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INTRODUCTION: Microgravity-induced bone loss increases urinary calcium excretion which increases kidney stone formation risk. Not all individuals show the same degree of increase in urinary calcium and some pre-flight characteristics may help identify individuals who may benefit from in-flight monitoring. In weightlessness the bone is unloaded, and the effect of this unloading may be greater for those who weigh more. We studied whether pre-flight body weight was associated with increased in-flight urinary calcium excretion using data from Skylab and the International Space Station (ISS). METHODS: A retrospective analysis of Skylab and ISS data was conducted. The study was reviewed and approved by the National Aeronautics and Space Administration (NASA) electronic Institutional Review Board (eIRB) and data were sourced from the Longitudinal Study of Astronaut Health (LSAH) database. The effect of weight on urinary calcium excretion was examined using linear mixed effect models with day-in-flight, weight, and program (Skylab or ISS) as fixed effects and the subject’s responses over time as random effects. RESULTS: The combined Skylab and ISS data included 45 participants (9 Skylab, 36 ISS). Both weight and day in flight were positively related to urinary calcium excretion. There was also an interaction between weight and day in flight with higher weight associated with higher calcium excretion earlier in the mission. DISCUSSION: Several factors can affect urinary calcium excretion in space including baseline urinary calcium excretion, dietary intake, and genetic makeup. This study shows that pre-flight weight is also a factor and could be included in the risk assessments for bone loss and kidney stone formation in space.

INTRODUCTION: Aerospace Medicine is experiencing a renaissance. The field provides physicians with the expertise to promote the health and safety of those traveling in space. Commercial spaceflight is now a reality, meaning that individuals with a variety of medical conditions will be flying in space. NASA has Mars plans and SpaceX plans to send humans to Mars within the next decade, so today’s medical students may be future physicians on these crews. Considering these developments, we evaluated interest in and exposure to Aerospace Medicine among medical students in the United States (US).METHODS: This study was approved by the Dartmouth College Committee for the Protection of Human Subjects and informed consent was obtained by each participant. A 19-question anonymous multiple-choice questionnaire was emailed to current medical students throughout the US. Information about demographics, career and research interests in Aerospace Medicine, opportunities available at students’ respective institutions, and possible avenues for supporting students’ interests was collected and analyzed.RESULTS: 1,244 students (490 men, 751 women, 3 other) with a mean age of 25.8 ± 3.0 years from 61 institutions completed the questionnaire. 1,061 (85.3%) expressed an interest in learning more about Aerospace Medicine if given the opportunity with 208 (16.7%) specifying an interest in research and 939 (75.5%) in career opportunities. 55 (4.4%) indicated that they had access to research opportunities at their institutions while 333 (47.2%) of those who did not, suggested they would pursue research if they had access. 98 (7.9%) of respondents reported that their institution offered an Aerospace Medicine Interest Group or elective. Students from institutions who offered an interest group, elective, or access to research opportunities expressed significantly more interest in Aerospace Medicine careers than those who did not (pDISCUSSION: Most respondents expressed an interest in learning about Aerospace Medicine during their training. A strong interest in research as well as career opportunities exists despite the majority of students reporting minimal access to opportunities to get involved in the field at most of the surveyed institutions. With growing interest and an expected increase in demand for physicians with a background in Aerospace Medicine, medical schools may be able to support students by increasing access to opportunities.

Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients towards the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug’s action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of nutrients and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.

Microbes frequently evolve in reproducible ways. Here, we show that differences in specific metabolic regulation rather than inter-strain interactions explain the frequent presence ofBacteria can evolve quickly, a skill that proves useful in ever-changing environments. For example, individuals in many bacterial species can start to work together under certain circumstances; this ability is underpinned by a system called quorum sensing, which allows cells to detect nearby conspecifics. However, species of harmful bacteria often lose their quorum sensing abilities when they infect humans. This is the case for

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients toward the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug’s action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of metabolites and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.

Matrices subordinate to trees are considered. An efficient normality characterization for any such matrix is given, and several consequences (not valid for general normal matrices) of it are established. In addition, the existence (and enumeration) of flat portions on the boundary of the field of values of matrices subordinate to a tree is characterized.

Ethnic diversity in the former Yugoslavia, measured as informational entropy increased in most regions at the level of the naselje, the opstina, and the region, 1961-1991 (no useful data for Slovenia, Macedonia, and Kosovo in 1991). Vojvodina is the most diverse region, Slovenia the least. An exception to the increase is Kosovo-Metohija, where diversity decreased 1961-1981 driven by already serious interethnic conflict. There is some diminution of the increase in diversity in some regions in 1991, possibly because of refugee flows in anticipation of the impending violence. This rather broad and steady increase in diversity leads to questions about the view that pre-existing ethnic hatreds among broad segments of the population led to the ethnic fracturing and collapse of Yugoslavia. Instead it suggests that this fracturing may instead have been the result of competition between political leaders, stimulated by serious economic difficulties, leading them to emphasize ethnicity in their search for popular support. From this the authors support the view that the collapse of Yugoslavia was from the top downward, not from the bottom upward.

Demographic analysis clarifies political issues in the collapse of Yugoslavia. In most regions, 1961-1991, ethnic diversity (estimated by informational entropy) increased and segregation (estimated by Theil's H) decreased. In a few regions there was a reversal in 1991 as migration flows or presentations of self perhaps changed in anticipation of war. The analysis strengthens refutations of the view that long standing ethnic hatreds were the root cause of the Yugoslav collapse and supports analyses that attribute collapse to general economic crisis, economic competition between regions, and failures at the peak of government.