bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinic audit on Chronic Obstructive Pulmonary Disease (COPD) management in public primary care setting: Hong Kong experience
Authors: Rui Catherine Chen Xiao , Nga Fu Sau , Kit Leung Wing , Wing Catherine Ng Sze , Yan Wendy Kwan Wing , Kwong Wong Tseng , Fai Chan Pang , Ying Michelle Wong Man , Kit Welchie Ko Wai , Jun Liang , Tung Eric Hui Ming , Chu Li Yim , Wan Luk , David Chao VK
Published: November 2020

Background

Chronic obstructive pulmonary disease (COPD) is a common condition encountered in primary care and presents a substantial burden to the health care system. This study aimed to audit COPD care at all public primary care clinics of Hong Kong and to work out improvement strategies.

Method

The computer record of COPD patients aged 40 or above and had been followed up at any of the 73 public primary care clinics under the Hospital Authority of Hong Kong (HAHK) were reviewed. Evidence-based audit criteria and performance standards were established after thorough literature review. In the first phase from 1st April 2017 to 31st March 2018, deficiencies of care were identified. It was followed by a one-year implementation phase through which a series of improvement strategies were executed. Outcome of the service enhancement was assessed in the second phase from 1st April 2019 to 31st March 2020. Student’s t test and Chi-square test were used to identify any statistically significant changes between the two.

Results

Totally 10,385 COPD cases were identified in Phase 1, among whom 3,102 (29.9%) were active smokers. Most of the patients were male (87.7%) and the mean age was 75.3±9.9 years old. Of those smokers, 1,788 (57.6%) had been referred to Smoking Counselling and Cessation Service (SCCS) and 1,578 (50.9%) actually attended it. 4,866 cases (46.9%) received Seasonal Influenza Vaccine (SIV) and 4,227 cases (40.7%) received Pneumococcal Vaccine (PCV). 1,983 patients (19.1%) had spirometry done before and 1,327 patients (12.8%) had been admitted to hospital due to acute exacerbation of COPD (AECOPD). With the concerted effort taken during the implementation phase, Phase 2 data showed a significant improvement in all criteria. There was a marked increase in the SIV and PCV uptake rate, spirometry performance rate and most importantly, a significant reduction in AECOPD rate leading to hospital admission (9.6%, P<0.00001).

Conclusion

COPD care at all public primary care clinics of HAHK had been significantly improved for all audit criteria via the systematic team approach, which in turn reduced the hospital admission rate and helped relieve the burden of the healthcare system.
Predicting critical illness on initial diagnosis of COVID-19 based on easily-obtained clinical variables: Development and validation of the PRIORITY model
Authors: Martinez-Lacalzada Miguel , Adrián Viteri-Noël Luis , Manzano Luis , Fabregate-Fuente Martin , Rubio-Rivas Manuel , Garcia Sara Luis , Fernández Francisco Arnalich , Beato Pérez José Luis , Núñez Juan Antonio Vargas , Manuel Elpidio Calvo , Espiño Álvarez Alexia Constanza , Castro Santiago J. Freire , Loureiro-Amigo Jose , Fontan Paula Maria Pesqueira , Pina Adela , María Álvarez Suárez Ana , Asiain Andrea Silva , García López Beatriz , del Pino Jairo Luque , Cánovas Jaime Sanz , Pérez Paloma Chazarra , María García García Gema , Núñez-Cortés Jesús Millán , Casas Rojo José Manuel , Gómez Huelgas Ricardo ,   for the SEMI-COVID-19 Network
Published: November 2020

Objectives

Currently available COVID-19 prognostic models have focused on laboratory and radiological data obtained following admission. However, these tests are not available on initial assessment or in resource-limited settings. We aim to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of COVID-19, to identify patients at risk of critical outcomes.

Methods

We used data from the SEMI-COVID-19 Registry, a nationwide multicenter cohort of consecutive patients hospitalized for COVID-19 from 132 centers in Spain. Clinical signs and symptoms, demographic variables, and medical history ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive model. We externally validated the final model in a separate cohort of patients admitted at less-complex hospitals (< 300 beds).We undertook decision curve analysis to assess the clinical usefulness of the predictive model. The primary outcome was a composite of in-hospital death, mechanical ventilation or admission to intensive care unit.

Results

There were 10,433 patients, 7,850 (primary outcome 25.1%) in the development cohort and 2,583 (primary outcome 27.0%) in the validation cohort. Variables in the final model included: age, cardiovascular disease, chronic kidney disease, dyspnea, tachypnea, confusion, systolic blood pressure, and SpO2≤93% or oxygen requirement.The C-statistic in the development cohort was 0.823 (95% CI,0.813-0.834). On external validation, the C-statistic was 0.792 (95% CI,0.772-0.812). The model showed a positive net benefit for threshold probabilities between 3% and 79%.

Conclusions

Among patients presenting with COVID-19, the model based on easily-obtained clinical information had good discrimination and generalizability for identifying patients at risk of critical outcomes without the need of additional testing. The online calculator provided would facilitate triage of patients during the pandemic. This study could provide a useful tool for decision-making in health systems under pandemic pressure and resource-limited settings.
Dietary supplements during the COVID-19 pandemic: insights from 1.4M users of the COVID Symptom Study app - a longitudinal app-based community survey
Authors: Louca Panayiotis , Murray Benjamin , Klaser Kerstin , Graham Mark S , Mazidi Mohsen , Leeming Emily R , Thompson Ellen , Bowyer Ruth , Drew David A , Nguyen Long H , Merino Jordi , Gomez Maria , Mompeo Olatz , Costeira Ricardo , Sudre Carole H , Gibson Rachel , Steves Claire J , Wolf Jonathan , Franks Paul W , Ourselin Sebastien , Chan Andrew T , Berry Sarah E , Valdes Ana M , Calder Philip C , Spector Tim D , Menni Cristina
Published: November 2020

Objectives

Dietary supplements may provide nutrients of relevance to ameliorate SARS-CoV-2 infection, although scientific evidence to support a role is lacking. We investigate whether the regular use of dietary supplements can reduce the risk of testing positive for SARS-CoV-2 infection in around 1.4M users of the COVID Symptom Study App who completed a supplement use questionnaire.

Design

Longitudinal app-based community survey and nested case control study.

Setting

Subscribers to an app that was launched to enable self-reported information related to SARS-CoV-2 infection for use in the general population in three countries.

Main Exposure

Self-reported regular dietary supplement usage since the beginning of the pandemic.

Main Outcome Measures

SARS-CoV-2 infection confirmed by viral RNA polymerase chain reaction test (RT-PCR) or serology test. A secondary outcome was new-onset anosmia.

Results

In an analysis including 327,720 UK participants, the use of probiotics, omega-3 fatty acids, multivitamins or vitamin D was associated with a lower risk of SARS-CoV-2 infection by 14%(95%CI: [8%,19%]), 12%(95%CI: [8%,16%]), 13%(95%CI: [10%,16%]) and 9%(95%CI: [6%,12%]), respectively, after adjusting for potential confounders. No effect was observed for vitamin C, zinc or garlic supplements. When analyses were stratified by sex, age and body mass index (BMI), the protective associations for probiotics, omega-3 fatty acids, multivitamins and vitamin D were observed in females across all ages and BMI groups, but were not seen in men. The same overall pattern of association was observed in both the US and Swedish cohorts. Results were further confirmed in a sub-analysis of 993,365 regular app users who were not tested for SARS-CoV-2 with cases (n= 126,556) defined as those with new onset anosmia (the strongest COVID-19 predictor).

Conclusion

We observed a modest but significant association between use of probiotics, omega-3 fatty acid, multivitamin or vitamin D supplements and lower risk of testing positive for SARS-CoV-2 in women. No clear benefits for men were observed nor any effect of vitamin C, garlic or zinc for men or women. Randomised controlled trials of selected supplements would be required to confirm these observational findings before any therapeutic recommendations can be made.
Prevalence of SARS-CoV-2 in household members and other close contacts of COVID-19 cases: a serologic study in canton of Vaud, Switzerland
Authors: Dupraz Julien , Butty Audrey , Duperrex Olivier , Estoppey Sandrine , Faivre Vincent , Thabard Julien , Zuppinger Claire , Greub Gilbert , Pantaleo Giuseppe , Pasquier Jérôme , Rousson Valentin , Egger Malik , Steiner-Dubuis Amélie , Vassaux Sophie , Masserey Eric , Bochud Murielle , Nusslé Semira Gonseth , D’Acremont Valérie
Published: November 2020

Background

Understanding community-based SARS-CoV-2 transmission is crucial to inform public health decisions. Research on SARS-CoV-2 transmission within households and other close settings using serological testing is scarce.

Methods

We invited COVID-19 cases diagnosed between February 27 and April 1, 2020 in canton of Vaud, Switzerland, to participate, along with household members and other close contacts. Anti-SARS-CoV-2 IgG antibodies were measured using a Luminex immunoassay. We estimated factors associated with serological status using generalized estimating equations.

Findings

Overall, 219 COVID-19 index cases, 302 household members, and 69 other close contacts participated between May 4 and June 27, 2020. More than half of household members (57·2%, 95%CI 49·7-64·3) had developed a serologic response to SARS-CoV-2, while 19·0% (95%CI 10·0-33·2) of other close contacts were seropositive. After adjusting for individual and household characteristics, infection risk was higher in household members aged 65 or more than in younger adults (aOR 3·63, 95%CI 1·05-12·60), and in those not strictly adhering to simple hygiene rules like hand washing (aOR 1·80, 95%CI 1·02-3·17). The risk was lower when more than 5 people outside home were met during the semi-confinement, compared to none (aOR 0·35, 95%CI 0·16-0·74). The individual risk of household members to be seropositive was lower in large households (22% less per each additional person).

Interpretation

We find that, during semi-confinement, household members of a COVID-19 case were at very high risk of getting infected, 3 times more than close contacts outside home. This highlights the need to provide clear messages on specific protective measures applicable at home. For elderly couples, who were especially at risk, providing them external support for daily basic activities is essential.

Funding

Center for Primary Care and Public Health (Unisanté), Canton of Vaud, Leenaards Foundation, Fondation pour l’Université de Lausanne. SerocoViD is part of Corona Immunitas coordinated by SSPH+.
The Prophylactic Effect of Oral Olanzapine on Postoperative Nausea and Vomiting in Laparoscopic Gynecological Surgery: A Randomized Clinical Trial
Authors: Seki Hiroyuki , Kuratani Norifumi , Shiga Toshiya , Miura Norikazu , Kondo Ichiro , Kinoshita Mao , Sento Yoshiki , Masuda Yuya , Ideno Sathoshi , Ikeda Kohei , Takano Koji , Kuwabara Yuuki , Kinugasa Rie , Amaya Fumimasa , Sawa Teiji , Sobue Kazuya , Morisaki Hiroshi
Published: November 2020

Background

Although the antiemetic effect of olanzapine on chemotherapy-induced nausea and vomiting has been characterized, the prophylactic role of olanzapine on postoperative nausea and vomiting (PONV) has not been fully elucidated. This clinical trial aims to examine the effectiveness of olanzapine for preventing PONV.

Methods

Patients undergoing laparoscopic gynecological surgery at 5 university hospitals in Japan will be randomly assigned to receive either 5 mg of oral olanzapine or placebo 2 hours before the induction of anesthesia. All patients will receive intravenous dexamethasone at the induction of anesthesia. The primary outcome will be the incidence of postoperative nausea and vomiting within 24 hours after surgery. Secondary endpoints will include longitudinal changes in the incidence of postoperative nausea and vomiting and overall patient satisfaction.

Discussion

This trial will provide a high quality evidence whether olanzapine prevents PONV in gynecological laparoscopy patients at a high risk for PONV.

Ethics and dissemination

The trial was approved by the institutional review board of the each participating study site. Study findings will be disseminated through peer-reviewed publications and in conference presentations.

Trial registration

UMIN Clinical Trials Registry (UMIN-CTR) ID: 000022634, Registered on October 1, 2016 https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000026031
Evaluation of four commercial, fully automated SARS-CoV-2 antibody tests suggests a revision of the Siemens SARS-CoV-2 IgG assay
Authors: Irsara Christian , Egger Alexander E. , Prokop Wolfgang , Nairz Manfred , Loacker Lorin , Sahanic Sabina , Sonnweber Thomas , Mayer Wolfgang , Schennach Harald , Loeffler-Ragg Judith , Bellmann-Weiler Rosa , Tancevski Ivan , Weiss Günter , Anliker Markus , Griesmacher Andrea , Hoermann Gregor
Published: November 2020

Objectives

Serological tests detect antibodies against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in the ongoing coronavirus disease-19 (COVID-19) pandemic. Independent external clinical validation of performance characteristics is of paramount importance.

Methods

Four fully automated assays, Roche Elecsys Anti-SARS-CoV-2, Abbott SARS-CoV-2 IgG, Siemens SARS-CoV-2 total (COV2T) and SARS-CoV-2 IgG (COV2G) were evaluated using 350 pre-pandemic samples and 700 samples from 245 COVID-19 patients (158 hospitalized, 87 outpatients).

Results

All tests showed very high diagnostic specificity. Sensitivities in samples collected at least 14 days after disease onset were slightly lower than manufacturers’ claims for Roche (93.04%), Abbott (90.83%), and Siemens COV2T (90.26%), and distinctly lower for Siemens COV2G (78.76%). Concordantly negative results were enriched for immunocompromised patients. ROC curve analyses suggest a lowering of the cut-off index for the Siemens COV2G assay. Finally, the combination of two anti-SARS-CoV-2 antibody assays is feasible when considering borderline reactive results.

Conclusions

Thorough on-site evaluation of commercially available serologic tests for detection of antibodies against SARS-CoV-2 remains imperative for laboratories. The potentially impaired sensitivity of the Siemens COV2G necessitates a switch to the company’s newly filed SARS-CoV-2 IgG assay (sCOVG) for follow-up studies. A combination of tests could be considered in clinical practice.
Oncological outcomes of primary renal malignancies other than clear cell renal carcinoma: A retrospective study from a tertiary center
Authors: Mehra Ketan , Ramanitharan Manikandan , Narayanan Dorairajan Lalgudi , Sreenivasan Sreerag Kodakkattil , Kalra Sidhartha
Published: November 2020

Introduction

A lot of research is available about clear cell renal carcinomas (ccRCC). But there are lesser known facts about other subtypes of renal malignancies. With advances in immunohistochemical and cytogenetic techniques, new variants of renal tumors are being increasingly reported. The treatment and prognosis of such rare malignancies is still an enigma. We performed this study to analyze the incidence, clinico-pathological features, surgical treatment, and survival of non-clear cell RCC at our institution.

Materials and Methods

The histopathological reports of 77 Nephrectomy specimens who underwent surgical treatment for suspected renal tumors from 2013-2018 were retrospectively reviewed. 19 (24%) of patients had documented uncommon histologic variants of RCC. The clinical, demographic, and histologic characteristics of these patients were analyzed, and survival was evaluated. The characteristic light microscopy and immunohistochemical features of these lesions were documented.

Results

Mean age was 45 years (21-67 years). Out of 19 patients, 14 (73.6%) were males, and 5 (26.4%) were females. Mean tumor size was 12 (6-31) cm in the largest dimension. 17 (22%) patients underwent radical nephrectomy, and 2 (2.5%) were treated with partial nephrectomy. Patients with collecting duct, synovial sarcoma, and primitive neuro-ectodermal tumor (PNET) had associated inferior vena caval thrombus and underwent venous thrombectomy. Adjuvant treatment in the form of chemotherapy was instituted in collecting duct, adult Wilms and pure sarcomas. There was no mortality in the papillary carcinoma, and the worst prognosis was encountered in

Conclusion

Sarcomatoid and collecting duct variants were associated with worse prognosis. Presently, aggressive surgical extirpation is the mainstay in the management of these histologic variants. Adjuvant chemotherapy and TKI inhibitors have a limited role.
Routine saliva testing for the identification of silent COVID-19 infections in healthcare workers
Authors: Zhang Kevin , Shoukat Affan , Crystal William , Langley Joanne M. , Galvani Alison P. , Moghadas Seyed M.
Published: November 2020

Objective

Current COVID-19 guidelines recommend symptom-based screening and regular nasopharyngeal (NP) testing for healthcare personnel in high-risk settings. We sought to estimate case detection percentages with various routine NP and saliva testing frequencies.

Design

Simulation modelling study.

Methods

We constructed a sensitivity function based on the average infectiousness profile of symptomatic COVID-19 cases to determine the probability of being identified at the time of testing. This function was fitted to reported data on the percent positivity of symptomatic COVID-19 patients using NP testing. We then simulated a routine testing program with different NP and saliva testing frequencies to determine case detection percentages during the infectious period, as well as the pre-symptomatic stage.

Results

Routine bi-weekly NP testing, once every two weeks, identified an average of 90.7% (SD: 0.18) of cases during the infectious period and 19.7% (SD: 0.98) during the pre-symptomatic stage. With a weekly NP testing frequency, the corresponding case detection percentages were 95.9% (SD: 0.18) and 32.9% (SD: 1.23), respectively. A 5-day saliva testing schedule had a similar case detection percentage as weekly NP testing during the infectious period, but identified about 10% more cases (mean: 42.5%; SD: 1.10) during the pre-symptomatic stage.

Conclusion

Our findings highlight the utility of routine non-invasive saliva testing for frontline healthcare workers to protect vulnerable patient populations. A 5-day saliva testing schedule should be considered to help identify silent infections and prevent outbreaks in nursing homes and healthcare facilities.
The impact of vaccination on COVID-19 outbreaks in the United States
Authors: Moghadas Seyed M. , Vilches Thomas N. , Zhang Kevin , Wells Chad R. , Shoukat Affan , Singer Burton H. , Meyers Lauren Ancel , Neuzil Kathleen M. , Langley Joanne M. , Fitzpatrick Meagan C. , Galvani Alison P.
Published: November 2020

Background

Global vaccine development efforts have been accelerated in response to the devastating COVID-19 pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States (US).

Methods

We developed an agent-based model of SARS-CoV-2 transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, while children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection, and specified 10% pre-existing population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current non-pharmaceutical interventions in the US.

Results

Vaccination reduced the overall attack rate to 4.6% (95% CrI: 4.3% - 5.0%) from 9.0% (95% CrI: 8.4% - 9.4%) without vaccination, over 300 days. The highest relative reduction (54-62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-ICU hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3% - 66.7%), 65.6% (95% CrI: 62.2% - 68.6%), and 69.3% (95% CrI: 65.5% - 73.1%), respectively, across the same period.

Conclusions

Our results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with non-pharmaceutical interventions is essential to achieve this impact.

Key points

Vaccination with a 95% efficacy against disease could substantially mitigate future attack rates, hospitalizations, and deaths, even if only adults are vaccinated. Non-pharmaceutical interventions remain an important part of outbreak response as vaccines are distributed over time.
Forecasting COVID-19 cases: A comparative analysis between Recurrent and Convolutional Neural Networks
Authors: Nabi Khondoker Nazmoon , Tahmid Md Toki , Rafi Abdur , Kader Muhammad Ehsanul , Haider Md. Asif
Published: November 2020

When the entire world is waiting restlessly for a safe and effective COVID-19 vaccine that could soon become a reality, numerous countries around the globe are grappling with unprecedented surges of new COVID-19 cases. As the number of new cases is skyrocketing, pandemic fatigue and public apathy towards different intervention strategies are posing new challenges to the government officials to combat the pandemic. Henceforth, it is indispensable for the government officials to understand the future dynamics of COVID-19 flawlessly in order to develop strategic preparedness and resilient response planning. In light of the above circumstances, probable future outbreak scenarios in Brazil, Russia and the United kingdom have been sketched in this study with the help of four deep learning models: long short term memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN) and multivariate convolutional neural network (MCNN). In our analysis, CNN algorithm has outperformed other deep learning models in terms of validation accuracy and forecasting consistency. It has been unearthed in our study that CNN can provide robust long term forecasting results in time series analysis due to its capability of essential features learning, distortion invariance and temporal dependence learning. However, the prediction accuracy of LSTM algorithm has been found to be poor as it tries to discover seasonality and periodic intervals from any time series dataset, which were absent in our studied countries. Our study has highlighted the promising validation of using convolutional neural networks instead of recurrent neural networks when it comes to forecasting with very few features and less amount of historical data.
Amplicon and metagenomic analysis of MERS-CoV and the microbiome in patients with severe Middle East respiratory syndrome (MERS)
Authors: Aljabr Waleed , Alruwaili Muhannad , Penrice-Randal Rebekah , Alrezaihi Abdulrahman , Harrison Abbie Jasmine , Ryan Yan , Bentley Eleanor , Jones Benjamin , Alhatlani Bader Y. , AlShahrani Dayel , Mahmood Zana , Rickett Natasha J. , Alosaimi Bandar , Naeem Asif , Alamri Saad , Alsran Hadel , Hamed Maaweya , Dong Xiaofeng , Assiri Abdullah , Alrasheed Abdullah R. , Hamza Muaawia , Carroll Miles W. , Gemmell Matthew , Darby Alistair , Donovan-Banfield I’ah , Stewart James P. , Matthews David A. , Davidson Andrew D. , Hiscox Julian A.
Published: November 2020

Middle East Respiratory Syndrome coronavirus (MERS-CoV) is a zoonotic infection that emerged in the Middle East in 2012. Symptoms range from mild to severe and include both respiratory and gastrointestinal illnesses. The virus is mainly present in camel populations with occasional spill overs into humans. The severity of infection in humans is influenced by numerous factors and similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underlying health complications can play a major role. Currently, MERS-CoV and SARS-CoV-2 are co-incident in the Middle East and a rapid way is required of sequencing MERS-CoV to derive genotype information for molecular epidemiology. Additionally, complicating factors in MERS-CoV infections are co-infections that require clinical management. The ability to rapidly characterise these infections would be advantageous. To rapidly sequence MERS-CoV, we developed an amplicon-based approach coupled to Oxford Nanopore long read length sequencing. The advantage of this approach is that insertions and deletions can be identified – which are the major drivers of genotype change in coronaviruses. This and a metagenomic approach were evaluated on clinical samples from patients with MERS. The data illustrated that whole genome or near whole genome information on MERS-CoV could be rapidly obtained. This approach provided data on both consensus genomes and the presence of minor variants including deletion mutants. Whereas, the metagenomic analysis provided information of the background microbiome.
REALDIST: Real-valued protein distance prediction
Authors: Adhikari Badri
Published: November 2020

Protein structure prediction continues to stand as an unsolved problem in bioinformatics and biomedicine. Deep learning algorithms and the availability of metagenomic sequences have led to the development of new approaches to predict inter-residue distances—the key intermediate step. Different from the recently successful methods which frame the problem as a multi-class classification problem, this article introduces a real-valued distance prediction method REALDIST. Using a representative set of 43 thousand protein chains, a variant of deep ResNet is trained to predict real-valued distance maps. The contacts derived from the real-valued distance maps predicted by this method, on the most difficult CASP13 free-modeling protein datasets, demonstrate a long-range top-L precision of 52%, which is 17% higher than the top CASP13 predictor Raptor-X and slightly higher than the more recent trRosetta method. Similar improvements are observed on the CAMEO ‘hard’ and ‘very hard’ datasets. Three-dimensional (3D) structure prediction guided by real-valued distances reveals that for short proteins the mean accuracy of the 3D models is slightly higher than the top human predictor AlphaFold and server predictor Quark in the CASP13 competition.
Reduced access to care among older American adults during CoVID-19 pandemic: results from a prospective cohort study
Authors: Das Ashis Kumar , Mishra Devi Kalyan , Gopalan Saji Saraswathy
Published: November 2020

Background

Due to preexisting conditions, older adults are at higher risk of COVID-19 related severe complications. Current evidence is limited on access to care for older adults during the COVID-19 pandemic.

Objectives

To examine the extent of reduced access to care among older American adults during the COVID-19 pandemic, identify predictors and reasons of reduced access.

Materials and methods

Using publicly available data from the COVID-19 module (interim release) of the Health and Retirement Study, we undertook descriptive analyses of older adults stratified by sex, age group, race, education, marital status, employment, receipt of social security benefits, health insurance, number of limitations in activities of daily living and pre-existing conditions. Associations between reduced access to care and predictors were estimated using a multivariable logistic regression model.

Results

About 30% of respondents delayed or avoided care during the pandemic. Reduced access was more likely to be reported by respondents that were female, younger, educated, not receiving social security benefits, with limitations in daily activities and three preexisting conditions. In terms of the reasons, the majority of the respondents (45.9%) reported that their visit was either cancelled or rescheduled by the provider; 13.9% thought they could wait, 10.9% could not get an appointment, 9.1% found it unaffordable, and 7.4% were afraid to visit the provider. Respondents reported of reduced access to doctor’s visits, surgery, prescription filling, and dental care.

Conclusions

We suggest urgent attention on improving access to care for older adults during the pandemic. For nonemergency conditions and routine care that can be delivered virtually, telehealth services can be strengthened. Additionally, health messaging can reemphasize that neglecting medical care might lead to increased morbidity and mortality among older adults from preexisting illnesses.
Nationwide SARS-CoV-2 Surveillance Study for Sewage and Sludges of Wastewater Treatment Plants in Turkey
Authors: Kocamemi Bilge Alpaslan , Kurt Halil , Sait Ahmet , Kadi Hamza , Sarac Fahriye , Aydın Ismail , Saatci Ahmet Mete , Pakdemirli Bekir
Published: November 2020

1.

Since the announcement of the pandemic of Covid-19 by WHO on March 11, 2020, the countries have started to monitor surveillance of SARS-CoV-2 through medical tests. However, people with no and very light symptoms are usually not medically tested or never hospitalized and they are missed. In the study of Wu et al. [1], it was realized that the urine and faeces of all infected people contain SARS-CoV-2. After that, sewage, and sludge-based SARS-CoV-2 surveillance studies have gained significant importance around the world (Fig.1). SARS-CoV-2 was detected in wastewaters in The Netherlands [2,3,4], USA [1,5,6,7, 8, 9, 10], Australia [11], France [12, 13, 14], China [15], Spain [16,17,18,19,20], Italy [21, 22,23], Israel [24], Turkey[25], Germany[26], Japan [27,28], India [29,30], Pakistan [31], Brazil [32,33], Chile [34], Denmark, France, Belgium[35], Equator [36] and Sweden [37] using different virus concentration techniques. Published data show that high concentrations of the SARS-CoV-2 RNA reaches to wastewater treatment plants (WWTPs). On 7th of May 2020, Turkey took its place among a few country which have been started wastewater based surveillance studies at the early stages of pandemic by reporting SARS-CoV-2 RT-qPCR levels of major WWTPs of Istanbul [25]. Turkey [38] first detected SARS-CoV-2 in both primary and waste activated sludges of Istanbul WWTPs. Later, USA [39] and Spain [40] were also studied on sludge samples. There are also studies evaluating the SARS-CoV-2 in WWTPs effluents [10,13,14, 28, 29,30, 34, 36].

This study aimed to scan distribution of Covid-19 through Turkey by SARS-CoV-2 measurements in influent, effluent and sludge samples of WWTPs. The influent, effluent and sludge samples were collected from main WWTPs located in 81 cities of Turkey through May 2020-July 2020. Among those 81 cities, Istanbul metropole with 15.5 million inhabitants was chosen as the pilot city since 65% of all cases in Turkey were present here. Hence, all treatment plants in Istanbul were scanned through the study. The viral activity tests were also conducted for the influent, effluent and sludge samples resulting high qPCR.
Coronavirus (COVID-19) Outbreak Prediction Using Epidemiological Models of Richards Gompertz Logistic Ratkowsky and SIRD
Authors: Sedaghat Ahmad , Abbas Oloomi Seyed Amir , Malayer Mahdi Ashtian , Rezaei Nima , Mosavi Amir
Published: November 2020

On 30 July 2020, a total number of 301,530 diagnosed COVID-19 cases were reported in Iran, with 261,200 recovered and 16,569 dead. The COVID-19 pandemic started with 2 patients in Qom city in Iran on 20 February 2020. Accurate prediction of the end of the COVID-19 pandemic and the total number of populations affected is challenging. In this study, several widely used models, including Richards, Gompertz, Logistic, Ratkowsky, and SIRD models, are used to project dynamics of the COVID-19 pandemic in the future of Iran by fitting the present and the past clinical data. Iran is the only country facing a second wave of COVID-19 infections, which makes its data difficult to analyze. The present study’s main contribution is to forecast the near-future of COVID-19 trends to allow non-pharmacological interventions (NPI) by public health authorities and/or government policymakers. We have divided the COVID-19 pandemic in Iran into two waves, Wave I, from February 20, 2020 to May 4, 2020, and Wave II from May 5, 2020, to the present. Two statistical methods, i.e., Pearson correlation coefficient (R) and the coefficient of determination (R2), are used to assess the accuracy of studied models. Results for Wave I Logistic, Ratkowsky, and SIRD models have correctly fitted COVID-19 data in Iran. SIRD model has fitted the first peak of infection very closely on April 6, 2020, with 34,447 cases (The actual peak day was April 7, 2020, with 30,387 active infected patients) with the re-production number R0=3.95. Results of Wave II indicate that the SIRD model has precisely fitted with the second peak of infection, which was on June 20, 2020, with 19,088 active infected cases compared with the actual peak day on June 21, 2020, with 17,644 cases. In Wave II, the re-production number R0=1.45 is reduced, indicating a lower transmission rate. We aimed to provide even a rough project future trends of COVID-19 in Iran for NPI decisions. Between 180,000 to 250,000 infected cases and a death toll of between 6,000 to 65,000 cases are expected in Wave II of COVID-19 in Iran. There is currently no analytical method to project more waves of COVID-19 beyond Wave II.
A Retrospective Longitudinal Study of COVID-19 as Seen by a Large Urban Hospital in Chicago
Authors: Chen Haotian , Varatharajah Yogatheesan , de Ramirez Sarah Stewart , Arnold Paul , Frankenberger Casey , Hota Bala , Iyer Ravishankar
Published: November 2020

The rapid spread of the novel coronavirus disease 2019 (COVID-19) has created high demand for medical resources, including personnel, intensive care unit beds, and ventilators. As thousands of patients are hospitalized, the disease has shown remarkable diversity in its manifestation; many patients with mild to no symptoms recover from the disease requiring minimal care, but some patients with severe disease progression require mechanical ventilation support in intensive care units (ICU) with an increased risk of death. Studying the characteristics of patients in these various strata can help us understand the varied progression of this disease, enable earlier interventions for at-risk patients, and help manage medical resources more efficiently. This paper presents a retrospective analysis of 10,123 COVID-19 patients treated at the Rush University Medical Center in Chicago, including their demographics, symptoms, comorbidities, laboratory values, vital signs, and clinical history. Specifically, we present a staging scheme based on discrete clinical events (i.e., admission to the hospital, admission to the ICU, mechanical ventilation, and death), and investigate the temporal trend of clinical variables and the effect of comorbidities in each of those stages. We then developed a prognostic model to predict ventilation demands at an individual patient level by analyzing baseline clinical variables, which entails (1) a least absolute shrinkage and selection operator (LASSO) regression and a decision tree model to identify predictors for mechanical ventilation; and (2) a logistic regression model based on these risk factors to predict which patients will eventually need ventilatory support. Our results indicate that the prognostic model achieves an AUC of 0.823 (95% CI: 0.765–0.880) in identifying patients who will eventually require mechanical ventilation.
AI4CoV: Matching COVID-19 Patients to Treatment Options Using Artificial Intelligence
Authors: Hsu Andrew I. , Yeh Amber S. , Chen Shao-Lang , Yeh Jerry J. , Lv DongQing , Hsu Jane Y.-J. , Huang Pai Jung
Published: November 2020

We developed AI4CoV, a novel AI system to match thousands of COVID-19 clinical trials to patients based on each patient’s eligibility to clinical trials in order to help physicians select treatment options for patients. AI4CoV leveraged Natural Language Processing (NLP) and Machine Learning to parse through eligibility criteria of trials and patients’ clinical manifestations in their clinical notes, both presented in English text, to accomplish 92.76% AUROC on a cross-validation test with 3,156 patient-trial pairs labeled with ground truth of suitability. Our retrospective multiple-site review shows that according to AI4CoV, severe patients of COVID-19 generally have less treatment options suitable for them than mild and moderate patients and that suitable and unsuitable treatment options are different for each patient. Our results show that the general approach of AI4CoV is useful during the early stage of a pandemic when the best treatments are still unknown.
Genome-wide CRISPR screens reveal APR-246 (Eprenetapopt) triggers ferroptosis and inhibits iron-sulfur cluster biogenesis
Authors: Fujihara Kenji M. , Zhang Bonnie , Jackson Thomas D. , Nijiagel Brunda , Ang Ching-Seng , Nikolic Iva , Sutton Viv , Trapani Joe , Simpson Kaylene J. , Stojanovski Diana , Leimuehler Silke , Haupt Sue , Phillips Wayne A. , Clemons Nicholas J.
Published: November 2020

The mechanisms by which cells respond and adapt to oxidative stress are largely unknown but are key to developing a rationale for cancer therapies that target antioxidant pathways. APR-246 is a mutant-p53 targeted therapeutic currently under clinical investigation in myeloid dysplastic syndrome (MDS) and acute myeloid leukemia1. Whilst the mechanism of action of APR-246 is thought to be reactivation of wild-type p53 activity through covalent modification of cysteine residues in the core domain of mutant-p53 protein2,3, here we report that the anti-neoplastic capacity of APR-246 lies predominantly in the conjugation of free cysteine. Genome-wide CRISPR perturbation screening, metabolite profiling and proteomics in response to APR-246 treatment in mutant-p53 cancer cells highlighted the role of GSH and mitochondrial metabolism in determining APR-246 efficacy. APR-246 sensitivity was increased through loss of key enzymes in mitochondrial one-carbon metabolism,SHMT2andMTHFD1L, due to diminished glycine supply forde novoGSH synthesis. Critically, we show that APR-246 induces iron-dependent, apoptotic machinery-independent cell death, ferroptosis. Whole-cell proteomics analyses indicated an upregulation of proteins involved in iron-sulfur cluster biogenesis (eg. FDX1). GSH, acetyl-CoA and NADH levels were also depleted in APR-246 treated cells. Importantly, we found that APR-246 inhibits iron-sulfur cluster biogenesis in the mitochondria of cancer cells through cysteine conjugation. This work not only details novel determinants of APR-246 activity in cancer cells, but also provides a clinical roadmap for targeting antioxidant pathways in tumours - beyond targeting mutant-p53 tumours.
Differentiation of human induced pluripotent stem cells into functional airway epithelium
Authors: Ahmed Engi , Fieldes Mathieu , Bourguignon Chloé , Mianné Joffrey , Petit Aurélie , Vernisse Charlotte , Jory Myriam , Cazevieille Chantal , Boukhaddaoui Hassan , Garnett James P. , Massiera Gladys , Vachier Isabelle , Assou Said , Bourdin Arnaud , De Vos John
Published: November 2020

Rationale

Highly reproduciblein vitrogeneration of human bronchial epithelium from pluripotent stem cells is an unmet key goal for drug screening to treat lung diseases. The possibility of using induced pluripotent stem cells (hiPSC) to model normal and diseased tissuein vitrofrom a simple blood sample will reshape drug discovery for chronic lung, monogenic and infectious diseases.

Methods

We devised a simple and reliable method that drives a blood sample reprogrammed into hiPSC subsequently differentiated within 45 days into air-liquid interface bronchial epithelium (iALI), through key developmental stages, definitive-endoderm (DE) and Ventralized-Anterior-Foregut-Endoderm (vAFE) cells.

Results

Reprogramming blood cells from one healthy and 3 COPD patients, and from skin-derived fibroblasts obtained in one PCD patient, succeeded in 100% of samples using Sendai viruses. Mean cell purity at DE and vAFE stages was greater than 80%, assessed by expression of CXCR4 and NKX2.1, avoiding the need of cell sorting. When transferred to ALI conditions, vAFE cells reliably differentiated within 4 weeks into bronchial epithelium with large zones covered by beating ciliated, basal, goblets, club cells and neuroendocrine cells as foundin vivo. Benchmarking all culture conditions including hiPSCs adaptation to single-cell passaging, cell density and differentiation induction timing allowed for consistently producing iALI bronchial epithelium from the five hiPSC lines.

Conclusions

Reliable reprogramming and differentiation of blood-derived hiPSCs into mature and functional iALI bronchial epithelium is ready for wider use and this will allow better understanding lung disease pathogenesis and accelerating the development of novel gene therapies and drug discovery.
Cell Layers: Uncovering clustering structure and knowledge in unsupervised single-cell transcriptomic analysis
Authors: Blair Andrew P. , Hu Robert K. , Farah Elie N. , Chi Neil C. , Pollard Katherine S. , Przytycki Pawel F. , Kathiriya Irfan S. , Bruneau Benoit G.
Published: November 2020

Motivation

Unsupervised clustering of single-cell transcriptomics is a powerful method for identifying cell populations. Static visualization techniques for single-cell clustering only display results for a single resolution parameter. Analysts will often evaluate more than one resolution parameter, but then only report one.

Results

We developed Cell Layers, an interactive Sankey tool for the quantitative investigation of gene expression, coexpression, biological processes, and cluster integrity across clustering resolutions. Cell Layers enhances the interpretability of single-cell clustering by linking molecular data and cluster evaluation metrics, to provide novel insight into cell populations.

Availability and implementation

Upon request
Bringing BOS to light: Uncovering the key enzyme in the biosynthesis of the neurotoxin β-ODAP in Grass Pea (Lathyrus sativusL.)
Authors: Goldsmith Moshe , Barad Shiri , Knafo Maor , Savidor Alon , Ben-Dor Shifra , Brandis Alexander , Mehlman Tevie , Peleg Yoav , Albeck Shira , Dym Orly , Ben-Zeev Efrat , Reich Ziv
Published: November 2020

Grass pea (Lathyrus sativusL.) is a grain legume commonly grown in parts of Asia and Africa for food and forage. While being a highly nutritious and robust crop, able to survive both drought and floods, it produces a neurotoxic compound, β-N-oxalyl-L-α,β-diaminopropionic acid (β-ODAP), which can cause a severe neurological disorder if consumed as a main diet component. So far, the enzyme that catalyzes the formation of β-ODAP has not been identified. By combining protein purification and enzymatic assays with transcriptomic and proteomic analyses, we were able to identify the enzyme β-ODAP synthetase (BOS) from grass pea. We show that BOS is an HXXXD-type acyltransferase of the BAHD superfamily and that its crystal structure is highly similar to that of plant hydroxycinnamoyl transferases. The identification of BOS, more than 50 years after it was proposed, paves the way towards the generation of non-toxic grass pea cultivars safe for human and animal consumption.
Separase cleaves the kinetochore protein Meikin to direct the meiosis I/II transition
Authors: Maier Nolan K , Ma Jun , Lampson Michael A , Cheeseman Iain M
Published: November 2020

To generate haploid gametes, germ cells undergo two consecutive meiotic divisions requiring key changes to the cell division machinery. Here, we explore the regulatory mechanisms that differentially control meiotic events. We demonstrate that the protease Separase rewires key cell division processes at the meiosis I/II transition by cleaving the meiosis-specific protein Meikin. In contrast to cohesin, which is inactivated by Separase proteolysis, cleaved Meikin remains functional, but results in a distinct activity state. Full-length Meikin and the C-terminal Meikin Separase-cleavage product both localize to kinetochores, bind to Plk1 kinase, and promote Rec8 cleavage, but our results reveal distinct roles for these proteins in controlling meiosis. Mutations that prevent Meikin cleavage or that conditionally inactivate Meikin at anaphase I both result in defective meiosis II chromosome alignment. Thus, Separase cleavage of Meikin creates an irreversible molecular switch to rewire the cell division machinery at the meiosis I/II transition.
Papillary and Reticular Fibroblasts Generate Distinct Microenvironments that Differentially Impact Angiogenesis
Authors: Mauroux Adèle , Joncour Pauline , Gillet Benjamin , Hughes Sandrine , Ardidie-Robouant Corinne , Marchand Laëtitia , Liabotis Athanasia , Mailly Philippe , Monnot Catherine , Germain Stephane , Bordes Sylvie , Closs Brigitte , Ruggiero Florence , Muller Laurent
Published: November 2020

Papillary and reticular dermis show distinct extracellular matrix (ECM) and vascularization, and fibroblasts isolated from these compartments have different gene expression patterns and behaviourin vitro.However, due to lack of relevant models, the contribution of skin fibroblast sub-populations to vascularization remains unknown. We thus cultured human papillary and reticular fibroblasts as cell sheets. Differential transcriptomic analysis was performed by RNA sequencing to characterize their microenvironment. Bioinformatic analysis revealed that each fibroblast population expressed specific angiogenesis and matrisome gene expression signatures resulting in specific ECM that differed both in composition and structure. The impact of secreted and ECM-bound factors was then assessed using 3D angiogenesis assays. When co-cultivated with endothelial cells, the papillary and reticular microenvironments induced the formation of distinct capillary networks mimicking the characteristics of vasculature of native dermis subcompartments (vessel diameter and density, number of branch points). Whereas conditioned media of papillary fibroblasts displayed intrinsic high angiogenic potential, reticular ones only contributed to capillary formation induced by exogenous VEGF. These results show that skin fibroblast populations regulate angiogenesis via both secreted and ECM-bound factors. Our work emphasizes the importance of papillary and reticular fibroblasts, not only for modelling dermis microenvironment but also for its vascularization.