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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.

The macrogeographic distribution of obesity in the United States, including the association between elevation and body mass index (BMI), is largely unexplained. This study examines the relationship between obesity and elevation, ambient temperature and urbanization.Data from a cross-sectional, nationally representative sample of 422603 US adults containing BMI, behavioral (diet, physical activity, smoking) and demographic (age, sex, race/ethnicity, education, employment, income) variables from the 2011 Behavioral Risk Factor Surveillance System were merged with elevation and temperature data from WorldClim and with urbanization data from the US Department of Agriculture. There was an approximately parabolic relationship between mean annual temperature and obesity, with maximum prevalence in counties with average temperatures near 18 °C. Urbanization and obesity prevalence exhibited an inverse relationship (30.9% in rural or nonmetro counties, 29.2% in metro counties with250000 people, 28.1% in counties with population from 250000 to 1 million and 26.2% in counties with1 million). After controlling for urbanization, temperature category and behavioral and demographic factors, male and female Americans living500 m above sea level had 5.1 (95% confidence interval (CI) 2.7-9.5) and 3.9 (95% CI 1.6-9.3) times the odds of obesity, respectively, as compared with counterparts living ≥ 3000 m above sea level.Obesity prevalence in the United States is inversely associated with elevation and urbanization, after adjusting for temperature, diet, physical activity, smoking and demographic factors.

Medical conditions arising from hymenopteran sting allergy or mass envenomation are a serious health concern, particularly in austere environments. Both practicing allergists and entomological pest control personnel should consider the relevance of stinging insects when responding to problems with Hymenoptera. Recent occupational reviews of civilian deaths from insect bites and stings prompted our review of the US Air Force Mortality Registry to determine the relevance of insect stings and bites as a cause of death in the US Air Force. After reviewing over 40 years of death records we identified 23 death records, among US Air Force Active duty, guard, or retirees that arose directly from hymenopteran stings.

Summary 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. Copyright © 2015 John Wiley & Sons, Ltd.

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.

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.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.

Regulation analysis is a methodology that quantifies to what extent a change in the flux through a metabolic pathway is regulated by either gene expression or metabolism. Two extensions to regulation analysis were developed over the past years: (i) the regulation of V(max) can be dissected into the various levels of the gene-expression cascade, such as transcription, translation, protein degradation, etc. and (ii) a time-dependent version allows following flux regulation when cells adapt to changes in their environment. The methodology of the original form of regulation analysis as well as of the two extensions will be described in detail. In addition, we will show what is needed to apply regulation analysis in practice.Studies in which the different versions of regulation analysis were applied revealed that flux regulation was distributed over various processes and depended on time, enzyme, and condition of interest. In the case of the regulation of glycolysis in baker's yeast, it appeared, however, that cells that remain under respirofermentative conditions during a physiological challenge tend to invoke more gene-expression regulation, while a shift between respirofermentative and respiratory conditions invokes an important contribution of metabolic regulation. The complexity of the regulation observed in these studies raises the question what is the advantage of this highly distributed and condition-dependent flux regulation.

revised) METHODS CONCLUSIONS RESULTS INTRODUCTION Assessment of 10 Influenza-Like Illness Case Definitions Using Department of Defense Global, Laboratory-Based, Influenza Surveillance Data Laurie DeMarcus, MPH1,2, Laurel Soderlund, MPH1,2, Jameson Voss, MD, MPH2 1Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. 2U.S. Air Force School of Aerospace Medicine, Epidemiology Consult Division, Public Health & Preventive Medicine Department, Wright-Patterson AFB, OH 45433

Obesity is a public health priority, which also threatens national security. Adenovirus 36 (Adv36) increases adiposity in animals and Adv36 antibody status is associated with human obesity, but it is unknown whether infection predicts the development of human adiposity.The objective of the study was to assess infection status and subsequent weight gain.The study had a retrospective cohort design.The study was conducted at Air Force fitness testing and clinical encounters.PARTICIPANTS included Air Force male enlistees, aged 18-22 years, with a baseline body mass index (BMI) of 20-30 kg/m(2) followed up from enlistment (beginning in 1995) until 2012 or separation from the Air Force.EXPOSURE included Adv36 infection status at the time of entry.Follow-up BMI, the primary outcome, and diagnosis of overweight/obesity by the International Classification of Diseases, ninth revision V85.25+ and 278.0* series (secondary outcome) were recorded.The last recorded follow-up BMI was similar among infected and uninfected, 26.4 and 27.2 kg/m(2), respectively (P.05). However, infected individuals had a higher hazard of a medical provider's diagnosis of overweight/obese over time (hazard ratio 1.8, 95% confidence interval 1.0-3.1, P = .04), adjusted for baseline BMI. Additionally, infected individuals who were lean at baseline (BMI of 22.5 kg/m(2)) had a 3.9 times greater hazard of developing an overweight/obese clinical diagnosis (95% confidence interval 1.5-9.7, P = .004) compared with uninfected lean individuals after adjusting for interaction (P = .03) between infection and baseline BMI.The presence of Adv36 antibodies was not associated with higher BMI at baseline or follow-up within this military population. However, being infected was associated with developing a clinical diagnosis of overweight/obesity, especially among those lean at baseline.

Background Although randomization is considered essential for causal inference, it is often not possible to randomize in nutrition and obesity research. To address this, we develop a framework for an experimental design—packet randomized experiments (PREs), which improves causal inferences when randomization on a single treatment variable is not possible. This situation arises when subjects are randomly assigned to a condition (such as a new roommate) which varies in one characteristic of interest (such as weight), but also varies across many others. There has been no general discussion of this experimental design, including its strengths, limitations, and statistical properties. As such, researchers are left to develop and apply PREs on an ad hoc basis, limiting its potential to improve causal inferences among nutrition and obesity researchers. Methods We introduce PREs as an intermediary design between randomized controlled trials and observational studies. We review previous research that used the PRE design and describe its application in obesity-related research, including random roommate assignments, heterochronic parabiosis, and the quasi-random assignment of subjects to geographic areas. We then provide a statistical framework to control for potential packet-level confounders not accounted for by randomization. Results Packet randomized experiments have successfully been used to improve causal estimates of the effect of roommates, altitude, and breastfeeding on weight outcomes. When certain assumptions are met, PREs can asymptotically control for packet-level characteristics. This has the potential to statistically estimate the effect of a single treatment even when randomization to a single treatment did not occur. Conclusions Applying PREs to obesity-related research will improve decisions about clinical, public health, and policy actions insofar as it offers researchers new insight into cause and effect relationships among variables.

BackgroundPhysical inactivity, ambient air pollution and obesity are modifiable risk factors for non-communicable diseases, with the first accounting for 10% of premature deaths worldwide. Although community level interventions may target each simultaneously, research on the relationship between these risk factors is lacking.ObjectivesAfter comparing spatial interpolation methods to determine the best predictor for particulate matter (PM2.5; PM10) and ozone (O3) exposures throughout the U.S., we evaluated the cross-sectional association of ambient air pollution with leisure-time physical inactivity among adults.MethodsIn this cross-sectional study, we assessed leisure-time physical inactivity using individual self-reported survey data from the Centers for Disease Control and Prevention's 2011 Behavioral Risk Factor Surveillance System. These data were combined with county-level U.S. Environmental Protection Agency air pollution exposure estimates using two interpolation methods (Inverse Distance Weighting and Empirical Bayesian Kriging). Finally, we evaluated whether those exposed to higher levels of air pollution were less active by performing logistic regression, adjusting for demographic and behavioral risk factors, and after stratifying by body weight category.ResultsWith Empirical Bayesian Kriging air pollution values, we estimated a statistically significant 16-35% relative increase in the odds of leisure-time physical inactivity per exposure class increase of PM2.5 in the fully adjusted model across the normal weight respondents (p-valueConclusionsIn a nationally representative, cross-sectional sample, increased community level air pollution is associated with reduced leisure-time physical activity particularly among the normal weight. Although our design precludes a causal inference, these results provide additional evidence that air pollution should be investigated as an environmental determinant of inactivity.

Quantitative analyses of the dynamics of single cells have become a powerful approach in current cell biology. They give us an unprecedented opportunity to study dynamics of molecular networks at a high level of accuracy in living single cells. Genetically identical cells, growing in the same environment and sharing the same growth history, can differ remarkably in their molecular makeup and physiological behaviors. The origins of this cell-to-cell variability have in many cases been traced to the inevitable stochasticity of molecular reactions. Those mechanisms can cause isogenic cells to have qualitatively different life histories. Many studies indicate that molecular noise can be exploited by cell populations to enhance survival prospects in uncertain environments. On the other hand, cells have evolved noise-suppression mechanisms to cope with the inevitable noise in their functioning so as to reduce the hazardous effects of noise. In this chapter, we discuss key experiments, theoretical results, and physiological consequences of molecular stochasticity to introduce this exciting field to a broader community of (systems) biologists.

In vitro enzymatic assays of cell-free extracts offer an opportunity to assess in vivo enzyme concentrations. If performed under conditions that resemble the conditions in vivo, they may also reveal some of the capacities and properties of the same enzymes in vivo; we shall call this the ex vivo approach. The kinetic characterization of purified enzymes has yet a different utility for systems biology, as does the in vivo determination of enzyme activities. All these approaches are different, and it is becoming important that the appropriate approach be used for the intended purpose. Here, we therefore discuss five approaches to the measurement of enzyme activity in terms of the source of the enzyme activity, the identity of the assay medium, and the purpose of the assay.