At normal aging, the brain exhibits signs of compromised bioenergetic and increased levels of products of interaction between reactive oxygen/nitrogen species (ROS/RNS) and brain constituents. Under normal conditions, steady-state levels of ATP and ROS/RNS fluctuate in certain ranges providing basis for stable homeostasis. However, from time to time these parameters leave a "comfort zone," and at adulthood, organisms are able to cope with these challenges efficiently, whereas at aging, efficiency of the systems maintaining homeostasis declines. That is very true for the brain due to high ATP demands which are mainly covered by mitochondrial oxidative phosphorylation. Such active oxidative metabolism gives rise to intensive ROS generation as side products. The situation is worsened by high brain level of polyunsaturated fatty acids which are substrates for ROS/RNS attack and production of lipid peroxides. In this review, organization of energetic metabolism in the brain with a focus on its interplay with ROS at aging is discussed. The working hypothesis on aging as a disbalance between oxidative stress and energy provision as a reason for brain aging is proposed. From this point of view, normal age-related physiological decline in the brain functions results from increased disbalance between decrease in capability of the brain to control constantly increased incapability to maintain ROS levels and produce ATP due to amplification of vicious cycles intensification of oxidative stress impairment of energy provision.
  The proportion of women as leading physicians in cardiology in university medicine has stagnated and the share of women in senior positions in cardiology is low compared with other medical specialist fields. Here, we analyze the typical barriers for women as doctors in cardiology and point to issues that make the discipline less attractive for both genders.
 
  In across-sectional study, astandardized online questionnaire was sent to 3873 members of the German Cardiac Society (DGK). Answers from 567 (278women, 289 men) were analyzed, using comparisons between groups, correlation analyses, and tests of normal distribution.
 
  For 47.4% of respondents (52.0%, of women; 42.8%, of men; p = 0.049), training had lasted longer than anticipated. Average monthly gross income (full-time work) differed significantly between women and men as specialists (p = 0.004) and assistant doctors (p = 0.030). Of women, 32.1% had experienced sexual harassment in the workplace. The main arguments against acareer in university medicinogy, more targeted support should be provided to young doctors and more flexibility introduced into work.Parasitoses are a frequent occurrence in pediatric consultations in both hospitals and private practices. Responsible for this are parasites that permanently infest human skin, such as Sarcoptes scabiei hominis and Pediculus humanus capitis (persistent parasites) as well as those that only attack the skin for feeding, such as Pulex irritans, Cimex lectularius und Neotrombicula autumnalis (transient parasites). The main symptom of parasitoses is pruritus, which is caused by a delayed allergic reaction to proteins in the saliva of the parasites. In some parasitoses, such as scabies, the pruritus is typical, occurs particularly at night and is associated with a considerable impairment in the quality of life due to the resulting lack of sleep, whereas the pruritus is often absent in the case of pediculosis capitis. In this article persistent and transient parasitoses are characterized based on the patient history, morphology and symptoms.
  To compare rib fracture detection and classification by radiologists using CT images with and without a deep learning model.
 
  A total of 8529 chest CT images were collected from multiple hospitals for training the deep learning model. The test dataset included 300 chest CT images acquired using a single CT scanner. The rib fractures were marked in the bone window on each CT slice by experienced radiologists, and the ground truth included 861 rib fractures. We proposed a heterogeneous neural network for rib fracture detection and classification consisting of a cascaded feature pyramid network and a classification network. The deep learning-based model was evaluated based on the external testing data. The precision rate, recall rate, F1-score, and diagnostic time of two junior radiologists with and without the deep learning model were computed, and the Chi-square, one-way analysis of variance, and least significant difference tests were used to analyze the results.
 
  The use of the deep learning model increased detection recall and classification accuracy (0.922 and 0.863) compared with the radiologists alone (0.812 vs.  https://www.selleckchem.com/products/fht-1015.html  0.850). The radiologists achieved a higher precision rate, recall rate, and F1-score for fracture detection when using the deep learning model, at 0.943, 0.978, and 0.960, respectively. When using the deep learning model, the radiologist's reading time was decreased from 158.3 ± 35.7s to 42.3 ± 6.8s.
 
  Radiologists achieved the highest performance in diagnosing and classifying rib fractures on CT images when assisted by the deep learning model.
 Radiologists achieved the highest performance in diagnosing and classifying rib fractures on CT images when assisted by the deep learning model.
  This is an update of the results from the previous report of the CORONADO (Coronavirus SARS-CoV-2 and Diabetes Outcomes) study, which aims to describe the outcomes and prognostic factors in patients with diabetes hospitalised for coronavirus disease-2019 (COVID-19).
 
  The CORONADO initiative is a French nationwide multicentre study of patients with diabetes hospitalised for COVID-19 with a 28-day follow-up. The patients were screened after hospital admission from 10 March to 10 April 2020. We mainly focused on hospital discharge and death within 28days.
 
  We included 2796 participants 63.7% men, mean age 69.7 ± 13.2years, median BMI (25th-75th percentile) 28.4 (25.0-32.4) kg/m
  . Microvascular and macrovascular diabetic complications were found in 44.2% and 38.6% of participants, respectively. Within 28days, 1404 (50.2%; 95% CI 48.3%, 52.1%) were discharged from hospital with a median duration of hospital stay of 9 (5-14) days, while 577 participants died (20.6%; 95% CI 19.2%, 22.2%). In multivariable models, younger age, routine metformin therapy and longer symptom duration on admission were positively associated with discharge.