus was associated with unsuccessful outcomes. In contrast, Lactobacillus was consistently enriched in patients with live birth outcomes.ConclusionsOur findings indicate that endometrial microbiota composition before embryo transfer is a useful biomarker to predict reproductive outcome, offering an opportunity to further improve diagnosis and treatment strategies.
UK and other SARS-CoV-2-Covariants - Simulation Modeling 70% Increase
Authors: Chang Ernie , Moselle Kenneth A. 
Published: February 2021

ABSTRACTCovidSIMVL, an agent-based contagion-based viral transmission simulation tool, was employed to simulate the effects of viral agents of differing levels of infectivity. The constructs “Velocity” and “Increase in Velocity” were operationalized in terms of rates of transmission events over successive iterations (generations) in a set of CovidSIMVL trials. Treating 40-70% increase in velocity as a target, based on reports in the literature for the UK variant (VUI 202012/01), the series of trials reported in the paper demonstrate the calibration of CovidSIMVL parameters to produce increases in transmission rates of 40-70% above a baseline value. A series of follow-up studies is proposed to evaluate three different possible explanations for reported increases in SARS-Cov2-2 infections that are being attributed to spread of the UK and other variants: (a) simulations where the inherent characteristics of the virus (infectivity) are varied (genomic studies); (b) simulations where the behaviour of agents is varied (e.g., movement within and between spaces) while inherent characteristics of the virus are held constant (behavioural studies); and (c) simulations where both inherent properties of the virus and the behaviour of agents are varying to “tease out” the interaction between biologically-based contributions to increased case counts, and contextual/behavioural contributions (epigenetic studies).
Design and Estimation for the Population Prevalence of Infectious Diseases
Authors: Oh Eric J. , Mikytuck Alyssa , Lancaster Vicki , Goldstein Joshua , Keller Sallie 
Published: February 2021

AbstractUnderstanding the prevalence of infections in the population of interest is critical for making data-driven public health responses to infectious disease outbreaks. Accurate prevalence estimates, however, can be difficult to calculate due to a combination of low population prevalence, imperfect diagnostic tests, and limited testing resources. In addition, strategies based on convenience samples that target only symptomatic or high-risk individuals will yield biased estimates of the population prevalence. We present Bayesian multilevel regression and poststratification models that incorporate probability sampling designs, the sensitivity and specificity of a diagnostic test, and specimen pooling to obtain unbiased prevalence estimates. These models easily incorporate all available prior information and can yield reasonable inferences even with very low base rates and limited testing resources. We examine the performance of these models with an extensive numerical study that varies the sampling design, sample size, true prevalence, and pool size. We also demonstrate the relative robustness of the models to key prior distribution assumptions via sensitivity analyses.
Loss of HMCES is synthetic lethal with APOBEC activity in cancer cells
Authors: Biayna Josep , Garcia-Cao Isabel , Álvarez Miguel M. , Salvadores Marina , Espinosa-Carrasco Jose , McCullough Marcel , Supek Fran , Stracker Travis H. 
Published: February 2021

AbstractAnalysis of cancer mutagenic signatures provides information about the origin of mutations and can inform the use of clinical therapies, including immunotherapy. In particular, APOBEC3A (A3A) has emerged as a major driver of mutagenesis in cancer cells and its expression results in DNA damage and susceptibility to treatment with inhibitors of the ATR and CHK1 checkpoint kinases. Here we report the implementation of CRISPR/Cas9 genetic screening to identify susceptibilities of multiple A3A-expressing lung adenocarcinoma cell lines. We identify HMCES, a protein recently linked to the protection of abasic sites, as a central protein for the tolerance of A3A expression. HMCES depletion results in synthetic lethality with A3A expression specifically in a TP53-mutant background. Analysis of previous screening data reveals a strong association between A3A mutational signatures and sensitivity to HMCES loss and indicates that HMCES is specialized in protecting against a narrow spectrum of DNA damaging agents in addition to A3A. We experimentally show that both HMCES disruption and A3A expression increase susceptibility of cancer cells to ionizing radiation, oxidative stress and ATR inhibition; strategies that are often applied in tumor therapies. Overall, our results suggest that HMCES is an attractive target for selective treatment of A3A expressing tumors.
Neuronal Switching Between Single- and Dual-Network Activity via Modulation of Intrinsic Membrane Properties
Authors: Fahoum Savanna-Rae H. , Blitz Dawn M. 
Published: February 2021

AbstractOscillatory networks underlie rhythmic behaviors (e.g. walking, chewing), and complex behaviors (e.g. memory formation, decision making). Flexibility of oscillatory networks includes neurons switching between single- and dual-network participation, even generating oscillations at two distinct frequencies. Modulation of synaptic strength can underlie this neuronal switching. Here we ask whether switching into dual-frequency oscillations can also result from modulation of intrinsic neuronal properties. The isolated stomatogastric nervous system of male Cancer borealis crabs contains two well-characterized rhythmic feeding-related networks (pyloric, ∼1 Hz; gastric mill, ∼0.1 Hz). The identified modulatory projection neuron MCN5 causes the pyloric-only LPG neuron to switch to dual pyloric/gastric mill bursting. Bath applying the MCN5 neuropeptide transmitter Gly1-SIFamide only partly mimics the LPG switch to dual activity, due to continued LP neuron inhibition of LPG. Here, we find that MCN5 uses a co-transmitter, glutamate, to inhibit LP, unlike Gly1-SIFamide excitation of LP. Thus, we modeled the MCN5-elicited LPG switching with Gly1-SIFamide application and LP photoinactivation. Using hyperpolarization of pyloric pacemaker neurons and gastric mill network neurons, we found that LPG pyloric-timed oscillations require rhythmic electrical synaptic input. However, LPG gastric mill-timed oscillations do not require any pyloric/gastric mill synaptic input and are voltage dependent. Thus, we identify modulation of intrinsic properties as an additional mechanism for switching a neuron into dual-frequency activity. Instead of synaptic modulation switching a neuron into a second network as a passive follower, modulation of intrinsic properties could enable a switching neuron to become an active contributor to rhythm generation in the second network.Significance StatementNeuromodulation of oscillatory networks can enable network neurons to switch from sing<bacle- to dual-network participation, even when two networks oscillate at distinct frequencies. We used small, well-characterized networks to determine whether modulation of synaptic strength, an identified mechanism for switching, is necessary for dual-network recruitment. We demonstrate that rhythmic electrical synaptic input is required for continued linkage with a “home” network, but that modulation of intrinsic properties is sufficient to switch a neuron into dual-frequency oscillations, linking it to a second network. Neuromodulator-induced switches in neuronal participation between networks occurs in motor, cognitive, and sensory networks. Our study highlights the importance of considering intrinsic properties as a pivotal target for enabling parallel participation of a neuron in two oscillatory networks.
Computational exploration of dynamic mechanisms of steady state visual evoked potentials at the whole brain level
Authors: Zhang Ge , Cui Yan , Zhang Yangsong , Cao Hefei , Zhou Guanyu , Shu Haifeng , Yao Dezhong , Xia Yang , Chen Ke , Guo Daqing 
Published: February 2021

AbstractPeriodic visual stimulation can induce stable steady-state visual evoked potentials (SSVEPs) distributed in multiple brain regions and has potential applications in both neural engineering and cognitive neuroscience. However, the underlying dynamic mechanisms of SSVEPs at the whole-brain level are still not completely understood. Here, we addressed this issue by simulating the rich dynamics of SSVEPs with a large-scale brain model designed with constraints of neuroimaging data acquired from the human brain. By eliciting activity of the occipital areas using an external periodic stimulus, our model was capable of replicating both the spatial distributions and response features of SSVEPs that were observed in experiments. In particular, we confirmed that alpha-band (8-12 Hz) stimulation could evoke stronger SSVEP responses; this frequency sensitivity was due to nonlinear entrainment and resonance, and could be modulated by endogenous factors in the brain. Interestingly, the stimulus-evoked brain networks also exhibited significant superiority in topological properties near this frequency-sensitivity range, and stronger SSVEP responses were demonstrated to be supported by more efficient functional connectivity at the neural activity level. These findings not only provide insights into the mechanistic understanding of SSVEPs at the whole-brain level but also indicate a bright future for large-scale brain modeling in characterizing the complicated dynamics and functions of the brain.
A Mathematical Model which Examines Age-Related Stochastic Fluctuations in DNA Maintenance Methylation
Authors: Zagkos Loukas , Roberts Jason , Auley Mark Mc 
Published: February 2021

AbstractDue to its complexity and its ubiquitous nature the ageing process remains an enduring biological puzzle. Many molecular mechanisms and biochemical process have become synonymous with ageing. However, recent findings have pinpointed epigenetics as having a key role in ageing and healthspan. In particular age related changes to DNA methylation offer the possibility of monitoring the trajectory of biological ageing and could even be used to predict the onset of diseases such as cancer, Alzheimer’s disease and cardiovascular disease. At the molecular level emerging evidence strongly suggests the regulatory processes which govern DNA methylation are subject to intracellular stochasticity. It is challenging to fully understand the impact of stochasticity on DNA methylation levels at the molecular level experimentally. An ideal solution is to use mathematical models to capture the essence of the stochasticity and its outcomes. In this paper we present a novel stochastic model which accounts for specific methylation levels within a gene promoter. We quantify the uncertainty of the eventual cite-specific methylation levels for different values of methylation age, depending on the initial methylation levels. Our model predicts the observed bistable levels in CpG islands. In addition, simulations with various levels of noise indicate that uncertainty predominantly spreads through the hypermethylated region of stability, especially for large values of input noise. A key outcome of the model is that CpG islands with intermediate methylation levels tend to be more susceptible to dramatic DNA methylation changes towards both hypomethylation and hypermethylation, due to increasing methylation age.
Quantitative assessment of constitutive G protein-coupled receptor activity with BRET-based G protein biosensors
Authors: Schihada Hannes , Shekhani Rawan , Schulte Gunnar 
Published: February 2021

AbstractHeterotrimeric G proteins constitute the primary transducers of G protein-coupled receptor (GPCR) signaling. Besides mediating ligand-induced GPCR activation, G proteins transduce basal levels of activity in various physiological and pathophysiological settings evoked by constitutively active, native GPCRs or disease-related receptor mutants. Several generations of optical biosensors were developed and optimized to monitor GPCR ligand-induced G protein activation, however, quantitative approaches to detect constitutively active GPCRs are not available. Here, we designed and validated a set of eight bioluminescence-resonance-energy-transfer (BRET)-based G protein sensors, covering all four major families of G proteins, and established a protocol to identify constitutive GPCR/G protein signaling in living cells. These sensors rely on the encoding of all three G protein subunits on a single plasmid, enabling their cellular expression at desired relative levels and resulting in reduced signal variability in mammalian cells. Based on this sensor platform, we further present here an experimental protocol to quantify constitutive signaling of native and mutated GPCRs through these heterotrimeric transducers. This approach will aid in the characterization of constitutively active GPCRs and the exploration of their role in health and disease.One Sentence SummaryThis Resource article describes the validation of a biophysical approach to directly assess the constitutive signaling activity of G protein-coupled receptors through heterotrimeric G proteins in living cells using optical biosensors.
Active microrheology using pulsed optical tweezers to probe viscoelasticity of Lamin A towards diagnosis of laminopathies
Authors: Mukherjee C. , Kundu A. , Dey R. , Banerjee A. , Sengupta K. 
Published: February 2021

AbstractLamins are nucleoskeletal proteins of mammalian cells that stabilize the structure and maintain the rigidity of the nucleus. These type V intermediate filament proteins which are predominantly of A and B types provide necessary tensile strength to the nucleus. Single amino acid missense mutations occurring all over the lamin A protein form a cluster of human diseases termed as laminopathies, a few of which principally affect the muscle and cardiac tissues responsible for load bearing functionalities of the body. One such mutation is lamin A350P which causes dilated cardiomyopathy in patients. It is likely that a change from alanine to proline in the α-helical 2B rod domain of the protein might severely disrupt the propensity of the filaments to polymerise into functional higher order structures required to form a fully functional lamina with its characteristic elasticity. In this study, we validate for the very first time, the application of active microrheology employing oscillating optical tweezers to investigate any alterations in the visco-elastic parameters of the mutant protein meshworkin vitro, which might translate into possible changes in nuclear plasticity. We confirm our findings from this robust yet fast method by imaging both the wild type and mutant lamins using a super resolution microscope, and observe changes in the mesh size which explain our measured changes in the viscoelastic parameters of the lamins. This method could naturally be extended to conduct microrheological measurements on any intermediate filament protein or any protein endowed with elastic behavior, with minor schematic modifications, thus bearing significant implications in laminopathies and other diseases which are associated with changes in structural rigidity of any cellular organelle.SignificanceLamin A mutations produce an array of diseases termed as laminopathies which are primarily characterized by alteration of elastic behavior of the nucleus which in turn leads to defects in mechanotransduction. This is the first report in the lamin arena which shows a fast, accurate and direct quantification of elastic moduli of lamin A using optical tweezers-based microrheology. This has very significant implications and can be registered to be a robust and universal method that could also be suitably used for probing changes in elastic properties of any proteins or surfactants in a disease scenario such as SARS-Cov2 (Covid-19), which is pandemic at this time.
Analysis of mitochondrial genome methylation using Nanopore single-molecule sequencing
Authors: Lüth Theresa , Klein Christine , Schaake Susen , Tse Ronnie , Pereira Sandro , Lass Joshua , Sinkkonen Lasse , Grünewald Anne , Trinh Joanne 
Published: February 2021

AbstractThe level and the biological significance of mitochondrial DNA (mtDNA) methylation in human cells is a controversial topic. Using long-read third-generation sequencing technology, mtDNA methylation can be detected directly from the sequencing data, which overcomes previously suggested biases, introduced by bisulfite treatment-dependent methods. We investigated mtDNA from whole blood-derived DNA and established a workflow to detect CpG methylation with Nanopolish. In order to obtain native mtDNA, we adjusted a whole-genome sequencing protocol and performed ligation library preparation and Nanopore sequencing. To validate the workflow, 897bp of methylated and unmethylated synthetic DNA samples at different dilution ratios were sequenced and CpG methylation was detected. Interestingly, we observed that reads with higher methylation in the synthetic DNA did not pass Guppy calling, possibly affecting conclusions about DNA methylation in Nanopore sequencing. We detected in all blood-derived samples overall low-level methylation across the mitochondrial genome, with exceptions at certain CpG sites. Our results suggest that Nanopore sequencing is capable of detecting low-level mtDNA methylation. However, further refinement of the bioinformatical pipelines including Guppy failed reads are recommended.