bluuebunny/crossref_metadata_2025 huggingface dataset:
Ranking videolaryngoscopes and direct laryngoscopes by orotracheal intubation performance in children: protocol of a systematic review and network meta-analysis of randomized clinical trials at patient level
Authors: C Carvalho Clístenes , LPA Regueira Stéphanie , Souza Ana Beatriz S , Medeiros Lucas MLF , Manoel Marielle BS
Published: January 2021

Background

Videolaryngoscopy was shown to improve glottic visualization in children as compared to direct laryngoscopy, but at the expenses of delayed time for intubation. As little evidence is available regarding the relative performance of different laryngoscopes at present, we designed this systematic review and network meta-analysis to rank the different videolaryngoscopes (VLs) and direct laryngoscopes (DLs) for orotracheal intubation in children.

Methods

We will conduct a search in PubMed, LILACS, Scielo, Embase, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL; 2021, Issue 1) on 27/01/2021. We will include randomized clinical trials fully reported with patients aged ≤ 18 years, making comparisons between different types of laryngoscopes (any of both VLs and DLs) for failed first intubation attempt, intubation time, number of attempts at intubation or number of unsuccessful intubations, failed intubation, glottic view score, or adverse responses to endotracheal intubation. Pooled effects will be estimated by both fixed and random-effects models and presented according to qualitative and quantitative heterogeneity assessment. Sensitivity analyses will be performed as well as a priori subgroup, meta-regression and multiple meta-regression analyses. Additionally, network meta-analyses will be applied to rank the different VLs and DLs. We will also assess the risk of selective publication by funnel plot asymmetry.

Discussion

This systematic review and network meta-analysis aim to understand which laryngoscopes perform better than others for orotracheal intubation.

Systematic review registration

The current protocol was submitted to PROSPERO on 25/01/2021.
Point-of-Care CRISPR-Cas-Assisted SARS-CoV-2 Detection in an Automated and Mobile Droplet Magnetofluidic Device
Authors: Chen Fan-En , Lee Pei-Wei , Park Joon Soo , Trick Alexander Y. , Chen Liben , Shah Kushagra , Hsieh Kuangwen , Wang Tza-Huei
Published: January 2021

In the fight against COVID-19, there remains unmet needs in developing point-of-care (POC) diagnostic testing tools that can rapidly and sensitively detect the causative SARS-CoV-2 virus to control disease transmission and improve patient management. Although recent CRISPR-Cas-assisted SARS-CoV-2 detection assays (such as DETECTR and SHERLOCK) are viewed as transformative solutions for POC diagnostic testing, their lack of simple sample processing and full integration within an automated and portable device hamper their potential for POC use. We report herein POC-CRISPR – a new single-step CRISPR-Cas-assisted assay that is coupled to droplet magnetofluidics (DM) – that leverages simple magnetic concentration and transport of nucleic acid-binding magnetic beads to accomplish sample preparation and assay automation. By further adapting the assay into a fully integrated thermoplastic cartridge within a palm-sized mobile device, POC-CRISPR was able to detect 1 genome equivalent (GE)/µL SARS-CoV-2 RNA from a sample volume of 100 µL in 30 min. Moreover, when evaluated with unprocessed clinical nasopharyngeal (NP) swab eluates, POC-CRISPR identified SARS-CoV-2 positive samples in as short as 20 min and achieved full concordance with standard RT-qPCR.
Modeling the asymptomatic prevalence of SARS-CoV-2 epidemic in Italy and the ISTAT survey
Authors: Traini Marco Claudio , Caponi Carla , Ferrari Riccardo , De Socio Giuseppe Vittorio
Published: January 2021

objectives

August 3rd, 2020, the Italian National Institute of Statistics (ISTAT) presented preliminary results of seroprevalence survey on the percentage of individuals affected by Covid-19. The survey aims to define (within the entire population of Italy) the portion of individuals that developed an antibody response against SARS-CoV-2. For the first time one has an estimate of the asymptomatic infected population and the possibility to acknowledge its potential rôle in the infection spread in Italy, one of the most affected areas in Europe. The information obtained allow a particularly sensitive validation of epidemiological models which include the asymptomatic class.

methods

The present study is devoted to the construction of a model able to simulate, in a systematic way, the asymptomatic group whose relevance in the, SARS-CoV-2 epidemic, has been recently investigated and discussed. The investigation involves the description of the first epidemic outbreak in Italy as well as the predictive analysis of the ongoing second wave. In particular the possible correction to the data of the serological tests because of their sensitivity and specificity.

results

The model: taken as an example of the models presently used, satisfactory reproduces the data of the ISTAT survey showing a relevant predictive power and relegating in a secondary position models which do not include, in the simulation, the presence of asymptomatic groups. The corrections due to the serological test sensitivity (in particular those ones depending on the symptoms onset) make the comparison between data and models less accurate.

conclusions

The predictions of the model confirm a relevant presence of asymptomatic individuals also during the second pandemic wave in Italy. The ratio of reported to unreported cases is predicted to be roughly 1:4. A more detailed knowledge of the results of the survey could allow to correct, in a relevant way, the data by means of the experimental evidences on the antibodies sensibility. The model analyses of the vaccination strategies, confirms the relevance of a massive administration with the beginning of the year to arrive at the end of the infection within August 2021.
Neighbourhood-level risk factors of COVID-19 incidence and mortality
Authors: van Ingen Trevor , Akingbola Samantha , Brown Kevin A. , Daneman Nick , Buchan Sarah A. , Smith Brendan T.
Published: January 2021

Background

Racialized and low income communities face disproportionally high rates of coronavirus 2019 (COVID-19) infection and death. However, data on inequities in COVID-19 across granular categories of socio-demographic characteristics is more sparse.

Methods

Neighbourhood-level counts of COVID-19 cases and deaths in Ontario, Canada recorded as of July 28th, 2020 were extracted from provincial and local reportable infectious disease surveillance systems. Associations between COVID-19 incidence and mortality and 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics were estimated with Poisson generalized linear mixed models. Housing characteristic variables were subsequently added to models to explore if housing may have a confounding influence on the relationships between immigration, race, and socio-economic status and COVID-19 incidence.

Results

There were large inequities in COVID-19 incidence and mortality across the socio-demographic variables examined. Neighbourhoods having a higher proportion immigrants, racialized populations, large households and low socio-economic status were associated with COVID-19 risk. Adjusting for housing characteristics, especially unsuitably crowded housing, attenuated COVID-19 risks. However persistent risk remained for neighbourhoods having high proportions of immigrants, racialized populations, and proportion of Black, Latin American, and South Asian residents.

Conclusions

Socio-demographic factors account for some of the neighbourhood-level differences in COVID-19 across Ontario. Housing characteristics account for a portion, but not all, of the excess burden of COVID-19 experienced by immigrant, racialized, low income and low education populations.
Assessing antimicrobial resistance, utilization and stewardship in Yemen: An exploratory mixed-methods study
Authors: Orubu ESF , Najwa A , Ching C , Bu Jawdeh S , Anderson J , Sheikh R , Hariri F , Basaleem H , Zaman MH
Published: January 2021

Antimicrobial resistance (AMR), largely driven by irrational use of antimicrobials, is a global, multi-faceted problem calling for a complete understanding of all contributory factors for effective containment. In conflict settings, war-wounds and malnutrition can combine with existing social determinants to increase demand for antibiotics, compounding irrational use. In this study, we focus on Yemen, a low-income country with active conflict for the last five years, and analyze the current status of awareness and stewardship efforts regarding AMR. We performed a survey of prescribers/physicians and pharmacists to describe perceptions of AMR prevalence, antibiotic use practices and stewardship in Yemen, supported by a non-systematic scoping literature review and a key informant interview. Participants (96%, n=57) reported a perceived high AMR prevalence rate. Prescribers (74%, 20/27) reported pressure to prescribe broad-spectrum antibiotics. In the majority of cases (81%, 22/27), Antimicrobial Sensitivity Tests (AST) were not performed to inform antibiotic choice. The main barrier to AST was cost. Most pharmacists (67%, 18/27) sold antibiotics without prescriptions. Amoxicillin (including amoxicillin-clavulanate) was the most-commonly prescribed (63%, 17/27) or dispensed (82%, 22/27) antibiotic. AST was rated the least important solution to AMR in Yemen. While there was awareness of a high AMR rate, stewardship is poor in Yemen. We note that barriers to the use of AST could be addressed through the deployment of low-cost AST kits. Compulsory continuing education emphasizing the use of AST to guide prescribing and patients’ awareness programs could help avoid irrational use.
Evidence for SARS-CoV-2 Spike Protein in the Urine of COVID-19 patients
Authors: George Santosh , Pal Anasuya Chattopadhyay , Gagnon Jacqueline , Timalsina Sushma , Singh Pallavi , Vydyam Pratap , Munshi Muhammad , Chiu Joy E. , Renard Isaline , Harden Christina A. , Ott Isabel M. , Watkins Anne E. , Vogels Chantal B.F. , Lu Peiwen , Tokuyama Maria , Venkataraman Arvind , Casanovas-Massana Arnau , Wyllie Anne L. , Rao Veena , Campbell Melissa , Farhadian Shelli F. , Grubaugh Nathan D. , Dela Cruz Charles S. , Ko Albert I. ,   ‘Yale IMPACT study’ team, Perez Amalia Berna , Akaho Elikplim H. , Moledina Dennis G , Testani Jeffrey , John Audrey R , Ledizet Michel , Mamoun Choukri Ben
Published: January 2021

SARS-CoV-2 infection has so far affected over 42 million people worldwide, causing over 1.1 million deaths. With the large majority of SARS-CoV-2 infected individuals being asymptomatic, major concerns have been raised about possible long-term consequences of the infection. We developed an antigen capture assay to detect SARS-CoV-2 spike protein in urine samples from COVID-19 patients whose diagnosis was confirmed by PCR from nasopharyngeal swabs (NP-PCR+). The study used a collection of 233 urine samples from 132 participants from Yale New Haven Hospital and the Children’s Hospital of Philadelphia obtained during the pandemic (106 NP-PCR+ and 26 NP-PCR-) as well as a collection of 20 urine samples from 20 individuals collected before the pandemic. Our analysis identified 23 out of 91 (25%) NP-PCR+ adult participants with SARS-CoV-2 spike S1 protein in urine (Ur-S+). Interestingly, although all NP-PCR+ children were Ur-S-, 1 NP-PCR-child was found to be positive for spike protein in urine. Of the 23 Ur-S+ adults, only 1 individual showed detectable viral RNA in urine. Our analysis further showed that 24% and 21% of NP-PCR+ adults have high levels of albumin and cystatin C in urine, respectively. Among individuals with albuminuria (>0.3 mg/mg of creatinine) statistical correlation could be found between albumin and spike protein in urine. Together, our data showe that 1 of 4 of SARS-CoV-2 infected individuals develop renal abnormalities such as albuminuria. Awareness about the long-term impact of these findings is warranted.
Forecasting virus outbreaks with social media data via neural ordinary differential equations
Authors: Núñez Matías , Barreiro Nadia L. , Barrio Rafael A. , Rackauckas Christopher
Published: January 2021

In the midst of the covid-19 pandemic, social media data collected in real time has the potential of being an early indicator of a new epidemic wave. This possibility is explored here by using a neural ordinary differential equation (neural ODE) that is trained to predict virus outbreaks for a geographic region. It learns from multivariate time series of signals obtained from a novel set of massive online surveys about COVID-19 symptoms. Once trained, the neural ODE is able to capture the dynamics of the interlinked local signals and accurately predict the number of new infections up to two months in advance. Moreover, it can estimate the future effects of changes in the number of infected at a given time, which can be associated with the flow of people entering or leaving a given region or, for instance, with a local vaccination campaign. This work gives compelling preliminary evidence for the predictive power of widely distributed social media surveys for public health application
Mitigation policies and vaccination in the COVID-19 pandemic: a modelling study
Authors: Valiati Naiara C.M. , Villela Daniel A.M.
Published: January 2021

The perspective of vaccination to protect human population from infection of SARS-CoV-2 virus has great potential to control the pandemic. Nevertheless, vaccine planning requires phased introduction with age groups, health workers, and vulnerable people. We developed a mathematical model capable of capturing the dynamics of the SARS-CoV-2 dissemination aligned with social distancing, isolation measures, and vaccination. The city of Rio de Janeiro provides a case study to analyze possible scenarios including non–pharmaceutical interventions and vaccination in the epidemic scenario. Our results shows that a combination of different policies such as case isolation and social distancing are more effective for mitigating the epidemics. Furthermore, these policies will still be necessary in a phased vaccination program. Therefore, health surveillance activities should be maintained along with vaccination planning in scheduled groups until a large vaccinated coverage is reached.
Disease-specific ACMG/AMP guidelines improve sequence variant interpretation for hearing loss
Authors: Patel Mayher J , DiStefano Marina T , Oza Andrea M , Hughes Madeline Y , Wilcox Emma H , Hemphill Sarah E , Cushman Brandon J , Grant Andrew R , Siegert Rebecca K , Shen Jun , Chapin Alex , Boczek Nicole J , Schimmenti Lisa A , Nara Kiyomitsu , Kenna Margaret , Azaiez Hela , Booth Kevin T , Griffith Andrew , Avraham Karen B , Kremer Hannie , Rehm Heidi L , Amr Sami S , Abou Tayoun Ahmad N ,   ClinGen Hearing Loss Clinical Domain Working Group
Published: January 2021

Purpose

The ClinGen Variant Curation Expert Panels (VCEPS) provide disease-specific rules for accurate variant interpretation. Using hearing loss-specific American College of Medical Genetics/Association for Molecular Pathology (HL-specific ACMG/AMP) guidelines, the ClinGen Hearing Loss VCEP (HL VCEP) illustrates the utility of expert specifications in resolving conflicting variant interpretations.

Methods

A total of 157 variants across nine hearing loss genes were curated and submitted to ClinVar by the HL VCEP. The curation process consisted of collecting published and unpublished data for each variant by biocurators, followed by bi-monthly meetings of an expert curation subgroup that reviewed all evidence and applied the HL-specific ACMG/AMP guidelines to reach a final classification.

Results

Before expert curation, 75% (117/157) of variants had single or multiple VUS submissions (17/157) or had conflicting interpretations in ClinVar (100/157). After applying the HL-specific ACMG/AMP guidelines, 24% (4/17) of VUS variants and 69% (69/100) of discordant variants were resolved into Benign (B), Likely Benign (LB), Likely Pathogenic (LP), or Pathogenic (P). Overall, 70% (109/157) variants had unambiguous classifications (B, LB, LP, P). We quantify the contribution of the HL-specified ACMG/AMP codes to variant interpretation.

Conclusion

Expert specification and application of the HL-specific ACMG/AMP guidelines effectively resolved discordant interpretations in ClinVar. This study supports the utility of ClinGen VCEPs in helping the community move towards more consistent variant interpretations, which will improve the care of patients with genetic disorders.
SARS-CoV-2 antigen rapid diagnostic test enhanced with silver amplification technology
Authors: Miyakawa Kei , Funabashi Rikako , Yamaoka Yutaro , Jeremiah Sundararaj Stanleyraj , Katada Junichi , Wada Atsuhiko , Takei Toshiki , Shimizu Kohei , Ozawa Hiroki , Kawakami Chiharu , Usuku Shuzo , Tanaka Nobuko , Yamazaki Etsuko , Shimizu Hideaki , Okabe Nobuhiko , Hasegawa Hideki , Ryo Akihide
Published: January 2021

Rapid diagnosis of COVID-19 is essential for instituting measures to prevent viral spread. SARS-CoV-2 antigen rapid diagnostic test (Ag-RDT) based on lateral flow immunochromatography assay (LFIA) principle can visually indicate the presence of SARS-CoV-2 antigens as a band. Ag-RDT is clinically promising as a point-of-care testing because it can give results in a short time without the need for special equipment. Although various antigen capture LFIAs are now available for rapid diagnosis for SARS-CoV-2 infection, they face the problems of low sensitivity. We have previously developed highly specific monoclonal antibodies (mAb) against SARS-CoV-2 nucleocapsid protein (NP) and in this study, we have employed these mAbs to develop a new LFIA that can detect SARS-CoV-2 NP in nasopharyngeal swab samples with higher sensitivity by combining them with silver amplification technology. We also compared the performance of our Ag-RDT against the commercially available Ag-RDTs using clinical samples to find that our newly developed LFIA performed best among tested, highlighting the superiority of silver amplification technology.
Racial and Ethnic Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: An Analysis of 45 States and the District of Columbia
Authors: Xu Jay J. , Chen Jarvis T. , Belin Thomas R. , Brookmeyer Ronald S. , Suchard Marc A. , Ramirez Christina M.
Published: January 2021

The coronavirus disease 2019 (COVID-19) epidemic in the United States has disproportionately impacted communities of color across the country. Focusing on COVID-19-attributable mortality, we expand upon a national comparative analysis of years of potential life lost (YPLL) attributable to COVID-19 by race/ethnicity (Bassett et al., 2020), estimating percentages of total YPLL for non-Hispanic Whites, non-Hispanic Blacks, Hispanics, non-Hispanic Asians, and non-Hispanic American Indian or Alaska Natives, contrasting them with their respective percent population shares, as well as age-adjusted YPLL rate ratios – anchoring comparisons to non-Hispanic Whites – in each of 45 states and the District of Columbia using data from the National Center for Health Statistics as of December 30, 2020. Using a novel Monte Carlo simulation procedure to quantify estimation uncertainty, our results reveal substantial racial/ethnic disparities in COVID-19-attributable YPLL across states, with a prevailing pattern of non-Hispanic Blacks and Hispanics experiencing disproportionately high and non-Hispanic Whites experiencing disproportionately low COVID-19-attributable YPLL. Furthermore, observed disparities are generally more pronounced when measuring mortality in terms of YPLL compared to death counts, reflecting the greater intensity of the disparities at younger ages. We also find substantial state-to-state variability in the magnitudes of the estimated racial/ethnic disparities, suggesting that they are driven in large part by social determinants of health whose degree of association with race/ethnicity varies by state.
R1441G but not G201S mutation enhances LRRK2 mediated Rab10 phosphorylation in human peripheral blood neutrophils
Authors: Fan Ying , Nirujogi Raja S. , Garrido Alicia , Martínez Javier Ruiz , Bergareche-Yarza Alberto , Mondragón Rezola Elisabet , Aragón Ana Vinagre , Croitoru Ioana , Pagola Ana Gorostidi , Markinez Laura Paternain , Alcalay Roy , Hickman Richard A. , Duering Jonas , Pratuseviciute Neringa , Padmanabhana Shalini , Valldeoriola Francesc , José Martí Maria , Tolosa Eduardo , Alessi Dario R , Sammler Esther
Published: January 2021

Gain-of kinase function variants in LRRK2 (leucine-rich repeat kinase 2) cause Parkinson’s disease (PD), albeit with incomplete and age-dependent penetrance, offering the prospect of disease-modifying treatment strategies via LRRK2 kinase inhibition. LRRK2 phosphorylates a subgroup of RabGTPases including Rab10 and pathogenic mutations enhance LRRK2-mediated phosphorylation of Rab10 at Thr73.

In this study we analyse LRRK2 dependent Rab10Thr73 phosphorylation in human peripheral blood neutrophils isolated from 101 individuals using quantitative immunoblotting and mass spectrometry. Our cohort includes 42 LRRK2 mutation carriers (21 with the G2019S mutation that resides in the kinase domain and 21 with the R1441G mutation that lies within the ROC-COR domain), 27 patients with idiopathic PD, and 32 controls.

We show that LRRK2 dependent Rab10 Thr73 phosphorylation is significantly elevated in all R1441G LRRKR2 mutation carriers irrespective of disease status. PD manifesting and non-manifesting G2019S mutation carriers as well as idiopathic PD samples did not display elevated Rab10 Thr73 phosphorylation. Furthermore, we analysed brain samples of 10 G2019S and 1 R1441H mutation carriers as well as 10 individuals with idiopathic PD and 10 controls. We find high variability for pRab10Thr73 phosphorylation amongst donors irrespective of genetic and disease state.

We conclude that in vivo LRRK2 dependent pRab10Thr73 analysis in human peripheral blood neutrophils is a specific and robust biomarker for LRRK2 kinase activation for individuals with mutations such as R1441G that enhance pRab10Thr73 phosphorylation over 2-fold. We provide the first evidence that the LRRK2 R1441G mutation enhances LRRK2 kinase activity in a primary human cell.
SARS-CoV-2 Seroepidemiology in Children and Adolescents
Authors: Levorson Rebecca E , Christian Erica , Hunter Brett , Sayal Jasdeep , Sun Jiayang , Bruce Scott A , Garofalo Stephanie , Southerland Matthew , Ho Svetlana , Levy Shira , Defillipi Christopher , Peake Lilian , Place Frederick C , Hourigan Suchitra K
Published: January 2021

Objectives

Pediatric SARS-CoV-2 data remain limited and seropositivity rates in children were reported as <1% early in the pandemic. Seroepidemiologic evaluation of SARS-CoV-2 in children in a major metropolitan region of the United States was performed.

Methods

Children and adolescents ≤19 years were enrolled in a cross-sectional, observational study of SARS-CoV-2 seroprevalence from July-October 2020 in Northern Virginia, United States. Demographic, health, and COVID-19 exposure information was collected, and blood was analyzed for SARS-CoV-2 spike protein total antibody. Risk factors associated with SARS-CoV-2 seropositivity were analyzed. Orthogonal antibody testing was performed, and samples were evaluated for responses to different antigens.

Results

In 1038 children, the anti-SARS-CoV-2 total antibody positivity rate was 8.5%. After multivariate logistic regression, significant risk factors included Hispanic ethnicity, public or absent insurance, a history of COVID-19 symptoms, exposure to person with COVID-19, a household member positive for SARS-CoV-2 and multi-family or apartment dwelling without a private entrance. 66% of seropositive children had no symptoms of COVID-19. Orthogonal antibody testing with a receptor binding domain specific antigen revealed a high concordance of 80.5%. Children also demonstrated a robust immune response to the nucleocapsid antigen.

Conclusions

A much higher burden of SARS-CoV-2 infection, as determined by seropositivity, was found in children than previously reported; this was also higher compared to adults in the same region at a similar time. Contrary to prior reports, we determined children shoulder a significant burden of COVID-19 infection. The role of children’s disease transmission must be considered in COVID-19 mitigation strategies including vaccination.

Article Summary

8.5% of children had SARS-CoV-2 antibodies in Fall 2020, double the adult rate. The role of pediatric infection is important to consider in mitigation strategies.

What’s Known on This Subject

SARS-CoV-2 pediatric seroepidemiologic data is limited. Reported viral rates underestimate the burden of infection in children due to mild or asymptomatic disease. Limited cohorts of children suggest low seropositivity rates compared to adults.

What This Study Adds

US children in the largest SARS-CoV-2 seroepidemiology study to date had double the rate of antibodies compared to adults. Most children were asymptomatic. Risk factors include age, ethnicity and living conditions. Most children made antibodies to different antigens of SARS-CoV-2.
The Impact of Distractions on Intracortical Brain-Computer Interface Control of a Robotic Arm
Authors: Guthrie Michael D. , Herrera Angelica J. , Downey John E. , Brane Lucas J. , Boninger Michael L. , Collinger Jennifer L.
Published: January 2021

This was an investigational device observational trial with the objective to evaluate the impact of distractions on intracortical brain-computer interface (BCI) performance. Two individuals with tetraplegia had microelectrode arrays implanted into their motor cortex for trials of intracortical BCI safety and performance. The primary task was moving a robotic arm between two targets as quickly as possible, performed alone and with various secondary distraction conditions. Primary outcomes included targets acquired, path efficiency, and subjective difficulty. There was no difference in the number of targets acquired for either subject with or without distractions. Median path efficiency was similar across all conditions (range: 0.766-0.846) except the motor distraction for Subject P2, where the median path efficiency dropped to 0.675 (p = 0.033, Mann-Whitney U test). Both subjects rated the overall difficulty of the task with and without distractions as low. Overall, intracortical BCI performance was robust to various distractions.
Nationwide Seroprevalence of SARS-CoV-2 in Saudi Arabia
Authors: Alharbi Naif Khalaf , Alghnam Suliman , Algaissi Abdullah , Albalawi Hind , Alenazi Mohammed W. , Albargawi Areeb M. , Alharbi Abdullah G. , Alhazmi Abdulaziz , Qarni Ali Al , Alfarhan Ali , Zowawi Hossam M. , Alhatmi Hind , Alghamdi Jahad , Alroqi Fayhan , Arabi Yaseen M. , Hashem Anwar M. , Bosaeed Mohammed , Aldibasi Omar
Published: January 2021

Background

Estimated seroprevalence of Coronavirus Infectious Disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) is a critical evidence for a better evaluation of the virus spread and monitoring the progress of the COVID-19 pandemic in a population. In the Kingdom of Saudi Arabia (KSA), SARS-CoV-2 seroprevalence has been reported in specific regions, but an extensive nationwide study has not been reported. Here, we report a nationwide study to determine the prevalence of SARS-CoV-2 in the population of KSA during the pandemic, using serum samples from healthy blood donors, non-COVID patients and healthcare workers (HCWs) in six different regions of the kingdom, with addition samples from COVID-19 patients.

Methods

A total of 11703 serum samples were collected from different regions of the KSA including; 5395 samples from residual healthy blood donors (D); 5877 samples from non-COVID patients collected through residual sera at clinical biochemistry labs from non-COVID patients (P); and 400 samples from consented HCWs. To determine the seroprevalence of SARS-CoV-2, all serum samples, in addition to positive control sera from RT-PCR confirmed COVID-19 patients, were subjected to in-house ELISA with a sample pooling strategy, which was further validated by testing individual samples that make up some of the pools, with a statistical estimation method to report seroprevalence estimates

Results

Overall (combining D and P groups) seroprevalence estimate was around 11% in Saudi Arabia; and was 5.1% (Riyadh), 1.5% (Jazan), 18.4% (Qassim), 20.8% (Hail), 14.7% (ER; Alahsa), and 18.8% in Makkah. Makkah samples were only D group and had a rate of 24.4% and 12.8% in the cities of Makkah and Jeddah, respectively. The seroprevalence in Saudi Arabia across the sampled areas would be 12 times the COVID-19 infection rate. Among HCWs, 7.5% (4.95-10.16 CI 95%) had reactive antibodies to SARS-CoV-2 without reporting any previously confirmed infection. This was higher in HCWs with hypertension. The study also presents the demographics and prevalence of co-morbidities in HCWs and subset of non-COVID-19 population.

Conclusion

Our study estimates the overall national serological prevalence of COVID-19 in Saudi Arabia to be 11%, with an apparent disparity between regions.
Health and Healthcare Variables Associated with Italy’s Excess Mortality during the First Wave of the COVID-19 pandemic: An Ecological Study
Authors: Buja Alessandra , Paganini Matteo , Fusinato Riccardo , Cocchio Silvia , Scioni Manuela , Rebba Vincenzo , Baldo Vincenzo , Boccuzzo Giovanna
Published: January 2021

Background

Healthcare factors have strongly influenced the propagation of COVID-19. The present study aims to examine whether excess mortality during the first phase of the COVID-19 outbreak in Italy was associated with health, healthcare, demographic, and socioeconomic indicators measured at a provincial level.

Methods

The present ecological study concerns the raw number of deaths from Jan. 1 to Apr. 30, 2020 and the mean number of deaths in the same months of 2015 to 2019, per province. Information on socioeconomic factors and healthcare settings were extracted from the most recently updated databases on the ISTAT website. Two multilevel, multivariate models were constructed to test whether excess mortality was associated with the indicators across 107 provinces in Italy.

Results

On linear multilevel, multivariate analysis, AIDS mortality rate (p-value <0.05) correlates positively with excess mortality, while a higher density of General Practitioners (number of GPs per 1,000 population) is associated with lower excess mortality (p-value <0.05). After controlling for the diffusion of COVID-19 in each province, the significance of GP density increases (p-value <0.001) and the rate of hospitalization in long-term care wards is positively associated (p-value <0.05) with excess mortality.

Conclusion

Some health and healthcare variables are strongly associated with excess mortality caused by COVID-19 in Italy and should be considered to implement mitigation policies and increase healthcare resilience.
A control framework to optimize public health policies in the course of the COVID-19 pandemic
Authors: Pataro Igor M L , Oliveira Juliane F , Morato Marcelo M , Amad Alan A S , Ramos Pablo I P , Pereira Felipe A C , Silva Mateus S , Jorge Daniel C P , Andrade Roberto F S , Barreto Maurício L , da Costa Marcus Americano
Published: January 2021

The SARS-CoV-2 pandemic triggered substantial economic and social disruptions. Mitigation policies varied across countries based on resources, political conditions, and human behavior. In the absence of widespread vaccination able to induce herd immunity, strategies to coexist with the virus while minimizing risks of surges are paramount, which should work in parallel with reopening societies. To support these strategies, we present a predictive control system coupled with a nonlinear model able to optimize the level of policies to stop epidemic growth. We applied this system to study the unfolding of COVID-19 in Bahia, Brazil, also assessing the effects of varying population compliance. We show the importance of finely tuning the levels of enforced measures to achieve SARS-CoV-2 containment, with periodic interventions emerging as an optimal control strategy in the long-term.

One-sentence summary

We present an adaptive predictive control algorithm to provide optimal public health measures to slow the COVID-19 transmission rate.
Investigation of the Stress and Sleep Physiology Correlates of Next-Day Memory for Details of a Social Stressor Testing Environment
Authors: Bottary Ryan , Kark Sarah M. , Daley Ryan T. , Denis Dan , Cunningham Tony J. , Payne Jessica D. , Kensinger Elizabeth A.
Published: January 2021

Despite evidence which demonstrates that psychosocial stress interacts with sleep to modulate memory, research that has examined next-day memory for the stressful environment itself has not accounted for post-stressor sleep. Here, participants completed the Trier Social Stress Test or a matched control task with psychophysiological monitoring and stress hormone assays. After a 24-hour delay that included overnight polysomnographically-recorded sleep, memory for objects in the testing room was assessed by having participants draw the testing room from the previous day from memory. As expected, stressed participants mounted greater psychophysiological and stress hormone responses to the stressor than participants in the control condition. However, there was only weak evidence that stress reactivity and post-encoding sleep interacted to modulate memory for testing room details. Instead, NREM sleep physiology on the night following testing room encoding was positively associated with memory for testing room details, though this association occurred in the control, but not stressed, participants.
Age-associated gut microbiota impairs hippocampus-dependent memory in a vagus-dependent manner
Authors: Rei Damien , Saha Soham , Haddad Marianne , Haider Rubio Anna , Perlaza Blanca Liliana , Ungeheuer Marie-Noelle , Sokol Harry , Lledo Pierre-Marie
Published: January 2021

Aging is known to be associated with hippocampus-dependent memory decline, but the underlying causes of the age-related memory impairment remain yet highly debated. Here we showed that fecal microbiota transplantation (FMT) from aged, but not young, animal donors in young mice is sufficient to trigger profound hippocampal alterations including astrogliosis, decreased adult neurogenesis, decreased novelty-induced neuronal activation and impairment in hippocampus-dependent memory. Furthermore, similar alterations were reported when mice were subjected to an FMT from aged human donors. To decipher the mechanisms involved in mediating these microbiota-induced effects on brain function, we mapped the vagus nerve (VN)-related neuronal activity patterns and report that aged-mice FM transplanted animals showed a reduction in neuronal activity in the ascending VN output brain structure, both in basal condition and following VN stimulation. Targeted pharmacogenetic manipulation of VN-ascending neurons demonstrated that the decrease in vagal activity is detrimental to hippocampal functions. In contrast, increasing vagal ascending activity alleviated the adverse effects of aged mice FMT on hippocampal functions, and had a pro-mnesic effect in aged mice. Thus, pharmacogenetic VN stimulation is a potential therapeutic strategy to lessen microbiota-dependent age-associated impairments in hippocampal functions.

Graphical abstract
A systematic analysis of genetically regulated differences in gene expression and the role of co-expression networks across 16 psychiatric disorders and substance use phenotypes
Authors: Gerring Zachary F , Thorp Jackson G , Gamazon Eric R , Derks Eske M
Published: January 2021

Genome-wide association studies (GWASs) have identified thousands of risk loci for many psychiatric and substance use phenotypes, however the biological consequences of these loci remain largely unknown. We performed a transcriptome-wide association study of 10 psychiatric disorders and 6 substance use phenotypes (collectively termed “mental health phenotypes”) using expression quantitative trait loci data from 532 prefrontal cortex samples. We estimated the correlation due to predicted genetically regulated expression between pairs of mental health phenotypes, and compared the results with the genetic correlations. We identified 1,645 genes with at least one significant trait association, comprising 2,176 significant associations across the 16 mental health phenotypes of which 572 (26%) are novel. Overall, the transcriptomic correlations for phenotype pairs were significantly higher than the respective genetic correlations. For example, attention deficit hyperactivity disorder and autism spectrum disorder, both childhood developmental disorders, showed a much higher transcriptomic correlation (r=0.84) than genetic correlation (r=0.35). Finally, we tested the enrichment of phenotype-associated genes in gene co-expression networks built from prefrontal cortex. Phenotype-associated genes were enriched in multiple gene co-expression modules and the implicated modules contained genes involved in mRNA splicing and glutamatergic receptors, among others. Together, our results highlight the utility of gene expression data in the understanding of functional gene mechanisms underlying psychiatric disorders and substance use phenotypes.
SAILER: Scalable and Accurate Invariant Representation Learning for Single-Cell ATAC-Seq Processing and Integration
Authors: Cao Yingxin , Fu Laiyi , Wu Jie , Peng Qinke , Nie Qing , Zhang Jing , Xie Xiaohui
Published: January 2021

Motivation

Single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) provides new opportunities to dissect epigenomic heterogeneity and elucidate transcriptional regulatory mechanisms. However, computational modelling of scATAC-seq data is challenging due to its high dimension, extreme sparsity, complex dependencies, and high sensitivity to confounding factors from various sources.

Results

Here we propose a new deep generative model framework, named SAILER, for analysing scATAC-seq data. SAILER aims to learn a low-dimensional nonlinear latent representation of each cell that defines its intrinsic chromatin state, invariant to extrinsic confounding factors like read depth and batch effects. SAILER adopts the conventional encoder-decoder framework to learn the latent representation but imposes additional constraints to ensure the independence of the learned representations from the confounding factors. Experimental results on both simulated and real scATAC-seq datasets demonstrate that SAILER learns better and biologically more meaningful representations of cells than other methods. Its noise-free cell embeddings bring in significant benefits in downstream analyses: Clustering and imputation based on SAILER result in 6.9% and 18.5% improvements over existing methods, respectively. Moreover, because no matrix factorization is involved, SAILER can easily scale to process millions of cells. We implemented SAILER into a software package, freely available to all for large-scale scATAC-seq data analysis.

Availability

The software is publicly available athttps://github.com/uci-cbcl/SAILER

Contact

jingz31@uci.eduandxhx@uci.edu
A Fast Lasso-Based Method for Inferring Pairwise Interactions
Authors: Elmes Kieran , Heywood Astra , Huang Zhiyi , Gavryushkin Alex
Published: January 2021

Abstract

Large-scale genotype-phenotype screens provide a wealth of data for identifying molecular alternations associated with a phenotype. Epistatic effects play an important role in such association studies. For example, siRNA perturbation screens can be used to identify pairwise gene-silencing effects. In bacteria, epistasis has practical consequences in determining antimicrobial resistance as the genetic background of a strain plays an important role in determining resistance. Existing computational tools which account for epistasis do not scale to human exome-wide screens and struggle with genetically diverse bacterial species such asPseudomonas aeruginosa. Combining earlier work in interaction detection with recent advances in integer compression, we present a method for epistatic interaction detection on sparse (human) exome-scale data, and an R implementation in the packagePint. Our method takes advantage of sparsity in the input data and recent progress in integer compression to perform lasso-penalised linear regression on all pairwise combinations of the input, estimating up to 200 million potential effects, including epistatic interactions. Hence the human exome is within the reach of our method, assuming one parameter per gene and one parameter per epistatic effect for every pair of genes. We demonstratePinton both simulated and real data sets, including antibiotic resistance testing and siRNA perturbation screens.
Predicting cross-tissue hormone-gene relations using balanced word embeddings
Authors: Jadhav Aditya , Kumar Tarun , Raghavendra Mohit , Loganathan Tamizhini , Narayanan Manikandan
Published: January 2021

Motivation

Large volumes of biomedical literature present an opportunity to build whole-body human models comprising both within-tissue and across-tissue interactions among genes. Current studies have mostly focused on identifying within-tissue or tissue-agnostic associations, with a heavy emphasis on associations among disease, genes and drugs. Literature mining studies that extract relations pertaining to inter-tissue communication, such as between genes and hormones, are solely missing.

Results

We present here a first study to identify from literature the genes involved in inter-tissue signaling via a hormone in the human body. Our models BioEmbedS and BioEmbedS-TS respectively predict if a hormone-gene pair is associated or not, and whether an associated gene is involved in the hormone’s production or response. Our models are classifiers trained on word embeddings that we had carefully balanced across different strata of the training data such as across production vs. response genes of a hormone (or) well-studied vs. poorly-represented hormones in the literature. Model training and evaluation are enabled by a unified dataset called HGv1 of ground-truth associations between genes and known endocrine hormones that we had compiled. Our models not only recapitulate known gene mediators of tissue-tissue signaling (e.g., at average 70.4% accuracy for BioEmbedS), but also predicts novel genes involved in inter-tissue communication in humans. Furthermore, the species-agnostic nature of our ground-truth HGv1 data and our predictive modeling approach, demonstrated concretely using human data and generalized to mouse, hold much promise for future work on elucidating inter-tissue signaling in other multi-cellular organisms.

Availability

Proposed HGv1 dataset along with our models’ predictions, and the associated code to reproduce this work are available respectively athttps://cross-tissue-signaling.herokuapp.com/, andhttps://github.com/BIRDSgroup/BioEmbedS.

Contact

nmanik@cse.iitm.ac.in
Synthqa - Hierarchical Machine Learning-Based Protein Quality Assessment
Authors: Korovnik Mikhail , Hippe Kyle , Hou Jie , Si Dong , Kishaba Kiyomi , Cao Renzhi
Published: January 2021

Motivation

It has been a challenge for biologists to determine 3D shapes of proteins from a linear chain of amino acids and understand how proteins carry out life’s tasks. Experimental techniques, such as X-ray crystallography or Nuclear Magnetic Resonance, are time-consuming. This highlights the importance of computational methods for protein structure predictions. In the field of protein structure prediction, ranking the predicted protein decoys and selecting the one closest to the native structure is known as protein model quality assessment (QA), or accuracy estimation problem. Traditional QA methods don’t consider different types of features from the protein decoy, lack various features for training machine learning models, and don’t consider the relationship between features. In this research, we used multi-scale features from energy score to topology of the protein structure, and proposed a hierarchical architecture for training machine learning models to tackle the QA problem.

Results

We introduce a new single-model QA method that incorporates multi-scale features from protein structures, utilizes the hierarchical architecture of training machine learning models, and predicts the quality of any protein decoy. Based on our experiment, the new hierarchical architecture is more accurate compared to traditional machine learning-based methods. It also considers the relationship between features and generates additional features so machine learning models can be trained more accurately. We trained our new tool, SynthQA, on the CASP dataset (CASP10 to CASP12), and validated our method on 33 targets from the latest CASP 14 dataset. The result shows that our method is comparable to other state-of-the-art single-model QA methods, and consistently outperforms each of the 14 used features.

Availability

https://github.com/Cao-Labs/SynthQA.git

Contact

caora@plu.edu
Generalizing about GC (hypoxia): Dys- & Dat-InformaticaComment on“Germinal center B cells selectively oxidize fatty acids for energy while conducting minimal glycolysis”
Authors: Boothby Mark R. , Raybuck Ariel , Cho Sung Hoon , Stengel Kristy R. , Hiebert Scott , Li Jingxin
Published: January 2021

Steadily accumulating evidence supports the concept that the outputs of immune responses are influenced by local nutrient and metabolite conditions or concentrations, as well as by the molecular programming of intermediary metabolism within immune cells. Humoral immunity and germinal center reactions are one setting in which these factors are under active investigation. Hypoxia has been highlighted as one example of how a particular nutrient is distributed in primary and secondary follicles during an antibody response, and how its sensors could impact the qualities of antibody output after immunization. Based on a bio-informatic analysis of mRNA levels in germinal center and other B cells, recently published work challenges the concept that there is any hypoxia or that it has any influence. In this perspective, we perform new analyses of published genomics data to explore potential sources of disparity and elucidate aspects of what on the surface might seem to be conflicting conclusions. In particular, the replicability and variance among data sets derived from different naïve as well as germinal center B cells are considered. The results of the investigation highlight several broader issues that merit consideration, especially at a time of heightened focus on scientific reports in the realm of immunity and antibody responses. From one finding of this re-analysis, it is proposed that a standard should be expected in which the relationship of new data sets compared to prior “fingerprints” of cell types should be reported transparently to referees and readers. In light of the strong evidence for diversity in the constituencies within germinal centers elicited by protein immunization, it also is proposed that a core practice should be to avoid overly broad conclusions about germinal centers in general when experimental systems are subject to substantial constraints imposed by technical features.