bluuebunny/crossref_metadata_2025_split huggingface dataset:
The SARS-CoV-2 receptor-binding domain expressed in Pichia pastoris as a candidate vaccine antigen
Authors: Limonta-Fernández Miladys , Chinea-Santiago Glay , Martín-Dunn Alejandro Miguel , Gonzalez-Roche Diamile , Bequet-Romero Monica , Marquez-Perera Gabriel , González-Moya Isabel , Canaan-Haden-Ayala Camila , Cabrales-Rico Ania , Espinosa-Rodríguez Luis Ariel , Ramos-Gómez Yassel , Andujar-Martínez Ivan , González-López Luis Javier , de la Iglesia Mariela Perez , Zamora-Sanchez Jesus , Cruz-Sui Otto , Lemos-Pérez Gilda , Cabrera-Herrera Gleysin , Valdes-Hernández Jorge , Martinez-Diaz Eduardo , Pimentel-Vazquez Eulogio , Ayala-Avila Marta , Guillén-Nieto Gerardo 
Published: July 2021

1.AbstractThe effort to develop vaccines based on economically accessible technological platforms available by developing countries vaccine manufacturers is essential to extend the immunization to the whole world population and to achieve the desired herd immunity, necessary to end the COVID-19 pandemic. Here we report on the development of a SARS-CoV-2 receptor-binding domain (RBD) protein, expressed in yeastPichia pastoris.The RBD was modified with addition of flexible N- and C-terminal amino acid extensions aimed to modulate the protein/protein interactions and facilitate protein purification. Fermentation with yeast extract culture medium yielded 30–40 mg/L. After purification by immobilized metal ion affinity chromatography and hydrophobic interaction chromatography, the RBD protein was characterized by mass-spectrometry, circular dichroism, and binding affinity to angiotensin-converting enzyme 2 (ACE2) receptor. The recombinant protein shows high antigenicity with convalescent human sera and also with sera from individuals vaccinated with the Pfizer-BioNTech mRNA or Sputnik V adenoviral-based vaccines. The RBD protein stimulates IFNγ, IL-2, IL-6, IL-4, and TNFα in mice secreting splenocytes from PBMC and lung CD3+ enriched cells. Immunogenicity studies with 50 µg of the recombinant RBD formulated with alum, induce high levels of binding antibodies in mice and non-human primates, assessed by ELISA plates covered with RBD protein expressed in HEK293T cells. The mouse sera inhibited the RBD binding to ACE2 receptor in anin-vitrotest and show neutralization of SARS-CoV-2 infection of Vero E6 cells. These data suggest that the RBD recombinant protein expressed in yeastP. pastorisis suitable as a vaccine candidate against COVID-19.HighlightsThe RBD protein (C-RBD-H6 PP) is expressed with high purity inP. pastoris.Physico-chemical characterization confirms the right folding of the protein.The recombinant protein shows high antigenicity with sera from convalescents.The sera from animals inhibit the RBD-ACE2 binding and neutralize the virus.The C-RBD-H6 protein stimulates IFNγ, IL-2, IL-6, IL-4, and TNFα in mice.
A Deep Learning Model for Screening Type 2 Diabetes from Retinal Photographs
Authors: Yun Jae-Seung , Kim Jaesik , Jung Sang-Hyuk , Cha Seon-Ah , Ko Seung-Hyun , Ahn Yu-Bae , Won Hong-Hee , Sohn Kyung-Ah , Kim Dokyoon 
Published: July 2021

AbstractObjectiveWe aimed to develop and evaluate a non-invasive deep learning algorithm for screening type 2 diabetes in UK Biobank participants using retinal images.Research Design and MethodsThe deep learning model for prediction of type 2 diabetes was trained on retinal images from 50,077 UK Biobank participants and tested on 12,185 participants. We evaluated its performance in terms of predicting traditional risk factors (TRFs) and genetic risk for diabetes. Next, we compared the performance of three models in predicting type 2 diabetes using 1) an image-only deep learning algorithm, 2) TRFs, 3) the combination of the algorithm and TRFs. Assessing net reclassification improvement (NRI) allowed quantification of the improvement afforded by adding the algorithm to the TRF model.ResultsWhen predicting TRFs with the deep learning algorithm, the areas under the curve (AUCs) obtained with the validation set for age, sex, and HbA1c status were 0.931 (0.928-0.934), 0.933 (0.929-0.936), and 0.734 (0.715-0.752), respectively. When predicting type 2 diabetes, the AUC of the composite logistic model using non-invasive TRFs was 0.810 (0.790-0.830), and that for the deep learning model using only fundus images was 0.731 (0.707-0.756). Upon addition of TRFs to the deep learning algorithm, discriminative performance was improved to 0.844 (0.826-0.861). The addition of the algorithm to the TRFs model improved risk stratification with an overall NRI of 50.8%.ConclusionsOur results demonstrate that this deep learning algorithm can be a useful tool for stratifying individuals at high risk of type 2 diabetes in the general population.
Multi-contrast magnetic resonance imaging of visual white matter pathways in glaucoma patients
Authors: Ogawa Shumpei , Takemura Hiromasa , Horiguchi Hiroshi , Miyazaki Atsushi , Matsumoto Kenji , Masuda Yoichiro , Yoshikawa Keiji , Nakano Tadashi 
Published: July 2021

AbstractPurposeGlaucoma is a disorder that involves visual field loss caused by retinal ganglion cell damage. Previous diffusion magnetic resonance imaging (dMRI) studies have demonstrated that retinal ganglion cell damage affects tissues in the optic tract (OT) and optic radiation (OR). However, because previous studies have used a simple diffusion tensor model to analyze dMRI data, the microstructural interpretation of white matter tissue changes remains uncertain. In this study, we used a multi-contrast MRI approach to further clarify the type of microstructural damage that occurs in glaucoma patients.MethodsWe collected multi-shell dMRI data from 17 glaucoma patients and 30 controls using 3T MRI. Using the dMRI data, we estimated three types of tissue property metrics: intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (IsoV). Quantitative T1 (qT1) data, which may be relatively specific to myelin, were collected from all subjects.ResultsIn the OT, all four metrics showed significant differences between the glaucoma and control groups. In the OR, only the ICVF showed significant between-group differences. ICVF was significantly correlated with qT1 in the OR of glaucoma patients, although qT1 did not show any abnormality at the group level.ConclusionsOur results suggest that at the group level, tissue changes in the glaucoma patients’ OR might be explained by axonal damage, which is reflected in the intracellular diffusion signals, rather than myelin damage. The significant correlation between ICVF and qT1 suggests that myelin damage might also occur in a smaller number of severe cases.
Neuropsychiatric disorders as risk factors and consequences of COVID-19: A Mendelian randomization study
Authors: Xiang Yong , Qiu Jinghong , Zhang Ruoyu , Chau Carlos Kwan-Long , Rao Shitao , So Hon-Cheong 
Published: July 2021

AbstractBackgroundMore than 180 million cases of COVID-19 have been reported worldwide. It has been proposed that neuropsychiatric disorders may be risk factors and/or consequences of COVID-19 infection. However, observational studies could be affected by confounding bias.MethodsWe performed bi-directional two-sample Mendelian randomization (MR) analysis to evaluate causal relationships between liability to COVID-19 (and severe/critical infection) and a wide range of neuropsychiatric disorders or traits. We employed GWAS summary statistics from the COVID-19 Host Genetics Initiative. A variety of MR methods including those accounting for horizontal pleiotropy were employed.ResultsOverall, we observed evidence that liability to COVID-19 or severe infection may be causally associated with higher risks of post-traumatic stress disorder (PTSD), bipolar disorder (BD) (especially BD II), schizophrenia (SCZ), attention deficit hyperactivity disorder (ADHD) and suicidal thought (ST) when compared to the general population. On the other hand, liability to a few psychiatric traits/disorders, for example ADHD, alcohol and opioid use disorders may be causally associated with higher risks of COVID-19 infection or severe disease. In genetic correlation analysis, cannabis use disorder, ADHD, and anxiety showed significant and positive genetic correlation with critical or hospitalized infection. All the above findings passed multiple testing correction at a false discovery rate (FDR)<0.05. For pneumonia, in general we observed a different pattern of causal associations. We observed bi-directional positive associations with depression- and anxiety-related phenotypes.ConclusionsIn summary, this study provides evidence for tentative bi-directional causal associations between liability to COVID-19 (and severe infection) and a number of neuropsychiatric disorders. Further replications and prospective studies are required to verify the findings.
Post-viral mental health sequelae in infected persons associated with COVID-19 and previous epidemics and pandemics: Systematic review and meta-analysis of prevalence estimates
Authors: Zürcher Simeon Joel , Banzer Céline , Adamus Christine , Lehmann Anja I. , Richter Dirk , Kerksieck Philipp 
Published: July 2021

AbstractAimsPost-viral mental health problems (MHP) in COVID-19 patients and survivors were anticipated already during early stages of this pandemic. We aimed to synthesize the prevalence of the anxiety, depression, post-traumatic and general distress domain associated with virus epidemics since 2002.MethodsIn this systematic review and meta-analysis, we searched PubMed, PsycINFO, and Embase from 2002 until April 14, 2021 for peer-reviewed studies reporting prevalence of MHP in adults with laboratory-confirmed or suspected SARS-CoV-1, H1N1, MERS-CoV, H7N9, Ebolavirus, or SARS-CoV-2 infection. We included studies that assessed post-viral MHP with validated and frequently used scales. A three-level random-effects meta-analysis for dependent sizes was conducted to account for multiple outcome reporting. We pooled MHP across all domains and separately by severity (above mild or moderate-to-severe) and by acute (one month), ongoing (one to three months), and post-illness stages (longer than three months). A meta-regression was conducted to test for moderating effects, particularly for exploring estimate differences between SARS-Cov-2 and previous pandemics and epidemics. PROSPERO registration: CRD42020194535.ResultsWe identified 59 studies including between 14 to 1002 participants and providing 187 prevalence estimates. MHP, in general, decreased from acute to post-illness from 46□3% to 38□8% and for mild and moderate-to-severe from 22□3% to 18□8%, respectively. We found no evidence of moderating effects except for non-random sampling and H1N1 showing higher prevalence. Pooled MHP differed somewhat between previous pandemics/ epidemics and SARS-CoV-2 but were in a comparable range.ConclusionsMHP prevalence estimates decreased over time but were still on a substantial level at post-illness. Post-viral mental health problems caused by SARS-CoV-2 could have been expected much earlier, given the previous post-viral sequelae.
The Impact of Non-Pharmaceutical Interventions on the First COVID-19 Epidemic Wave in South Africa
Authors: Mabuka Thabo , Ncube Nesisa , Ross Michael , Silaji Andrea , Macharia Willie , Ndemera Tinashe , Lemeke Tlaleng 
Published: July 2021

AbstractOn the 5thof March 2020, South Africa reported its first cases of COVID-19. This signalled the onset of the first COVID-19 epidemic wave in South Africa. The response by the Government of South Africa to the COVID-19 epidemic in South Africa was the use of non-pharmaceutical interventions (NPIs). In this study, a semi-reactive COVID-19 model, the ARI COVID-19 SEIR model, was used to investigate the impact of NPIs in South Africa to understand their effectiveness in the reduction of COVID-19 transmission in the South African population. This study also investigated the COVID-19 testing, reporting, hospitalised cases and excess deaths in the first COVID-19 epidemic wave in South Africa. The results from this study show that the COVID-19 NPI policies implemented by the Government of South Africa played a significant role in the reduction of COVID-19 active, hospitalised cases and deaths in South Africa’s first COVID-19 epidemic wave.
Longitudinal testing for SARS-CoV-2 RNA in day care centers in Hesse, Germany, during increased local incidence and with VOC Alpha as dominant variant: Results of the SAFE KiDS 2 and SAFE KiDS 3 study
Authors: Schenk Barbara , Hoehl Sebastian , Rudych Olga , Menger Dominic , Farmand Samira , Wrobel Franziska , Kreutzer Emilie , Gebert Daniela , Flohr Melanie , Berger Franziska , Weigel Vanessa , Kortenbusch Marhild , Berger Annemarie , Ciesek Sandra 
Published: July 2021

AbstractIn the summer of 2020, we investigated the rate of inapparent shedding of SARS-CoV-2 in a representative sample of day care centers from Hesse, Germany, and found a low positivity rate during a period of low local community spread.To investigate the influence of a high local incidence setting, we conducted the SAFE KiDS 2 study. 577 children and 334 staff members of 47 day care centers were tested for respiratory and gastrointestinal shedding of SARS-CoV-2, and three infections with SARS-CoV-2 in the infectious period were detected. We conclude that viral shedding occurred infrequently while the original “wild-type” variant was dominant.The more transmissible SARS-CoV-2 variant Alpha (B.1.1.7) became the dominant strain after SAFE KiDS 2 was concluded. The SAFE KiDS 3 study investigated the impact of the Alpha variant of SARS-CoV-2 on inapparent viral shedding in the day care setting. In this study, 756 children and 226 staff members from 46 day care centers provided self-collected saliva swabs, the so-called “Lollipop” swabs, which were tested by RT-PCR. In the four-week study period, none of the participants tested positive for SARS-CoV-2 RNA, demonstrating that inapparent shedding of SARS-CoV-2 in the day care setting was also rare during the dominance of the Alpha variant.The influence of the variant of concern Delta on day care centers has yet to be studied.
Connection between two historical tuberculosis outbreak sites in Japan, Honshu, due to a new ancestral L2 sublineage
Authors: Guyeux Christophe , Senelle Gaetan , Refrégier Guislaine , Cambau Emmanuelle , Sola Christophe 
Published: July 2021

SummaryBy gathering an initial collection of 680 public Sequence Read Archives from the Mycobacterium tuberculosis complex (MTC) including 190 belonging to the lineage 2 Beijing, and using a new bioinformatical pipeline, TB-Annotator, that analyzes more than 50,000 characters, we characterized a phylogenetically significant L2 sublineage from isolates found in Tochigi province, that we designate as Asia Ancestral 5. These isolates harbor a number of specific criteria (42 specific SNPs) and their intra-cluster pairwise distance suggested historical and not epidemiological transmission. These isolates harbor a mutation in rpoC, and do not fulfill, either the Modern Beijing lineage criteria (L2.2.1.2.2) or the other currently known Ancestral Beijing lineages described so far. Asia Ancestral 5 isolates do not possess mutT2 58 and ogt 12 characteristics of Modern Beijing, but possess ancient evolutionary characteristics. By looking into the literature, we found in a reference isolate ID381, found in Kobe and Osaka, and defined as “G3”, 36 out of 42 shared and specific SNPs in the same sublineage. Using this study, we also confirmed the intermediate position of the Asia Ancestral 4 recently described in Thailand and suggest an improved classification of the L2 that now includes Asia Ancestral 4 and 5. Increasing the recruitment to around 3000 genomes (including 642 belonging to L2) confirmed our results and suggest new historical ancestral L2 phylogenetically relevant branches that remain to be investigated in detail. We discuss some anthropological and historical data from Japan history and its link to Korea and China. This study shows that the reconstruction of the early history of tuberculosis pandemia in Asia is likely to reveal complex patterns since its emergence.
Tuberculostearic acid, a potential parameter for scoring system construction for Tuberculous meningitis diagnosis
Authors: Fong Tsz Hei , Shi Wangpan , Li Siyi , Liu Guanghui , Ng Chung Lam , Jiang Haishan 
Published: July 2021

AbstractThis study aimed to validate the value of tuberculostearic acid (TBSA) whether it could implicate the existence of M. tuberculosis and assist for clinical diagnosis of Tuberculous Meningitis (TBM). Gas Chromatography/mass spectrometry was used to detect TBSA in the chemically pretreated cerebrospinal fluid of suspected TBM patients. In total, 140 patients were admitted for our study included 27 confirm TBM patients and 50 TBSA positive patients. Sensitivity of 0.7407 (CI 95%: 0.5372-0.8889) and specificity of 0.7345 (CI 95%: 0.6432-0.8132) were calculated. The Lancet consensus scoring system was also applied to evaluate the possibility of TBM in suspected patients, finding that TBSA positive patients showed a similar distributive grouping as the definite TBM patients. Our study implicates that the prospective use of TBSA is worth combining into a scoring system for characterizing the features of Mtb, showing a great potential of TBM diagnosis by TBSA in the future.
Prospective sero surveillance among healthcare workers vaccinated with ChAdOx1 nCoV-19 Corona vaccine in a tertiary hospital of Kerala, India
Authors: Njarekkattuvalappil Swathi Krishna , Bhaskaran Ramesh , V Sree Raj , Jose Ponnu , Rafi Aboobacker Mohammed , Thomas Joe , Innah Susheela J , Raphael Lucy , G Unnikrishnan U , Rajmohan Priyanka , Valsan Chithra , Kuttichira Praveenlal 
Published: July 2021

AbstractBackgroundIndia started Covid-19 vaccination from January 16, 2021 after the approval of two candidate vaccines namely Covishield ™ and Covaxin ™. We report antibody responses among healthcare workers following two doses of Covishield ™ vaccination in a tertiary care setting.MethodsThis prospective serosurveillance study was done among healthcare workers of Jubilee Mission Medical College, vaccinated during January- March 2021. Blood samples were drawn from 170 participants after their 1st dose and from 156 participants after their 2nd dose of Covishield ™ to measure the specific Ig G antibodies against the recombinant S1 subunit of the S protein of SARS-CoV-2.ResultsThe median level of anti SARS CoV-2 Ig G antibody 28 days after the first dose vaccination is 3.64 S/C (IQR=5.91) and 11.6 S/C (IQR= 5.97) after 14 days of second dose vaccination. Protective levels of anti SARS CoV-2 Ig G antibodies is developed by 25 participants (14.7%) after 28 days of first dose of vaccination and by 109 participants (69.9%) after 14 days of second dose. 18-44 years age group (p=0.027) and absence of comorbidities (p=0.079) are associated with protective IgG levels.ConclusionsRise in specific Ig G is observed after vaccination. Higher antibody response is observed with younger age group and absence of comorbidities, though statistically not significant. The influence of BMI is also not significant.
Gene and metabolite expression dependence on body mass index in human myocardium
Authors: Adebayo Adewale S , Roman Marius , Yusoff Syabira , Gulston Melanie , Joel-David Lathishia , Anthony Bony , Lai Florence Y , Murgia Antonio , Eagle-Hemming Bryony , Sheikh Sophia , Kumar Tracy , Aujla Hardeep , Dott Will , Griffin Julian L , Murphy Gavin J , Woźniak Marcin J 
Published: July 2021

AbstractWe hypothesized that body mass index (BMI) dependent changes in myocardial gene expression and energy-related metabolites underlie the biphasic association between BMI and mortality (the obesity paradox) in cardiac surgery. We performed transcriptome profiling and measured a panel of 144 metabolites in 53 and 55, respectively, myocardial biopsies from a cohort of sixty-seven adult patients undergoing coronary artery bypass grafting (registration: NCT02908009). The initial analysis identified 239 transcripts with biphasic BMI dependence. 120 displayed u-shape and 119 n-shape expression patterns. The identified local minima or maxima peaked at BMI 28-29. Based on these results and to best fit the WHO classification, we grouped the patients into three groups: BMI<25, 25≤BMI≤32, and BMI>32. The group analysis indicated that protein translation-related pathways were downregulated in 25≤BMI≥32 compared with BMI<25 patients. Muscle contraction transcripts were upregulated in 25≤BMI≥32 patients, and cholesterol synthesis and innate immunity transcripts were upregulated in the BMI>32 group. Transcripts involved in translation, muscle contraction and lipid metabolism also formed distinct correlation networks with biphasic dependence on BMI. Metabolite analysis identified acylcarnitines and ribose-5-phosphate increasing in the BMI>32 group and α-ketoglutarate increasing in the BMI<25 group. Molecular differences in the myocardium mirror the biphasic relationship between BMI and mortality.
Characterizing parametric differences between the two waves of COVID-19 in India
Authors: Omprakash Arpit 
Published: July 2021

ABSTRACTThe first case of COVID-19 in India was reported on January 30, 2020 [1]. The number of infections rose steeply and preventative measures such as lockdowns were implemented to slow down the spread of the disease. Infections peaked around mid-September the same year and the cases gradually started declining. Following the relaxation of lockdown and the appearance of mutant strains of the virus, a much severe second wave of COVID-19 emerged starting mid-February. For characterization and comparison of both the waves, a SIQR (Susceptible-Infected-Quarantined-Removed) model is used in this paper. The results indicate that a single patient can infect approximately 2.44 individuals in the population. The epidemic doubling time was calculated to be 11.8 days. It is predicted that the actual number of infected patients is grossly underestimated (by a factor of 16) by current testing methods.
A new model of unreported COVID-19 cases outperforms three known epidemic-growth models in describing data from Cuba and Spain
Authors: Ramirez-Torres Erick E. , Selva Castañeda Antonio R. , Randez Luis , Valdés García Luis E. , Cabrales Luis E. Bergues , Sisson Scott A. , Montijano Juan I. 
Published: July 2021

AbstractEstimating the unreported cases of Covid-19 in a region/country is a complicated problem. We propose a new mathematical model that, combined with a deterministic model of the total growth of cases, describes the time evolution of the unreported cases for each reported Covid-19 case. The new model considers the growth of unreported cases in plateau periods and the decrease towards the end of an epidemic wave. We combined the new model with a Gompertz-growth model, a generalized logistic model, and a susceptible-infectious-removed (SIR) model; and fitted them via Bayesian methods to data from Cuba and Spain. The combined-model fits yielded better Bayesian-Information-Criterion values than the Gompertz, logistic, and SIR models alone. This suggests the new model can achieve improved descriptions of the evolution of a Covid-19 epidemic wave. The new model is also able to provide reliable predictions of the epidemic evolution in a short period of time. We include in the paper the steps that researchers should take to use the new model for predictions with other data.