bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-trait association studies discover pleiotropic loci between Alzheimer’s disease and cardiometabolic traits
Authors: Bone William P. , Siewert Katherine M. , Jha Anupama , Klarin Derek , Damrauer Scott M. ,   the VA Million Veteran Project, Chang Kyong-Mi , Tsao Philip S. , Assimes Themistocles L. , Ritchie Marylyn D. , Voight Benjamin F.
Published: September 2020

Identification of genetic risk factors that are shared between Alzheimer’s disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Motivated by previous epidemiological correlations observed between cardiometabolic traits and AD, we performed a set of bivariate genome-wide association studies coupled with colocalization analysis to identify loci that are shared between AD and eleven cardiometabolic traits. We identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci. One associated locus was tagged by a low-frequency coding variant in the geneDOCK4and is potentially implicated in its alternative splicing. Statistical colocalization with expression quantitative trait loci identified by the Genotype-Tissue Expression (GTEx) project identified additional candidate genes, includingACE, the target of the hypertensive drug class of ACE-inhibitors. We found that the allele associated with decreasedACEexpression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic. Overall, our results support a complex genetic relationship between AD and these cardiometabolic traits, and the candidate causal genes identified suggest that blood pressure and immune response play a role in the pleiotropy between these traits.
Safety and immunogenicity of ChAd63-KH vaccine in post kala azar dermal leishmaniasis patients in Sudan
Authors: Younis Brima M. , Osman Mohamed , Khalil Eltahir A.G. , Santoro Francesco , Furini Simone , Wiggins Rebecca , Keding Ada , Carraro Monica , Anas E.A. Musa , Abdarahaman Mujahid A.A. , Mandefield Laura , Bland Martin , Aebischer Toni , Gabe Rhian , Layton Alison M. , Lacey Charles J. N. , Kaye Paul M. , Musa Ahmed M.
Published: September 2020

Post kala azar dermal leishmaniasis (PKDL) is a chronic, stigmatising skin condition occurring frequently after apparent clinical cure from visceral leishmaniasis. Given an urgent need for new treatments, we conducted a Phase IIa safety and immunogenicity trial of ChAd63-KH vaccine in Sudanese patients with persistent PKDL. LEISH2a (NCT02894008) was an open label three-phase clinical trial involving sixteen adult and eight adolescent patients with persistent PKDL (median duration 30 months; range 6 -180 months). Patients received a single intramuscular vaccination of 1×1010 viral particles (v.p.; adults only) or 7.5×1010 v.p. (adults and adolescents), with primary (safety) and secondary (clinical response and immunogenicity) endpoints evaluated over 42-120 days follow up. AmBisome® was provided to patients with significant remaining disease at their last visit. ChAd63-KH vaccine showed minimal adverse reactions in PKDL patients and induced potent innate and cell-mediated immune responses measured by whole blood transcriptomics and ELISpot. 7 patients (30.4%) monitored to study completion showed >90% clinical improvement and 6 (25%) showed partial improvement. A logistic regression model applied to blood transcriptomic data identified immune modules predictive of patients with >90% clinical improvement. A randomised controlled trial to determine whether these clinical responses were vaccine related and whether ChAd63-KH vaccine has clinical utility is underway.
Identifying COVID-19 cases in primary care settings
Authors: Mao Yinan , Tan Yi-Roe , Thein Tun Linn , Chai Yi Ann Louis , Cook Alex R , Dickens Borame L , Lew Yii Jen , Lim Fong Seng , Lim Jue Tao , Sun Yinxiaohe , Sundaram Meena , Soh Alexius , En Tan Glorijoy Shi , Wong Franco Pey Gein , Young Barnaby , Zeng Kangwei , Chen Mark , Seng Desmond Ong Luan
Published: September 2020

Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 SARS-CoV-2 positive cases and 564 controls, accounting for the time course of illness at point of assessment. Clinical differentiators of cases and controls were used to derive model-based risk scores. Significant symptoms included abdominal pain, cough, diarrhea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5°C and 37.9°C, and temperature above 38°C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, we firstly used leave-one-out cross-validation, which confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. Secondly, in a separate ongoing prospective study of 237 COVID-19 and 346 primary care patients presenting with symptoms of acute respiratory infection, the baseline model had a sensitivity of 0.57 and specificity of 0.89, and in retrospective notes review of 100 COVID-19 cases diagnosed in primary care, sensitivity was 0.56. A web-app based tool has been developed for easy implementation as an adjunct to laboratory testing to differentiate COVID-19 positive cases among patients presenting in outpatient settings.
A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, Brazil
Authors: Fernandes Fernando Timoteo , de Oliveira Tiago Almeida , Teixeira Cristiane Esteves , de Moraes Batista Andre Filipe , Costa Gabriel Dalla , Filho Alexandre Dias Porto Chiavegatto
Published: September 2020

Introduction

The new coronavirus disease (COVID-19) is a challenge for clinical decision-making and the effective allocation of healthcare resources. An accurate prognostic assessment is necessary to improve survival of patients, especially in developing countries. This study proposes to predict the risk of developing critical conditions in COVID-19 patients by training multipurpose algorithms.

Methods

A total of 1,040 patients with a positive RT-PCR diagnosis for COVID-19 from a large hospital from São Paulo, Brazil, were followed from March to June 2020, of which 288 (28%) presented a severe prognosis, i.e. Intensive Care Unit (ICU) admission, use of mechanical ventilation or death. Routinely-collected laboratory, clinical and demographic data was used to train five machine learning algorithms (artificial neural networks, extra trees, random forests, catboost, and extreme gradient boosting). A random sample of 70% of patients was used to train the algorithms and 30% were left for performance assessment, simulating new unseen data. In order to assess if the algorithms could capture general severe prognostic patterns, each model was trained by combining two out of three outcomes to predict the other.

Results

All algorithms presented very high predictive performance (average AUROC of 0.92, sensitivity of 0.92, and specificity of 0.82). The three most important variables for the multipurpose algorithms were ratio of lymphocyte per C-reactive protein, C-reactive protein and Braden Scale.

Conclusion

The results highlight the possibility that machine learning algorithms are able to predict unspecific negative COVID-19 outcomes from routinely-collected data.
Health-Related Quality of Life in the Spironolactone to Reduce ICD Therapy (SPIRIT) Trial
Authors: Liberato Ana Carolina Sauer , Raitt Merritt H. , Zarraga Ignatius GE , MacMurdy Karen S. , Dougherty Cynthia M.
Published: September 2020

Purpose

The Spironolactone to Reduce ICD Therapy (SPIRIT) trial was designed to determine whether once daily spironolactone would: 1) reduce the incidence of ventricular tachycardia (VT) and ventricular fibrillation (VF), and 2) improve health related quality of life (HRQOL) and symptoms. The purpose of this paper is to describe the long term HRQOL outcomes in the SPIRIT trial and compare QOL in those who did or did not receive implantable cardioverter defibrillator (ICD) shocks during follow-up.

Methods

Ninety participants age 66±10 years, 96% men, 75% with NYHA class II, with an ICD at moderately high risk for recurrent VT/VF were randomized to spironolactone 25mg (N=44) or placebo (N=46). HRQOL was measured every 6 months for 24 months using 3 instruments: Patient Concerns Assessment (PCA), Short Form Health Survey-Veterans Version (SF-36V), and the Kansas City Cardiomyopathy Questionnaire (KCCQ). Linear mixed modeling was used to compare changes in HRQOL across 24-months. ANCOVA was used to compare HRQOL between those getting an ICD shock or not.

Results

Over 24-months, there were no differences in HRQOL between the spironolactone vs. placebo groups. Those who experienced at least 1 ICD shock vs. those with no ICD shocks, reported significantly lower HRQOL and more symptoms at 6-months and 24 months.

Conclusions

Spironolactone had no significant impact on HRQOL. Patients receiving one or more ICD shocks reported significant reductions in HRQOL and higher symptoms.
Predicting and interpreting COVID-19 transmission rates from the ensemble of government policies
Authors: Sruthi C. K. , Biswal Malay Ranjan , Saraswat Brijesh , Joshi Himanshu , Prakash Meher K.
Published: September 2020

Several questions resonate as the governments relax their COVID-19 mitigation policies - is it too early to relax them, were the policies as effective as they could have been. Answering these questions about the past or crafting newer policy decisions in the future requires a quantification of how policy choices affect the spread of the infection. Policy landscape as well as the infection trajectories from different states and countries diverged so fast that comparing and learning from them has not been easy. In this work, we standardize and pool together the ensemble of lockdown and graded re-opening policies adopted by the 50 states of USA in any given week between 9th March and 9th August. Using artificial intelligence (AI) on this pooled data, we build a predictive model (, ) for the weekly-averaged transmission rate of infections. Predictability conceptually raises the possibility of an evidence-based or data-driven mitigation policy-making by evaluating the relative merits of the different policy scenarios. Probing the predictions with interpretable AI highlights how factors such as the closing of bars or the use of masks influence transmission, effects which have been hard to decouple from the ensemble of policy instrument combinations. While acknowledging the limitations of our predictions as well as of the infection testing, we ask the theoretical question if the observed transmission rates in the states were as efficient as they could have been under various levels of restrictions, and if the mitigation policies of the states are ‘overdesigned’. The model can be further refined with a more detailed inclusion of geographies and policy compliances, as well as expanded as newer policies emerge.
Dynamic data-driven meta-analysis for prioritisation of host genes implicated in COVID-19
Authors: Parkinson Nicholas , Rodgers Natasha , Fourman Max Head , Wang Bo , Zechner Marie , Swets Maaike C. , Millar Jonathan E. , Law Andy , Russell Clark D. , Baillie J. Kenneth , Clohisey Sara
Published: September 2020

The increasing body of literature describing the role of host factors in COVID-19 pathogenesis demonstrates the need to combine diverse, multi-omic data to evaluate and substantiate the most robust evidence and inform development of therapies.

Here we present a dynamic ranking of host genes implicated in human betacoronavirus infection (SARS-CoV-2, SARS-CoV, MERS-CoV, seasonal coronaviruses). Researchers can search and review the ranked genes and the contribution of different experimental methods to gene rank at https://baillielab.net/maic/covid19.

We conducted an extensive systematic review of experiments identifying potential host factors. Gene lists from diverse sources were integrated using Meta-Analysis by Information Content (MAIC). This previously described algorithm uses data-driven gene list weightings to produce a comprehensive ranked list of implicated host genes.

From 32 datasets, the top ranked gene was PPIA, encoding cyclophilin A, a drug-gable target using cyclosporine.Other highly-ranked genes included proposed prognostic factors (CXCL10, CD4, CD3E) and investigational therapeutic targets (IL1A) for COVID-19. Gene rankings also inform the interpretation of COVID-19 GWAS results, implicating FYCO1 over other nearby genes in a disease-associated locus on chromosome 3.

As new data are published we will regularly update list of genes as a resource to inform and prioritise future studies.
The impact of thrombosis and bleeding among patients with Myeloproliferative Neoplasm: Systematic Review and Meta-Analysis
Authors: Brhanie Tsegahun Worku , Fava Carmen , Jovanovski Aleksandar
Published: September 2020

Background

Thrombosis and bleeding are the most common complications which contribute to significant morbidity and mortality of myeloproliferative patients. This study aimed to find out the incidence of thrombotic and bleeding events during diagnosis and follow up among patients with myeloproliferative neoplasm. This might help in the early detection of thrombosis and bleeding and prevention of such complications for MPN patients.

Methods

A systematic review and meta-analysis was conducted to assess the incidence of thrombosis and bleeding. Data extracted from the literatures in Google scholars, Mendeley, PubMed, and EMBASE databases. Studies that had thrombosis and/or bleeding reports with any types of myeloproliferative neoplasm were included in this study. We used random effect model to estimate the odd ratio, relative risk and risk difference with 95%CI of each studies and the pooled results based on Cochrane methods of Revman. A funnel plot and I2test checked to see the publication bias and heterogeneity respectively.

Results

Nineteen studies with 14706 participants that had fitted the inclusion criteria were included in the overall thrombosis study. Five studies (n=931) included for incidence thrombosis at diagnosis and follow up. The pooled overall frequency thrombosis was 18.6%. The pooled incidence of thrombosis at diagnosis was 26.5% and odds ratio (OR= 3.17,95%CI 0.96 to10.43); relative risk (RR= 2.07,95%CI 0.98 to 4.34); risk difference (RD=21%, 95%CI −0.05 to 0.48, high certainty). Thrombosis had significant differences during diagnosis and follow up. A history of thrombosis, age >60years, and smoking were some of the risk factors for thrombosis.

Conclusions

Based on the findings, thrombosis and bleeding are the highest complications occurred among myeloproliferative neoplasm patients. This problem is also common both during diagnosis and follow up of MPN patients. Early detection and follow up is needed to prevent MPN complications.
Evaluation of ultrasonic renal volume in relation to body size in patients with hypertension: Comparative cross-sectional study
Authors: Kedir Elias , Berhane Melkamu , Nigatu Tilahun Alemayehu , Ayalew Almaz , Zewdu Mesfin
Published: September 2020

Introduction

Estimation of renal size is useful parameter in the diagnosis of abnormal structural change on the kidneys due to the adverse effects of chronic diseases like hypertension. This study evaluated renal volume by ultrasound in relation to body size parameters, notably BMI and body surface area in hypertensive and non-hypertensive individuals.

Methods

A hospital-based comparative cross-sectional study was conducted from February to September 2018 at the Radiology department of the Jimma University Medical Center (JUMC). The study included consecutively selected samples of ambulatory hypertensive patients and non-hypertensive controls recruited consecutively on voluntary basis. After providing verbal informed consent, each subject underwent abdominal ultrasound examination; length, width and thickness of both kidneys were measured and used for estimation of renal volume. The statistical evaluation included independent samples t-tests for mean differences with regard to ultrasonic renal measurements between hypertensive and non-hypertensive groups,

Results

A total of 145 adults aged 16 - 80 years (mean ±SD=44 ±17) participated in the study. In the hypertensive group, renal volume ranged 36.1 - 201.6 (mean=97.7) cm3 for the right kidney and 39.6 - 189.5 (mean=104.4) cm3 for the left kidney, whilst it was 61.8 - 159.5 (mean=101.1) cm3 for the right and 35.8 - 253.7 (mean=111.8) cm3 for the left kidney among the control group. Both kidneys were slightly smaller in the hypertensive group as compared to the controls. Right renal volume to BSA ratio ranged from 23.5 - 100.6 (mean=58.2) cm3/m2 in hypertensive group, while it was between 37.0 and 96.1 (mean=62.6) cm3/m2 among the control group (p=0.076). Left renal volume to BSA of the patients which ranged from 24.1 - 97.1 (mean=62.2) cm3/m2 was significantly (p=0.012) lower than that of the non-hypertensive group, which was between 23.6 and 132.5 (mean=69.3) cm3/m2.

Conclusion

The results of this study have shown slightly smaller bilateral renal volume among hypertensive patients as compared the controls. We recommend large scale research in other parts of Ethiopia so that nationally representative data can be obtained.
Cancer Risk Assessment Tool: A new general model to estimate cure-rate fraction in patients under tumor therapy
Authors: Nascimento Diego C. , Ramos Pedro L. , Gonzatto Oilson A. , Ferreira Gabriel G. , de Castro Patrícia P.M. , Barbosa Renan S. , Boen Vinicius O. , Valentim Vinicius H. , Silva Luiz G. , Gomes Mariana M. , Perdoná Gleice S. C. , Louzada Francisco
Published: September 2020

Cure fraction is not an easy task to be calculated relating probabilistic estimations to an event. For instance, cancer patients may abandon treatment, be cured, or die due to another illness, causing limitations regarding the information about the odds of cancer cure (related to the patient follow-up) and may mislead the researcher’s inference. In this paper, we overcame this limitation and proposed a risk assessment tool related to the lifetime of cancer patients to survival functions to help medical decision-making. Moreover, we proposed a new machine learning algorithm, so-called long-term generalized weighted Lindley (LGWL) distribution, solving the inferential limitation caused by the censored information. Regarding the robustness of this distribution, some mathematical properties are shown and inferential procedures discussed, under the maximum likelihood estimators’ perspective. Empirical results used TCGA lung cancer data (but not limited to this cancer type) showing the competitiveness of the proposed distribution to the medical field. The cure-rate is dynamic but quantifiable. For instance, after 14 years of development/spread of lung cancer, the group of patients under the age of 70 had a cure fraction of 32%, while the group of elderly patients presented a cure fraction of 22%, whereas those estimations using the traditional (long-term) Weibull distribution is 31% and 17%. The LGWL returned closer curves to the empirical distribution, then were better adjusted to the adopted data, elucidating the importance of cure-rate fraction in survival models.
A Rational-Choice Model of Covid-19 Transmission with Endogenous Quarantining and Two-sided Prevention
Authors: Bhattacharya Joydeep , Chakraborty Shankha , Yu Xiumei
Published: September 2020

This paper offers a parsimonious, rational-choice model to study the effect of pre-existing inequalities on the transmission of COVID-19. Agents decide whether to “go out” (or self-quarantine) and, if so, whether to wear protection such as masks. Three elements distinguish the model from existing work. First, non-symptomatic agents do not know if they are infected. Second, some of these agents unknowingly transmit infections. Third, we permit two-sided prevention via the use of non-pharmaceutical interventions: the probability of a person catching the virus from another depends on protection choices made by each. We find that a mean-preserving increase in pre-existing income inequality unambiguously increases the equilibrium proportion of unprotected, socializing agents and may increase or decrease the proportion who self-quarantine. Strikingly, while higher pre-COVID inequality may or may not raise the overall risk of infection, it increases the risk of disease in social interactions.
Data-driven Optimized Control of the COVID-19 Epidemics
Authors: Shirin Afroza , Lin Yen Ting , Sorrentino Francesco
Published: September 2020

Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening ‘in phases’. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population.
Acute kidney injury is associated with severe and fatal outcomes in patients with Coronavirus disease 2019 (COVID-19) infection: a systematic review and meta-analysis of observational studies
Authors: Parohan Mohammad , Yaghoubi Sajad , Djalali Mahmoud , Seraji Asal , Javanbakht Mohammad Hassan , Mousavi Zahra
Published: September 2020

Coronavirus disease 2019 (COVID-19) is a pandemic impacting 213 countries and territories with more than 17,918,582 cases worldwide. Kidney dysfunction has been reported to occur in severe and death cases. This meta-analysis was done to summarize available studies on the association between acute kidney injury and severity of COVID-19 infection. Online databases including Web of Science, PubMed/Medline, Cochrane Library, Scopus and Google Scholar were searched to detect relevant articles up to 1 July 2020, using relevant keywords. To pool data, a random- or fixed-effects model was used based on the heterogeneity between studies. In total, 50 studies with 8,180 COVID-19 confirmed cases (severe cases=1,823 and death cases=775), were included in this meta-analysis. Higher serum levels of creatinine (weighted mean difference (WMD) for disease severity=5.47 μmol/L, 95% CI=2.89 to 8.05, P<0.001 and WMD for mortality=18.32 μmol/L, 95% CI=12.88 to 23.75, P<0.001), blood urea nitrogen (BUN) (WMD for disease severity=1.10 mmol/L, 95% CI=0.67 to 1.54, P<0.001 and WMD for mortality=3.56 mmol/L, 95% CI=2.65 to 4.48, P<0.001) and lower levels of estimated glomerular filtration rate (eGFR) (WMD for disease severity=-15.34 mL/min/1.73 m2, 95% CI=-18.46 to -12.22, P<0.001 and WMD for mortality=-22.74 mL/min/1.73 m2, 95% CI=-27.18 to -18.31, P<0.001) were associated with a significant increase in the severity and mortality of COVID-19 infection. Acute kidney injury, as assessed by kidney biomarkers (serum creatinine, BUN and eGFR), was associated with severe outcome and death from COVID-19 infection.
Population-based seroprevalence of SARS-CoV-2 is more than halfway through the herd immunity threshold in the State of Maranhão, Brazil
Authors: Silva Antônio Augusto Moura da , Lima-Neto Lídio Gonçalves , Azevedo Conceição de Maria Pedrozo e Silva , Costa Léa Márcia Melo da , Bragança Maylla Luana Barbosa Martins , Filho Allan Kardec Duailibe Barros , Wittlin Bernardo Bastos , Souza Bruno Feres , Oliveira Bruno Luciano Carneiro Alves de , Carvalho Carolina Abreu de , Thomaz Erika Barbara Abreu Fonseca , Simões-Neto Eudes Alves , Leite Júnior Jamesson Ferreira , Cosme Lécia Maria Sousa Santos , Campos Marcos Adriano Garcia , Queiroz Rejane Christine de Sousa , Costa Sérgio Souza , Carvalho Vitória Abreu de , Simões Vanda Maria Ferreira , Alves Maria Teresa Seabra Soares de Brito , Santos Alcione Miranda dos
Published: September 2020

Background

Few population-based studies on the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been performed to date, and most of them have used lateral flow immunoassays with finger-prick, which may yield false-negative results and thus underestimate the true infection rate.

Methods

A population-based household survey was performed in the State of Maranhão, Brazil, from 27 July 2020 to 8 August 2020 to estimate the seroprevalence of SARS-CoV-2 using a serum testing electrochemiluminescence immunoassay. A three-stage cluster sampling stratified by four state regions was used. The estimates took clustering, stratification, and non-response into account. Qualitative detection of IgM and IgG antibodies was performed in a fully-automated Elecsys® Anti-SARS-CoV-2 electrochemiluminescence immunoassay on the Cobas® e601 analyser (Roche Diagnostics).

Findings

A total of 3156 individuals were interviewed. Seroprevalence of total antibodies against SARS-CoV-2 was 40·4% (95%CI 35·6-45·3). Population adherence to non-pharmaceutical interventions was higher at the beginning of the pandemic than in the last month. SARS-CoV-2 infection rates were significantly lower among mask wearers and among those who maintained social and physical distancing in the last month compared to their counterparts. Among the infected, 62·2% had more than three symptoms, 11·1% had one or two symptoms, and 26·0% were asymptomatic. The infection fatality rate was 0·17%, higher for males and advanced age groups. The ratio of estimated infections to reported cases was 22·2.

Interpretation

To the best of our knowledge, the seroprevalence of SARS-CoV-2 estimated in this population-based survey was the highest and the closest to the herd immunity threshold reported to date. Our results suggest that the herd immunity threshold is not as low as 20%, but at least higher than or equal to around 40%. The infection fatality rate was one of the lowest reported so far, and the proportion of asymptomatic cases was low.
A Systematic Review of Droplet and Aerosol Generation in Dentistry
Authors: Innes N. , Johnson I.G. , Al-Yaseen W. , Harris R. , Jones R. , Kc S. , McGregor S. , Robertson M. , Wade W.G. , Gallagher J.E.
Published: September 2020

Objectives

Against the COVID-19 pandemic backdrop and potential disease transmission risk by dental procedures that can generate aerosol and droplets, this review aimed to identify which clinical dental procedures do generate droplets and aerosols with subsequent contamination, and for these, characterise their pattern, spread and settle.

Data Sources

Six databases were searched and citation chasing undertaken (to 11/08/20).

Study selection

Screening stages were undertaken in duplicate, independently, by two researchers. Data extraction was performed by one reviewer and verified by another.

Results

Eighty-three studies met the inclusion criteria and covered: Ultrasonic scaling (USS, n=44), highspeed air-rotor (HSAR, n=31); oral surgery (n=11), slow-speed handpiece (n=4); air-water (triple) syringe (n=4), air-polishing (n=4), prophylaxis (n=2) and hand-scaling (n=2). Although no studies investigated respiratory viruses, those on bacteria, blood splatter and aerosol showed activities using powered devices produced the greatest contamination. Contamination was found for all activities, and at the furthest points studied. The operator’s torso operator’s arm, and patient’s body were especially affected. Heterogeneity precluded significant inter-study comparisons but intra-study comparisons allowed construction of a proposed hierarchy of procedure contamination risk: higher risk (USS, HSAR, air-water syringe [air only or air/water together], air polishing, extractions using motorised handpieces); moderate (slow-speed handpieces, prophylaxis with pumice, extractions) and lower (air-water syringe [water only] and hand scaling.

Conclusion

Significant gaps in the evidence, low sensitivity of measures and variable quality limit firm conclusions around contamination for different procedures. However, a hierarchy of contamination from procedures can be proposed for challenge/verification by future research which should consider standardised methodologies to facilitate research synthesis.

Clinical significance

This manuscript addresses uncertainty around aerosol generating procedures (AGPs) in dentistry. Findings indicate a continuum of procedure-related aerosol generation rather than the current binary AGP or non-AGP perspective. This informs discussion around AGPs and direct future research to help support knowledge and decision making around COVID-19 and dental procedures.
Wing tags severely impair movement in African Cape Vultures
Authors: Curk Teja , Scacco Martina , Safi Kamran , Wikelski Martin , Fiedler Wolfgang , Kemp Ryno , Wolter Kerri
Published: September 2020

Background

The use of tracking technologies is key for the study of animal movement and pivotal to ecological and conservation research. However, the potential effects of devices attached to animals are sometimes neglected. The impact of tagging not only rises welfare concerns, but can also bias the data collected, causing misinterpretation of the observed behaviour which invalidates the comparability of information across individuals and populations. Patagial (wing) tags have been extensively used as a marking method for visual resightings in endangered vulture species, but their effect on the aerodynamics of the birds and their flight behaviour is yet to be investigated. Using GPS backpack mounted devices, we compared the flight performance of 27 captive and wild Cape Vultures (Gyps coprotheres), marked with either patagial tags or coloured leg bands.

Results

Individuals equipped with patagial tags were less likely to fly, travelled shorter distances and flew slower compared to individuals equipped with leg bands. These effects were also observed in one individual that recovered its flight performance after replacing its patagial tag by a leg band.

Conclusions

Although we did not measure the effects of patagial tags on body condition or survival, our study strongly suggests that they have severe adverse effects on vultures’ flight behaviour and emphasises the importance of investigating the effects that tagging methods can have on the behaviour and conservation of the study species, as well as on the quality of the scientific results.
A Population Receptive Field Model of the Magnetoencephalography Response
Authors: Kupers Eline R , Edadan Akhil , Benson Noah C , Zuiderbaan Wietske , de Jong Maartje C , Dumoulin Serge O , Winawer Jonathan
Published: September 2020

1

Computational models which predict the neurophysiological response from experimental stimuli have played an important role in human neuroimaging. One type of computational model, the population receptive field (pRF), has been used to describe cortical responses at the millimeter scale using functional magnetic resonance imaging (fMRI) and electrocorticography (ECoG). However, pRF models are not widely used for non-invasive electromagnetic field measurements (EEG/MEG), because individual sensors pool responses originating from several centimeter of cortex, containing neural populations with widely varying spatial tuning. Here, we introduce a forward-modeling approach in which pRFs estimated from fMRI data are used to predict MEG sensor responses. Subjects viewed contrast-reversing bar stimuli sweeping across the visual field in separate fMRI and MEG sessions. Individual subject’s pRFs were modeled on the cortical surface at the millimeter scale using the fMRI data. We then predicted cortical time series and projected these predictions to MEG sensors using a biophysical MEG forward model, accounting for the pooling across cortex. We compared the predicted MEG responses to observed visually evoked steady-state responses measured in the MEG session. We found that pRF parameters estimated by fMRI could explain a substantial fraction of the variance in steady-state MEG sensor responses (up to 60% in individual sensors). Control analyses in which we artificially perturbed either pRF size or pRF position reduced MEG prediction accuracy, indicating that MEG data are sensitive to pRF properties derived from fMRI. Our model provides a quantitative approach to link fMRI and MEG measurements, thereby enabling advances in our understanding of spatiotemporal dynamics in human visual field maps.
Synonymization of the male-based ant genusPhaulomyrma(Hymenoptera, Formicidae) withLeptanillabased upon Bayesian total-evidence phylogenetic inference
Authors: Griebenow Zachary H.
Published: September 2020

Although molecular data have proven indispensable in confidently resolving the phylogeny of many clades across the tree of life, these data may be inaccessible for certain taxa. The resolution of taxonomy in the ant subfamily Leptanillinae is made problematic by the absence of DNA sequence data for leptanilline taxa that are known only from male specimens, including the monotypic genusPhaulomyrmaWheeler & Wheeler. Focusing upon the considerable diversity of undescribed male leptanilline morphospecies, the phylogeny of 35 putative morphospecies sampled from across the Leptanillinae, plus an outgroup, is inferred from 11 nuclear loci and 41 discrete male morphological characters using a Bayesian total-evidence framework, withPhaulomyrmarepresented by morphological data only. Based upon the results of this analysisPhaulomyrmais synonymized withLeptanillaEmery, and male-based diagnoses forLeptanillathat are grounded in phylogeny are provided, under both broad and narrow circumscriptions of that genus. This demonstrates the potential utility of a total-evidence approach in inferring the phylogeny of rare extant taxa for which molecular data are unavailable and begins a long-overdue systematic revision of the Leptanillinae that is focused on male material.
Genome-wide signatures of plastid-nuclear coevolution point to repeated perturbations of plastid proteostasis systems across angiosperms
Authors: Forsythe Evan S. , Williams Alissa M. , Sloan Daniel B.
Published: September 2020

Nuclear and plastid (chloroplast) genomes experience different mutation rates, levels of selection, and transmission modes, yet key cellular functions depend on coordinated interactions between proteins encoded in both genomes. Functionally related proteins often show correlated changes in rates of sequence evolution across a phylogeny (evolutionary rate covariation or ERC), offering a means to detect previously unidentified suites of coevolving and cofunctional genes. We performed phylogenomic analyses across angiosperm diversity, scanning the nuclear genome for genes that exhibit ERC with plastid genes. As expected, the strongest hits are highly enriched for plastid-targeted proteins, providing evidence that cytonuclear interactions affect rates of molecular evolution at genome-wide scales. Many identified nuclear genes function in post-transcriptional regulation and the maintenance of protein homeostasis (proteostasis), including protein translation (in both the plastid and cytosol), import, quality control and turnover. We also identified nuclear genes that exhibit strong signatures of coevolution with the plastid genome but lack organellar-targeting annotations, making them candidates for having previously undescribed roles in plastids. In sum, our genome-wide analyses reveal that plastid- nuclear coevolution extends beyond the intimate molecular interactions within chloroplast enzyme complexes and may be driven by frequent rewiring of the machinery responsible for maintenance of plastid proteostasis in angiosperms.
Pocket MUSE: an affordable, versatile and high performance fluorescence microscope using a smartphone
Authors: Liu Yehe , Rollins Andrew M. , Levenson Richard M. , Fereidouni Farzad , Jenkins Michael W.
Published: September 2020

Smartphone microscopes can be effective tools for a broad range of imaging applications. In this manuscript, we demonstrate the first practical implementation of Microscopy with Ultraviolet Surface Excitation (MUSE) in a compact smartphone microscope called Pocket MUSE, resulting in a remarkably effective design. Fabricated with parts from consumer electronics that are readily available at low cost, the small optical module attaches directly over the rear lens in a smartphone and enables high quality multichannel fluorescence microscopy with submicron resolution over a 10X equivalent field of view. In addition to the novel optical configuration, Pocket MUSE is compatible with a series of simple, portable and user-friendly sample preparation strategies that can be directly implemented for various microscopy applications for point-of-care diagnostics, at-home health monitoring, plant biology, STEM education, environmental studies, etc.
Clinical Feasibility and Preliminary Outcomes of a Novel Mixed Reality Based System to Manage Phantom Pain for Patients with Lower Limb Amputation.: A Pilot Study
Authors: Annaswamy M. , Bahirat Kanchan , Raval Gargi , Chung Yu Yen , Prabhakaran Balakrishnan
Published: September 2020

Objective

This report describes the details of Mr. MAPP, a virtual mirror therapy system and the results of a clinical feasibility and evaluation study of a pilot sample of patients with history of lower limb amputation and phantom limb pain.

Materials and Methods

Mr. MAPP system uses a Kinect V2 RGB-D camera to capture the patient, generates a live interactive 3D model, and incorporates it into a virtual exergame. Mr. MAPP mirrors their preserved limb and allows participants to visualize their amputated limb virtually and perform their prescribed exercise program. Mr. MAPP creates a digital diary of their therapy sessions by recording game performance and errors. Ten consecutive patients with history of limb loss and phantom pain were targeted for this pilot study. They received a Mr. MAPP system and a laptop for home use for 1-month. Outcome measures including pain intensity and pain interference measured on Numerical Rating Scale (NRS) and McGill Pain Questionnaire (MPQ) as well as functional outcomes measured on Patient Specific Functional Scale (PSFS) were obtained at baseline, and after 1-month.

Results

Seven participants were enrolled, out of which four completed the study. The study was temporarily suspended due to restrictions imposed during the COVID-19 public health emergency. In-game performance data showed a trend towards improvement in most participants. Compared to baseline, NRS and MPQ scores at 1-month showed no clear trends. PSFS scores improved for 1 participant and remained unchanged for others.

Conclusion

Gamified home exercises performed via a novel, mixed-reality system—Mr. MAPP— using which virtual mirror therapy was delivered, is feasible and has potential to improve pain and pain related function in patients with lower limb amputations and phantom limb pain.
Virtual metabolic human dynamic model for pathological analysis and therapy design for diabetes
Authors: Kurata Hiroyuki
Published: September 2020

A virtual metabolic human model is a valuable complement to experimental biology and clinical studies, becausein vivoresearch involves serious ethical and technical problems. I have proposed a multi-organ and multi-scale kinetic model that formulates the reactions of enzymes and transporters with the regulation of enzyme activities and hormonal actions under prandial and rest conditions. The model consists of 202 ordinary differential equations for metabolites with 217 reaction rates and 1132 kinetic parameter constants. It is the most comprehensive, largest and highly predictive model of the whole-body metabolism. Use of the model revealed the mechanisms by which individual disorders, such as steatosis, β cell dysfunction and insulin resistance, were combined to cause type 2 diabetes. The model predicted a glycerol kinase inhibitor to be an effective medicine for type 2 diabetes, which not only decreased hepatic triglyceride but also reduced plasma glucose. The model also enabled us to rationally design combination therapy.
De novogenome assembly of the Tobacco Hornworm moth (Manduca sexta)
Authors: Gershman Ariel , Romer Tatiana Gelaf , Fan Yunfan , Razaghi Roham , Smith Wendy A. , Timp Winston
Published: September 2020

The Tobacco hornworm,Manduca sexta,is a lepidopteran insect that is used extensively as a model system for studying insect biology, development, neuroscience and immunity. However, current studies rely on the highly fragmented reference genome Msex_1.0, which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. We present the new reference genome forM. sexta, JHU_Msex_v1.0, applying a combination of modern technologies in ade novoassembly to increase continuity, accuracy, and completeness. The assembly is 470 Mb and is ~20x more continuous than the original assembly, with scaffold N50 >14 Mb. We annotated the assembly by lifting over existing annotations and supplementing with additional supporting RNA-based data for a total of 25,256 genes. The new reference assembly is accessible in annotated form for public use. We demonstrate that improved continuity of theM. sextagenome improves resequencing studies and benefits future research onM. sextaas a model organism.
EEG Artifact to Signal: Predicting Horizontal Gaze Position from SOBI-DANS Identified Ocular Artifact Components
Authors: Sun Rui , Chan Cynthia , Hsiao Janet , Tang Akaysha C.
Published: September 2020

Ocular artifact in EEG has long been viewed as a problem for interpreting EEG data in basic and applied research. The removal of such artifacts has been an on-going effort over many decades. We have recently introduced a hybrid method combining second-order blind identification (SOBI) with DANS, a novel automatic identification method, to extract components containing specifically signals associated with horizontal and vertical saccadic eye movements (H and V Comps) and found that these components’ event-related potentials in response to saccadic eye movement are systematically modulated by movement directions and distances. Here in a case study, taking advantage of signals about gaze positions contained in the ocular artifact components, we introduced a novel concept of EEG-based virtual eye tracking (EVET) and presented its first prototype. Specifically, we determined (1) the amount of data needed for constructing models of horizontal gaze positions; (2) the asymptotic performance levels achieved with such models. We found that for the specific calibration task, 4 blocks of data (4 saccades per target position) are needed for reaching an asymptotic performance with a prediction accuracy of 0.44 and prediction reliability of 1.67. These results demonstrated that it is possible to track horizontal gaze position via EEG alone, ultimately enabling coregistration of eye movement and the neural signals.
Species and intra-specific competition affect growth in greenhouse more than mycorrhizal colonization onQuercus rubraandAcer rubrumseedlings
Authors: Maier Michael
Published: September 2020

Aims

Distributions of mycorrhizal guilds correlate with differences in soil nutrient availability and tend to predominate ecosystems where plant growth and development are limited by either soil phosphorus (AM, arbuscular mycorrhiza) or nitrogen (EM, ectomycorrhiza) (Read, 1991). In an effort to characterize functional trait differences, we designed a common garden greenhouse experiment to measure growth and colonization responses between two tree seedling species (Acer rubrumandQuercus rubra) that associate with the two major mycorrhizal guilds.

Methods

In a fully factorial, 12-week greenhouse common garden experiment, seedlings were treated to three levels of nitrogen and phosphorus availability, and grown under inter- and intra-species competition. Change in heights and stem diameters were tracked and mycorrhizal colonization was quantified by percent of total and morphology.

Results

Relative growth rates were higher forAcer rubrumseedlings across treatments and intra-species competition had a strong negative effect on height and stem diameter, especially forQuercus rubra. Both species were highly colonized (>50%) by typically endomycorrhizal forms (arbuscules and vesicles) but varied in the distribution of morphological forms present in cells.

Conclusions

This study highlights the plasticity of tree seedling symbiosis during early developmental stages and challenges the strict static categorization of plant species associations with particular mycorrhizal guilds.
Methylene Blue Inhibits In Vitro the SARS-CoV-2 Spike – ACE2 Protein-Protein Interaction – A Mechanism That Can Contribute to Its Antiviral Activity Against COVID-19
Authors: Bojadzic Damir , Alcazar Oscar , Buchwald Peter
Published: September 2020

Due to our interest in the chemical space of organic dyes to identify potential small-molecule inhibitors (SMIs) for protein-protein interactions (PPIs), we initiated a screen of such compounds to assess their inhibitory activity against the interaction between SARS-CoV-2 spike protein and its cognate receptor ACE2, which is the first critical step initiating the viral attachment and entry of this coronavirus responsible for the ongoing COVID-19 pandemic. As part of this, we found that methylene blue, a tricyclic phenothiazine compound approved by the FDA for the treatment of methemoglobinemia and used for other medical applications (including the inactivation of viruses in blood products prior to transfusion when activated by light), inhibits this interaction. We confirmed that it does so in a concentration-dependent manner with a low micromolar half-maximal inhibitory concentration (IC50= 3 μM) in our protein-based ELISA-type setup, while chloroquine, siramesine, and suramin showed no inhibitory activity in this assay. Erythrosine B, which we have shown before to be a promiscuous SMI of PPIs, also inhibited this interaction with an activity similar, possibly slightly higher, than those found for it for other PPIs. This PPI inhibitory activity of methylene blue could contribute to its antiviral activity against SARS-CoV-2 even in the absence of light by blocking its attachment to ACE2-expressing cells and making this inexpensive and widely available drug potentially useful in the prevention and treatment of COVID-19 as an oral or inhaled medication.