bluuebunny/crossref_metadata_2025 huggingface dataset:
Point-of-care testing in a high-income country paediatric emergency department – a qualitative study in Sweden
Authors: Rasti Reza , Brännström Johanna , Mårtensson Andreas , Zenk Ingela , Gantelius Jesper , Gaudenzi Giulia , Alvesson Helle M. , Alfvén Tobias
Published: June 2021

Objectives

In many resource-limited health systems, point-of-care tests (POCTs) are the only means for clinical patient sample analyses. However, the speed and simplicity of POCTs also makes their use appealing to clinicians in high-income countries (HICs), despite their having greater laboratory accessibility. Although also part of the clinical routine in HICs, the utility of POCTs is relatively unknown in such settings as compared to others.

In a Swedish paediatric emergency department (PED) where POCT use is routine, we aimed to characterize health care providers’ perspectives on the clinical utility of POCTs and explore their implementation in the local setting; to compare such experiences to those reported in other settings; and finally, to gather requests for ideal novel POCTs.

Design

Qualitative study using focus group discussions. A data-driven content analysis approach was used for analysis.

Setting

The PED of a secondary paediatric hospital in Stockholm, Sweden.

Participants

Twenty-four health care providers clinically active at the PED were enrolled in six focus groups.

Results

A range of POCTs was routinely used. The emerging themeUtility of POCTs is double-edgedillustrated the perceived utility of POCTs. While POCT services were considered to have clinical and social value, the local testing practice was named to distract from the care for patients. Requests were made for novel POCTs and their implementation.

Conclusion

Despite their clinical integration, deficient implementation routines limit the benefits of POCT services to this well-resourced paediatric clinic. As such deficiencies are shared with other settings, it is suggested that some characteristics of POCTs and of their utility are less related to resource level and more to policy deficiency. To address this, we propose the appointment of skilled laboratory personnel as ambassadors to hospital clinics offering POCT services, to ensure higher utility of such services.

ARTICLE SUMMARY

Strengths and limitations of this study

This is the first study to present the use and utility of POCTs in a HIC paediatric hospital setting, directly from the perspective of its clinical staff.

Our main finding is that deficient implementation routines limit benefit of POCT services in this well-resourced setting, strongly indicating that such deficiencies are irrespective of resource level, and more related to policy deficiency.

The findings of the relatively small study size may be contextual, yet we believe our main conclusions to be generalizable as most of our findings are compatible with those reported in other settings.

The study is strengthened by the diversity of its participants, corresponding to the multi-professional staffing of the PED.
Impact of COVID-19 on deaths from respiratory diseases: Panel Data evidence from Chile
Authors: Barría-Sandoval Claudia , Mendez Angie , Ferreira Guillermo , Toffoletto María Cecilia
Published: June 2021

The COVID-19 pandemic has left other pathologies commonly present in the population in a secondary context. Therefore, it is necessary to study the evolution of these diseases in the presence or absence of COVID-19.

Objectives

The present study had the following objectives: 1. To evaluate the relationship between the COVID-19 epidemic and the possible decrease in deaths from respiratory diseases in Chile. 2 Study the relationship between meteorological variables and severity of COVID-19 with respect to deaths from respiratory diseases from January 2018 to February 2021.

Methods

The variable number of deaths due to respiratory diseases in Chile was analyzed considering the monthly records of meteorological variables (temperature, precipitation and humidity) in each Region of Chile and severity of COVID-19, to evaluate the mortality trend before and after the pandemic. For this, different Non-Observable Heterogeneity Models for Panel Data were used

Results

Our findings show that among the variables that affect the mortality rate from respiratory diseases, there are the number of deaths from COVID-19 that has a negative effect, the number of patients with COVID-19 in intensive care unit (ICU) that has a positive effect and the minimum temperature with a negative effect. These results are supported by the application of the panel regression with one-way random-effects models.

Conclusion

This study revealed that there is an unexpected reduction in deaths from respiratory diseases in Chile in the post-pandemic period. Therefore, it can be concluded that this variable decreased with the appearance of the COVID-19 pandemic.
Data-Driven Prediction of COVID-19 Cases in Germany for Decision Making
Authors: Refisch Lukas , Lorenz Fabian , Riedlinger Torsten , Taubenböck Hannes , Fischer Martina , Grabenhenrich Linus , Wolkewitz Martin , Binder Harald , Kreutz Clemens
Published: June 2021

Background

The COVID-19 pandemic has led to a high interest in mathematical models describing and predicting the diverse aspects and implications of the virus outbreak. Model results represent an important part of the information base for the decision process on different administrative levels. The Robert-Koch-Institute (RKI) initiated a project whose main goal is to predict COVID-19-specific occupation of beds in intensive care units: Steuerungs-Prognose von Intensivmedizinischen COVID-19 Kapazitäten (SPoCK). The incidence of COVID-19 cases is a crucial predictor for this occupation.

Methods

We developed a model based on ordinary differential equations for the COVID-19 spread with a time-dependent infection rate described by a spline. Furthermore, the model explicitly accounts for weekday-specific reporting and adjusts for reporting delay. The model is calibrated in a purely data-driven manner by a maximum likelihood approach. Uncertainties are evaluated using the profile likelihood method. The uncertainty about the appropriate modeling assumptions can be accounted for by including and merging results of different modelling approaches.

Results

The model is calibrated based on incident cases on a daily basis and provides daily predictions of incident COVID-19 cases for the upcoming three weeks including uncertainty estimates for Germany and its subregions. Derived quantities such as cumulative counts and 7-day incidences with corresponding uncertainties can be computed. The estimation of the time-dependent infection rate leads to an estimated reproduction factor that is oscillating around one. Data-driven estimation of the dark figure purely from incident cases is not feasible.

Conclusions

We successfully implemented a procedure to forecast near future COVID-19 incidences for diverse subregions in Germany which are made available to various decision makers via an interactive web application. Results of the incidence modeling are also used as a predictor for forecasting the need of intensive care units.
Switched forced SEIRDV compartmental models to monitor COVID-19 spread and immunization in Italy
Authors: Antonelli Erminia , Piccolomini Elena Loli , Zama Fabiana
Published: June 2021

This paper presents a new hybrid compartmental model for studying the COVID-19 epidemic evolution in Italy since the beginning of the vaccination campaign started on 2020/12/27 and shows forecasts of the epidemic evolution in Italy. The proposed compartmental model subdivides the population into six compartments and extends the SEIRD model proposed in [E.L.Piccolomini and F.Zama, PLOS ONE, 15(8):1–17, 08 2020] by adding the Vaccinated population and framing the global model as a hybrid-switched dynamical system. Aiming to represent the quantities that characterize the epidemic behaviour from an accurate fit to the observed data, we partition the observation time interval into sub-intervals. The model parameters change according to a switching rule depending on the data behaviour and the infection rate continuity condition. In particular, we study the representation of the infection rate both as linear and exponential piecewise continuous functions. We choose the length of sub-intervals balancing the data fit with the model complexity through the Bayesian Information Criterion. The calibration of the model shows an excellent representation of the epidemic behaviour and thirty days forecasts have proven to reproduce the infection spread reliably. Finally, we discuss different possible forecast scenarios obtained by simulating an increased vaccination rate.
Covid-19 Incidence And Mortality By Age Strata And Comorbidities In Mexico City: A Focus In The Pediatric Population
Authors: González-García Nadia , Castilla-Peón María F , Solórzano Santos Fortino , Juárez Rodolfo Jiménez , Martínez Bustamante Maria Elena , Minero Hibert Miguel Angel , Garduño-Espinosa Juan
Published: June 2021

Background

SARS-COV2 appears less frequently and less severely in the pediatric population than in the older age groups. There is a need to precisely estimate the specific risks for each age group to design health and education policies suitable for each population

Objective

This study aimed to describe the risk of death in SARS-COV2 infected subjects by age group and according to the presence of comorbidities.

Methods

We analyzed data of confirmed SARS-COV2 infection cases where symptoms began between February 22th, 2020, and April 18th, 2021, as published by the General Epidemiology Direction (DGE) of the Mexican Ministry of Health. We calculated COVID-19 incidence and mortality by age group using population data from the Statistics and Population National Institute (INEGI), and estimated the association between risk of death and the presence of comorbidities.

Results

Mortality in SARS-COV2 infected people varied considerably, between 7 to 155 deaths per million per year in the under-20 age groups compared to 441 to 15,929 in the older age groups. Mortality in pediatric populations is strongly associated with comorbidities (OR: 4.6-47.9) compared to the milder association for older age groups (OR: 3.16-1.23).

Conclusions

The risk of death from SARS-COV2 infection in children is low and is strongly associated with comorbidities.
Quantifying the Tradeoff Between Energy Consumption and the Risk of Airborne Disease Transmission for Building HVAC Systems
Authors: Risbeck Michael James , Bazant Martin Z. , Jiang Zhanhong , Lee Young M. , Drees Kirk H. , Douglas Jonathan D.
Published: June 2021

It has been established that combinations of increased ventilation, improved filtration, and other HVAC techniques can reduce the likelihood of airborne disease transmission in buildings. However, with only qualitative guidance, it is difficult for building managers to make informed decisions. Furthermore, the possible actions almost always require additional energy consumption, which is generally not well characterized. To address this knowledge gap, we propose simplified physics-based models that can be used to quantify both the expected transmission rate and the associated energy consumption that result from HVAC system operation. By formulating all disinfection mechanisms in terms of "equivalent outdoor air", a common basis is established for comparing and combining different strategies. The transmission rate can thus be modeled by considering the airborne concentration of infectious particles that would result from an infector in the space. Energy consumption is then estimated by considering the change in HVAC variables and applying standard analysis. To illustrate the insights provided by these models, we present examples of how the proposed analysis can be applied to specific spaces, highlighting the fact that underlying transmission risk and energy-optimal disinfection strategies can vary significantly based on space characteristics.
Temporal Analysis of Social Determinants Associated with COVID-19 Mortality
Authors: Debopadhaya Shayom , Erickson John S. , Bennett Kristin P.
Published: June 2021

This study examines how social determinants associated with COVID-19 mortality change over time. Using US county-level data from July 5 and December 28, 2020, the effect of 19 high-risk factors on COVID-19 mortality rate was quantified at each time point with negative binomial mixed models. Then, these high-risk factors were used as controls in two association studies between 40 social determinants and COVID-19 mortality rates using data from the same time points. The results indicate that counties with certain ethnic minorities and age groups, immigrants, prevalence of diseases like pediatric asthma and diabetes and cardiovascular disease, socioeconomic inequalities, and higher social association are associated with increased COVID-19 mortality rates. Meanwhile, more mental health providers, access to exercise, higher income, chronic lung disease in adults, suicide, and excessive drinking are associated with decreased mortality. Our temporal analysis also reveals a possible decreasing impact of socioeconomic disadvantage and air quality, and an increasing effect of factors like age, which suggests that public health policies may have been effective in protecting disadvantaged populations over time or that analysis utilizing earlier data may have exaggerated certain effects. Overall, we continue to recognize that social inequality still places disadvantaged groups at risk, and we identify possible relationships between lung disease, mental health, and COVID-19 that need to be explored on a clinical level.

CCS CONCEPTS

Applied computing → Health informatics.
Expert Opinion on COVID-19 Vaccination and the Use of Cladribine Tablets in Clinical Practice
Authors: Rieckmann Peter , Centonze Diego , Giovannoni Gavin , Hua Le H. , Oreja-Guevara Celia , Selchen Daniel , Soelberg Sørensen Per , Vermersch Patrick , Wiendl Heinz , Salloukh Hashem , Yamout Bassem
Published: June 2021

Background

Gaps in current evidence and guidance leave clinicians with unanswered questions on the use of cladribine tablets for the treatment of multiple sclerosis (MS) in the era of the COVID-19 pandemic, in particular relating to COVID-19 vaccination.

Objective

We describe a consensus-based program led by international MS experts with the aim of supplementing current guidelines and treatment labels by providing timely recommendations relating to COVID-19 vaccination and the use of cladribine tablets in clinical practice.

Methods

A steering committee (SC) of 10 international MS experts identified seven clinical questions to answer concerning the use of cladribine tablets and COVID-19 vaccination, which addressed issues relating to patient selection, timing and efficacy, and safety. Clinical recommendations to address each question were drafted using available evidence combined with expert opinion from the SC. An extended faculty of 28 MS experts, representing 19 countries, in addition to the 10 SC members, voted on the recommendations. Consensus on recommendations was achieved when ≥75% of respondents expressed an agreement score of 7–9, on a 9-point scale.

Results

Consensus was achieved on all 13 recommendations. Clinical recommendations are provided on whether all patients with MS receiving cladribine tablets should be vaccinated against COVID-19, and whether they should be prioritized; the timing of vaccination around dosing of cladribine tablets (i.e., before and after a treatment course); and the safety of COVID-19 vaccination for these patients.

Conclusions

These expert recommendations provide timely guidance on COVID-19 vaccination in patients receiving cladribine tablets, which is relevant to everyday clinical practice.
Ilioinguinal versus modified Stoppa approach for open reduction and internal fixation of displaced acetabular fractures: A Protocol for Systematic Review and Meta-Analysis
Authors: Srivastava Amit , Rajnish Rajesh Kumar , Kumar Prasoon , Haq Rehan Ul , Dhammi Ish Kumar
Published: June 2021

Background

The fracture of the acetabulum is one of the most challenging fractures to manage and operate for orthopaedic surgeons. To get a good surgical outcome, anatomical reduction of fractures and reconstruction of the joint is of utmost importance. To achieve a good postoperative outcome an appropriate surgical approach is necessary to achieve an anatomical reduction of fractures and fewer complications.

Objective

The current review aims to compare the outcomes of the ilioinguinal versus modified Stoppa approach for open reduction and internal fixation (ORIF) of displaced acetabular fractures by analyzing the evidence from the current literature.

Methods

A systematic review of the literature will be conducted in accordance with the PRISMA guidelines. The primary searches will be conducted on the Medline (PubMed), Embase, Scopus, and Cochrane Library databases, using a pre-defined search strategy. The studies of any design in the English language will be included which compared the outcomes of the ilioinguinal and modified Stoppa approach for ORIF of displaced acetabular fractures and reported at least one outcome of interest. Studies that do not compare the outcomes of the ilioinguinal and modified Stoppa approach for the treatment of displaced acetabular fractures in adults (>18 years of age), case reports, conference abstracts, posters, book chapters, review articles, biomechanical studies, technical tips, cadaveric studies, and articles not in the English language will be excluded. Both qualitative and quantitative analyses will be done. Qualitative analysis will be done using appropriate tables and diagrams. Wherever feasible, quantitative analysis to be done with the appropriate software. The risk-of-bias assessment will be done using the MINORS tool for the non-randomized comparative studies, and The Cochrane Collaboration’s risk-of-bias tool will be used for randomized control trials.
Investigating phenotypes of pulmonary COVID-19 recovery – a longitudinal observational prospective multicenter trial
Authors: Sonnweber Thomas , Tymoszuk Piotr , Sahanic Sabina , Boehm Anna , Pizzini Alex , Luger Anna , Schwabl Christoph , Nairz Manfred , Kurz Katharina , Koppelstätter Sabine , Aichner Magdalena , Puchner Bernhard , Egger Alexander , Hoermann Gregor , Wöll Ewald , Weiss Günter , Widmann Gerlig , Tancevski Ivan , Löffler-Ragg Judith
Published: June 2021

Background

COVID-19 is associated with long-term pulmonary symptoms and may result in chronic pulmonary impairment. The optimal procedures to prevent, identify, monitor, and treat these pulmonary sequelae are elusive.

Research question

To characterize the kinetics of pulmonary recovery, risk factors and constellations of clinical features linked to persisting radiological lung findings after COVID-19.

Study design and methods

A longitudinal, prospective, multicenter, observational cohort study including COVID-19 patients (n = 108). Longitudinal pulmonary imaging and functional readouts, symptom prevalence, clinical and laboratory parameters were collected during acute COVID-19 and at 60-, 100- and 180-days follow-up visits. Recovery kinetics and risk factors were investigated by logistic regression. Classification of clinical features and study participants was accomplished by k-means clustering, the k-nearest neighbors (kNN), and naive Bayes algorithms.

Results

At the six-month follow-up, 51.9% of participants reported persistent symptoms with physical performance impairment (27.8%) and dyspnea (24.1%) being the most frequent. Structural lung abnormalities were still present in 45.4% of the collective, ranging from 12% in the outpatients to 78% in the subjects treated at the ICU during acute infection. The strongest risk factors of persisting lung findings were elevated interleukin-6 (IL6) and C-reactive protein (CRP) during recovery and hospitalization during acute COVID-19. Clustering analysis revealed association of the lung lesions with increased anti-S1/S2 antibody, IL6, CRP, and D-dimer levels at the early follow-up suggesting non-resolving inflammation as a mechanism of the perturbed recovery.

Finally, we demonstrate the robustness of risk class assignment and prediction of individual risk of delayed lung recovery employing clustering and machine learning algorithms.

Interpretation

Severity of acute infection, and systemic inflammation is strongly linked to persistent post-COVID-19 lung abnormality. Automated screening of multi-parameter health record data may assist the identification of patients at risk of delayed pulmonary recovery and optimize COVID-19 follow-up management.

Clinical Trial Registration

ClinicalTrials.gov: NCT04416100
Network analysis shows decreased ipsilesional structural connectivity in glioma patients
Authors: Fekonja Lucius S. , Wang Ziqian , Cacciola Alberto , Roine Timo , Aydogan D. Baran , Mewes Darius , Vellmer Sebastian , Vajkoczy Peter , Picht Thomas
Published: June 2021

Gliomas that infiltrate networks and systems, such as the motor system, often lead to substantial functional impairment in multiple systems. Network-based statistics (NBS) allow to assess local network differences (1) and graph theoretical analyses (2) enable investigation of global and local network properties. Here, we used network measures to characterize glioma-related decreases in structural connectivity by comparing the ipsi- with the contralesional hemispheres of patients and correlated findings with neurological assessment.

We found that lesion location resulted in differential impairment of both short and long connectivity patterns. Network analysis showed reduced global and local efficiency in the ipsilesional hemisphere compared to the contralesional hemispheric networks. In network science, reduced global and local efficiency reflect the impairment of information transfer across different regions of a network.

One-Sentence Summary

Network analyses show glioma-related decreased ipsilesional structural connectivity and correlates with neurological status.
Multi-centre post-implementation evaluation of SARS-CoV-2 antigen-based point of care tests used for asymptomatic screening of continuing care healthcare workers
Authors: Kanji Jamil N , Proctor Dustin T , Stokes William , Berenger Byron M , Silvius James , Tipples Graham , Joffe A Mark , Venner Allison A
Published: June 2021

OBJECTIVES

Frequent screening of SARS-CoV-2 among asymptomatic populations using antigen-based point of care tests (APOCT) is occurring globally with limited clinical performance data. The positive predictive value (PPV) of two APOCT used in the asymptomatic screening of SARS-CoV-2 among healthcare workers (HCW) at continuing care (CC) sites across Alberta, Canada was evaluated.

METHODS

Between February 22 and May 2, 2021, CC sites implemented SARS-CoV-2 voluntary screening of their asymptomatic HCW. Onsite testing with Abbott Panbio or BD Veritor occurred on a weekly or twice weekly basis. Positive APOCT were confirmed with a real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) reference method.

RESULTS

A total of 71,847 APOCT (17,689 Veritor and 54,158 Panbio) were performed among 369 CC sites. Eighty-seven (0.12%) APOCT were positive, of which 39 (0.05%) confirmed as true positives using rRT-PCR. Use of the Veritor and Panbio resulted in a 76.6% and 30.0% false positive detection, respectively (p<0.001). This corresponded to a 23.4% and 70.0% PPV for the Veritor and Panbio, respectively.

CONCLUSIONS

Frequent screening of SARS-CoV-2 among asymptomatic HCW in CC, using APOCT, resulted in a very low detection rate and a high detection of false positives. Careful assessment between the risks vs benefits of APOCT programs in this population needs to be thoroughly considered before implementation.
Inflection in prevalence of SARS-CoV-2 infections missing the N501Y mutation as a marker of rapid Delta (B.1.617.2) lineage expansion in Ontario, Canada
Authors: Brown Kevin A. , Joh Eugene , Buchan Sarah A. , Daneman Nick , Mishra Sharmistha , Patel Samir , Day Troy
Published: June 2021

Background

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta lineage (B.1.617.2) was implicated in the SARS-CoV-2 surge in India. We sought to describe the rapid expansion of the Delta lineage in Ontario, Canada (population 15 million) using mutation profile information and confirmatory whole genome sequencing.

Methods

All laboratory-confirmed SARS-CoV-2 cases reported to Public Health Ontario between April 1st and June 12th 2021, with cycle threshold values ≤35, were eligible for screening for the N501Y and the E484K mutations. We classified cases via mutation screening as: (1) N501Y-/E484K- (wild-type/Delta), (2) Alpha (N501Y+/E484K-), (3) Beta/Gamma (N501Y+/E484K+), or (4) N501Y-/E484K+ (predominantly B.1.525, and B.1.1.318).

Results

The N501Y-/E484K- mutation profile went from having a 29% transmission deficit relative to Alpha (relative Re = 0.71, 95%CI: 0.64, 0.77) on April 1st to having a 50% transmission advantage on June 12th (relative Re = 1.50, 95%CI: 1.31, 1.71). Whole genome sequencing of N501Y-/E484K-cases (N=583) confirmed that the pattern of increasing relative reproduction number coincided with the replacement of wild-type with Delta variant (from 2.2% in early April, to 83% in late May).

Discussion

Delta is rapidly overtaking other SARS-CoV-2 variants in Ontario, and has a substantial transmission advantage. An inflection in the proportion of cases missing the N501Y mutation from rapidly decreasing to rapidly increasing,3 may be an early warning signal for Delta lineage expansion.
Examining the epigenetic mechanisms of childhood adversity and sensitive periods: a gene set-based approach
Authors: Zhu Yiwen , Lussier Alexandre A. , Smith Andrew D.A.C. , Simpkin Andrew J. , Suderman Matthew J. , Walton Esther , Dunn Erin C.
Published: June 2021

Background

Sensitive periods are developmental stages of heightened plasticity when exposure to childhood adversity may exert lasting impacts. A few biological pathways are known to play key roles in regulating sensitive period plasticity across brain development. Epigenetic mechanisms including DNA methylation (DNAm) may provide a means through which life experiences during sensitive periods induce long-term biological changes. In the current study, we investigated the possibility that adversity during sensitive periods led to DNAm changes in genes that regulate the timing and duration of sensitive periods in development.

Methods

Using childhood adversity data and genome-wide DNAm profiles from the Avon Longitudinal Study of Parents and Children (n=785), we summarized DNAm variation of CpG sites in the promoters of genes regulating sensitive periods with the first two principal components (PCs). DNAm summaries were calculated for genes regulating sensitive period opening (ngenes=15), closing (ngenes=36), and expression/duration (ngenes=8). We then performed linear discriminant analysis to test associations between these DNAm summaries and the timing of exposure to seven types of adversity.

Results

Sexual or physical abuse and financial hardship during middle childhood (6-7 years) were associated with DNAm of genes regulating the onset and duration of sensitive periods. Sensitivity analyses assessing the presence of any exposure before age 7 and a composite measure of adversity yielded fewer signals, highlighting the importance of accounting for timing and adversity type.

Conclusions

With our novel gene set-based approach, we have uncovered suggestive evidence that epigenetic regulation of developmental plasticity may be affected by early life adversity. The complementarity of our gene-level view of the epigenome to the more common and granular epigenome-wide association study may yield novel mechanistic insights not only for adversity but also for other exposures and outcomes.
Long term positivity of SARS-CoV-2 total immunoglobulins in convalescent plasma and blood donors
Authors: Martín M Carmen , Jimenez Ana , Ortega Nuria , Parrado Alba , Page Isabel , González M Isabel , Blanco-Peris Lydia
Published: June 2021

Background

One of the most questioned issues about SARS-CoV2 immunity is how long does it last. Whether lasting differences exist between infection and vaccination boosted immunity is yet to be known. The answer to this question will determine key issues such as the reliability of individual and herd immunity or the need of sanitary restrictions or periodical revaccination. The aim of this study was to determine how long total anti SARS-CoV2 antibodies due to past infection persist in peripheral blood and whether sex, age or haematological features can influence their lasting.

Material and Methods

A total of 2432 donations SARS-CoV-2 from 662 repeat donors from April 2020 to February 2021 were analysed. Donors were 69.7% males and their average age was 46. An automated chemilumiscence immunoassay for total antibodies recognizing N protein of SARS-CoV-2 in human serum and plasma was performed.

Results and discussion

In 97.6% donors with follow-up, anti SARS-CoV-2 protein N total antibodies remained positive up to 46 weeks after first positive determination. Blood group was not related to antibody waning. Lower lymphocyte counts and higher neutrophils and as well higher seric IgA would help predict future negativization of antibodies. The vast majority of donors keep their total immunoglobulins anti SARS-CoV-2 positive for longer than 10 months. Ageing might have a protective effect against antibody waning but, given the small number of cases that become negative, more studies, or larger cohorts would be needed to confirm these facts.
Diet quality and risk and severity of COVID-19: a prospective cohort study
Authors: Merino Jordi , Joshi Amit D. , Nguyen Long H. , Leeming Emily R. , Mazidi Mohsen , Drew David A , Gibson Rachel , Graham Mark S. , Lo Chun-Han , Capdevila Joan , Murray Benjamin , Hu Christina , Selvachandran Somesh , Kwon Sohee , Ma Wenjie , Menni Cristina , Hammers Alexander , Bhupathiraju Shilpa N. , Sharma Shreela V. , Sudre Carole , Astley Christina M. , Willet Walter C. , Chavarro Jorge E. , Ourselin Sebastien , Steves Claire J. , Wolf Jonathan , Franks Paul W. , Spector Tim D. , Berry Sarah E. , Chan Andrew T.
Published: June 2021

Objective

Poor metabolic health and certain lifestyle factors have been associated with risk and severity of coronavirus disease 2019 (COVID-19), but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its intersection with socioeconomic deprivation.

Design

We used data from 592,571 participants of the smartphone-based COVID Symptom Study. Diet quality was assessed using a healthful plant-based diet score, which emphasizes healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate hazard ratios (HR) and 95% confidence intervals (95% CI) for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalization with oxygen support, respectively.

Results

Over 3,886,274 person-months of follow-up, 31,815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR, 0.91; 95% CI, 0.88-0.94) and severe COVID-19 (HR, 0.59; 95% CI, 0.47-0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate for lowest vs highest quartile of diet score was 22.5 (95% CI, 18.8-26.3) and 40.8 (95% CI, 31.7-49.8; 10,000 person-months) among persons living in areas with low and high deprivation, respectively.

Conclusions

A dietary pattern characterized by healthy plant-based foods was associated with lower risk and severity of COVID-19. These association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.
Mathematical and Statistical models as tools for the control of mosquito-borne diseases: The experience of Costa Rica
Authors: Vásquez Paola , Sanchez Fabio , Barboza Luis A. , García Yury E. , Calvo Juan G. , Chou Shu-Wei , Mery Gustavo
Published: June 2021

The modeling of infectious diseases provides valuable input for developing mitigating strategies and implementing public health interventions. This article highlights results and current research conducted in Costa Rica using mathematical, statistical, and computational tools to analyze transmission dynamics and provide quantitative information for developing mosquito-borne disease prevention/control methods and resource allocation planning.
Modules in connectomes of phase-synchronization comprise anatomically contiguous, functionally related regions
Authors: Williams N , Wang SH , Arnulfo G , Nobili L , Palva S , Palva JM
Published: June 2021

Modules in brain functional connectomes are essential to balancing segregation and integration of neuronal activity. Connectomes are the complete set of pairwise connections between brain regions. Non-invasive Electroencephalography (EEG) and Magnetoencephalography (MEG) have been used to identify modules in connectomes of phase-synchronization. However, their resolution is suboptimal because of spurious phase-synchronization due to EEG volume conduction or MEG field spread. Here, we used invasive, intracerebral recordings from stereo-electroencephalography (SEEG,N= 67), to identify modules in connectomes of phase-synchronization. To generate SEEG-based group-level connectomes affected only minimally by volume conduction, we used submillimeter accurate localization of SEEG contacts and referenced electrode contacts in cortical grey matter to their closest contacts in white matter. Combining community detection methods with consensus clustering, we found that the connectomes of phase-synchronization were characterized by distinct and stable modules at multiple spatial scales, across frequencies from 3 to 320 Hz. These modules were highly similar within canonical frequency bands. Unlike the distributed brain systems identified with functional Magnetic Resonance Imaging (fMRI), modules up to the high-gamma frequency band comprised only anatomically contiguous regions. Notably, the identified modules comprised cortical regions involved in shared repertoires of sensorimotor and cognitive functions including memory, language and attention. These results suggest that the identified modules represent functionally specialised brain systems, which only partially overlap with the brain systems reported with fMRI. Hence, these modules might regulate the balance between functional segregation and functional integration through phase-synchronization.

Highlights

Large-cohort SEEG used for phase-synchronization connectomics

Connectomes of phase-synchronization possess distinct and stable modules

Modules in connectomes are highly similar within canonical frequency bands

Modules in connectomes comprise anatomically contiguous regions

Modules in connectomes comprise functionally related regions
Engineered human induced pluripotent cells enable genetic code expansion in brain organoids
Authors: van Husen Lea S. , Katsori Anna-Maria , Meineke Birthe , Tjernberg Lars O. , Schedin-Weiss Sophia , Elsässer Simon J.
Published: June 2021

Human induced pluripotent stem cell (hiPSC) technology has revolutionized human biology. A wide range of cell types and tissue models can be derived from hiPSCs to study complex human diseases. Here, we use PiggyBac mediated transgenesis to engineer hiPSCs with an expanded genetic code. We demonstrate that genomic integration of expression cassettes for a pyrrolysyl-tRNA synthetase (PylRS), pyrrolysyl-tRNA (PylT) and the target protein of interest enables site-specific incorporation of a non-canonical amino acid (ncAA) in response to amber stop codons. Neural stem cells, neurons and brain organoids derived from the engineered hiPSCs continue to express the amber suppression machinery and produce ncAA-bearing reporter. The incorporated ncAA can serve as a minimal bioorthogonal handle for further modifications by labeling with fluorescent dyes. Site-directed ncAA mutagenesis will open a wide range of applications to probe and manipulate proteins in brain organoids and other hiPSC-derived cell types and complex tissue models.

TOC
Application of a convolutional neural network to the quality control of MRI defacing
Authors: Delbarre Daniel J. , Santos Luis , Ganjgahi Habib , Horner Neil , McCoy Aaron , Westerberg Henrik , Häring Dieter A. , Nichols Thomas E. , Mallon Ann-Marie
Published: June 2021

Large-scale neuroimaging datasets present unique challenges for automated processing pipelines. Mo-tivated by a large clinical trials dataset of Multiple Sclerosis with over 235,000 MRI scans, we consider the challenge of defacing - anonymisation to remove identifying facial features. The defacing process must undergo quality control (QC) checks to ensure that the facial features have been adequately anonymised and that the brain tissue is left completely intact. Visual QC checks – particularly on a project of this scale – are time-consuming and can cause delays in preparing data. We have developed a convolutional neural network (CNN) that can assist with the QC of the application of MRI defacing; our CNN is able to distinguish between scans that are correctly defaced, and can also classify defacing failures into three sub-types to facilitate parameter tuning during remedial re-defacing. Since integrating the CNN into our anonymisation pipeline, over 75,000 scans have been processed. Strict thresholds have been applied so that ambiguous classifications are referred for visual QC checks, however all scans still undergo a time-efficient verification check before being marked as passed. After applying the thresholds, our network is 92% accurate and is able to classify nearly half of the scans without the need for protracted manual checks. Even with the introduction of the verification checks, incorporation of the CNN has reduced the time spent undertaking QC checks by 42% during initial defacing, and by 35% overall. With the help of the CNN, we have been able to successfully deface 96% of the scans in the project whilst maintaining high QC standards. In a similarly sized new project of this scale, we would expect the model to reduce the time spent on manual QC checks by 125 hours. Our approach is applicable to other projects with the potential to greatly improve the efficiency of imaging anonymisation pipelines.
The Forget-Me-Not dHCP study: 7 Tesla high resolution diffusion imaging in the unfixed post-mortem neonatal brain
Authors: Wu Wenchuan , Baxter Luke , Rieger Sebastian W , Adams Eleri , Andersson Jesper LR , Andrade Maria Cobo , Andritsou Foteini , Bastiani Matteo , Fry Ria Evans , Frost Robert , Fitzgibbon Sean , Foxley Sean , Fowler Darren , Gallagher Chris , Howard Amy FD , Hajnal Joseph V , Moultrie Fiona , Monk Vaneesha , Porter David Andrew , Papp Daniel , Price Anthony , Sallet Jerome , Sanders Michael , Wilkinson Dominic , Smith Stephen M , Slater Rebeccah , Miller Karla L
Published: June 2021

Diffusion MRI of the neonatal brain allows investigation of the organisational structure of maturing fibres during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. The Forget-Me-Not study, part of the Developing Human Connectome Project (dHCP), aims to acquire and publicly distribute high-resolution diffusion MRI data for unfixed post-mortem neonatal brain at 7T with a custom-built head coil. This paper describes how the study addressed logistical, technical and ethical challenges relating to recruitment pipeline, care pathway, tissue preservation, scan setup and protocol optimisation. Results from the first subject recruited to the study demonstrate high-quality diffusion MRI data. Preliminary voxel-wise and tractography-based analyses are presented for the cortical plate, subplate and white matter pathways, with comparison to age-matched in vivo dHCP data. These results demonstrate that high quality post-mortem data can be acquired and provide a sensitive means to explore the developing human brain, as well as altered diffusion properties consistent with post-mortem changes, at high resolution.
High viral abundance and low diversity are associated with increased CRISPR-Cas prevalence across microbial ecosystems
Authors: Meaden S. , Biswas A. , Arkhipova K. , Morales S. E. , Dutilh B. E. , Westra E. R. , Fineran P. C.
Published: June 2021

CRISPR-Cas are adaptive immune systems that protect their hosts against viruses and other parasitic mobile genetic elements. Consequently, selection from viruses and other genetic parasites is often assumed to drive the acquisition and maintenance of these immune systems in nature, but this remains untested. Here, we analyse the abundance of CRISPR arrays in natural environments using metagenomic datasets from 332 terrestrial, aquatic and host-associated ecosystems. For each metagenome we quantified viral abundance and levels of viral community diversity to test whether these variables can explain variation in CRISPR-Cas abundance across ecosystems. We find a strong positive correlation between CRISPR-Cas abundance and viral abundance. In addition, when controlling for differences in viral abundance, we found that the CRISPR-Cas systems are more abundant when viral diversity is low. We also found differences in relative CRISPR-Cas abundance among environments, with environmental classification explaining ∼24% of variation in CRISPR-Cas abundance. However, the correlations with viral abundance and diversity are broadly consistent across diverse natural environments. These results indicate that viral abundance and diversity are major ecological factors that drive the selection and maintenance of CRISPR-Cas in microbial ecosystems.

Significance statement

Numerous studies demonstrate that CRISPR-Cas immune systems can provide defence against bacteriophage and archaeal viruses, yet little is known about the ecological conditions where CRISPR-Cas immunity is favoured. Moreover, our knowledge is largely confined to laboratory studies and it is unknown if viruses are a key selective driver of CRISPR-Cas in nature. Using metagenomic data from diverse environments we find that both viral abundance and the abundance of CRISPR-Cas immune systems correlate positively across most environments. Furthermore, CRISPR-Cas systems are more prevalent when viral diversity is low. These results extend previous theoretical work by demonstrating that viruses are a key driver of selection of CRISPR-Cas immune systems across many natural ecosystems.
Conformational changes in Lassa virus L protein associated with promoter binding and RNA synthesis activity
Authors: Kouba Tomas , Vogel Dominik , Thorkelsson Sigurdur R. , Quemin Emmanuelle R. J. , Williams Harry M. , Milewski Morlin , Busch Carola , Günther Stephan , Grünewald Kay , Rosenthal Maria , Cusack Stephen
Published: June 2021

Lassa virus, which causes annual outbreaks in West Africa with increasing case numbers in recent years, is recognized by the WHO R&D blueprint as a significant threat for public health with high epidemic potential and no effective countermeasures. The viral large (L) protein, which contains the RNA-dependent RNA polymerase, is a key player for transcription of viral mRNA and genome replication. Here we present nine cryo-EM structures of Lassa virus L protein in the apo-, promoter-bound pre-initiation and active RNA synthesis states. We characterize distinct binding pockets for the conserved genomic 3’ and 5’ promoter RNAs and show how full-promoter binding induces a distinct pre-initiation conformation. In the apo- and elongation states, the endonuclease is inhibited by the binding of two distinct L protein peptides in the active site, respectively, whereas in the pre-initiation state, the endonuclease is uninhibited. In the stalled, early elongation state, a template-product duplex is bound in the active site cavity together with an incoming non-hydrolysable nucleotide. In this configuration, the full C-terminal region of the L protein, including the putative cap-binding domain, is highly ordered. The structural data are complemented by in vitro and cell-based studies testing a broad range of L protein mutants to probe functional relevance. These data advance our mechanistic understanding of how this flexible and multifunctional molecular machine is activated and will underpin antiviral drug development targeting the arenavirus L protein.
AI for predicting chemical-effect associations at the chemical universe level – deepFPlearn
Authors: Schor Jana , Scheibe Patrick , Bernt Matthias , Busch Wibke , Lai Chih , Hackermüller Jörg
Published: June 2021

Many chemicals are out there in our environment, and all living species are exposed. However, numerous chemicals pose risks, such as developing severe diseases, if they occur at the wrong time in the wrong place. For the majority of the chemicals, these risks are not known. Chemical risk assessment and subsequent regulation of use require efficient and systematic strategies. Lab-based methods – even if high throughput – are too slow to keep up with the pace of chemical innovation. Existing computational approaches are designed for specific chemical classes or sub-problems but not usable on a large scale. Further, the application range of these approaches is limited by the low amount of available labeled training data.

We present the ready-to-use and stand-alone program deepFPlearn that predicts the association between chemical structures and effects on the gene/pathway level using a combined deep learning approach. deepFPlearn uses a deep autoencoder for feature reduction before training a deep feedforward neural network to predict the target association. We received good prediction qualities and showed that our feature compression preserves relevant chemical structural information. Using a vast chemical inventory (unlabeled data) as input for the autoencoder did not reduce our prediction quality but allowed capturing a much more comprehensive range of chemical structures. We predict meaningful - experimentally verified-associations of chemicals and effects on unseen data. deepFPlearn classifies hundreds of thousands of chemicals in seconds.

We provide deepFPlearn as an open-source and flexible tool that can be easily retrained and customized to different application settings at https://github.com/yigbt/deepFPlearn.

Supplementary information

Supplementary data are available at bioRxiv online.

Contact

jana.schor@ufz.de
Isolation and characterizations of a novel H6N1 avian influenza virus from Von Schrenck’s Bittern (Ixobrychus eurhythmus) in Jiangxi province, China
Authors: Attaran Hamidreza , Jin Wen , Luo Jing , Wang Chengmin , He Hongxuan
Published: June 2021

In June 2013, the first case of human infection with an avian H6N1 virus was reported in a Taiwanese woman. Although this was a single non-fatal case, the virus continues to circulate in Taiwanese poultry. As with any emerging avian virus that infects humans, there is concern that acquisition of human-type receptor specificity could enable transmission in the human population. Despite mutations in the receptor-binding pocket of the human H6N1 isolate, it has retained avian-type (NeuAca2-3Gal) receptor specificity.

An H6N1 AIV was isolated from a Von Schrenck’s Bittern during national active surveillance project for avian influenza viruses (AIVs) in wild birds in Jiangxi province, China 2018. Phylogenetic analysis showed that this strain received its genes from H1, H2, H3, H4, H6 and H10 AIVs in different places. This strain was found to be minimally pathogenic in mice and was able to replicate in mice without prior adaptation. Considering that the reassorted H6N1 virus was isolated from Von Schrenck’s Bittern in this study, it is possible that this bird can play an important role in the generation of novel reassorted H6 AIVs.

In this study, H6N1 virus is a wild virus migration brought from different regions of the AIV gene into the natural gene pool, resulting in the production of a recombinant new virus. The H6N1 virus can be seen as a link in the evolution of the virus and the evolution of other viruses.