bluuebunny/crossref_metadata_2025_split huggingface dataset:
Graphics processing unit-accelerated Monte Carlo simulation of polarized light in complex three-dimensional media
Authors: Yan Shijie , Jacques Steven L. , Ramella-Roman Jessica C. , Fang Qianqian 
Published: January 2022

AbstractSignificanceMonte Carlo (MC) methods have been applied for studying interactions between polarized light and biological tissues, but most existing MC codes supporting polarization modeling can only simulate homogeneous or multi-layered domains, resulting in approximations when handling realistic tissue structures.AimOver the past decade, the speed of MC simulations has seen dramatic improvement with massively-parallel computing techniques. Developing hardware-accelerated MC simulation algorithms that can accurately model polarized light inside 3-D heterogeneous tissues can greatly expand the utility of polarization in biophotonics applications.ApproachHere we report a highly efficient polarized MC algorithm capable of modeling arbitrarily complex media defined over a voxelated domain. Each voxel of the domain can be associated with spherical scatters of various radii and densities. The Stokes vector of each simulated photon packet is updated through photon propagation, creating spatially resolved polarization measurements over the detectors or domain surface.ResultsWe have implemented this algorithm in our widely disseminated MC simulator, Monte Carlo eXtreme (MCX). It is validated by comparing with a reference CPU-based simulator in both homogeneous and layered domains, showing excellent agreement and a 931-fold speedup.ConclusionThe polarization-enabled MCX (pMCX) offers biophotonics community an efficient tool to explore polarized light in bio-tissues, and is freely available at http://mcx.space/.
hAMRoaster: a tool for comparing performance of AMR gene detection software
Authors: Wissel Emily F. , Talbot Brooke M. , Toyosato Noriko A. B. , Petit Robert A , Hertzberg Vicki , Dunlop Anne , Read Timothy D. 
Published: January 2022

AbstractBackgroundThe use of shotgun metagenomics for AMR detection is appealing because data can be generated from clinical samples with minimal processing. Detecting antimicrobial resistance (AMR) in clinical genomic data is an important epidemiological task, yet a complex bioinformatic process. Many software tools exist to detect AMR genes, but they have mostly been tested in their detection of genotypic resistance in individual bacterial strains. Further, these tools use different databases, or even different versions of the same databases. Understanding the comparative performance of these bioinformatics tools for AMR gene detection in shotgun metagenomic data is important because this data type is increasingly used in public health and clinical settings.MethodsWe developed a software pipeline, hAMRoaster (Harmonized AMR Output compAriSon Tool ER;https://github.com/ewissel/hAMRoaster), for assessing accuracy of prediction of antibiotic resistance phenotypes. For evaluation purposes, we simulated a highly resistant mock community and several low resistance metagenomic short read (Illumina) samples based on sequenced strains with known phenotypes. We benchmarked nine open source bioinformatics tools for detecting AMR genes that 1) were conda or Docker installable, 2) had been actively maintained, 3) had an open source license, and 4) took FASTA or FASTQ files as input. hAMRoaster calculated sensitivity, specificity, precision, and accuracy for each tool, comparing detected AMR genes to susceptibility testing.ConclusionOverall, all tools were precise and accurate at all genome coverage levels tested (5x, 50x, 100x sequenced bases / genome length) in the highly resistant mock community with more variability in the low resistance community (1x coverage). This study demonstrated that different bioinformatic tools and pipelines yield differences in AMR gene identification across drug classes, and that these differences become important if researchers are interested in resistance to specific drug classes.SignificanceSoftware selection for metagenomic AMR prediction should be driven by the context of the clinical/research questions and tolerance for true and false negative results. The ability to assess which bioinformatics tool best fits a particular dataset prior to beginning a large-scale project allows for more efficient processing and analysis using optimal tools for a particular research question. As prediction software and databases are in a state of constant refinement, the approach used here—creating synthetic communities containing taxa and phenotypes of interest along with using hAMRoaster to assess performance of candidate software—offers a template to aid researchers in selecting the most appropriate strategy at the time of analysis.
The AAA+ ATPase RavA-ViaA complex sensitizes Escherichia coli to aminoglycosides under anaerobic low energy conservation conditions
Authors: Khoury Jessica Y. El , Zamarreño Beas Jordi , Huguenot Allison , Py Béatrice , Barras Frédéric 
Published: January 2022

AbstractAminoglycosides have been used against Gram-negative bacteria for decades. Yet, uncertainties remain about various aspects of their uptake mechanism. Moreover their killing efficiency is well known to vary as a function of growth conditions and types of metabolism used by the targeted bacterium. Here we show that RavA, an AAA+ ATPase from the MoxR subfamily, associated with its VWA-containing partner, ViaA sensitize E. coli to lethal concentrations of AG, including gentamycin (Gm) and tobramycin, but not of antibiotics of other classes. We show this sensitizing effect to be due to enhanced Gm uptake in a proton motive force dependent manner. We evaluated the influence of RavA ViaA throughout a series of growth conditions, including aerobiosis and anaerobiosis. This led us to observe that the sensitizing effect of RavA ViaA varies with the respiratory chain used, i.e. RavA ViaA influence was prominent in the absence of exogenous electron acceptor or with fumarate, i.e. in poor energy conservation conditions, and dispensable in the presence of nitrate or oxygen, i.e. in high level of energy conservation. We propose RavA ViaA to be able to sense energetic state of the cell and to be used under low energy conditions for facilitating uptake of chemicals across the membrane, including Gm.Author SummaryAntibiotic resistance is a major public health, social and economic problem. Aminoglycosides are known for their high efficiency against Gram-negative bacteria but their use is restricted to life threatening infections because of their nephrotoxicity and ototoxicity at therapeutic dose. Elucidation of AG sensitization mechanisms in bacteria will allow the use of a decreased effective dose of AGs. Here we identified new molecular actors, RavA and ViaA, which sensitize E. coli to AG under anaerobiosis. RavA belongs to the AAA+ ATPase family while ViaA bears a VWA motif. Moreover we show here that the influence of RavA ViaA on AG sensitivity varies with growth conditions and respiratory metabolism used by E. coli. This is a significant step forward as anaerobiosis is well known to reduce antibacterial activity of AG. This study emphasizes the crucial importance of the relationships between culture conditions, metabolism and antibiotic resistance.
Genome-wide Analysis Reflects Novel 5-Hydroxymethylcytosines Implicated in Diabetic Nephropathy
Authors: Yang Ying , Zeng Chang , Yang Kun , Zhang Zhou , Cai Qinyun , He Chuan , Zhang Wei , Liu Song-Mei 
Published: January 2022

ABSTRACTLong-term complications of type 2 diabetes (T2D) are the major causes for T2D-related disability and mortality. Notably, diabetic nephropathy (DN) has become the most frequent cause of end-stage renal disease (ESRD) in most countries. Understanding epigenetic contributors to DN can provide novel insights into this complex disorder and lay the foundation for more effective monitoring tools and preventive interventions, critical for achieving the ultimate goal of improving patient care and reducing healthcare burden. We have used a selective chemical labeling technique (5hmC-Seal) to profile genome-wide distributions of 5-hydroxymethylcytosines (5hmC), a gene activation mark, in patient-derived circulating cell-free DNA (cfDNA). Differentially modified 5hmC genes were identified across T2D patients with DN (n = 12), T2D patients with non-DN vascular complications (non-DN) (n = 29), and T2D patients with no complications (controls) (n = 14). Specifically, differential 5hmC markers between DN and controls revealed relevant pathways such as NOD-like receptor signaling pathway and tyrosine metabolism. A ten-gene panel was shown to provide differential 5hmC patterns between controls and DN, as well as between controls and non-DN patients using a machine learning approach. The 5hmC profiles in cfDNA reflected novel DN-associated epigenetic modifications relevant to the disease pathogenesis of DN. Importantly, these findings in cfDNA, a convenient liquid biopsy, have the potential to be exploited as a clinically useful tool for predicting DN in high risk T2D patients.
Development of an effective immune response in adults with Down Syndrome after SARS-CoV-2 vaccination
Authors: Esparcia-Pinedo Laura , Yarci-Carrión Ayla , Mateo-Jiménez Gloria , Ropero Noelia , Gómez-Cabañas Laura , Lancho-Sánchez Ángel , Martín-Gayo Enrique , Sanchez-Madrid Francisco , Moldenhauer Fernando , Gutiérrez-Cobos Ainhoa , de Asúa Diego Real , Alfranca Arantzazu 
Published: January 2022

ABSTRACTImmune dysregulation in individuals with Down syndrome (DS) leads to an increased risk for hospitalization and death due to COVID-19 and may impair the generation of protective immunity after vaccine administration. The cellular and humoral responses of 55 DS patients who received a complete SARS-CoV-2 vaccination regime at one to three (V1) and six (V2) months were characterised. SARS-CoV-2-reactive CD4+ and CD8+ T lymphocytes with a predominant Th1 phenotype were observed at V1, and increased at V2. Likewise, a sustained increase of SARS-CoV-2-specific circulating Tfh (cTfh) cells was observed one to three months after vaccine administration. Specific IgG antibodies against SARS-CoV-2 S protein were detected in 96% and 98% of subjects at V1 and V2, respectively, though IgG titers decreased significantly between both timepoints.SUMMARYThe work shows the cellular and humoral responses to SARS-CoV-2 vaccination of individuals with Down syndrome (DS) after one to three (V1) and six (V2) months. An effective immune response after six months was observed in 98% of DS individuals.
Cerebrospinal fluid neurofilament light chain differentiates behavioural variant frontotemporal dementia progressors from ‘phenocopy’ non-progressors
Authors: Eratne Dhamidhu , Keem Michael , Lewis Courtney , Kang Matthew , Walterfang Mark , Loi Samantha , Kelso Wendy , Cadwallader Claire , Berkovic Samuel F , Li Qiao-Xin , Masters Colin L , Collins Steven , Santillo Alexander , Velakoulis Dennis ,   The MiND Study Group
Published: January 2022

AbstractBackgroundDistinguishing behavioural variant frontotemporal dementia (bvFTD) from non-neurodegenerative ‘non-progressor’, ‘phenocopy’ mimics of frontal lobe dysfunction, can be one of the most challenging clinical dilemmas. A biomarker of neuronal injury, neurofilament light chain (NfL), could reduce misdiagnosis and delay.MethodsCerebrospinal fluid (CSF) NfL, amyloid beta 1-42 (AB42), total and phosphorylated tau (T-tau, P-tau) levels were examined in patients with an initial diagnosis of bvFTD. Based on follow up information, patients were categorised as Progressors. Non-Progressors were subtyped in to Phenocopy Non-Progressors (non-neurological/neurodegenerative final diagnosis), and Static Non-Progressors (static deficits, not fully explained by non-neurological/neurodegenerative causes).ResultsForty-three patients were included: 20 Progressors, 23 Non-Progressors (15 Phenocopy, 8 Static), 20 controls. NfL concentrations were lower in Non-Progressors (Non-Progressors Mean, M=554pg/mL, 95%CI:[461, 675], Phenocopy Non-Progressors M=459pg/mL, 95%CI:[385, 539], Static Non-Progressors M=730pg/mL, 95%CI:[516, 940]), compared to bvFTD Progressors (M=2397pg/mL, 95%CI:[1607, 3332]). NfL distinguished Progressors from Non-Progressors with the highest accuracy (area under the curve 0.92, 90%/87% sensitivity/specificity, 86%/91% positive/negative predictive value, 88% accuracy). Static Non-Progressors tended to have higher T-tau and P-tau levels compared to Phenocopy Non-Progressors.ConclusionThis study demonstrated strong diagnostic utility of CSF NfL to distinguish bvFTD from phenocopy non-progressor variants, at baseline, with high accuracy, in a real-world clinical setting. This has important clinical implications, to improve outcomes for patients and clinicians facing this challenging clinical dilemma, as well as for healthcare services, and clinical trials. Further research is required to investigate heterogeneity within the non-progressor group and potential diagnostic algorithms, and prospective studies are underway assessing plasma NfL
Improved prediction of new COVID-19 cases using a simple vector autoregressive model: Evidence from seven New York State counties
Authors: Kitaoka Takayoshi , Takahashi Harutaka 
Published: January 2022

AbstractWith the rapid spread of COVID-19, there is an urgent need for a framework to accurately predict COVID-19 transmission. Recent epidemiological studies have found that a prominent feature of COVID-19 is its ability to be transmitted before symptoms occur, which is generally not the case for seasonal influenza and SARS. Several COVID-19 predictive epidemiological models have been proposed; however, they share a common drawback—they are unable to capture the unique asymptomatic nature of COVID-19 transmission. Here, we propose vector autoregression (VAR) as an epidemiological county-level prediction model that captures this unique aspect of COVID-19 transmission by introducing newly infected cases in other counties as lagged explanatory variables. Using the number of new COVID-19 cases in seven New York State counties, we predicted new COVID-19 cases in the counties over the next 4 weeks. We then compared our prediction results with those of 11 other state-of-the-art prediction models proposed by leading research institutes and academic groups. The results showed that VAR prediction is superior to other epidemiological prediction models in terms of the root mean square error of prediction. Thus, we strongly recommend the simple VAR model as a framework to accurately predict COVID-19 transmission.
Estimating body fat distribution – a driver of cardiometabolic health – from silhouette images
Authors: Klarqvist Marcus D. R. , Agrawal Saaket , Diamant Nathaniel , Ellinor Patrick T. , Philippakis Anthony , Ng Kenney , Batra Puneet , Khera Amit V. 
Published: January 2022

ABSTRACTBackgroundInter-individual variation in fat distribution is increasingly recognized as clinically important but is not routinely assessed in clinical practice because quantification requires medical imaging.ObjectivesWe hypothesized that a deep learning model trained on an individual’s body shape outline – or “silhouette” – would enable accurate estimation of specific fat depots, including visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volumes, and VAT/ASAT ratio. We additionally set out to study whether silhouette-estimated VAT/ASAT ratio may stratify risk of cardiometabolic diseases independent of body mass index (BMI) and waist circumference.MethodsTwo-dimensional coronal and sagittal silhouettes were constructed from whole-body magnetic resonance images in 40,032 participants of the UK Biobank and used to train a convolutional neural network to predict VAT, ASAT, and GFAT volumes, and VAT/ASAT ratio. Logistic and Cox regressions were used to determine the independent association of silhouette-predicted VAT/ASAT ratio with type 2 diabetes and coronary artery disease.ResultsMean age of the study participants was 65 years and 51% were female. A deep learning model trained on silhouettes enabled accurate estimation of VAT, ASAT, and GFAT volumes (R2: 0.88, 0.93, and 0.93, respectively), outperforming a comparator model combining anthropometric and bioimpedance measures (ΔR2 = 0.05-0.13). Next, we studied VAT/ASAT ratio, a nearly BMI- and waist circumference-independent marker of unhealthy fat distribution. While the comparator model poorly predicted VAT/ASAT ratio (R2: 0.17-0.26), a silhouette-based model enabled significant improvement (R2: 0.50-0.55). Silhouette-predicted VAT/ASAT ratio was associated with increased prevalence of type 2 diabetes and coronary artery disease.ConclusionsBody silhouette images can estimate important measures of fat distribution, laying the scientific foundation for population-based assessment.
A deep learning model for breast ductal carcinoma in situ classification in whole slide images
Authors: Kanavati Fahdi , Ichihara Shin , Tsuneki Masayuki 
Published: January 2022

AbstractThe pathological differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) is of pivotal importance for determining optimum cancer treatment(s) and clinical outcomes. Since conventional diagnosis by pathologists using micro-scopes is limited in terms of human resources, it is necessary to develop new techniques that can rapidly and accurately diagnose large numbers of histopathological specimens. Computational pathology tools which can assist pathologists in detecting and classifying DCIS and IDC from whole slide images (WSIs) would be of great benefit for routine pathological diagnosis. In this paper, we trained deep learning models capable of classifying biopsy and surgical histopathological WSIs into DCIS, IDC, and benign. We evaluated the models on two independent test sets (n=1,382, n=548), achieving ROC areas under the curves (AUCs) up to 0.960 and 0.977 for DCIS and IDC, respectively.
Coupled abiotic-biotic cycling of nitrous oxide in tropical peatlands
Authors: Buessecker Steffen , Sarno Analissa F. , Reynolds Mark C. , Chavan Ramani , Park Jin , Ortiz Marc Fontánez , Pérez-Castillo Ana G. , Pisco Grober Panduro , Urquiza-Muñoz José David , Reis Leonardo P. , Ferreira-Ferreira Jefferson , Furtunato Maia Jair M. , Holbert Keith E. , Penton C. Ryan , Hall Sharon J. , Gandhi Hasand , Boëchat Iola G. , Gücker Björn , Ostrom Nathaniel E. , Cadillo-Quiroz Hinsby 
Published: January 2022

AbstractAtmospheric nitrous oxide (N2O) is a potent greenhouse gas thought to be mainly derived from microbial metabolism as part of the denitrification pathway. Here, we report that in unexplored peat soils of Central and South America, N2O production can be driven by abiotic reactions (≤ 98 %) highly competitive to their enzymatic counterparts. Extracted soil iron positively correlated with in-situ abiotic N2O production determined by isotopic tracers. Moreover, we found that microbial N2O reduction accompanied abiotic production, essentially closing a coupled abiotic-biotic N2O cycle. Anaerobic N2O consumption occurred ubiquitously (pH 6.4-3.7), with proportions of diverse clade II N2O-reducers increasing with consumption rates. Our findings show denitrification in tropical peat soils is not a purely biological process, but rather a “mosaic” of abiotic and biotic reduction reactions. We predict hydrological and temperature fluctuations differentially affect abiotic and biotic drivers and further contribute to the high N2O flux variation in the region.
An ancient truncated duplication of the anti-Mullerian hormone receptor type 2 gene is a potential conserved master sex determinant in the Pangasiidae catfish family
Authors: Wen Ming , Pan Qiaowei , Jouanno Elodie , Montfort Jerome , Zahm Margot , Cabau Cédric , Klopp Christophe , Iampietro Carole , Roques Céline , Bouchez Olivier , Castinel Adrien , Donnadieu Cécile , Parrinello Hugues , Poncet Charles , Belmonte Elodie , Gautier Véronique , Avarre Jean-Christophe , Dugue Remi , Gustiano Rudhy , Hà Trần Thị Thúy , Campet Marc , Sriphairoj Kednapat , Ribolli Josiane , de Almeida Fernanda L. , Desvignes Thomas , Postlethwait John H. , Bucao Christabel Floi , Robinson-Rechavi Marc , Bobe Julien , Herpin Amaury , Guiguen Yann 
Published: January 2022

ABSTRACTThe evolution of sex determination (SD) mechanisms in teleost fishes is amazingly dynamic, as reflected by the variety of different master sex-determining genes identified, even sometimes among closely related species. Pangasiids are a group of economically important catfishes in many South-Asian countries, but little is known about their sex determination system. Here, we generated novel genomic resources for 12 Pangasiid species and provided a first characterization of their SD system. Based on an Oxford Nanopore long-read chromosome-scale high quality genome assembly of the striped catfish Pangasianodon hypophthalmus, we identified a duplication of the anti-Müllerian hormone receptor type II gene (amhr2), which was further characterized as being sex-linked in males and expressed only in testicular samples. These first results point to a male-specific duplication on the Y chromosome (amhr2by) of the autosomal amhr2a. Sequence annotation revealed that the P. hypophthalmus Amhr2by is truncated in its N-terminal domain, lacking the cysteine-rich extracellular part of the receptor that is crucial for ligand binding, suggesting a potential route for its neofunctionalization. Short-read genome sequencing and reference-guided assembly of 11 additional Pangasiid species, along with sex-linkage studies, revealed that this truncated amhr2by duplication is also conserved as a male-specific gene in many Pangasiids. Reconstructions of the amhr2 phylogeny suggested that amhr2by arose from an ancient duplication / insertion event at the root of the Siluroidei radiation that is dated around 100 million years ago. Altogether these results bring multiple lines of evidence supporting that amhr2by is an ancient and conserved master sex-determining gene in Pangasiid catfishes, a finding that highlights the recurrent usage of the transforming growth factor β pathway in teleost sex determination and brings another empirical case towards the understanding of the dynamics or stability of sex determination systems.
Plasma cell maintenance and antibody secretion are under the control of Sec22b-mediated regulation of organelle dynamics
Authors: Bonaud Amélie , Gargowitsch Laetitia , Gilbert Simon M. , Rajan Elanchezhian , Herrerias Pablo Canales , Stockholm Daniel , Rahman Nabila F. , Collins Mark O. , Hill Danika L. , Alloatti Andres , Alouche Nagham , Balor Stéphanie , Soldan Vanessa , Gillet Daniel , Barbier Julien , Bachelerie Françoise , Smith Kenneth G.C. , Bruhns Pierre , Amigorena Sebastian , Balabanian Karl , Linterman Michelle A. , Peden Andrew A. , Espéli Marion 
Published: January 2022

AbstractDespite the essential role of plasma cells in health and disease, the cellular mechanisms controlling their survival and secretory capacity are still poorly understood. Here, we identified the SNARE Sec22b as a unique and critical regulator of plasma cell maintenance and function. In absence of Sec22b, plasma cells were barely detectable and serum antibody titres were dramatically reduced. Accordingly, Sec22b deficient mice fail to mount a protective immune response. At the mechanistic level, we demonstrated that Sec22b is indispensable for efficient antibody secretion but also for plasma cell fitness through the regulation of the morphology of the endoplasmic reticulum and mitochondria. Altogether, our results unveil a critical role for Sec22b-mediated regulation of plasma cell biology through the control of organelle dynamics.