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Nuclear movement is a fundamental process of eukaryotic cell biology. Skeletal muscle presents an intriguing model to study nuclear movement because its development requires the precise positioning of multiple nuclei within a single cytoplasm. Furthermore, there is a high correlation between aberrant nuclear positioning and poor muscle function. Although many genes that regulate nuclear movement have been identified, the mechanisms by which these genes act are not known. Using Drosophila melanogaster muscle development as a model system and a combination of live-embryo microscopy and laser ablation of nuclei, we have found that clustered nuclei encompass at least two phenotypes that are caused by distinct mechanisms. Specifically, Ensconsin is necessary for productive force production to drive any movement of nuclei, whereas Bocksbeutel and Klarsicht are necessary to form distinct populations of nuclei that move to different cellular locations. Mechanistically, Ensconsin regulates the number of growing microtubules that are used to move nuclei, whereas Bocksbeutel and Klarsicht regulate interactions between nuclei.

Nuclear movement is a fundamental process of eukaryotic cell biology. Skeletal muscle presents an intriguing model to study nuclear movement because its development requires the precise positioning of multiple nuclei within a single cytoplasm. Furthermore, there is a high correlation between aberrant nuclear positioning and poor muscle function. Although many genes that regulate nuclear movement have been identified, the mechanisms by which these genes act is not known. UsingDrosophila melanogastermuscle development as a model system, and a combination of live-embryo microscopy and laser ablation of nuclei, we have found that phenotypically similar mutants are based in different molecular disruptions. Specifically, ensconsin (DrosophilaMAP7) regulates the number of growing microtubules that are used to move nuclei whereas bocksbeutel (Drosophilaemerin) and klarsicht (DrosophilaKASH-protein regulate interactions between nuclei.

Background Hospital-associated infections (HAI) such as methicillin-resistant Staphylococcus aureus (MRSA) can have devastating consequences. The World Health Organization created the 5 moments for hand hygiene. It was identified in the neonatal intensive care unit (NICU) pod setting that health care workers did not always recognize opportunities due to workflow complexities. It was hypothesized that introducing hand hygiene simulations would increase hand hygiene awareness which would decrease prevalence of HAI MRSA screen positive NICU infants. Methods This was a pre/post study performed in a level 4 NICU with 54 beds from February 2018 through November 2019. Participants included 146 nurses, 30 physicians, 18 respiratory therapists, and 5 additional therapists. In January 2019, each discipline created a scenario which guided the participant through a clinical situation and monitored opportunities for hand hygiene. Simulations were carried out in empty pods in the NICU to closely mimic actual working conditions. MRSA screening was performed via nasal MRSA PCR or culture with testing of infants born outside the hospital on admission and routine testing of all infants every two weeks. The rate of MRSA-positive infants' pre-intervention and post-intervention was obtained, and a chi-squared test was utilized to compare the rates and determine statistical significance (p-value Results In the 11 months prior to the intervention, there were 13 infants with positive HAI MRSA screens across 11,010 patient days (1 per 847). In the subsequent 11 months, there were 6 infants with positive HAI MRSA screens across 12,191 patient days (1 per 2,032) When comparing these two rates, the p-value is 0.067. Conclusions We observed a decrease in the rate of infants with positive HAI MRSA screens following our introduction of hand hygiene simulations although that difference did not reach statistical significance. The fact that the scenarios were created by frontline care providers was one of the keys to success.

Gemellais a genus of Gram-positive bacteria found in the digestive tract of humans. They rarely cause systemic illness but have been recently implicated in several serious infections. We report infective endocarditis caused byGemella bergeriin a 23-year-old with a bicuspid aortic valve status post-intervention in infancy.

Drosophila is used as a model system to show that the common phenotype of mispositioned nuclei occurs via distinct mechanisms in Emery–Dreifuss muscular dystrophy and centronuclear myopathy., Muscle cells are a syncytium in which the many nuclei are positioned to maximize the distance between adjacent nuclei. Although mispositioned nuclei are correlated with many muscle disorders, it is not known whether this common phenotype is the result of a common mechanism. To answer this question, we disrupted the expression of genes linked to Emery–Dreifuss muscular dystrophy (EDMD) and centronuclear myopathy (CNM) in Drosophila and evaluated the position of the nuclei. We found that the genes linked to EDMD and CNM were each necessary to properly position nuclei. However, the specific phenotypes were different. EDMD-linked genes were necessary for the initial separation of nuclei into distinct clusters, suggesting that these factors relieve interactions between nuclei. CNM-linked genes were necessary to maintain the nuclei within clusters as they moved toward the muscle ends, suggesting that these factors were necessary to maintain interactions between nuclei. Together these data suggest that nuclear position is disrupted by distinct mechanisms in EDMD and CNM.

Background: Body mass index (BMI) is widely accepted in determining obesity. Skinfold thickness measurements have been commonly used to determine percentage of body fat. Hypothesis: The authors hypothesize that because BMI does not measure fat directly but relies on body weight alone, a large percentage of athletic adolescents will be misclassified as obese by BMI. Design: Cross-sectional study. Methods: To compare BMI and skinfold measurements as indicators for obesity in the adolescent athletic population, anthropometric data (height, weight, percentage body fat, age, and sex) were recorded from 33 896 student athletes (average age, 15 years; range, 11-19 years) during preparticipation physical examinations from 1985 to 2003. BMI was calculated from height and weight. Percentage of body fat was determined by measuring skinfold thickness. Results: According to their BMI percentile, 13.31% of adolescent athletes were obese. Using the skinfold method, only 5.95% were obese. Of those classified as obese by the BMI, 62% were considered false positives by the skinfold method. In contrast, there was a 99% probability that the nonobese by BMI would not be obese by the skinfold method (negative predictive value = 0.99). Conclusions: BMI is a measurement of relative body weight, not body composition. Because lean mass weighs far more than fat, many adolescent athletes are incorrectly classified as obese based on BMI. Skinfold testing provides a more accurate body assessment than BMI in adolescent athletes. Clinical Relevance: Correct body composition data can help to provide better diet and activity guidelines and prevent the psychological problems associated with being labeled as obese.