Military training increases tibial density and size. Female sex hormones may influence the adaption of bone to loading, but it is unknown if women using different hormonal contraceptives adapt similarly to military training. One hundred and sixteen women (57 women not using hormonal contraceptives [non-users], 38 combined oral contraceptive pill [COCP] users, 21 depot medroxyprogesterone acetate [DMPA] users) completed this study. Tibial volumetric bone mineral density (vBMD) and geometry were measured by peripheral quantitative computed tomography (4 %, 14 %, 38 %, and 66 % sites) at the start (week 1) and end (week 14) of British Army basic training. Circulating markers of bone and calcium metabolism were measured at weeks 1, 2, 4, 6, 10, and 14. Training increased trabecular vBMD at the 4 % site, periosteal perimeter at the 14 % and 66 % sites, and total area, cortical area, cortical thickness, and bone strength at all sites (0.1 to 1.6 %, p ≤ 0.009), with no differences between hormonal contraceptive groups (p ≥ 0.127). Trabecular vBMD increased at the 14 % site in non-users (0.8 %, p = 0.005), but not in COCP or DMPA users (p ≥ 0.205). Periosteal perimeter increased at the 38 % site in COCP (0.4 %, p < 0.001) and DMPA (0.5 %, p < 0.001) users, but not in non-users (p = 0.058). Training had no effect on periosteal perimeter at the 4 % site or cortical vBMD or endosteal perimeter at any site (p ≥ 0.168). βCTX decreased and PINP increased during training with no difference between hormonal contraceptive groups. Training increased iPTH in non-users, but not COCP or DMPA users. Hormonal contraceptives may exert site-specific effects on the mechanobiology of bone, with higher endogenous oestradiol promoting trabecularisation and inhibiting periosteal expansion in non-users compared with hormonal contraceptive users.
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http://dx.doi.org/10.1016/j.bone.2024.117012 | DOI Listing |
Int J Psychophysiol
December 2024
Department of Psychiatry, University Medical Centre, Utrecht, the Netherlands; Brain Research and Innovation Centre, Ministry of Defence, Utrecht, the Netherlands.
Military personnel often encounter situations that can trigger acute stress, which may affect operational performance. Therefore, it is important to examine stress responses in controlled environments to obtain more insights in performance-influencing effects of acute stress. This study investigated the impact of passive heat exposure combined with virtual combat scenarios on cardiovascular and psychophysiological parameters in a controlled setting.
View Article and Find Full Text PDFBMC Med Educ
December 2024
King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.
Introduction: Recent international consensus statements advocate for the integration of Point-of-Care Ultrasound (PoCUS) into the global undergraduate medical curriculum. Some medical schools outside Saudi Arabia have already incorporated PoCUS into their undergraduate curricula to enhance anatomy, physiology and pathology instruction. However, there are no data on the potential role of PoCUS in the preclinical training of medical students in Saudi Arabia.
View Article and Find Full Text PDFMil Med
December 2024
School of Physical Education-FEF/UNICAMP, State University of Campinas, Campinas, SP 13083-970, Brazil.
Introduction: The present study aimed to identify the physical demands of Brazilian Air Force (BAF) critical Combat Tasks (CTs) and investigate the occurrence of differences in their difficulty perceived ratings, considering aspects such as sex, military experience, and academic degree of the evaluators.
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BMC Med Res Methodol
December 2024
Department of Military Health Statistics, Faculty of Preventive Medicine, Air Force Medical University/Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, Shaanxi, China.
Background: Accurate fasting plasma glucose (FPG) trend prediction is important for management and treatment of patients with type 2 diabetes mellitus (T2DM), a globally prevalent chronic disease. (Generalised) linear mixed-effects (LME) models and machine learning (ML) are commonly used to analyse longitudinal data; however, the former is insufficient for dealing with complex, nonlinear data, whereas with the latter, random effects are ignored. The aim of this study was to develop LME, back propagation neural network (BPNN), and mixed-effects NN models that combine the 2 to predict FPG levels.
View Article and Find Full Text PDFWaste Manag
December 2024
Department of Biomedical Engineering, Military Institute of Science and Technology, Dhaka, Bangladesh. Electronic address:
Efficient waste management is essential to minimizing environmental harm as well as encouraging sustainable progress. The escalating volume and sophistication of waste present significant challenges, prompting innovative methods for effective waste categorization and management. Deep learning models have become highly intriguing tools for automating trash categorization activities, providing effective ways to optimize processes for handling waste.
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