, or the specialty as a whole.

The supply of radiation oncology residency positions now far exceeds demand by graduating US medical students. Efforts to nullify a market correction revealed by medical student behavior via continued reliance on the SOAP to fill historical levels of training positions may not be in the best of interest of trainees, individual programs, or the specialty as a whole.Type 1 diabetic animal models, generated by injecting streptozotocin (STZ), have been widely used in research. We previously reported that juvenile-onset diabetes mellitus (JDM) rats, which were prepared by administering STZ to 17-day-old rats, developed cognitive impairments and hippocampal synaptic plasticity deficiencies, which were restored by glucagon-like peptide-1 (GLP-1). GLP-1 and GLP-2 are simultaneously derived from proglucagon and act through their own specific receptors. The present study was performed to investigate the potential of GLP-2 in JDM rats. The results obtained demonstrated that GLP-2 restored impairments in spatial working memory and hippocampal long-term depression (LTD) in JDM rats, and that the MEK1/2 inhibitor, U0126, inhibited this recovery. Therefore, GLP-2 has potential in the treatment of cognitive deficits in childhood-onset diabetes.The coronavirus disease 2019 (COVID-19) pandemic resulted in a surge of research activity. Since its outset, efforts have been made to guide the rapid generation of research in medicine. There are gaps in some areas of rehabilitation research for patients with COVID-19. The development of a specific research framework might serve to help monitor the status of research (mapping), shape and strengthen research by pointing to under-investigated areas, and promote rehabilitation research in this context. This article introduces and discusses the COVID-19 Rehabilitation Research Framework (CRRF) and presents the methodology used for its development. The questions have been developed among the World Health Organization (WHO) Rehabilitation Programme, Cochrane Rehabilitation, and the experts of its Rehabilitation-COVID-19 Evidence-based Response Action International Multiprofessional Steering Committee. The framework is divided into 2 parts and includes 20 questions organized in 4 groups epidemiology, and evidence at the micro- (individual), meso- (health services), and macro- (health systems) levels. The CRRF offers a comprehensive view of the research areas relevant to COVID-19 and rehabilitation that are necessary to inform best practice and ensure rehabilitation services and health systems can best serve the population with COVID-19. The collaboration between Cochrane Rehabilitation and the WHO Rehabilitation Programme in establishing the CRRF brought together perspectives from the health systems, health management, and clinical evidence. The authors encourage researchers to use the CRRF when planning studies on rehabilitation in the context of COVID-19.

To systematically review the association between ulnar nerve hypermobility (UNH) at the elbow and ulnar neuropathy (UNE).

Cumulative Index to Nursing and Allied Health, MEDLINE, and Embase databases were searched for English language studies published up to July 4, 2020.

We included case-control, cohort, and randomized controlled studies that established the presence or absence of UNH and UNE. Twenty out of 654 studies identified met the inclusion criteria.

Two reviewers independently extracted data for analysis. Risk of bias and applicability were assessed with the QUADAS-2 tool.

We compared rates of UNH between patients diagnosed with and without UNE and found no significant difference. The meta-analysis pooled rate of UNH was 0.37 (95% confidence interval, 0.20-0.57) for those without UNE and 0.33 (95% confidence interval, 0.23-0.45) for those with UNE.

The clinical finding of UNH is unhelpful when assessing for UNE, as the presence of UNH does not make the diagnosis of UNE more likely.

The clinical finding of UNH is unhelpful when assessing for UNE, as the presence of UNH does not make the diagnosis of UNE more likely.The accuracy of brain age estimates from magnetic resonance (MR) images has improved with the advent of deep learning artificial intelligence (AI) models. However, most previous studies on predicting age emphasized aging from childhood to adulthood and old age, and few studies have focused on early brain development in children younger than 2 years of age. Here, we performed brain age estimates based on MR images in children younger than 2 years of age using deep learning. Our AI model, developed with one slice each of raw T1- and T2-weighted images from each subject, estimated brain age with a mean absolute error of 8.2 weeks (1.9 months). see more The estimates of our AI model were close to those of human specialists. The AI model also estimated the brain age of subjects with a myelination delay as significantly younger than the chronological age. These results indicate that the prediction accuracy of our AI model approached that of human specialists and that our simple method requiring less data and preprocessing facilitates a radiological assessment of brain development, such as monitoring maturational changes in myelination.The brain electrophysiological component P3, associated with good cognitive abilities, deteriorates during healthy aging. Both cognitive functions and P3 component amplitude respond positively to exercise, but the effects of resistance training on P3 are much less studied. Short-term resistance training interventions in older adults indicate modulation towards larger P3 amplitude, but this association has not been studied with a longitudinal study design. We investigated magnetoencephalographically recorded P3 (P3m) in a unique study design of nine aged men (mean age 77.7 y) with quasi-supervised resistance training background over a 10-year period and eight controls of similar age (mean age 77.5 y) with no training background. We elicited P3m utilizing lower limb electrical stimulation, as the resistance training program was mostly directed to lower limbs. Somatosensory oddball paradigm was performed with the right foot’s fourth toe as standard (90%) and hallux as deviant (10%). Participants were asked to respond to deviants with a button press using their left index finger.