bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social predictors of food insecurity during the stay-at-home order due to the COVID-19 pandemic in Peru. Results from a cross-sectional web-based survey
Authors: Cañari-Casaño Jorge L. , Cochachin-Henostroza Omaira , Elorreaga Oliver A. , Dolores-Maldonado Gandy , Aquino-Ramírez Anthony , Huaman-Gil Sindy , Giribaldi-Sierralta Juan P. , Aparco Juan Pablo , Antiporta Daniel A. , Penny Mary E. 
Published: February 2021

SUMMARYBackgroundStay-at-home orders and social distancing have been implemented as the primary tools to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, this approach has indirectly lead to the unemployment of 2·3 million Peruvians, in Lima, Perú alone. As a result, the risk of food insecurity may have increased, especially in low-income families who rely on a daily wage. This study estimates the prevalence of moderate or severe food insecurity (MSFI) and identifies the associated factors that explain this outcome during the stay-at-home order.MethodsA cross-sectional web-based survey, with non-probabilistic sampling, was conducted between May 18 and June 30, 2020, during the stay-at-home order in Peru. We used social media advertisements on Facebook to reach 18-59-year-olds living in Peru. MSFI was assessed using the Food Insecurity Experience Scale (FIES). Rasch model methodology requirements were considered, and factors associated with MSFI were selected using stepwise forward selection. A Poisson generalized linear model (Poisson GLM), with log link function, was employed to estimate adjusted prevalence ratios (aPR).FindingsThis analysis is based on 1846 replies. The prevalence of MSFI was 23·2%, and FIES proved to be an acceptable instrument with reliability 0·72 and infit 0·8-1·3. People more likely to experience MSFI were those with low income (less than 255 US$/month) in the pre-pandemic period (aPR 3·77; 95%CI, 1·98-7·16), those whose income was significantly reduced during the pandemic period (aPR 2·27; 95%CI, 1·55-3·31), and those whose savings ran out in less than 21 days (aPR 1·86; 95%CI, 1·43-2·42). Likewise, heads of households (aPR 1·20; 95%CI, 1·00-1·44) and those with probable SARS-CoV2 cases as relatives (aPR 1·29; 95%CI, 1·05-1·58) were at an increased risk of MSFI. Additionally, those who perceived losing weight during the pandemic (aPR 1·21; 95%CI, 1·01-1·45), and increases in processed foods prices (aPR 1·31; 95%CI, 1·08-1·59), and eating less minimally processed food (aPR 1·82; 95%CI, 1·48-2·24) were more likely to experience MSFI.InterpretationPeople most at risk of MSFI were those in a critical economic situation before and during the pandemic. Social protection policies should be reinforced to prevent or mitigate these adverse effects.FundingNone.
Dynamics of neutralizing antibody responses in acute-phase COVID-19: A potential relationship between disease progression and rapid neutralizing antibody response
Authors: Kawasuji Hitoshi , Morinaga Yoshitomo , Tani Hideki , Kimura Miyuki , Yamada Hiroshi , Yoshida Yoshihiro , Takegoshi Yusuke , Kaneda Makito , Murai Yushi , Kimoto Kou , Ueno Akitoshi , Miyajima Yuki , Kawago Koyomi , Fukui Yasutaka , Sakamaki Ippei , Yamamoto Yoshihiro 
Published: February 2021

AbstractIntroductionAdaptive immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dynamics remain largely unknown. The neutralizing antibody (NAb) levels in patients with coronavirus disease 2019 (COVID-19) are helpful for understanding the pathology.Patients and MethodsUsing SARS-CoV-2 pseudotyped virus, serum sample neutralization values in symptomatic COVID-19 patients were measured using the chemiluminescence reduction neutralization test (CRNT). At least two sequential serum samples collected during hospitalization were analyzed to assess NAbs neutralizing activity dynamics at different time points.ResultsOf the 11 patients, four (36.4%), six (54.5%), and one (9.1%) had moderate, severe, and critical disease, respectively. Fifty percent neutralization (N50%-CRNT) was observed upon admission in 90.9% (10/11); all patients acquired neutralizing activity 2–12 days after onset. In patients with moderate disease, neutralization was observed at earliest within two days after symptom onset. In patients with severe-to-critical disease, neutralization activity increased, plateauing 9–16 days after onset. Neutralization activity on admission was significantly higher in patients with moderate disease than in patients with severe-to-critical disease (relative % of infectivity, 6.4% vs. 41.1%; P=.0011).ConclusionsNeutralization activity on admission inversely correlated with disease severity. The rapid NAb response may play a crucial role in preventing the progression of COVID-19.
Gastrointestinal carriage of Klebsiella pneumoniae in a general adult population in Norway: a cross-sectional study of risk factors and bacterial genomic diversity
Authors: Raffelsberger Niclas , Hetland Marit Andrea Klokkhammer , Svendsen Kristian , Småbrekke Lars , Löhr Iren H. , Andreassen Lotte Leonore Eivindsdatter , Brisse Sylvain , Holt Kathryn E. , Sundsfjord Arnfinn , Samuelsen Ørjan , Gravningen Kirsten 
Published: February 2021

SummaryBackgroundKlebsiella pneumoniae is a leading public health threat due to its increasing prevalence of antibiotic resistance. Gastrointestinal carriage of K. pneumoniae is a risk factor for subsequent infections in hospitalised patients. We determined risk factors for gastrointestinal carriage and the genomic population structure of K. pneumoniae colonising humans in a representative sample of a general population.Methods2,975 individuals (54% women) ≥40y participating in the population-based Tromsø Study 7 (2015-2016) were included. Faecal samples were screened for K. pneumoniae which were characterised using whole-genome sequencing. Risk factors for carriage were analysed using data from the Norwegian Prescription Database and questionnaires, using multivariable logistic regression.FindingsPrevalence of K. pneumoniae gastrointestinal carriage was 16·3% (95% CI 15·0-17·7%) with no gender difference. Risk factors associated with carriage included age ≥60y, travel to Greece or Asia past 12 months (adjusted odds ratio 1·49, 95% CI 1·11-2·00), Crohn’s disease/ulcerative colitis (2·26, 1·20-4·27), use of protein pump inhibitors (1·62, 1·18-2·22) and non-steroidal anti-inflammatory drugs past six months (1·38, 1·04-1·84), and antibiotic use last month (1·73, 1·05-2·86). Prevalence was higher among those having used combinations of drug classes and decreased over time with respect to preceding antibiotic use. The K. pneumoniae population was diverse with 300 sequence types among 484 isolates distributed across four phylogroups. Among the isolates, 5·2% and 11·6% harboured acquired resistance and virulence factors, respectively.InterpretationIdentification of risk factors for gastrointestinal carriage in a representative sample of a general population allows for identification of individuals that may have a higher risk of extraintestinal infection during hospitalisation. The diverse population structure of K. pneumoniae carriage isolates reflects the ecologically adaptive capacity of the bacterium, and the low antibacterial consumption probably contributes to the low prevalence of resistance in clinical isolates in Norway.
Clinical and Economic Impact of Widespread Rapid Testing to Decrease SARS-CoV-2 Transmission
Authors: Paltiel A. David , Zheng Amy , Sax Paul E. 
Published: February 2021

ABSTRACTBackgroundThe value of frequent, rapid testing to reduce community transmission of SARS-CoV-2 is poorly understood.ObjectiveTo define performance standards and predict the clinical, epidemiological, and economic outcomes of nationwide, home-based, antigen testing.DesignA simple compartmental epidemic model estimated viral transmission, clinical history, and resource use, with and without testing.Data SourcesParameter values and ranges informed by Centers for Disease Control guidance and published literature.Target PopulationUnited States population.Time Horizon60 days.PerspectiveSocietal.Costs include: testing, inpatient care, and lost workdays.InterventionHome-based SARS-CoV-2 antigen testing.Outcome MeasuresCumulative infections and deaths, numbers isolated and/or hospitalized, and total costs.Results of Base-Case AnalysisWithout a testing intervention, the model anticipates 15 million infections, 125,000 deaths, and $10.4 billion in costs ($6.5 billion inpatient; $3.9 billion lost productivity) over a 60-day horizon. Weekly availability of testing may avert 4 million infections and 19,000 deaths, raising costs by $21.5 billion. Lower inpatient outlays ($5.9 billion) would partially offset additional testing expenditures ($12.0 billion) and workdays lost ($13.9 billion), yielding incremental costs per infection (death) averted of $5,400 ($1,100,000).Results of Sensitivity AnalysisOutcome estimates vary widely under different behavioral assumptions and testing frequencies. However, key findings persist across all scenarios: large reductions in infections, mortality, and hospitalizations; and costs per death averted roughly an order of magnitude lower than commonly accepted willingness-to-pay values per statistical life saved ($5-17 million).LimitationsAnalysis restricted to at-home testing and limited by uncertainties about test performance.ConclusionHigh-frequency home testing for SARS-CoV-2 using an inexpensive, imperfect test could contribute to pandemic control at justifiable cost and warrants consideration as part of a national containment strategy.Primary Funding SourcesDr. Paltiel was supported by grant R37DA015612 from the National Institute on Drug Abuse of the National Institutes of Health.Dr. Sax was supported by grant R01AI042006 from the National Institute of Allergy and Infectious Diseases of the National Institutes of Health.
Decreased SARS-CoV-2 viral load following vaccination
Authors: Levine-Tiefenbrun Matan , Yelin Idan , Katz Rachel , Herzel Esma , Golan Ziv , Schreiber Licita , Wolf Tamar , Nadler Varda , Ben-Tov Amir , Kuint Jacob , Gazit Sivan , Patalon Tal , Chodick Gabriel , Kishony Roy 
Published: February 2021

AbstractBeyond their substantial protection of individual vaccinees, it is hoped that the COVID-19 vaccines would reduce viral load in breakthrough infections thereby further suppress onward transmission. Here, analyzing positive SARS-CoV-2 test results following inoculation with the BNT162b2 mRNA vaccine, we find that the viral load is reduced 4-fold for infections occurring 12-28 days after the first dose of vaccine. These reduced viral loads hint to lower infectiousness, further contributing to vaccine impact on virus spread.
Human spinal cord differentiation proceeds rapidly in vitro and only initially maintains differentiation pace in a heterologous environment
Authors: Dady Alwyn , Davidson Lindsay , Halley Pamela A. , Storey Kate G. 
Published: February 2021

AbstractSpecies-specific differentiation pace in in vitro assays indicates that some aspects of neural differentiation are driven by cell-autonomous processes. Here we describe a novel in vitro human neural rosette assay that recapitulates the temporal sequence of dorsal spinal cord differentiation but proceeds more rapidly than in the human embryonic spinal cord, suggesting that in vitro conditions lack endogenous signalling dynamics. To test the extent to which this in vitro assay represents a cell intrinsic differentiation programme, human iPSC-derived neural rosettes were homo-chronically grafted into the faster differentiating chicken embryonic neural tube. Strikingly, in vitro human differentiation pace was not accelerated, even in single host-integrated cells. Moreover, rosette differentiation eventually stalled in a neural progenitor cell state. These findings demonstrate the requirement for timely extrinsic signalling to accurately recapitulate human neural differentiation tempo, and suggest that while intrinsic properties limit differentiation pace, such signals are also required to maintain differentiation progression.
Efficient gradient-based parameter estimation for dynamic models using qualitative data
Authors: Schmiester Leonard , Weindl Daniel , Hasenauer Jan 
Published: February 2021

AbstractMotivationUnknown parameters of dynamical models are commonly estimated from experimental data. However, while various efficient optimization and uncertainty analysis methods have been proposed for quantitative data, methods for qualitative data are rare and suffer from bad scaling and convergence.ResultsHere, we propose an efficient and reliable framework for estimating the parameters of ordinary differential equation models from qualitative data. In this framework, we derive a semi-analytical algorithm for gradient calculation of the optimal scaling method developed for qualitative data. This enables the use of efficient gradient-based optimization algorithms. We demonstrate that the use of gradient information improves performance of optimization and uncertainty quantification on several application examples. On average, we achieve a speedup of more than one order of magnitude compared to gradient-free optimization. Additionally, in some examples, the gradient-based approach yields substantially improved objective function values and quality of the fits. Accordingly, the proposed framework substantially improves the parameterization of models from qualitative data.AvailabilityThe proposed approach is implemented in the open-source Python Parameter EStimation TOolbox (pyPESTO). All application examples and code to reproduce this study are available athttps://doi.org/10.5281/zenodo.4507613.
The landscape of high-affinity human antibodies against intratumoral antigens
Authors: Rakocevic Goran , Glotova Irina , de Santiago Ines , Toptas Berke Cagkan , Popovic Milena , Popovic Milos , Leone Dario , Stachyra Andrew L. , Rozenfeld Raphael , Kural Deniz , Biasci Daniele 
Published: February 2021

AbstractHigh expression of immunoglobulin transcripts is often detected in human tumours and correlates with favourable clinical outcomes across different cancer types. However, the antigens recognized by such immunoglobulins (Ig) and their biological significance remain largely unknown. We computationally inferred the paired sequence of thousands of clonally expanded Ig using bulk RNA sequencing data from solid tumors in The Cancer Genome Atlas (TCGA). After expressing 283 Ig as recombinant antibodies in mammalian cells, we individually tested them against a library of twenty thousands full-length human proteins and an additional library of six thousand structurally intact membrane proteins, thus identifying their candidate target antigens. Using surface plasmon resonance we then confirmed 16 high-affinity antibodies that bind to their targets withKDin the nanomolar range. Our work provides insights into the antigens that drive B cell responses in human cancers, while also obtaining fully human, high-affinity recombinant antibodies against them.
Spatial transcriptomics reveals unique molecular fingerprints of human nociceptors
Authors: Tavares-Ferreira Diana , Shiers Stephanie , Ray Pradipta R. , Wangzhou Andi , Jeevakumar Vivekanand , Sankaranarayanan Ishwarya , Cervantes Anna , Reese Jeffrey C , Chamessian Alexander , Copits Bryan A. , Dougherty Patrick M. , Gereau Robert W. , Burton Michael D. , Dussor Gregory , Price Theodore J. 
Published: February 2021

AbstractNociceptors are specialized sensory neurons that detect damaging or potentially damaging stimuli and are found in the dorsal root (DRG) and trigeminal ganglia. These neurons are critical for the generation of neuronal signals that ultimately create the perception of pain. These neurons are also primary targets for acute and chronic pain therapeutics. Single-cell transcriptomics on mouse nociceptors has transformed our understanding of pain mechanisms. We sought to generate equivalent information for human nociceptors with the goal of identifying transcriptomic signatures of nociceptors, identifying species differences and elucidating new drug targets. We used spatial transcriptomics to molecularly characterize transcriptomes of single dorsal root ganglion (DRG) neurons from 8 organ donors. We identified 12 clusters of human sensory neurons, 5 of which are C nociceptors; as well as 1 Aβ nociceptor, 2 Aδ, 2 Aβ and 1 proprioceptor subtypes. By focusing on expression profiles for ion channels, G-protein coupled receptors (GPCRs) and other pharmacological targets, we provide a rich map of drug targets in the human DRG with direct comparison to mouse sensory neuron transcriptomes. We also compare human DRG neuronal subtypes to non-human primates showing conserved patterns of gene expression among many cell types, but divergence among specific nociceptor subsets. Finally, we identify sex differences in human DRG subpopulation transcriptomes, including a marked increase inCALCAexpression in female pruritogen receptor enriched nociceptors. Our data open the door to development of drug discovery programs for new pain targets and unparalleled molecular characterization of clinical sensory disorders.One Sentence SummaryWe used spatial transcriptomics to molecularly characterize human sensory neurons, comparing them to mouse and non-human primate finding similarities but also divergence, in particular among drug targets.
A data-driven method to learn a jump diffusion process from aggregate biological gene expression data
Authors: Gao Jia-Xing , Wang Zhen-Yi , Zhang Michael Q. , Qian Min-Ping , Jiang Da-Quan 
Published: February 2021

AbstractDynamic models of gene expression are urgently required. Different from trajectory inference and RNA velocity, our method reveals gene dynamics by learning a jump diffusion process for modeling the biological process directly. The algorithm needs aggregate gene expression data as input and outputs the parameters of the jump diffusion process. The learned jump diffusion process can predict population distributions of gene expression at any developmental stage, achieve long-time trajectories for individual cells, and offer a novel approach to computing RNA velocity. Moreover, it studies biological systems from a stochastic dynamics perspective. Gene expression data at a time point, which is a snapshot of a cellular process, is treated as an empirical marginal distribution of a stochastic process. The Wasserstein distance between the empirical distribution and predicted distribution by the jump diffusion process is minimized to learn the dynamics. For the learned jump diffusion equation, its trajectories correspond to the development process of cells and stochasticity determines the heterogeneity of cells. Its instantaneous rate of state change can be taken as “RNA velocity”, and the changes in scales and orientations of clusters can be noticed too. We demonstrate that our method can recover the underlying nonlinear dynamics better compared to parametric models and diffusion processes driven by Brownian motion for both synthetic and real world datasets. Our method is also robust to perturbations of data because it only involves population expectations.
Genomic analyses of 10,376 individuals provides comprehensive map of genetic variations, structure and reference haplotypes for Chinese population
Authors: Cong Peikuan , Bai Wei-Yang , Li Jinchen , Li Nan , Gai Sirui , Khederzadeh Saber , Liu Yuheng , Qiu Mochang , Zhu Xiaowei , Zhao Pianpian , Xia Jiangwei , Yu Shihui , Zhao Weiwei , Liu Junquan , Guan Penglin , Qian Yu , Tao Jianguo , Yang Mengyuan , Tian Geng , Xie Shuyang , Liu Keqi , Tang Beisha , Zheng Hou-Feng 
Published: February 2021

AbstractHere, we initiated the Westlake BioBank for Chinese (WBBC) pilot project with 4,535 whole-genome sequencing individuals and 5,481 high-density genotyping individuals. We identified 80.99 million SNPs and INDELs, of which 38.6% are novel. The genetic evidence of Chinese population structure supported the corresponding geographical boundaries of the Qinling-Huaihe Line and Nanling Mountains. The genetic architecture within North Han was more homogeneous than South Han, and the history of effective population size of Lingnan began to deviate from the other three regions from 6 thousand years ago. In addition, we identified a novel locus (SNX29) under selection pressure and confirmed several loci associated with alcohol metabolism and histocompatibility systems. We observed significant selection of genes on epidermal cell differentiation and skin development only in southern Chinese. Finally, we provided an online imputation server (https://wbbc.westlake.edu.cn/) which could result in higher imputation accuracy compared to the existing panels, especially for lower frequency variants.
Insights on SARS-CoV-2’s Mutations for Evading Human Antibodies: Sacrifice and Survival
Authors: Luan Binquan , Huynh Tien 
Published: February 2021

AbstractRecent mutations on the receptor binding domain (RBD) of the SARS-CoV-2’s spike protein have been manifested as the major cause of the wide and rapid spread of the virus. Especially, the variant B.1.351 in South Africa with the hallmark of triple mutations (N501Y, K417N and E484K) is worrisome. Quickly after the outbreak of this new variant, several studies showed that both N501Y and E484K can enhance the binding between RBD and the human ACE2 receptor. However, the mutation K417N seems to be unfavorable because it removes one interfacial salt-bridge. So far, it is still not well understood why the K417N mutation is selected in the viral evolution. Here, we show that despite the loss in the binding affinity (1.48 kcal/mol) between RBD and ACE2 the K417N mutation abolishes a buried interfacial salt-bridge between RBD and the neutralizing antibody CB6 and thus substantially reduces their binding energy by 9.59 kcal/mol, facilitating the variants to efficiently elude CB6 (as well as many other antibodies). Thus, when proliferating from person to person the virus might have adapted to the human immune system through evasive mutations. Taking into account limited and relevant experimental works in the field, we show that our theoretical predictions are consistent with existing experimental findings. By harnessing the revealed molecular mechanism for variants, it becomes feasible to redesign therapeutic antibodies accordingly to make them more efficacious.
Long-term conservation effects of protected areas in stochastic population dynamics
Authors: Takashina Nao 
Published: February 2021

AbstractTerrestrial and marine protected areas are essential tools in mitigating anthropogenic impacts and promoting population persistence and resource sustainability. Adequately implemented protected areas (PAs) promote long-term conservation effects. Stochasticity causes fluctuations in the conservation effects of PAs, and so it is important to investigate the variabilities of these conservation effects to inform their long-term conservation effects. To investigate long-term conservation effects, I develop and analyze new models of stochastic processes that encompass the fluctuations generated by demographic or environmental stochasticity in PAs management. The stochastic model is built upon individual processes. In the model, density-independent mortality, migration between PAs and non-PAs, and site preferences characterize the features of the PA. The effect of PAs size is also examined. The long-term conservation effects are quantified using the coefficient of variation (CV) of population size in PAs, where a lower CV indicates higher robustness in stochastic variations. Typically, the results from this study demonstrate that sufficiently reduced density-independent mortality in PAs and high site preference and immigration rate of PA are likely to decrease the CV. However, different types of stochasticity induce rather different consequences: under demographic stochasticity, the CV is always reduced when PAs increase the population size therein, but an increased population size by PAs does not always decrease the CV under environmental stochasticity. The deterministic dynamics of the model are investigated, facilitating effective management decisions.