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INTRODUCTION: The easiest way to prevent noise-induced hearing loss (NIHL) is to wear earplugs. The Republic of Korea (ROK) Ministry of National Defense (MND) is supplying earplugs to prevent NIHL, but many patients still suffer from this. We speculated that earplugs would have a high NIHL rate, depending on the rate of use of earplugs, regardless of the rate of supply. Therefore, we conducted this study to investigate the relationship between the use of earplugs and hearing loss by ROK military personnel. METHODS: The study used data from the Military Health Survey conducted in 2014–2015, which included 13 470 questionnaires completed by ROK military personnel. Hearing loss and earplug use were self-reported. Logistic regression analysis was used to assess associations between earplug use and hearing loss. RESULTS: The study sample included 13 470 ROK military personnel (response rate of 71.2%) (Army, 8330 (61.8%); Navy/Marines, 2236 (16.6%); and Air Force, 2904 (21.6%)). Overall, 18.8% of Korean military personnel reported that they always wore earplugs, and 2.8% reported hearing loss. In logistic regression analysis, there were significant differences in the rates of hearing loss associated with wearing earplugs sometimes (OR=1.48, 95% CI 1.07 to 2.05) and never wearing earplugs (OR=1.53, 95% CI 1.12 to 2.10). In subgroup analysis, in Air Force, non-combat branch, forward area and long-term military service personnel increased hearing loss was associated with not wearing earplugs. CONCLUSION: Our study confirmed that within the ROK military, there is an association between hearing loss and lack of earplug use. In the ROK MND, Army, Navy/Marines and Air Force headquarters must provide guidelines for the use of earplugs during field training to protect military personnel's hearings and, if necessary, need to be regulated or institutionalised.

The electronic structure of SrPd2Ge2 single crystals is studied by angle-resolved photoemission spectroscopy (ARPES), scanning tunneling spectroscopy (STS), and band structure calculations within the local-density approximation (LDA). The STS measurements show a single s-wave superconducting energy gap (0) = 0.5 meV. The photon-energy dependence of the observed Fermi surface reveals a strongly three-dimensional character of the corresponding electronic bands. By comparing the experimentally measured and calculated Fermi velocities a renormalization factor of 0.95 is obtained, which is much smaller than typical values reported in Fe-based superconductors. We ascribe such an unusually low band renormalization to the different orbital character of the conduction electrons and, using ARPES and STS data, argue that SrPd2Ge2 is likely to be a conventional superconductor, which makes it clearly distinct from isostructural iron pnictide superconductors of the "122" family ; This work was supported by the DFG priority program SPP1458, Grants No. KN393/4, BO1912/2-1, and No. BO3537/1-1 (D.S.I. and J.T.P.); by the Slovak Research and Development Agency under Contract No. VVCE-0058-07, Slovak VEGA Grants No. 0148/10 and No. 1/0138/10, and the 7th FP MNT-ERA.Net II. ESO (T.S., P.S., J.G.R, and P.S.); by the Spanish MEC under projects Consolider Ingenio Molecular Nanoscience CSD2007-00010 and FIS2008-00454 (J.G.R.); and by the Korean government (MEST) Grants No. R15-2008-006-01002-0 and 2011-0028736 (N.H.S., B.K.C.)

Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD.