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Eight weeks of curcumin supplementation and endurance training, whether done separately or simultaneously, significantly reduced fasting blood glucose, glycosylated hemoglobin and serum insulin levels (P<0.05). The combination of curcumin supplementation and endurance training compared to the other two interventions caused a significant further decrease in these glycemic indexes (P<0.05).

The findings of this study showed that eight weeks of curcumin supplementation and endurance training helped each other in improving the glycemic indexes of women with type 2 diabetes.

The findings of this study showed that eight weeks of curcumin supplementation and endurance training helped each other in improving the glycemic indexes of women with type 2 diabetes.

A wide variety of psychiatric conditions are associated with social cognitive deficits. The relationship between social cognition and many factors, especially executive functions (EF), has been examined, but there is no study examining sleep and social cognition in children with attention deficit activity disorder (ADHD). It is important to find new approaches and intervention areas to improve their social cognitive skills. The main hypothesis of our study was that sleep disturbance would predict lower social cognition scores. We hypothesized that sleep disturbances and EF impairment could predict lower social cognitive performance.

Eighty-five children aged 7-12 years with drug-naïve ADHD were included in the study. Reading the Mind in the Eyes Test (RMET) and Faux Pas Recognition Test (FPRT) were used for social cognition performance; Stroop test was used for executive function performance. Sleep disturbance was evaluated with Children's Sleep Habits Questionnaire (CSHQ), ADHD severity with Conners Parethe relationship between sleep and social cognition.

These results showed that sleep disturbance and EF are both associated with social cognitive impairment, sleep particularly with the cognitive component. Identifying sleep problems in children with ADHD may provide helpful information in understanding and treating social cognitive impairments. This study is the first to draw attention to the relationship between sleep and social cognition.This article reports the synthesis of a novel ternary Visible-Light-Driven (VLD) photocatalyst and antibacterial agent. The two-dimensional graphitic carbon nitride nanosheets (g-C3N4 NSs) and 7% molybdenum doped zinc oxide nanoparticles (Mo doped ZnO NPs) were used for the synthesis of the 65% g-C3N4 hybridized with 7% Mo doped ZnO novel ternary nanocomposite (Mo doped ZnO/g-C3N4 ternary NC). The synthesis process, as well as the structures, morphologies, photocatalytic and antibacterial properties of the synthesized ternary NC and constituents, were investigated by using several spectroscopic and microscopic techniques. selleck chemicals llc It was revealed through the Transmission Electron Microscopy (TEM) characterization of the synthesized NC that the Mo doped ZnO NPs were found uniformly embedded upon the well-stacked g-C3N4NSs. It was further discovered by the bandgap analysis that the light absorbance ability of the ternary NC exists in the visible region of the light spectrum. The photocatalytic degradation of the methylene blue (MB) by the use of novel ternary NC in an aqueous medium was analyzed while using Ultra Violet-Visible (UV-Visible) spectroscopy. Trapping experiments of active species during the photodegradation and Electron Spin Resonance (ESR) experiment revealed that the superoxide and hydroxyl radicals were the leading species liable for MB deterioration. The ternary NC exhibited superior photocatalytic performance as compared with binary doped or hybridized nanomaterials (NMs) and mono photocatalysts due to the facility of effective migration and separation of the charge carriers across the (Mo doped ZnO NPs)/g-C3N4 NSs interface of the heterojunction. The increased generation of the reactive oxygen species (ROS), O2-, and •OH radicals the photogenerated charge carriers within the Mo doped ZnO/g-C3N4 NC were found responsible for its enhanced antibacterial performance.Species distribution models (SDMs), in which species occurrences are related to a suite of environmental variables, have been used as a decision-making tool in ecosystem management. Complex machine learning (ML) algorithms that lack interpretability may hinder the use of SDMs for ecological explanations, possibly limiting the role of SDMs as a decision-support tool. To meet the growing demand of explainable MLs, several interpretable ML methods have recently been proposed. Among these methods, SHaply Additive exPlanation (SHAP) has drawn attention for its robust theoretical justification and analytical gains. In this study, the utility of SHAP was demonstrated by the application of SDMs of four benthic macroinvertebrate species. In addition to species responses, the dataset contained 22 environmental variables monitored at 436 sites across five major rivers of South Korea. A range of ML algorithms was employed for model development. Each ML model was trained and optimized using 10-fold cross-validation. Model evaluation based on the test dataset indicated strong model performance, with an accuracy of ≥0.7 in all evaluation metrics for all MLs and species. However, only the random forest algorithm showed a behavior consistent with the known ecology of the investigated species. SHAP presents an integrated framework in which local interpretations that incorporate local interaction effects are combined to represent the global model structure. Consequently, this framework offered a novel opportunity to assess the importance of variables in predicting species occurrence, not only across sites, but also for individual sites. Furthermore, removing interaction effects from variable importance values (SHAP values) clearly revealed non-linear species responses to variations in environmental variables, indicating the existence of ecological thresholds. This study provides guidelines for the use of a new interpretable method supporting ecosystem management.

Midwives play an important role in health promotion and prevention of alcohol-related harm, but previous research has suggested that although most midwives report advising on abstinence, evidence exist that women are informed that "some" alcohol is not harmful. The aim of this qualitative study was to explore midwives' views on implementation of the 2016 Chief Medical Officers' alcohol guidelines in antenatal care in the UK.

Focus groups and individual interviews with 22 midwives working in maternity and educational settings in the UK were conducted either in person or over telephone. Data were subjected to thematic analysis.

Conflict between guidelines from different sources and lack of knowledge of the abstinence advice issued in the Guidelines were barriers to discussing abstinence. Communication with women and building relationships were key facilitators supporting alcohol discussions. How alcohol was addressed appeared to vary across the UK with no uniform approach. Building a trusted relationship are provided support to change unhealthy behaviours.

Patients with chronic stroke have reduced capacity for performing activities of daily living (ADLs) and are at increased risk for falls during walking due to long-term changes to muscle tone and force, as well as movement control.

To investigate the efficacy of lateral stair walking training on muscle strength of affected lower extremities, balance, ADLs, and gait ability in patients with chronic stroke.

The experimental group received 15 min of lateral stair walking exercise along with 15 min of traditional physiotherapy, whereas the control group received only traditional physiotherapy for 30 min. Both groups received the intervention once a week for 12 weeks. Outcome measurements included muscle strength, postural assessment scale for stroke patients (PASS), Fugal-Meyer assessment for lower extremity (FMA-LE), Barthel index (BI), timed up and go test (TUG), and the gait parameters which were determined by the Reha-Watch system.

A total of 24 participants completed the study. The experimental group eral stair walking training into clinical rehabilitation programs. Lateral stair walking training in patients with chronic stroke can be used as an effective treatment to improve gait, balance performance, and ADLs.The brain electrical activity, recorded and materialized as electroencephalogram (EEG) signals, is known to be very useful in the diagnosis of brain-related pathology. However, manual examination of these EEG signals has various limitations, including time-consuming inspections, the need for highly trained neurologists, and the subjectiveness of the evaluation. Thus, an automated EEG pathology detection system would be helpful to assist neurologists to enhance the treatment procedure by making a quicker diagnosis and reducing error due to the human element. This work proposes the application of a time-frequency spectrum to convert the EEG signals onto the image domain. The spectrum images are then applied to the Convolutional Neural Network (CNN) to learn robust features that can aid the automatic detection of pathology and normal EEG signals. Three popular CNN in the form of the DenseNet, Inception-ResNet v2, and SeizureNet were employed. The extracted deep-learned features from the spectrum images are then passed onto the support vector machine (SVM) classifier. The effectiveness of the proposed approach was assessed using the publicly available Temple University Hospital (TUH) abnormal EEG corpus dataset, which is demographically balanced. The proposed SeizureNet-SVM-based system achieved state-of-the-art performance accuracy, sensitivity, and specificity of 96.65%, 90.48%, and 100%, respectively. The results show that the proposed framework may serve as a diagnostic tool to assist clinicians in the detection of EEG pathology for early treatment.

Multiple sclerosis (MS) is a neurodegenerative disease that affects the central nervous system, especially the brain, spinal cord, and optic nerve. Diagnosis of this disease is a very complex process and generally requires a lot of time. In addition, treatments are applied without any information on the disability course in each MS patient. For these two reasons, the objective of this study was to improve the MS diagnosis and predict the long-term course of disability in MS patients based on clinical data and retinal nerve fiber layer (RNFL) thickness, measured by optical coherence tomography (OCT).

A total of 104 healthy controls and 108 MS patients, 82 of whom had a 10-year follow-up, were enrolled. Classification algorithms such as multiple linear regression (MLR), support vector machines (SVM), decision tree (DT), k-nearest neighbours (k-NN), Naïve Bayes (NB), ensemble classifier (EC) and long short-term memory (LSTM) recurrent neural network were tested to develop two predictive models MS diagnosis mand predict the course of MS. This advance could help clinicians select more specific treatments for each MS patient. Therefore, our findings underscore the potential of RNFL thickness as a reliable MS biomarker.This study investigated the effects of l-arginine and l-lysine on the water holding capacity, shear force, color, and protein denaturation of frozen porcine Longissimus lumborum. Four batches were prepared, each corresponding to samples of an experimental treatment without a cryoprotective solution, injecting a 0.3% sodium tripolyphosphate and 0.5% NaCl solution, a 0.5% l-arginine solution, or a 0.5% l-lysine solution. The results showed that both l-arginine and l-lysine decreased thawing loss, cooking loss, shear force, L⁎ values, b⁎ values, and surface hydrophobicity, but they increased pH values, a⁎ values, percentages of peak areas for T21 relaxation times, and Ca2+-ATPase activity. Additionally, both histological and transmission electron microscopy images showed that l-lysine, and especially l-arginine could inhibit the formation of gaps between fiber bundles, alleviate the disruption of intracellular spaces, and maintain the structural integrity of sarcomeres. Overall, the results showed that both l-arginine and l-lysine hindered the structural damage of muscle fibers during freezing and protected myofibrillar proteins from denaturation, ultimately contributing to superior quality attributes.