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Posttranscriptional regulation by microRNA (miRNA) facilitates exercise and diet-induced skeletal muscle adaptations. However, the impact of diet on miRNA expression during postexercise recovery remains unclear. The objective of this study was to examine the effects of consuming carbohydrate or a nutrient-free control on skeletal muscle miRNA expression during 3 h of recovery from aerobic exercise. Using a randomized, crossover design, seven men (means ± SD, age: 21 ± 3 yr; body mass: 83 ± 13 kg; V̇o

While a growing body of evidence suggests youth with autism are at increased risk of experiencing a mental health crisis, no study has screened for crises in an outpatient setting. The current study fills this gap by examining a) the feasibility and utility of conducting routine crisis screenings; b) the psychometrics of a brief crisis screener (the Mental Health Crisis Assessment Scale-Revised; MCAS-R); and, c) the prevalence of and types of behaviors associated with crises.This study was conducted at two different outpatient mental health clinics. Screenings were conducted using the MCAS-R, a 23-item parent report measure. A total of 406 youth with autism (76% Male; 72% White; M = 11.2y; SD = 3.5y), evenly divided across clinics, were screened. Seven clinicians conducted a clinical visit, which incorporated the results of the MCAS-R, to determine whether the child was in crisis.Eighty percent of youth were successfully screened, suggesting crisis screening is feasible. Most parents (73%) felt the MCAS-R helped communicate concerns with the clinician; few (6%) felt the survey was too long or upsetting. All clinicians (100%) indicated that the MCAS-R was very helpful in facilitating communication and identifying/mitigating safety concerns; although, 33% reported screenings "sometimes" interrupted clinical flow. The MCAS-R strongly aligned with clinician ratings (88% correctly classified). Twenty percent of youth met the cutoff for crisis; aggression and self-injurious behaviors were the most common reasons for crises.This study suggests that outpatient crisis screening via the MCAS-R is feasible, accurate, and well received by parents and clinicians.ASD: Autism Spectrum Disorder; MCAS-R: Mental Health Assessment Crisis Scale-Revised; DSM-5: Diagnostic and Statistical Manual, 5

MicroRNAs (miRNAs) regulate molecular processes governing muscle metabolism. Physical activity and energy balance influence both muscle anabolism and substrate metabolism, but whether circulating and skeletal muscle miRNAs mediate those effects remains unknown. This study assessed the impact of sustained physical activity with participants in energy balance (BAL) or deficit (DEF) on circulating and skeletal muscle miRNAs. Using a randomized cross-over design, 10 recreational active healthy males (mean ± SD, 22 ± 5 years, 87 ± 11 kg) completed 72 h of high aerobic exercise-induced energy expenditures in BAL (689 ± 852 kcal/day) or DEF (-2047 ± 920 kcal/day). Blood and muscle samples were collected under rested/fasted conditions before (PRE) and immediately after 120 min load carriage exercise bout at the end (POST) of the 72 h. Trials were separated by 7 days. Circulating and skeletal muscle miRNAs were measured using microarray RT-qPCR. Independent of energy status, 36 circulating miRNAs decreased (P 0.05), while 10 miRNAs increased and three miRNAs decreased in skeletal muscle (P 0.05) at POST compared to PRE. Of these, miR-122-5p, miR-221-3p, miR-222-3p and miR-24-3p decreased in circulation and increased in skeletal muscle. Two circulating (miR-145-5p and miR-193a-5p) and four skeletal muscle (miR-21-5p, miR-372-3p, miR-34a-5p and miR-9-5p) miRNAs had time-by-treatment effects (P 0.05). These data suggest that changes in miRNA profiles are more sensitive to increased physical activity compared to energy status, and that changes in circulating miRNAs in response to high levels of daily aerobic exercise are not reflective of changes in skeletal muscle miRNAs. KEY POINTS: Circulating and skeletal muscle miRNA profiles are more sensitive to high levels of aerobic exercise-induced energy expenditure compared to energy status. Changes in circulating miRNA in response to high levels of daily sustained aerobic exercise are not reflective of changes in skeletal muscle miRNA.

Small- and medium-sized enterprises (SMEs) can have significant resources, capacities, and influence in their communities, suggesting they have the potential to be agents for transformative sustainability. However, SMEs will need to move beyond firm-centered sustainable business practices towards strategic approaches that encompass and contribute to resilience-building processes. Amid the unfolding COVID-19 pandemic, we explored what types of sustainable business practices of SMEs can contribute to individual, organizational, and community resilience. We identified six clusters of practice that are important in this regard. The clusters are not solely technical or “environmental” but rather illustrative of deeper sustainable values shaped by organizational structure, culture, and behavior. This paper suggests that SMEs can pursue transformative approaches to sustainability that are more environmentally, socially, and economically sustainable and better able to withstand shocks like the COVID-19 pandemic and can be significant contributors to community resilience. We conclude with a series of future research priorities critical to examine a largely unexplored nexus in the private sector, the linkages and dynamics between sustainability practice, resilience building, and broader community pathways.

Purpose The incidence of inguinal hernia is higher in elderly because of aging-related diseases like prostatism, bronchitis, collagen laxity. A conservative management is common in elderly to reduce surgery-related risks, however watchful waiting can expose to obstruction and strangulation. The aim of the present study was to assess the impact of emergency surgery in a large series of elderly with complicated groin hernia and to identify the independent risk factors for postoperative morbidity and mortality. The predictive performance of prognostic risk scores has been also assessed. Methods This is a prospective observational study carried out between January 2017 and June 2018 in elderly patients who underwent emergency surgery for complicated hernia in 38 Italian hospitals. Pre-operative, surgical and postoperative data were recorded for each patient. ASA score, Charlson’s comorbidity index, P-POSSUM and CR-POSSUM were assessed. Results 259 patients were recruited, mean age was 80 years. A direct repair without mesh was performed in 62 (23.9%) patients. Explorative laparotomy was performed in 56 (21.6%) patients and bowel resection was necessary in 44 (17%). Mortality occurred in seven (2.8%) patients. Fifty-five (21.2%) patients developed complications, 12 of whom had a major one. At univariate and multivariate analyses, Charlson’s comorbidity index ≥ 6, altered mental status, and need for laparotomy were associated with major complications and mortality Conclusion Emergency surgery for complicated hernia is burdened by high morbidity and mortality in elderly patients. Preoperative comorbidity played a pivotal role in predicting complications and mortality and therefore Charlson’s comorbidity index could be adopted to select patients for elective operation

While advanced diffusion techniques have been found valuable in many studies, their clinical availability has been hampered partly due to their long scan times. Moreover, each diffusion technique can only extract a few relevant microstructural features. Using multiple diffusion methods may help to better understand the brain microstructure, which requires multiple expensive model fittings. In this work, we compare deep learning (DL) approaches to jointly estimate parametric maps of multiple diffusion representations/models from highly undersampled q-space data.We implement three DL approaches to jointly estimate parametric maps of diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and multi-compartment spherical mean technique (SMT). A per-voxel q-space deep learning (1D-qDL), a per-slice convolutional neural network (2D-CNN), and a 3D-patch-based microstructure estimation with sparse coding using a separable dictionary (MESC-SD) network are considered.The accuracy of estimated diffusion maps depends on the q-space undersampling, the selected network architecture, and the region and the parameter of interest. The smallest errors are observed for the MESC-SD network architecture (less than 10Our experiments show that DL methods are very efficient tools to simultaneously estimate several diffusion maps from undersampled q-space data. These methods can significantly reduce both the scan (