bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of SARS CoV-2 infection among Health Care Workers of a hybrid tertiary COVID 19 hospital in Kerala
Authors: Jessy S J , Beegum M Shamha , Genga S , Bindu G , Chintha S , Sasidharan Sukshma , Tonio Ansu , Aravind R 
Published: July 2021

AbstractBack ground and objectivesThis study was undertaken to estimate the prevalence of SARS-CoV-2 infection among Health care workers [HCWs] of a hybrid COVID treatment hospital in Kerala.MethodsThe study was conducted during 3rd week of January 2021. Among 3550 HCWs, 979 subjects were selected by stratified random sampling and grouped into high risk and low risk category based on job setting. Demographic details and clinical information regarding previous history of COVID 19 were collected at the time of SARS-CoV-2 IgG testing.ResultsFrom 979 subjects, the data with respect to 940 health care workers were analysed. SARS-CoV-2 IgG was detected in 19.1% of HCWs. Seroprevalence among high risk group was 20.3% and that in low risk group was 7.4% [p=0.005]. In high-risk group, seropositivity was noted in 30.54 % of nurses, 19% hospital attenders, 18.9% resident doctors and 6.4% consultant doctors. In those with past history of SARS-CoV-2 infection, seropositivity was 75.4%. In those who were COVID positive during July2020, 33.3% were still IgG reactive.Interpretation and conclusionThe study reported 19.1% SARS CoV-2 IgG reactivity among health care workers in our hospital. Seropositivity was significantly higher in high risk group compared to low risk group. Antibody decay kinetics in our study is comparable to that in published literature. Infection control challenges in hybrid hospitals account for higher seropositivity in this study compared to overall seroprevalence among HCWs in Kerala.
Delta variants of SARS-CoV-2 cause significantly increased vaccine breakthrough COVID-19 cases in Houston, Texas
Authors: Christensen Paul A. , Olsen Randall J. , Long S. Wesley , Subedi Sishir , Davis James J. , Hodjat Parsa , Walley Debbie R. , Kinskey Jacob C. , Saavedra Matthew Ojeda , Pruitt Layne , Reppond Kristina , Shyer Madison N. , Cambric Jessica , Gadd Ryan , Thakur Rashi M. , Batajoo Akanksha , Mangham Regan , Pena Sindy , Trinh Trina , Yerramilli Prasanti , Nguyen Marcus , Olson Robert , Snehal Richard , Gollihar Jimmy , Musser James M. 
Published: July 2021

AbstractGenetic variants of SARS-CoV-2 have repeatedly altered the course of the COVID-19 pandemic. Delta variants of concern are now the focus of intense international attention because they are causing widespread COVID-19 disease globally and are associated with vaccine breakthrough cases. We sequenced the genomes of 16,965 SARS-CoV-2 from samples acquired March 15, 2021 through September 20, 2021 in the Houston Methodist hospital system. This sample represents 91% of all Methodist system COVID-19 patients during the study period. Delta variants increased rapidly from late April onward to cause 99.9% of all COVID-19 cases and spread throughout the Houston metroplex. Compared to all other variants combined, Delta caused a significantly higher rate of vaccine breakthrough cases (23.7% for Delta compared to 6.6% for all other variants combined). Importantly, significantly fewer fully vaccinated individuals required hospitalization. Individuals with vaccine breakthrough cases caused by Delta had a low median PCR cycle threshold (Ct) value (a proxy for high virus load). This value was closely similar to the median Ct value for unvaccinated patients with COVID-19 caused by Delta variants, suggesting that fully vaccinated individuals can transmit SARS-CoV-2 to others. Patients infected with Alpha and Delta variants had several significant differences. Our integrated analysis emphasizes that vaccines used in the United States are highly effective in decreasing severe COVID-19 disease, hospitalizations, and deaths.
Why is patient safety a challenge? Insights from the Professionalism Opinions of Medical Students’ (PoMS) Research
Authors: McGurgan P , Calvert K. , Narula K. , Nathan E. , Celenza A. , Jorm C. 
Published: July 2021

AbstractIntroductionDespite increased emphasis on education and training for patient safety in medical schools, there is little known about factors influencing decision making regarding patient safety behaviours. This study examined the nature and magnitude of factors which may influence opinions around patient safety related behaviours as a means of providing insights into how Australian doctors and medical students view these issues relative to members of the public.MethodsA national, multicentre, prospective, on-line cross sectional survey was conducted using responses to hypothetical clinical scenarios. Three cohorts were surveyed - Australian enrolled medical students, medical doctors and members of the public.Participant responses were compared for the different contextual variables within the scenarios and the participants’ demographic characteristics – student, doctor, member of the public, gender and age (if public or doctors)/ seniority in the course (if a medical student).ResultsIn total there were 2602 medical student participants, 809 doctors and 503 members of the Australian public. Medical doctors were more likely than other cohorts to have statistically significant differences in how they viewed the acceptability of patient safety related behaviours; doctors were more tolerant of medical students not reporting concerning behaviours. Medical students’ opinions frequently demonstrated a ‘transition effect’, bridging between the doctors and publics’ attitudes, consistent with professional identity formation.ConclusionsOpinions on the acceptability of medical students’ patient safety related behaviours were influenced by the demographics of the cohort and the contextual complexity of the scenario. Although the survey used hypothetical scenarios, doctors and medical students’ opinions appear to be influenced by cognitive dissonances, biases and heuristics which may negatively affect patient safety.‘Opinion is the medium between knowledge and ignorance’ Plato
Increase in ventilatory ratio indicates progressive alveolar damage and suggests poor prognosis in severe COVID-19: A single-center retrospective observational study
Authors: Kaku Natsuko , Nakagama Yu , Shirano Michinori , Shinomiya Sari , Shimazu Kazuhiro , Yamazaki Katsuaki , Maehata Yoshito , Morita Ryo , Nitahara Yuko , Yamamoto Hiromasa , Mizobata Yasumitsu , Kido Yasutoshi 
Published: July 2021

AbstractBackgroundThe symptoms of severe COVID-19 are complex and wide-ranging even in intensive care unit (ICU) patients, who may successfully discontinue respiratory support in a short period or conversely require prolonged respiratory support. Damage in the lungs of COVID-19 patients is characterized pathologically as diffuse alveolar damage, the degree of which correlates with the severity of the disease. We hypothesized that the ventilatory ratio (VR), a surrogate parameter for the dead space fraction, might stratify the severity of COVID-19 and predict the successful discontinuation of respiratory support.MethodsForty COVID-19 patients in our ICU were enrolled in this study. Respiratory variables were collected from 2 hours (day 0) after the initiation of respiratory support. We monitored the longitudinal values of VR and other respiratory parameters for 28 days. Patients successfully discontinued from respiratory support by day 28 of ICU stay were defined as the successfully discontinued group, while those who died or failed to discontinue were defined as the failed to discontinue group. VR and other respiratory parameters were compared between these groups.ResultsExcept for advanced age, prolonged ventilation period, and higher mortality in the failed to discontinue group, there were no significant differences between the groups in terms of any other background or respiratory parameter at 2 hours (day 0) after initiation of respiratory support. Longitudinal VR monitoring revealed significantly higher VR values in the failed to discontinue group than the successfully discontinued group on day 4 of respiratory support. Upon predicting the failure to discontinue respiratory support, the area under the receiver operating characteristic curve of VR values on day 4 of respiratory support was 0.748. A threshold of 1.56 achieved the highest predictive performance with a sensitivity of 0.667 and a specificity of 0.762. This threshold enabled the prediction of the successfully discontinued outcome at 0.810 of the negative predictive value.ConclusionsElevated VR values on day 4 of respiratory support were predictive of successful discontinuation of respiratory support in patients with severe COVID-19. Longitudinal VR values after initiation of respiratory support can be used as a practical index to stratify severe COVID-19.
Longitudinal analysis of antibody responses to the Pfizer BNT162b2 vaccine in Patients Undergoing Maintenance Hemodialysis
Authors: Weigert André , Bergman Marie-Louise , Gonçalves Lígia , Godinho Iolanda , Duarte Nádia , Abrantes Rita , Borges Patrícia , Brennand Ana , Malheiro Vanessa , Matoso Paula , Akpogheneta Onome , Kosack Lindsay , Cruz Pedro , Nogueira Estela , Pereira Magda , Ferreira Ana , Marques Marco , Nunes Telmo , Viana João , Demengeot Jocelyne , Penha-Gonçalves Carlos 
Published: July 2021

ABSTRACTBackgroundHemodialyzed patients are at higher risk for COVID-19 and were prioritized in the Portuguese vaccination campaignMethodsWe performed a prospective, longitudinal, cohort analysis of 143 patients on hemodialysis and 143 age-matched controls along BTN162b2 vaccination. ELISA quantified anti-full-length Spike IgG, IgM and IgA levels prior to the first vaccine dose (t0); 3 weeks later (second dose, t1); and 3 weeks later (t2); 127 patients were re-evaluated140 (t3) and 180 days (t4) after the first dose.ResultsSeroconversion at t1 was remarkably low in patients, with positivity for anti-spike IgG, IgM and IgA antibodies of 29.4%, 12% and 41%, respectively, increasing to 90.9% (IgG) and 83.9% (IgA) in t2, (IgM remained unchanged). Below 70 years of age anti-spike IgG levels at t1 were significantly lower compared to age-matched controls and showed a profile similar to older individuals. Immunosuppression was associated with lower antibody responses (p=0.005 at t1; p=0.008 at t2). Previous unresponsiveness to hepatitis B vaccination (75/129, 58% of patients negative for anti-HBs antibodies) did not correlate with humoral unresponsiveness to BTN162b2. Anti-spike IgG, IgM and IgA positivity and antibody levels significantly decay at t3, with IgG levels showing further waning at t4.ConclusionsThe large majority of hemodialyzed patients showed IgG seroconversion upon BNT162b2 mRNA vaccination, albeit a sizable proportion of patients presented poor responses. Follow-up of antibody responses 180 days post vaccination unveiled significant decay of anti-spike antibodies and warrant close monitoring of COVID-19 infection and further studies on reinforced vaccination schedules in patients undergoing maintenance hemodialysis.
Monday effect on confirmed cases of COVID-19 in Japan*
Authors: Nakagawa Kuninori , Kanatani Taro 
Published: July 2021

AbstractWe examined the phenomenon of fewer new confirmed cases of COVID-19 on Mondays in Japan, which we refer to as the Monday effect, and reveal the details of this effect. Specifically, we estimated the difference between the number of new positive cases that decreased over the weekend and the number of new confirmed cases that decreased at the beginning of the week. In Japan, prefectures aggregate and announce the number of confirmed daily cases. This analysis allows us to examine whether there is a Monday effect in each prefecture. We show that the Monday effect is due to the decreased number of inspections on the weekend appearing at the beginning of the week due to a time lag. Our results indicate that the administrative system causes delays in some prefectures, and that some prefectures are less likely to conduct screenings on holidays. Our results also suggest that delays generally occur in prefectures with a population of over 2 million. Congestion, Reporting delay, Public health, COVID-19
Probing the association between resting state brain network dynamics and psychological resilience
Authors: Kraft Dominik , Fiebach Christian J. 
Published: July 2021

AbstractThis study aimed at replicating a previously reported negative correlation between node flexibility and psychological resilience, i.e., the ability to retain mental health in the face of stress and adversity. To this end, we used multiband resting-state BOLD fMRI (TR = .675 sec) from 52 participants who had filled out three psychological questionnaires assessing resilience. Time-resolved functional connectivity was calculated by performing a sliding window approach on averaged time series parcellated according to different established atlases. Multilayer modularity detection was performed to track network reconfigurations over time and node flexibility was calculated as the number of times a node changes community assignment. In addition, node promiscuity (the fraction of communities a node participates in) and node degree (as proxy for time-varying connectivity) were calculated to extend previous work. We found no substantial correlations between resilience and node flexibility. We observed a small number of correlations between the two other brain measures and resilience scores, that were however very inconsistently distributed across brain measures, differences in temporal sampling, and parcellation schemes. This heterogeneity calls into question the existence of previously postulated associations between resilience and brain network flexibility and highlights how results may be influenced by specific analysis choices.Author SummaryWe tested the replicability and generalizability of a previously proposed negative association between dynamic brain network reconfigurations derived from multilayer modularity detection (node flexibility) and psychological resilience. Using multiband resting-state BOLD fMRI data and exploring several parcellation schemes, sliding window approaches, and temporal resolutions of the data, we could not replicate previously reported findings regarding the association between node flexibility and resilience. By extending this work to other measures of brain dynamics (node promiscuity, degree) we observe a rather inconsistent pattern of correlations with resilience, that strongly varies across analysis choices. We conclude that further research is needed to understand the network neuroscience basis of mental health and discuss several reasons that may account for the variability in results.
A machine learning model for screening of body fluid cytology smears
Authors: Sanyal Parikshit , Paul Sayak , Rana Vandana , Kulhari Kanchan 
Published: July 2021

AbstractIntroductionBody fluid cytology is one of the commonest investigations performed in indoor patients, both for diagnosis of suspected carcinoma as well as staging of known carcinoma. Carcinoma is diagnosed in body fluids by the pathologist through microscopic examination and searching for malignant epithelial cell clusters. The process of screening body fluid smears is a time consuming and error prone process.AimWe have attempted to construct a machine learning model which can screen body fluid cytology smears for malignant cells.Materials and methodsMGG stained Ascitic / pleural fluid cytology smears were included from 21 cases (14 malignant, 07 benign) in this study. A total of 693 microphotographs were taken at 40x magnification at the same illumination and after correction of white balance. A Magnus Microphotography system was used for photography. The images were split into the training set (195 images), test set (120 images) and validation set (378 images).A machine learning model, a convolutional neural network, was developed in the Python programming language using the Keras deep learning library. The model was trained with the images of the training set. After completion of training, the model was evaluated on the test set of images.ResultsEvaluation of the model on the test set produced a sensitivity of 97.87%, specificity 85.26%, PPV 95.18%, NPV 93.10% In 06 images, the model has failed to detect singly scattered malignant cells/ clusters. 14 (3.7%) false positives was reported by the model.The machine learning model shows potential utility as a screening tool. However, it needs improvement in detecting singly scattered malignant cells and filtering inflammatory infiltrate.
High potency of sequential therapy with only β-lactam antibiotics
Authors: Batra Aditi , Roemhild Roderich , Rousseau Emilie , Franzenburg Soeren , Niemann Stefan , Schulenburg Hinrich 
Published: July 2021

ABSTRACTEvolutionary adaptation is a major source of antibiotic resistance in bacterial pathogens. Evolution- informed therapy aims to constrain resistance by accounting for bacterial evolvability. Sequential treatments with antibiotics that target different bacterial processes were previously shown to limit adaptation through genetic resistance trade-offs and negative hysteresis. Treatment with homogeneous sets of antibiotics is generally viewed to be disadvantageous, as it should rapidly lead to cross-resistance. We here challenged this assumption by determining the evolutionary response of Pseudomonas aeruginosa to experimental sequential treatments involving both heterogenous and homogeneous antibiotic sets. To our surprise, we found that fast switching between only β-lactam antibiotics resulted in increased extinction of bacterial populations. We demonstrate that extinction is favored by low rates of spontaneous resistance emergence and low levels of spontaneous cross- resistance among the antibiotics in sequence. The uncovered principles may help to guide the optimized use of available antibiotics in highly potent, evolution-informed treatment designs.
Rewiring phospholipid biosynthesis reveals robustness in membrane homeostasis and uncovers lipid regulatory players
Authors: Peter Arun T. John , van Schie Sabine N. S. , Cheung Ngaam J. , Michel Agnès H. , Peter Matthias , Kornmann Benoît 
Published: July 2021

AbstractIntracellular transport of lipids by Lipid Transport Proteins (LTPs) is thought to work alongside vesicular transport to shuttle lipids from their place of synthesis to their destinations. Whereas many LTPs have been identified, it is largely unknown which routes and which LTPs a given lipid utilizes to navigate the multiple membranes of eukaryotic cells. The major and essential phospholipids, phosphatidylethanolamine (PE) and phosphatidylcholine (PC) can be produced by multiple pathways and, in the case of PE, also at multiple locations. Here, we present an approach in which we simplify and rewire yeast phospholipid synthesis by redirecting PE and PC synthesis reactions to distinct subcellular locations using chimeric enzymes fused to specific organelle targeting motifs. In rewired conditions, viability is expected to depend on homeostatic adaptation to the ensuing lipostatic perturbations and on efficient interorganelle lipid transport. We therefore performed genetic screens to identify factors involved in both of these processes. Among the candidates identified, we find genes linked to transcriptional regulation of lipid homeostasis, lipid metabolism and transport. In particular, we identify a requirement for Csf1 –an uncharacterized protein harboring a Chorein-N lipid transport domain- for survival under certain rewired conditions as well as lipidomic adaptation to cold, implicating Csf1 in interorganelle lipid transport and homeostatic adaptation.
How sequence context-dependent mutability drives mutation rate variation in the genome
Authors: Oman Madeleine , Alam Aqsa , Ness Rob W. 
Published: July 2021

AbstractThe rate of mutations varies >100-fold across the genome, altering the rate of evolution, and susceptibility to genetic diseases. The strongest predictor of mutation rate is the sequence itself, varying 75-fold between trinucleotides. The fact that DNA sequence drives its own mutation rate raises a simple but important prediction; highly mutable sequences will mutate more frequently and eliminate themselves in favour of sequences with lower mutability, leading to a lower equilibrium mutation rate. However, purifying selection constrains changes in mutable sequences, causing higher rates of mutation. We conduct a simulation using real human mutation data to test if (1) DNA evolves to a low equilibrium mutation rate and (2) purifying selection causes a higher equilibrium mutation rate in the genome’s most important regions. We explore how this simple process affects sequence evolution in the genome, and discuss the implications for modelling evolution and susceptibility to DNA damage.
An Orally Available Cathepsin L Inhibitor Protects Lungs Against SARS-CoV-2-Induced Diffuse Alveolar Damage in African Green Monkeys
Authors: Frueh Felix W. , Maneval Daniel C. , Bohm Rudolf P. , Dufour Jason P. , Blair Robert V. , Powell Kathy , Aye Pyone P. , Golden Nadia A. , Roy Chad J , Spencer Sky , Russsell-Lodrigue Kasi , Plante Kenneth S. , Plante Jessica A. , McKerrow James , Rappaport Jay 
Published: July 2021

AbstractThe COVID-19 pandemic resulted from global infection by the SARS-CoV-2 coronavirus and rapidly emerged as an urgent health issue requiring effective treatments. To initiate infection, the Spike protein of SARS-CoV-2 requires proteolytic processing mediated by host proteases. Among the host proteases proposed to carry out this activation is the cysteine protease cathepsin L. Inhibiting cathepsin L has been proposed as a therapeutic strategy for treating COVID-19. SLV213 (K777) is an orally administered small molecule protease inhibitor that exhibits in vitro activity against a range of viruses, including SARS-CoV-2. To confirm efficacy in vivo, K777 was evaluated in an African green monkey (AGM) model of COVID-19. A pilot experiment was designed to test K777 in a prophylactic setting, animals were pre-treated with 100mg/kg K777 (N=4) or vehicle (N=2) before inoculation with SARS-CoV-2. Initial data demonstrated that K777 treatment reduced pulmonary pathology compared to vehicle-treated animals. A second study was designed to test activity in a therapeutic setting, with K777 treatment (33 mg/kg or 100 mg/kg) initiated 8 hours after exposure to the virus. In both experiments, animals received K777 daily via oral gavage for 7 days. Vehicle-treated animals exhibited higher lung weights, pleuritis, and diffuse alveolar damage. In contrast, lung pathology was reduced in K777-treated monkeys, and histopathological analyses confirmed the lack of diffuse alveolar damage. Antiviral effects were further demonstrated by quantitative reductions in viral load of samples collected from upper and lower airways. These preclinical data support the potential for early SLV213 treatment in COVID-19 patients to prevent severe lung pathology and disease progression.