310 research outputs found

    Insulin Responsiveness in Metabolic Syndrome after Eight Weeks of Cycle Training

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    Introduction Insulin resistance in obesity is decreased after successful diet and exercise. Aerobic exercise training alone was evaluated as an intervention in subjects with the metabolic syndrome. Methods Eighteen nondiabetic, sedentary subjects, 11 with the metabolic syndrome, participated in 8 wk of increasing intensity stationary cycle training. Results Cycle training without weight loss did not change insulin resistance in metabolic syndrome subjects or sedentary control subjects. Maximal oxygen consumption (V˙O2max), activated muscle AMP-dependent kinase, and muscle mitochondrial marker ATP synthase all increased. Strength, lean body mass, and fat mass did not change. The activated mammalian target of rapamycin was not different after training. Training induced a shift in muscle fiber composition in both groups but in opposite directions. The proportion of type 2x fibers decreased with a concomitant increase in type 2a mixed fibers in the control subjects, but in metabolic syndrome, type 2x fiber proportion increased and type 1 fibers decreased. Muscle fiber diameters increased in all three fiber types in metabolic syndrome subjects. Muscle insulin receptor expression increased in both groups, and GLUT4 expression increased in the metabolic syndrome subjects. The excess phosphorylation of insulin receptor substrate 1 (IRS-1) at Ser337 in metabolic syndrome muscle tended to increase further after training in spite of a decrease in total IRS-1. Conclusions In the absence of weight loss, the cycle training of metabolic syndrome subjects resulted in enhanced mitochondrial biogenesis and increased the expression of insulin receptors and GLUT4 in muscle but did not decrease the insulin resistance. The failure for the insulin signal to proceed past IRS-1 tyrosine phosphorylation may be related to excess serine phosphorylation at IRS-1 Ser337, and this is not ameliorated by 8 wk of endurance exercise training

    Sexual and social stimuli elicit rapid and contrasting genomic responses

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    Sensory physiology has been shown to influence female mate choice, yet little is known about the mechanisms within the brain that regulate this critical behaviour. Here we examine preference behaviour of 58 female swordtails, Xiphophorus nigrensis, in four different social environments (attractive and unattractive males, females only, non-attractive males only and asocial conditions) followed by neural gene expression profiling. We used a brain-specific cDNA microarray to identify patterns of genomic response and candidate genes, followed by quantitative PCR (qPCR) examination of gene expression with variation in behaviour. Our microarray results revealed patterns of genomic response differing more between classes of social stimuli than between presence versus absence of stimuli. We identified suites of genes showing diametrically opposed patterns of expression: genes that are turned ‘on’ while females interact with attractive males are turned ‘off’ when interacting with other females, and vice versa. Our qPCR results identified significant predictive relationships between five candidate genes and specific mate choice behaviours (preference and receptivity) across females exposed to males, with no significant patterns identified in female or asocial conditions or with overall locomotor activity. The identification of stimulus- and behaviour-specific responses opens an exciting window into the molecular pathways associated with social behaviour and mechanisms that underlie sexual selection

    When a calorie is not just a calorie : Diet quality and timing as mediators of metabolism and healthy aging

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    Funding Information: We thank Dr. Yih-Woei Fridell of the National Institute on Aging for organizing the meeting, as well as the NIA Division of Aging Biology for their support. We thank Dr. Gino Cortopassi for his edits and suggestions. The figures were created with BioRender.com. The Mihaylova lab is supported in part by the NIA (R00AG054760), Office of the NIH Director (DP2CA271361), the American Federation for Aging Research, the V Foundation, Pew Biomedical Scholar award, and startup funds from the Ohio State University. The Delibegovic lab is funded by the British Heart Foundation, Diabetes UK, BBSRC, NHS Grampian, Tenovus Scotland, and the Development Trust (University of Aberdeen). J.J.R. is supported by NIA PO1AG062817, R21AG064290, and R21AG071156. Research support for J.B. was from NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants R01DK127800, R01DK113011, R01DK090625, and R01DK050203 and the National Institute on Aging (NIA) grants R01AG065988 and P01AG011412, as well as the University of Chicago Diabetes Research and Training Center grant P30DK020595. This work was supported by NIH grants AG065992 to G.M. and AG068550 to G.M. and S.P. as well as UAB Startup funds 3123226 and 3123227 to G.M. R.S. is supported by NIH grants RF1AG043517, R01AG065985, R01DK123327, R56AG074568, and P01AG031782. Z.C. is primarily funded by The Welch Foundation (AU-1731-20190330) and NIH/NIA (R01AG065984, R56AG063746, RF1AG061901, and R56AG076144). A.C. is supported by NIA grant R01AG065993. W.W.J. is supported by the NIH (R01DC020031). M.S.-H. is supported by NIH R01 R35GM127049, R01 AG045842, and R21 NS122366. The research in the Dixit lab was supported in part by NIH grants AG031797, AG045712, P01AG051459, AR070811, AG076782, AG073969, and AG068863 and Cure Alzheimer's Fund (CAF). A.E.T.-M. is supported by the NIH/NIA (AG075059 and AG058630), NIAMS (AR071133), NHLBI (HL153460), pilot and feasibility funds from the NIDDK-funded UAB Nutrition Obesity Research Center (DK056336) and the NIA-funded UAB Nathan Shock Center (AG050886), and startup funds from UAB. J.A.M. is supported by the Intramural Research Program, NIA, NIH. The Panda lab is supported by the NIH (R01CA236352, R01CA258221, RF1AG068550, and P30CA014195), the Wu Tsai Human Performance Alliance, and the Joe and Clara Tsai Foundation. The Lamming lab is supported in part by the NIA (AG056771, AG062328, AG061635, and AG081482), the NIDDK (DK125859), startup funds from UW-Madison, and the U.S. Department of Veterans Affairs (I01-BX004031), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government. D.W.L. has received funding from, and is a scientific advisory board member of, Aeovian Pharmaceuticals, which seeks to develop novel, selective mTOR inhibitors for the treatment of various diseases. S.P. is the author of the books The Circadian Code and The Circadian Diabetes Code. Funding Information: We thank Dr. Yih-Woei Fridell of the National Institute on Aging for organizing the meeting, as well as the NIA Division of Aging Biology for their support. We thank Dr. Gino Cortopassi for his edits and suggestions. The figures were created with BioRender.com . The Mihaylova lab is supported in part by the NIA ( R00AG054760 ), Office of the NIH Director ( DP2CA271361 ), the American Federation for Aging Research , the V Foundation , Pew Biomedical Scholar award, and startup funds from the Ohio State University . The Delibegovic lab is funded by the British Heart Foundation , Diabetes UK , BBSRC , NHS Grampian , Tenovus Scotland , and the Development Trust ( University of Aberdeen ). J.J.R. is supported by NIA PO1AG062817 , R21AG064290 , and R21AG071156 . Research support for J.B. was from NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants R01DK127800 , R01DK113011 , R01DK090625 , and R01DK050203 and the National Institute on Aging (NIA) grants R01AG065988 and P01AG011412 , as well as the University of Chicago Diabetes Research and Training Center grant P30DK020595 . This work was supported by NIH grants AG065992 to G.M. and AG068550 to G.M. and S.P., as well as UAB Startup funds 3123226 and 3123227 to G.M. R.S. is supported by NIH grants RF1AG043517 , R01AG065985 , R01DK123327 , R56AG074568 , and P01AG031782 . Z.C. is primarily funded by The Welch Foundation ( AU-1731-20190330 ) and NIH/NIA ( R01AG065984 , R56AG063746 , RF1AG061901 , and R56AG076144 ). A.C. is supported by NIA grant R01AG065993 . W.W.J. is supported by the NIH ( R01DC020031 ). M.S.-H. is supported by NIH R01 R35GM127049 , R01 AG045842 , and R21 NS122366 . The research in the Dixit lab was supported in part by NIH grants AG031797 , AG045712 , P01AG051459 , AR070811 , AG076782 , AG073969 , and AG068863 and Cure Alzheimer's Fund (CAF). A.E.T.-M. is supported by the NIH/NIA ( AG075059 and AG058630 ), NIAMS ( AR071133 ), NHLBI ( HL153460 ), pilot and feasibility funds from the NIDDK -funded UAB Nutrition Obesity Research Center ( DK056336 ) and the NIA -funded UAB Nathan Shock Center ( AG050886 ), and startup funds from UAB . J.A.M. is supported by the Intramural Research Program, NIA, NIH . The Panda lab is supported by the NIH ( R01CA236352 , R01CA258221 , RF1AG068550 , and P30CA014195 ), the Wu Tsai Human Performance Alliance , and the Joe and Clara Tsai Foundation . The Lamming lab is supported in part by the NIA ( AG056771 , AG062328 , AG061635 , and AG081482 ), the NIDDK ( DK125859 ), startup funds from UW-Madison , and the U.S. Department of Veterans Affairs ( I01-BX004031 ), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government.Peer reviewedPostprin

    Pre-Training Muscle Characteristics of Subjects Who Are Obese Determine How Well Exercise Training Will Improve Their Insulin Responsiveness

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    Pre-training muscle characteristics of subjects who are obese determine how well exercise training will improve their insulin responsiveness. J Strength Cond Res 31(3): 798–808, 2017—Only half of prediabetic subjects who are obese who underwent exercise training without weight loss increased their insulin responsiveness. We hypothesized that those who improved their insulin responsiveness might have pretraining characteristics favoring a positive response to exercise training. Thirty nondiabetic subjects who were obese volunteered for 8 weeks of either strength training or endurance training. During training, subjects increased their caloric intake to prevent weight loss. Insulin responsiveness by euglycemic clamps and muscle fiber composition, and expression of muscle key biochemical pathways were quantified. Positive responders initially had 52% higher intermediate muscle fibers (fiber type IIa) with 27% lower slow-twitch fibers (type I) and 23% lower expression of muscle insulin receptors. Whether after weight training or stationary bike training, positive responders\u27 fiber type shifted away from type I and type IIa fibers to an increased proportion of type IIx fibers (fast twitch). Muscle insulin receptor expression and glucose transporter type 4 (GLUT4) expression increased in all trained subjects, but these moderate changes did not consistently translate to improvement in whole-body insulin responsiveness. Exercise training of previously sedentary subjects who are obese can result in muscle remodeling and increased expression of key elements of the insulin pathway, but in the absence of weight loss, insulin sensitivity improvement was modest and limited to about half of the participants. Our data suggest rather than responders being more fit, they may have been less fit, only catching up to the other half of subjects who are obese whose insulin responsiveness did not increase beyond their pretraining baseline

    Study of Flare Assessment in Systemic Lupus Erythematosus Based on Paper Patients.

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    OBJECTIVE: To determine the level of agreement of disease flare severity (distinguishing severe, moderate, and mild flare and persistent disease activity) in a large paper-patient exercise involving 988 individual cases of systemic lupus erythematosus. METHODS: A total of 988 individual lupus case histories were assessed by 3 individual physicians. Complete agreement about the degree of flare (or persistent disease activity) was obtained in 451 cases (46%), and these provided the reference standard for the second part of the study. This component used 3 flare activity instruments (the British Isles Lupus Assessment Group [BILAG] 2004, Safety of Estrogens in Lupus Erythematosus National Assessment [SELENA] flare index [SFI] and the revised SELENA flare index [rSFI]). The 451 patient case histories were distributed to 18 pairs of physicians, carefully randomized in a manner designed to ensure a fair case mix and equal distribution of flare according to severity. RESULTS: The 3-physician assessment of flare matched the level of flare using the 3 indices, with 67% for BILAG 2004, 72% for SFI, and 70% for rSFI. The corresponding weighted kappa coefficients for each instrument were 0.82, 0.59, and 0.74, respectively. We undertook a detailed analysis of the discrepant cases and several factors emerged, including a tendency to score moderate flares as severe and persistent activity as flare, especially when the SFI and rSFI instruments were used. Overscoring was also driven by scoring treatment change as flare, even if there were no new or worsening clinical features. CONCLUSION: Given the complexity of assessing lupus flare, we were encouraged by the overall results reported. However, the problem of capturing lupus flare accurately is not completely solved

    Effects of a refugee elective on medical student perceptions

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    <p>Abstract</p> <p>Background</p> <p>There are growing numbers of refugees throughout the world. Refugee health is a relatively unstudied and rarely taught component of medical education. In response to this need, a Refugee Health Elective was begun. Medical student perceptions toward cultural aspects of medicine and refugee health before and after participation in the elective were measured.</p> <p>Methods</p> <p>Preliminary questionnaires were given to all preclinical students at the academic year commencement with follow-up questionnaires at the refugee elective's conclusion. Both questionnaires examined students' comfort in interacting with patients and familiarity with refugee medical issues, alternative medical practices, and social hindrances to medical care. The preliminary answers served as a control and follow-up questionnaire data were separated into participant/non-participant categories. All preclinical medical students at two Midwestern medical schools were provided the opportunity to participate in the Refugee Health Elective and surveys. The 3 data groups were compared using unadjusted and adjusted analysis techniques with the Kruskall-Wallis, Bonferroni and ANCOVA adjustment. P-values < 0.05 were considered significant.</p> <p>Results</p> <p>408 and 403 students filled out the preliminary and follow-up questionnaires, respectfully, 42 of whom participated in the elective. Students considering themselves minorities or multilingual were more likely to participate. Elective participants were more likely to be able to recognize the medical/mental health issues common to refugees, to feel comfortable interacting with foreign-born patients, and to identify cultural differences in understanding medical/mental health conditions, after adjusting for minority or multilingual status.</p> <p>Conclusion</p> <p>As medical schools integrate a more multicultural curriculum, a Refugee Health Elective for preclinical students can enhance awareness and promote change in attitude toward medical/mental health issues common to refugees. This elective format offers tangible and effective avenues for these topics to be addressed.</p
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