bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of multi epitope-based peptide vaccine against E protein of human COVID-19: An immunoinformatics approach
Authors: Abdelmageed Miyssa I. , Abdelmoneim Abdelrahman H. , Mustafa Mujahed I. , Elfadol Nafisa M. , Murshed Naseem S. , Shantier Shaza W. , Makhawi Abdelrafie M. 
Published: February 2020

AbstractBackgroundNew endemic disease has been spread across Wuhan City, China on December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a “public-health emergency of international concern” due to the rapid and increasing spread of the disease worldwide. Currently, there is no vaccine or approved treatment for this emerging infection; thus the objective of this study is to design a multi epitope peptide vaccine against COVID-19 using immunoinformatics approach.MethodSeveral techniques facilitating the combination of immunoinformatics approach and comparative genomic approach were used in order to determine the potential peptides for designing the T cell epitopes-based peptide vaccine using the envelope protein of 2019-nCoV as a target.ResultsExtensive mutations, insertion and deletion were discovered with comparative sequencing in COVID-19 strain. Additionally, ten peptides binding to MHC class I and MHC class II were found to be promising candidates for vaccine design with adequate world population coverage of 88.5% and 99.99%, respectively.ConclusionT cell epitopes-based peptide vaccine was designed for COVID-19 using envelope protein as an immunogenic target. Nevertheless, the proposed vaccine is rapidly needed to be validated clinically in order to ensure its safety, immunogenic profile and to help on stopping this epidemic before it leads to devastating global outbreaks.
Radiation associated brain image changes after proton therapy for skull base head and neck cancers
Authors: Engeseth Grete May , Stieb Sonja , Radwan Mohamed Abdallah Sherif , He Renjie , Stokkevåg Camilla Hanquist , Brydøy Marianne , Fuller Clifton Dave , Garden Adam S , Rosenthal David I , Phan Jack , Morrison William H , Reddy Jay P , Wu Richard , Zhang Xiaodong , Frank Steven Jay , Gunn Gary Brandon 
Published: February 2020

AbstractBackground and purposeTo characterize patterns and outcomes of brain MR image changes after proton therapy (PT) for skull base head and neck cancer (HNC).Material and methods127 patients treated with PT for HNC who had received at least 40 Gy(RBE) to the brain and had ≥ 1 follow-up MRI > 6 months after PT were analyzed. MRIs were reviewed for radiation- associated image changes (RAIC). MRIs were rigidly registered to planning CTs, and RAIC were contoured on T1 (post-contrast) and T2 weighted sequences, and dose-volume parameters extracted. Probability of RAIC over time was calculated using multistate analysis. Univariate/multivariate analyses were performed using Cox Regression. Recursive partitioning analysis was used to investigate dose-volume correlates of RAIC development.Results17.3% developed RAIC. All RAIC events were asymptomatic and occurred in the temporal lobe (14), frontal lobe (6) and cerebellum (2). The median volume of the RAIC on post-contrast T1 was 0.5 cc at their maximum size. The RAIC spontaneously resolved in 27.3%, progressed in 27.3% and improved or were stable in 29.6% of patients. The 3-year actuarial rate of developing RAIC was 14.3%. Brain and RAIC lesion doses were generally higher for temporal lobe RAIC compared to frontal lobe RAIC. RAIC was observed in 63% of patients when V67 Gy(RBE) of the brain ≥ 0.17 cc.ConclusionRAIC lesions after PT were asymptomatic and either resolved or regressed in the majority of the patients. The estimated dose–volume correlations confirm the importance of minimizing focal high doses to brain when achievable.
Analysis of the epidemic growth of the early 2019-nCoV outbreak using internationally confirmed cases
Authors: Zhao Qingyuan , Chen Yang , Small Dylan S 
Published: February 2020

AbstractBackgroundOn January 23, 2020, a quarantine was imposed on travel in and out of Wuhan, where the 2019 novel coronavirus (2019-nCoV) outbreak originated from. Previous analyses estimated the basic epidemiological parameters using symptom onset dates of the confirmed cases in Wuhan and outside China.MethodsWe obtained information on the 46 coronavirus cases who traveled from Wuhan before January 23 and have been subsequently confirmed in Hong Kong, Japan, Korea, Macau, Singapore, and Taiwan as of February 5, 2020. Most cases have detailed travel history and disease progress. Compared to previous analyses, an important distinction is that we used this data to informatively simulate the infection time of each case using the symptom onset time, previously reported incubation interval, and travel history. We then fitted a simple exponential growth model with adjustment for the January 23 travel ban to the distribution of the simulated infection time. We used a Bayesian analysis with diffuse priors to quantify the uncertainty of the estimated epidemiological parameters. We performed sensitivity analysis to different choices of incubation interval and the hyperparameters in the prior specification.ResultsWe found that our model provides good fit to the distribution of the infection time. Assuming the travel rate to the selected countries and regions is constant over the study period, we found that the epidemic was doubling in size every 2.9 days (95% credible interval [CrI], 2 days—4.1 days). Using previously reported serial interval for 2019-nCoV, the estimated basic reproduction number is 5.7 (95% CrI, 3.4—9.2). The estimates did not change substantially if we assumed the travel rate doubled in the last 3 days before January 23, when we used previously reported incubation interval for severe acute respiratory syndrome (SARS), or when we changed the hyperparameters in our prior specification.ConclusionsOur estimated epidemiological parameters are higher than an earlier report using confirmed cases in Wuhan. This indicates the 2019-nCoV could have been spreading faster than previous estimates.
Clinical characteristics of 2019 novel coronavirus infection in China
Authors: Guan Wei-jie , Ni Zheng-yi , Hu Yu , Liang Wen-hua , Ou Chun-quan , He Jian-xing , Liu Lei , Shan Hong , Lei Chun-liang , Hui David S.C. , Du Bin , Li Lan-juan , Zeng Guang , Yuen Kwok-Yung , Chen Ru-chong , Tang Chun-li , Wang Tao , Chen Ping-yan , Xiang Jie , Li Shi-yue , Wang Jin-lin , Liang Zi-jing , Peng Yi-xiang , Wei Li , Liu Yong , Hu Ya-hua , Peng Peng , Wang Jian-ming , Liu Ji-yang , Chen Zhong , Li Gang , Zheng Zhi-jian , Qiu Shao-qin , Luo Jie , Ye Chang-jiang , Zhu Shao-yong , Zhong Nan-shan 
Published: February 2020

AbstractBackgroundSince December 2019, acute respiratory disease (ARD) due to 2019 novel coronavirus (2019-nCoV) emerged in Wuhan city and rapidly spread throughout China. We sought to delineate the clinical characteristics of these cases.MethodsWe extracted the data on 1,099 patients with laboratory-confirmed 2019-nCoV ARD from 552 hospitals in 31 provinces/provincial municipalities through January 29th, 2020.ResultsThe median age was 47.0 years, and 41.90% were females. Only 1.18% of patients had a direct contact with wildlife, whereas 31.30% had been to Wuhan and 71.80% had contacted with people from Wuhan. Fever (87.9%) and cough (67.7%) were the most common symptoms. Diarrhea is uncommon. The median incubation period was 3.0 days (range, 0 to 24.0 days). On admission, ground-glass opacity was the typical radiological finding on chest computed tomography (50.00%). Significantly more severe cases were diagnosed by symptoms plus reverse-transcriptase polymerase-chain-reaction without abnormal radiological findings than non-severe cases (23.87% vs. 5.20%, P<0.001). Lymphopenia was observed in 82.1% of patients. 55 patients (5.00%) were admitted to intensive care unit and 15 (1.36%) succumbed. Severe pneumonia was independently associated with either the admission to intensive care unit, mechanical ventilation, or death in multivariate competing-risk model (sub-distribution hazards ratio, 9.80; 95% confidence interval, 4.06 to 23.67).ConclusionsThe 2019-nCoV epidemic spreads rapidly by human-to-human transmission. Normal radiologic findings are present among some patients with 2019-nCoV infection. The disease severity (including oxygen saturation, respiratory rate, blood leukocyte/lymphocyte count and chest X-ray/CT manifestations) predict poor clinical outcomes.
Apathy is not associated with reduced ventral striatal volume in patients with schizophrenia
Authors: Burrer Achim , Caravaggio Fernando , Manoliu Andrei , Plitman Eric , Gütter Karoline , Habermeyer Benedikt , Stämpfli Philipp , Abivardi Aslan , Schmidt André , Borgwardt Stefan , Chakravarty Mallar , Lepage Martin , Dagher Alain , Graff-Guerrero Ariel , Seifritz Erich , Kaiser Stefan , Kirschner Matthias 
Published: February 2020

AbstractBackgroundA growing body of neuroimaging research has revealed a relationship between blunted activation of the ventral striatum (VS) and apathy in schizophrenia. In contrast, the association between reduced striatal volume and apathy is less well established, while the relationship between VS function and structure in patients with schizophrenia remains an open question. Here, we aimed to replicate previous structural findings in a larger independent sample and to investigate the relationship between VS hypoactivation and VS volume.MethodsWe included brain structural magnetic resonance imaging (MRI) data from 60 patients with schizophrenia (SZ) that had shown an association of VS hypoactivation with apathy during reward anticipation and 58 healthy controls (HC). To improve replicability, we applied analytical methods developed in two previously published studies: Voxel-based morphometry and the Multiple Automatically Generated Templates (MAGeT) algorithm. VS and dorsal striatum (DS) volume were correlated with apathy correcting for age, gender and total brain volume. Additionally, left VS activity was correlated with left VS volume.ResultsWe failed to replicate the association between apathy and reduced VS volume and did not find a correlation with DS volume. Functional and structural left VS measures exhibited a trend-level correlation (rs=0.248, p=0.067, r2=0.06).ConclusionsOur present data suggests that functional and structural striatal neuroimaging correlates of apathy can occur independently. Replication of previous findings may have been limited by other factors (medication, illness duration, age) potentially related to striatal volume changes in SZ. Finally, associations between reward-related VS function and structure should be further explored.
Incorporating Human Movement Data to Improve Epidemiological Estimates for 2019-nCoV
Authors: Cao Zhidong , Zhang Qingpeng , Lu Xin , Pfeiffer Dirk , Wang Lei , Song Hongbing , Pei Tao , Jia Zhongwei , Zeng Daniel Dajun 
Published: February 2020

AbstractEstimating the key epidemiological features of the novel coronavirus (2019-nCoV) epidemic proves to be challenging, given incompleteness and delays in early data reporting, in particular, the severe under-reporting bias in the epicenter, Wuhan, Hubei Province, China. As a result, the current literature reports widely varying estimates. We developed an alternative geo-stratified debiasing estimation framework by incorporating human mobility with case reporting data in three stratified zones, i.e., Wuhan, Hubei Province excluding Wuhan, and mainland China excluding Hubei. We estimated the latent infection ratio to be around 0.12% (18,556 people) and the basic reproduction number to be 3.24 in Wuhan before the city’s lockdown on January 23, 2020. The findings based on this debiasing framework have important implications to prioritization of control and prevention efforts.One Sentence SummaryA geo-stratified debiasing approach incorporating human movement data was developed to improve modeling of the 2019-nCoV epidemic.
Genetic overlap and causal associations between smoking behaviours and psychiatric traits and disorders in adolescents and adults
Authors: Barkhuizen Wikus , Dudbridge Frank , Ronald Angelica 
Published: February 2020

AbstractBackgroundEpidemiological research shows that smoking is associated with psychiatric disorders and psychotic experiences, even after controlling for confounds such as cannabis use and sleep problems. We investigated degree of genetic overlap and tested for causal associations between smoking and psychiatric traits and disorders using genetic data. We tested whether genetic associations existed beyond genetic influences shared with confounding variables.MethodsGenetic correlations were estimated with LD-score regression between smoking behaviours (N=262,990-632,802) and psychiatric disorders (schizophrenia, bipolar disorder and depression; N=41,653-173,005), psychotic experiences in adolescents (N=6,297-10,098) and adults (N=116,787-117,794) and adult schizotypy (N=3,967-4,057). Genomic Structural Equation Modelling was performed to explore the associations while accounting for genetic influences of confounders (cannabis and alcohol use, risk-taking and insomnia). Causal associations were tested using Generalized Summary-based Mendelian Randomization (GSMR).ResultsSignificant genetic correlations were found between smoking and psychiatric disorders (rg = .10 - .38) and adult PE (rg = .33 - .40). After accounting for covarying genetic influences, genetic associations between most smoking phenotypes and schizophrenia and depression remained but not between smoking behaviours and bipolar disorder or most psychotic experiences. GSMR results supported a causal role of smoking initiation on psychiatric disorders and adolescent cognitive and negative psychotic experiences.ConclusionsPleiotropy between smoking behaviours and schizophrenia and depression exists beyond the common genetic basis of known confounders. Smoking also appears to be causally associated with psychiatric disorders and with cognitive PEs and negative symptoms during adolescence. Exploration of the biological links underlying smoking and psychiatric illness would be well-justified.
Epigenome-wide association study using prediagnostic bloods identifies a new genomic region (near TMEM204 and IFT140) associated with pancreatic cancer risk
Authors: Michaud Dominique S. , Ruan Mengyuan , Koestler Devin C. , Pei Dong , Marsit Carmen J. , De Vivo Immaculata , Kelsey Karl T. 
Published: February 2020

AbstractBackgroundEpigenome-wide association studies (EWAS) using peripheral blood have identified specific sites of DNA methylation associated with risk of various cancers and may hold promise to identify novel biomarkers of risk; however, few studies have been performed for pancreatic cancer and none using a prospective study design.MethodsUsing a nested case-control study design, incident pancreatic cancer cases and matched controls were identified from participants who provided blood at baseline in three prospective cohort studies (Nurses’ Health Study, Health Professionals Follow-up Study and Physicians’ Health Study). DNA methylation levels were measured in DNA extracted from leukocytes using the Illumina MethylationEPIC array. Average follow-up period for this analysis was 13 years.ResultsA region in chromosome 16 near genesTMEM204 and IFT140 was identified as being differentially methylated in cases and controls. For some CpGs in the region, the associations were stronger with shorter time to diagnosis (e.g., OR= 5.95, 95% CI = 1.52-23.12, for top vs bottom quartile, for <5 years between blood draw and cancer diagnosis) but associations remained significantly higher even when cases were diagnosed over 10 years after blood collection. Statistically significant differences in DNA methylation levels were also observed in the gastric secretion pathway using GSEA analysis.ConclusionsChanges in DNA methylation in peripheral blood may mark alterations in metabolic or immune pathways (potentially including alterations in immune subtypes) that play a role in pancreatic cancer. Identifying new biological pathways in carcinogenesis of pancreatic cancer using EWAS approach could provide new opportunities for improving treatment and prevention.
Negative selection on human genes causing severe inborn errors depends on disease outcome and both the mode and mechanism of inheritance
Authors: Rapaport Franck , Boisson Bertrand , Gregor Anne , Béziat Vivien , Boisson-Dupuis Stephanie , Bustamante Jacinta , Jouanguy Emmanuelle , Puel Anne , Rosain Jeremie , Zhang Qian , Zhang Shen-Ying , Gleeson Joseph G. , Quintana-Murci Lluis , Casanova Jean-Laurent , Abel Laurent , Patin Etienne 
Published: February 2020

AbstractBackgroundGenetic variants underlying severe diseases are less likely to be transmitted to the next generation, and are thus gradually and selectively eliminated from the population through negative selection. Here, we study the determinants of this evolutionary process in genes underlying severe diseases in humans.ResultsWe propose a novel approach, CoNeS, integrating known negative selection scores through principal component projection. We compare evidence for negative selection at 319 genes underlying inborn errors of immunity (IEI), which are life-threatening monogenic disorders. We find that genes underlying autosomal dominant (AD) or X-linked IEI are under stronger negative selection than those underlying autosomal recessive (AR) IEI, which are under no stronger selection than genes not known to be disease-causing. However, we find that genes with mutations causing AR IEI that are lethal before reproductive maturity and that display complete penetrance are under stronger negative selection than other genes underlying AR IEI. We also find that genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. Finally, we replicate these results in a study of 1,140 genes causing inborn errors of neurodevelopment.ConclusionsThese findings collectively show that the clinical outcomes of inborn errors, together with the mode and mechanism of inheritance of these errors, determine the strength of negative selection acting on severe disease-causing genes. These findings suggest that estimating the intensity of negative selection with CoNeS may facilitate the selection of candidate genes in patients suspected to carry an inborn error.
Genetic Adaptation in New York City Rats
Authors: Harpak Arbel , Garud Nandita , Rosenberg Noah A. , Petrov Dmitri A. , Combs Matthew , Pennings Pleuni S. , Munshi-South Jason 
Published: February 2020

AbstractBrown rats (Rattus norvegicus) thrive in urban environments by navigating the anthropocentric environment and taking advantage of human resources and by-products. From the human perspective, rats are a chronic problem that causes billions of dollars in damage to agriculture, health and infrastructure. Did genetic adaptation play a role in the spread of rats in cities? To approach this question, we collected whole-genome sequences from 29 brown rats from New York City (NYC) and scanned for genetic signatures of adaptation. We tested for (i) high-frequency, extended haplotypes that could indicate selective sweeps and (ii) loci of extreme genetic differentiation between the NYC sample and a sample from the presumed ancestral range of brown rats in northeast China. We found candidate selective sweeps near or inside genes associated with metabolism, diet, the nervous system and locomotory behavior. Patterns of differentiation between NYC and Chinese rats at putative sweep loci suggests that many sweeps began after the split from the ancestral population. Together, our results suggest several hypotheses on adaptation in rats living in close proximity to humans.
SlKIX8 and SlKIX9 are negative regulators of leaf and fruit growth in tomato
Authors: Swinnen Gwen , Mauxion Jean-Philippe , Baekelandt Alexandra , De Clercq Rebecca , Van Doorsselaere Jan , Inzé Dirk , Gonzalez Nathalie , Goossens Alain , Pauwels Laurens 
Published: February 2020

AbstractPlant organ size and shape are major agronomic traits that depend on cell division and expansion, which are both regulated by complex gene networks. In several eudicot species belonging to the rosid clade, organ growth is controlled by a repressor complex consisting of PEAPOD (PPD) and KINASE-INDUCIBLE DOMAIN INTERACTING (KIX) proteins. The role of these proteins in asterids, which together with the rosids constitute most of the core eudicot species, is still unknown. We used CRISPR-Cas9 genome editing to targetSlKIX8andSlKIX9in the asterid model species tomato (Solanum lycopersicum) and analyzed loss-of-function phenotypes. We found that loss of function ofSlKIX8andSlKIX9led to the production of enlarged, dome-shaped leaves and that these leaves exhibited increased expression of putative SlPPD target genes. Unexpectedly,kix8 kix9mutants carried enlarged fruits with increased pericarp thickness due to cell expansion. At the molecular level, protein interaction assays indicated that SlKIX8 and SlKIX9 act as adaptors between the SlPPD and SlTOPLESS co-repressor proteins. Our results show that KIX8 and KIX9 are regulators of organ growth in asterids and can provide strategies to improve important traits in produce such as thickness of the fruit flesh.One sentence summaryTwo transcriptional repressors negatively regulate organ growth in tomato with loss-of-function lines producing enlarged fruits due to an appearance of more expanded cells in the fruit flesh.
ARF suppresses 5’-terminal oligopyrimidine mRNA translation
Authors: Cottrell Kyle A. , Chiou Ryan C. , Weber Jason D. 
Published: February 2020

AbstractTumor cells require nominal increases in protein synthesis in order to maintain high proliferation rates. As such, tumor cells must acquire enhanced ribosome production. How many of the mutations in tumor cells ultimately achieve this aberrant production is largely unknown. The gene encoding ARF is the most commonly deleted gene in human cancer. ARF plays a significant role in regulating ribosomal RNA synthesis and processing, ribosome export into the cytoplasm, and global protein synthesis. Utilizing ribosome profiling, we show that ARF is a major suppressor of 5’-terminal oligopyrimidine mRNA translation. Genes with increased translational efficiency following loss of ARF include many ribosomal proteins and translation factors. Knockout ofp53caused a similar increase in 5’-TOP mRNA translation. The 5’-TOP regulators mTORC1, eIF4G1 and LARP1 are dysregulated in ARF and p53 null cells.
Batch Equalization with a Generative Adversarial Network
Authors: Qian Wesley Wei , Xia Cassandra , Venugopalan Subhashini , Narayanaswamy Arunachalam , Peng Jian , Ando D. Michael 
Published: February 2020

AbstractAdvances in automation and imaging have made it possible to capture large image datasets for experiments that span multiple weeks with multiple experimental batches of data. However, accurate biological comparisons across the batches is challenged by the batch-to-batch variation due to uncontrollable experimental noise (e.g., different stain intensity or illumination conditions). To mediate the batch variation (i.e. the batch effect), we developed a batch equalization method that can transfer images from one batch to another while preserving the biological phenotype. The equalization method is trained as a generative adversarial network (GAN), using the StarGAN architecture that has shown considerable ability in doing style transfer for consumer images. After incorporating an additional objective that disentangles batch effect from biological features using an existing GAN framework, we show that the equalized images have less batch information as determined by a batch-prediction task and perform better in a biologically relevant task (e.g., Mechanism of Action prediction).