SARS-CoV-2 Genome-Based Severity Predictions Correspond to Lower qPCR Values and Higher Viral Load.

The 2019 coronavirus disease (COVID-19) pandemic has demonstrated the importance of predicting, identifying, and tracking mutations throughout a pandemic event. As the COVID-19 global pandemic surpassed one year, several variants had emerged resulting in increased severity and transmissibility. Here, we used PCR as a surrogate for viral load and consequent severity to evaluate the real-world capabilities of a genome-based clinical severity predictive algorithm. Using a previously published algorithm, we compared the viral genome-based severity predictions to clinically derived PCR-based viral load of 716 viral genomes. For those samples predicted to be "severe" (probability of severe illness >0.5), we observed an average cycle threshold (Ct) of 18.3, whereas those in in the "mild" category (severity probability <0.5) had an average Ct of 20.4 (P=0.0017). We also found a nontrivial correlation between predicted severity probability and cycle threshold (r = -0.199). Finally, when divided into severity probability quartiles, the group most likely to experience severe illness (≥75% probability) had a Ct of 16.6 (n = 10), whereas the group least likely to experience severe illness (<25% probability) had a Ct of 21.4 (n = 350) (P=0.0045). Taken together, our results suggest that the severity predicted by a genome-based algorithm can be related to clinical diagnostic tests and that relative severity may be inferred from diagnostic values.

SARS-CoV-2 genome-based severity predictions correspond to lower qPCR values and higher viral load

The 2019 coronavirus disease (COVID-19) pandemic has demonstrated the importance of predicting, identifying, and tracking mutations throughout a pandemic event. As the COVID-19 global pandemic surpassed one year, several variants had emerged resulting in increased severity and transmissibility. In order to reduce the impact on human life, it is critical to rapidly identify which genetic variants result in increased virulence or transmission. To address the former, we evaluated if a genome-based predictive algorithm designed to predict clinical severity could predict polymerase chain reaction (PCR) results, as a surrogate for viral load and severity. Using a previously published algorithm, we compared the viral genome-based severity predictions to clinically-derived PCR-based viral load of 716 viral genomes. For those samples predicted to be "severe" (predicted severity score > 0.5), we observed an average cycle threshold (Ct) of 18.3, whereas those in in the "mild" category (severity prediction < 0.5) had an average Ct of 20.4 (P = 0.0017). We found a non-trivial correlation between predicted severity probability and cycle threshold (r = -0.199). Additionally, when divided into quartiles by prediction severity probability, the most probable quartile ([≥]75% probability) had a Ct of 16.6 (n=10) as compared to those least probable to be severe (<25%) of 21.4 (n=350) (P = 0.0045). Taken together, our results suggest that the severity predicted by a genome-based algorithm can be related to the metrics from the clinical diagnostic test, and that relative severity may be inferred from diagnostic values.

Variants in SARS-CoV-2 associated with mild or severe outcome.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The viral genetic variants associated with outcome severity are still being discovered. METHODS: We downloaded 155 958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID. Of these genomes, 3637 samples included useable metadata on patient outcomes. Using this subset, we evaluated whether SARS-CoV-2 viral genomic variants improved prediction of reported severity beyond age and region. First, we established whether including genomic variants as model features meaningfully increased the predictive power of our model. Next, we evaluated specific variants in order to determine the magnitude of association with severity and the frequency of these variants among SARS-CoV-2 genomes. RESULTS: Logistic regression models that included viral genomic variants outperformed other models (area under the curve = 0.91 as compared with 0.68 for age and gender alone; P < 0.001). We found 84 variants with odds ratios greater than 2 for outcome severity (17 and 67 for higher and lower severity, respectively). The median frequency of associated variants was 0.15% (interquartile range 0.09-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome. CONCLUSION: Numerous SARS-CoV-2 variants have 2-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.Lay summary: This study explores which, if any, SARS-CoV-2 viral genomic variants are associated with mild or severe COVID-19 patient outcomes. Our results suggest that there are common genomic variants in SARS-CoV-2 that are more often associated with negative patient outcomes, which may impact downstream public health measures.

Summit on Exercise Collapse Associated with Sickle Cell Trait: Finding the "Way Ahead".

ABSTRACT: Although largely benign, sickle cell trait (SCT) has been associated with exertion-related events, to include sudden death. In 2011, a summit on SCT introduced the term exercise collapse associated with SCT (ECAST). A series of ECAST deaths in military personnel in 2019 prompted reevaluation of current efforts and led to a second summit in October 2019 hosted by the Consortium for Health and Military Performance of the Uniformed Services University in Bethesda, MD. The goals were to (1) review current service policies on SCT screening, (2) develop draft procedural instructions for executing current policy on SCT within the Department of Defense, (3) develop draft clinical practice guidelines for management of ECAST, (4) establish a framework for education on SCT and ECAST, and (5) prepare a research agenda to address identified gaps.

Variants in SARS-CoV-2 Associated with Mild or Severe Outcome

IntroductionThe coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The molecular characteristics of the virus that predict better or worse outcome are largely still being discovered. MethodsWe downloaded 155,958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID and evaluated whether variants improved prediction of reported severity beyond age and region. We also evaluated specific variants to determine the magnitude of association with severity and the frequency of these variants among the genomes. ResultsLogistic regression models that included viral genomic variants outperformed other models (AUC=0.91 as compared with 0.68 for age and gender alone; p<0.001). Among individual variants, we found 17 single nucleotide variants in SARS-CoV-2 have more than two-fold greater odds of being associated with higher severity and 67 variants associated with [≤] 0.5 times the odds of severity. The median frequency of associated variants was 0.15% (interquartile range 0.09%-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome. ConclusionNumerous SARS-CoV-2 variants have two-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.

Musculoskeletal Injuries and Automation in Aerial Port Operations.

INTRODUCTION: Aerial ports are being modernized with automated technologies, but the impact on musculoskeletal injury (MSKI) is unknown.METHODS: In this retrospective cohort study of U.S. Air Force aerial port technicians and traffic management technicians, we compared reported injury rates from January 2006-December 2016 and Veterans Benefits Administration disability compensation claims awarded from January 2001-March 2017. Ton-adjusted injury rates, associated lost/affected duty time, and percent risk attributable to lack of automation were compared at Dover Air Force Base (which features base-specific automation), Travis Air Force Base, Ramstein Air Base, and Yokota Air Base.RESULTS: Injuries most often occurred during aircraft/flight line activities and were typically sprains/strains, with extremities being most affected. Among aerial port technicians there were 8.0 injury reports per 1000 person-years compared to 5.2 per 1000 among traffic management technicians (incidence rate ratio = 1.5; 95% CI: 0.9, 3.0). Of the aerial port technicians with a compensation award, 70.7% included an MSKI component, whereas 75.7% of traffic management awards included an MSKI component. Aerial port technicians at Dover AFB experienced 1.4 injury reports per 1000 personnel per 1000 cargo-tons per year, lower than the other ports: 3.2 (Travis); 3.7 (Ramstein); and 7.6 (Yokota). Overall, 56% of injuries at Travis, 62% at Ramstein, and 82% at Yokota could be attributed to absence of Dover-like automation. However, mean lost/affected duty days at Dover (12.4) far exceeded those at the other bases (range: 4.5-8.6).DISCUSSION: Automating aerial ports may reduce injury rates, but the impact on lost/affected duty time requires further investigation.Bylsma VFH, Webber BJ, Erich RA, Voss JD. Musculoskeletal injuries and automation in aerial port operations. Aerosp Med Hum Perform. 2020; 91(8):669-673.

Digital Image Analysis of Heterogeneous Tuberculosis Pulmonary Pathology in Non-Clinical Animal Models using Deep Convolutional Neural Networks.

Efforts to develop effective and safe drugs for treatment of tuberculosis require preclinical evaluation in animal models. Alongside efficacy testing of novel therapies, effects on pulmonary pathology and disease progression are monitored by using histopathology images from these infected animals. To compare the severity of disease across treatment cohorts, pathologists have historically assigned a semi-quantitative histopathology score that may be subjective in terms of their training, experience, and personal bias. Manual histopathology therefore has limitations regarding reproducibility between studies and pathologists, potentially masking successful treatments. This report describes a pathologist-assistive software tool that reduces these user limitations, while providing a rapid, quantitative scoring system for digital histopathology image analysis. The software, called 'Lesion Image Recognition and Analysis' (LIRA), employs convolutional neural networks to classify seven different pathology features, including three different lesion types from pulmonary tissues of the C3HeB/FeJ tuberculosis mouse model. LIRA was developed to improve the efficiency of histopathology analysis for mouse tuberculosis infection models, this approach has also broader applications to other disease models and tissues. The full source code and documentation is available from https://Github.com/TB-imaging/LIRA.

Executive, language, or both? An examination of the construct validity of verbal fluency measures.

The purpose of the present study was to evaluate whether phonemic and semantic verbal fluency were more related to aspects of language processing than executive functioning (EF). An exploratory factor analysis was performed on a college-aged sample of 320 healthy participants using principle axis factoring and promax rotation on nine measures of EF. The first three factors, labeled: working memory, fluid reasoning, and shifting/updating, were extracted and used as latent executive variables. Participants were also split into low, medium, and high phonemic and semantic verbal fluency ability groups. Phonemic and semantic fluency correlated similarly across all three extracted EF factors and word knowledge. Using one-way analysis of variance (ANOVAs), there was a main effect for both phonemic and semantic verbal fluency groups and all outcome variables (i.e., the EF factors and word knowledge). Tukey HSD post hoc analyses showed that those in the low verbal fluency ability groups had significantly lower scores across all outcome measures compared to the high verbal fluency ability groups. Across all analyses, semantic fluency had stronger relations with the EF factors, signifying a large executive component involved in the task. Both phonemic and semantic fluency were similarly related to multiple dimensions of EF and word knowledge and should be considered executive language tasks.

Evaluation of the Association Between Genetic Variants in Circadian Rhythm Genes and Posttraumatic Stress Symptoms Identifies a Potential Functional Allele in the Transcription Factor TEF.

Previous studies suggest that genetic variants within genes affecting the circadian rhythm influence the development of posttraumatic stress symptoms (PTSS). In the present study, we used data from three emergency care-based cohorts to search genetic variants in circadian pathway genes previously associated with neuropsychiatric disorders for variants that influence PTSS severity. The three cohorts used included a discovery cohort of African American men and women enrolled following motor vehicle collision (n = 907) and two replication cohorts: one of multi-ethnic women enrolled following sexual assault (n = 274) and one of multi-ethnic men and women enrolled following major thermal burn injury (n = 68). DNA and RNA were collected from trauma survivors at the time of initial assessment. Validated questionnaires were used to assess peritraumatic distress severity and to assess PTSS severity 6 weeks, 6 months, and 1 year following trauma exposure. Thirty-one genetic variants from circadian rhythm genes were selected for analyses, and main effect and potential gene*stress and gene*sex interactions were evaluated. Secondary analyses assessed whether associated genetic variants affected mRNA expression levels. We found that six genetic variants across five circadian rhythm-associated genes predicted PTSS outcomes following motor vehicle collision (p < 0.05), but only two of these variants survived adjustment for multiple comparisons (False Discovery Rate < 5%). The strongest of these associations, an interaction between the PAR-zip transcription factor, thyrotroph embryonic factor (TEF) variant rs5758324 and peritraumatic distress, predicted PTSS development in all three cohorts. Further analysis of genetic variants in the genetic region surrounding TEFrs5758324 (±125,000 nucleotides) indicated that this allele showed the strongest association. Further, TEF RNA expression levels (determined via RNA-seq) were positively associated with PTSS severity in distressed individuals with at least one copy of the TEFrs5758324 minor allele. These results suggest that rs5758324 genetic variant in TEF, a regulator of clock-controlled genes and key mediator of the core circadian rhythm, influence PTSS severity in a stress-dependent manner.

Assessment of 12 influenza-like illness case definitions using Department of Defense Global, Laboratory-based Influenza Surveillance Program data, 2011-2014.

Despite the growth in influenza surveillance programs, standardization of a globally accepted influenza-like illness (ILI) case definition remains difficult. With 2011-2014 Department of Defense Global, Laboratory-based Influenza Surveillance Program (DISP) data, 12 case definitions were evaluated using a combination of ILI case definitions from the Centers for Disease Control and Prevention, World Health Organization, and the DISP. The sensitivity, specificity, positive and negative predictive values, and odds ratios for each case definition were calculated. Additionally, area under the curve (AUC) was calculated for a receiver operating characteristic (ROC) curve to compare the case definitions. Between 2 October 2011 and 27 September 2014, 52.3% (5,575 of 10,662) of respiratory specimens submitted met the inclusion criteria. The case definition for the DISP had a sensitivity of 54.6% and specificity of 63.7%. Case definitions should be selected according to the objectives of the surveillance system and resources available. Sensitive case definitions capture a larger proportion of cases but at the cost of testing more specimens. Definitions with higher specificity result in fewer false positives but may miss more cases.

Student, instructor, and observer agreement regarding frequencies of scientific teaching practices using the Measurement Instrument for Scientific Teaching-Observable (MISTO).

BACKGROUND: The Scientific Teaching (ST) pedagogical framework encompasses many of the best practices recommended in the literature and highlighted in national reports. Understanding the growth and impact of ST requires instruments to accurately measure the extent to which practitioners implement ST in their courses. Researchers have typically relied on students, instructors, or observers to document course teaching practices, but it remains unclear whether and how these perspectives differ from each other. To address this issue, we modified our previously published instrument to generate the Measurement Instrument for Scientific Teaching-Observable (MISTO), which can be completed by students, instructors, and observers, and we investigated the degree of similarity between these three perspectives across 70 undergraduate science courses at seven different institutions in the USA. RESULTS: We found that the full MISTO and Active Learning subcategory scores showed the highest correlations among the three perspectives, but the degree of correlation between perspectives varied for the other subcategories. Match scores between students and instructors were significantly higher than observer matches for the full MISTO and for the Active Learning, Inclusivity, and Responsiveness subcategories. CONCLUSIONS: We find that the level and type of agreement between perspectives varies across MISTO subcategories and that this variation likely stems from intrinsic differences in the course access and scoring decisions of the three perspectives. Building on this data, we recommend MISTO users consider their research goals, available resources, and potential artifacts that may arise when deciding which perspective best fits their needs in measuring classroom teaching practices.

Viral Infections and Obesity.

PURPOSE OF REVIEW: Obesity is a multifactorial disease that is now endemic throughout most of the world. Although addressing proximate causes of obesity (excess energy intake and reduced energy expenditure) have been longstanding global health priorities, the problem has continued to worsen at the global level. RECENT FINDINGS: Numerous microbial agents cause obesity in various experimental models-a phenomena known as infectobesity. Several of the same agents alter metabolic function in human cells and are associated with human obesity or metabolic dysfunction in humans. We address the evidence for a role in the genesis of obesity for viral agents in five broad categories: adenoviridae, herpesviridae, phages, transmissible spongiform encephalopathies (slow virus), and other encephalitides and hepatitides. Despite the importance of this topic area, there are many persistent knowledge gaps that need to be resolved. We discuss factors motivating further research and recommend that future infectobesity investigation should be more comprehensive, leveraged, interventional, and patient-centered.

Role of adenoviruses in obesity.

UNLABELLED: Five human adenovirus subtypes, Ad5, Ad9, Ad31, Ad36, and Ad37, and a non-human adenovirus, SMAM1, are linked to increased adiposity in vitro or in vivo. Experimental infection with Ad5, Ad36, and Ad37 produced excess adiposity or weight gain in animals. Ad9 and Ad31 increase fat storage in tissue culture but are not associated with animal or human obesity. Ad36 is the most extensively studied adipogenic adenovirus and is correlated with some measure of overweight/obesity in humans from multiple countries. The correlation is strongest and most consistent in children, but some studies have been negative in both children and adults. About 30% of overweight/obese children and adults and about 15-20% of lean individuals have Ad36 antibodies in epidemiologic studies. The mechanisms of action of Ad36 are due to the early gene 4, open reading frame 1 (E4-ORF1). Blocking E4-ORF1 with siRNA prevents the effects of Ad36, and transfection of lentivirus with E4-ORF1 reproduces the Ad36 effects. Increased adiposity is caused by stimulation of at least three pathways by Ad36. Cell membrane glucose receptors are increased via the Ras pathway, leading to increased intracellular glucose. Fatty acid synthase is increased, which converts the glucose to fatty acids. Finally, peroxisome proliferator-activated receptor-γ is increased, resulting in differentiation of adult stem cells into adipocytes. CONCLUSIONS: several adenoviruses increase adiposity in animals and are associated with obesity in humans. There are critical gaps in the literature needing further investigation including evaluation of other adenovirus subtypes and better research designs to improve the strength of causal inferences.

Update on the Epidemiology of Concussion/Mild Traumatic Brain Injury.

Mild traumatic injuries to the brain (e.g., concussion) are common and have been recognized since antiquity, although definitions have varied historically. Nonetheless, studying the epidemiology of concussion helps clarify the overall importance, risk factors, and at-risk populations for this injury. The present review will focus on recent findings related to the epidemiology of concussion including definition controversies, incidence, and patterns in the population overall and in the military and athlete populations specifically. Finally, as this is an area of active research, we will discuss how future epidemiologic observations hold promise for gaining greater clarity about concussion and mild traumatic brain injury.

Pneumonia Outbreak Caused by Chlamydophila pneumoniae among US Air Force Academy Cadets, Colorado, USA.

During October 2013-May 2014, there were 102 cases of pneumonia diagnosed in US Air Force Academy cadets. A total of 73% of tested nasal washes contained Chlamydophila pneumoniae. This agent can be considered to be present on campus settings during outbreaks with numerous, seemingly disconnected cases of relatively mild pneumonia.