Examining the psychometric characteristics of the metacognition questionnaire in teaching: a cross-sectional study.

Background: The role of metacognition as a common concept in education is undeniable. One of the challenges in the field of metacognition is to measure the impact of metacognition in teaching with practical tools. Therefore, this study aimed to investigate the psychometric characteristics of the metacognition questionnaire in teaching. Methods: In this cross-sectional study, the statistical population of the study included all teachers in 2020 which was selected by an available sampling method of 137 people. The data were collected using a teacher's metacognition questionnaire (TMI). A Confirmatory, Pearson correlation coefficient was used to analyze the data. For this purpose, the use of SPSS-25 and LISREL software has been used. Results: of exploratory and confirmatory factor analysis indicate that. The validity and retest of the total score were calculated to be 0.93 and 0.86, respectively. The credibility of its subscales was also acceptable. Conclusion: As a result, it can be stated that the questionnaire has the proper psychometric properties for use in Iranian society and can be used as a valid tool for identifying teachers with teaching problems and teaching methods.

Reducing symptoms of attention deficit/hyperactivity disorder (ADHD) in elementary students: the effectiveness of neurofeedback.

Introduction and importance: This research was conducted to investigate the effectiveness of neurofeedback on the symptoms of hyperactivity and attention deficit in primary school students with attention deficit/hyperactivity disorder (ADHD) disorder. Case presentation: The present study utilized a randomized clinical trial with pre-test and post-test measurements and included a control group. The research population included all primary school students with ADHD in 2023; 50 of these children were selected as the experimental group based on the accessible sampling method, and 50 were also included in the control group. Neurofeedback treatment sessions for the experimental group were 30 sessions. Research data were collected in three stages: pre-test and post-test, using a questionnaire based on the Conners rating scale from parents. SPSS-25 analyzed the data. Clinical discussion: The results showed that neurofeedback is associated with significant effectiveness in the symptoms of attention deficit disorder and hyperactivity of students (P<0.05). Conclusion: Based on the findings of this research, it can be said that neurofeedback treatment is effective in reducing attention deficit and hyperactivity symptoms of students with ADHD disorder. It is suggested to widely use neurofeedback to reduce the symptoms of attention deficit and hyperactivity disorder.

Unveiling the neuro-cognitive paradigm: a new approach to the treatment of anxiety: a comprehensive review.

This study aimed to explore the neuro-cognitive paradigm in anxiety diseases by integrating neurobiological and cognitive perspectives. The ideal was to enhance our understanding of the complex interplay between neural and cognitive processes in anxiety and its counteraccusations for treatment. A comprehensive review of the literature was conducted, examining studies that delved into the neurobiological supplements and cognitive impulses in anxiety. The findings revealed the involvement of brain regions similar to the amygdala, prefrontal cortex, and hippocampus in anxiety diseases, along with dysregulation in neurotransmitter systems. Cognitive impulses, including attentional bias towards trouble, interpretation bias, and memory impulses, were constantly observed in individuals with anxiety. The results stressed the bidirectional relationship between neurobiology and cognition, demonstrating that neurobiological factors impact cognitive processes, and cognitive factors modulate neural exertion. Integrated interventions targeting both neurobiological and cognitive factors showed a pledge in treating anxiety diseases. The study linked gaps in the literature and emphasized the significance of considering artistic factors and developing individualized treatment approaches. Overall, this study contributes to a comprehensive understanding of anxiety diseases and informs unborn exploration and clinical practice.

Exploring emotional intelligence in artificial intelligence systems: a comprehensive analysis of emotion recognition and response mechanisms.

This study aims to dissect the current state of emotion recognition and response mechanisms in artificial intelligence (AI) systems, exploring the progress made, challenges faced, and implicit operations of integrating emotional intelligence into AI. This study utilized a comprehensive review approach to investigate the integration of emotional intelligence (EI) into artificial intelligence (AI) systems, concentrating on emotion recognition and response mechanisms. The review process entailed formulating research questions, systematically searching academic databases such as PubMed, Scopus, and Web of Science, critically evaluating relevant literature, synthesizing the data, and presenting the findings in a comprehensive format. The study highlights the advancements in emotion recognition models, including the use of deep literacy ways and multimodal data emulsion. It discusses the challenges in emotion recognition, similar to variability in mortal expressions and the need for real-time processing. The integration of contextual information and individual traits is emphasized as enhancing the understanding of mortal feelings. The study also addresses ethical enterprises, similar as sequestration and impulses in training data. The integration of emotional intelligence into AI systems presents openings to revise mortal-computer relations. Emotion recognition and response mechanisms have made significant progress, but challenges remain. Unborn exploration directions include enhancing the robustness and interpretability of emotion recognition models, exploring cross-cultural and environment-apprehensive emotion understanding, and addressing long-term emotion shadowing and adaption. By further exploring emotional intelligence in AI systems, further compassionate and responsive machines can be developed, enabling deeper emotional connections with humans.

Quality of life and depression in patients with Parkinson's disease: effectiveness of group cognitive-behavioral therapy: a randomized controlled study.

Background: Group cognitive-behavioral therapy has demonstrated its effectiveness in treating various psychological disorders. Nevertheless, there is insufficient evidence supporting its application in enhancing both the quality of life and depression among Parkinson's patients. Consequently, this study was undertaken to examine the efficacy of group cognitive-behavioral therapy in ameliorating depression symptoms and enhancing the quality of life in individuals afflicted with Parkinson's disease. Materials and methods: A randomized clinical trial with pre-test and post-test measurements, including a control group, was conducted. The sample consisted of individuals referred to Roozbeh Hospital in Tehran with Parkinson's disease in 2023. Ninety participants were selected using convenience sampling and randomly assigned to either an experimental or a control group, with 45 participants in each. The experimental group received a three-month cognitive-behavioral therapy intervention consisting of 12 sessions of 90 min. Pre-test and post-test measures included the Beck Depression Questionnaire and the World Health Organization Quality of Life Questionnaire. Data analysis was performed using multivariate analysis of covariance (MANCOVA) in SPSS-25. Results: The results revealed a significant difference between the experimental and control groups in terms of depression and quality of life. The cognitive-behavioral therapy intervention significantly reduced depression and significantly improved the quality of life in individuals with Parkinson's disease (P≤0.01). Conclusion: Group cognitive-behavioral therapy can be an effective approach for reducing depression and improving the quality of life in individuals with Parkinson's disease. Therefore, therapists and healthcare providers can utilize cognitive-behavioral therapy to enhance the well-being of individuals with Parkinson's disease.

Improving mental health infrastructure across the Middle East.

This study explores the difficulties and possible remedies, for enhancing health services and decreasing stigma in the Middle East. The paper underscores the significance of education integrating Western methods, involving leaders educating young people and utilizing social media. It also draws attention to social challenges in the region while offering strategies to train health professionals to be culturally sensitive. The goal is to improve healthcare standards, in the Middle East by tackling barriers and fostering empathy and respect.

Transient blindness due to mild reversible encephalopathy in a 7-year-old boy.

Mild encephalopathy with a reversible splenial lesion (MERS) is a rare phenomenon, which shows transient lesion in corpus callosum and causes temporary encephalopathy features. A disturbance of consciousness and abnormal and delirious behavior are the most significant neurological symptoms. A seven-year-old child with a history of fever and cough was admitted to our hospital due to sudden bilateral blindness. His physical examination showed confusion, fever, and delirious behavior. No sign of meningeal irritation or focal neurological deficit was observed. The electroencephalogram showed diffuse slow waves representing mild encephalopathy. Brain MRI showed a signal alteration in the splenium of the corpus callosum, and magnetic resonance angiography (MRA) was normal. This finding was suggestive of a reversible cytotoxic lesion. Treatment with empiric antivirals was initiated, and the symptoms were completely resolved. In a few children, sudden blindness has been reported to be an initial symptom of MERS. There is currently no evidence of efficient treatment methods. However, to convince patients and their families about the good outcome of the disease, the diagnosis of MERS provides pediatricians with useful prognostic information.

Patient's airway monitoring during cardiopulmonary resuscitation using deep networks.

Cardiopulmonary resuscitation (CPR) is a crucial life-saving technique commonly administered to individuals experiencing cardiac arrest. Among the important aspects of CPR is ensuring the correct airway position of the patient, which is typically monitored by human tutors or supervisors. This study aims to utilize deep transfer learning for the detection of the patient's correct and incorrect airway position during cardiopulmonary resuscitation. To address the challenge of identifying the airway position, we curated a dataset consisting of 198 recorded video sequences, each lasting 6-8 s, showcasing both correct and incorrect airway positions during mouth-to-mouth breathing and breathing with an Ambu Bag. We employed six cutting-edge deep networks, namely DarkNet19, EfficientNetB0, GoogleNet, MobileNet-v2, ResNet50, and NasnetMobile. These networks were initially pre-trained on computer vision data and subsequently fine-tuned using the CPR dataset. The validation of the fine-tuned networks in detecting the patient's correct airway position during mouth-to-mouth breathing achieved impressive results, with the best sensitivity (98.8 %), specificity (100 %), and F-measure (97.2 %). Similarly, the detection of the patient's correct airway position during breathing with an Ambu Bag exhibited excellent performance, with the best sensitivity (100 %), specificity (99.8 %), and F-measure (99.7 %).

Brown-Vialetto-Van Laere syndrome.

Brown-Vialetto-Van Laere syndrome (BVVLS) is a rare neurodegenerative disorder of childhood. According to the previous reports, it has various primary signs and symptoms. Because of the simple treatment with riboflavin supplementation, it is important to have suspicious to this disease and begin treatment even before genetic test confirm. We report a five-year-old girl with BVVLS that manifest with hearing problems, first. There was obvious improvement in her disease clinical signs with riboflavin supplementation treatment.

Increasing the tolerance of mothers with children with autism: the effectiveness of cognitive therapy based on mindfulness - experimental research.

Introduction and importance: Autism spectrum disorder significantly impacts the life and psychosocial health of the family, resulting in high levels of anxiety, stress, isolation, and indecisiveness among parents. This study aimed to determine the effectiveness of cognitive therapy based on mindfulness in increasing the tolerance of mothers of children with autism. Case presentation: The study used a semi-experimental pre-test-post-test design with a control group. The study population comprised mothers referred to autism centers in Tehran. Eighty mothers were randomly divided into two groups, with 40 in each group. The Connor and Davidson Resilience Scale was used to measure the level of tolerance in both groups in the pre-test and post-test stages. The experimental group underwent cognitive therapy group therapy based on mindfulness, comprising eight sessions of 120 min. On the other hand, the control group did not receive any intervention. Clinical discussion: The results of the study showed that the tolerance scores of the experimental group significantly increased after the intervention, in both the post-test and follow-up stages. Conclusion: Therefore, the results of this research emphasize the importance of using this intervention in increasing the tolerance of mothers of children with autism spectrum disorder and creating new horizons in the clinical interventions of these people.

Discovery of common molecular signatures and drug repurposing for COVID-19/Asthma comorbidity: ACE2 and multi-partite networks.

Angiotensin-converting enzyme 2 (ACE2) is identified as the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the ongoing global coronavirus disease-2019 (COVID-19) pandemic. This study aimed to elucidate potential therapeutic avenues by scrutinizing approved drugs through the identification of the genetic signature associated with SARS-CoV-2 infection in individuals with asthma. This exploration was conducted through an integrated analysis, encompassing interaction networks between the ACE2 receptor and common host (co-host) factors implicated in COVID-19/asthma comorbidity. The comprehensive analysis involved the identification of common differentially expressed genes (cDEGs) and hub-cDEGs, functional annotations, interaction networks, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and module construction. Interaction networks were used to identify overlapping disease modules and potential drug targets. Computational biology and molecular docking analyzes were utilized to discern functional drug modules. Subsequently, the impact of the identified drugs on the expression of hub-cDEGs was experimentally validated using a mouse model. A total of 153 cDEGs or co-host factors associated with ACE2 were identified in the COVID-19 and asthma comorbidity. Among these, seven significant cDEGs and proteins - namely, HRAS, IFNG, JUN, CDH1, TLR4, ICAM1, and SCD-were recognized as pivotal host factors linked to ACE2. Regulatory network analysis of hub-cDEGs revealed eight top-ranked transcription factors (TFs) proteins and nine microRNAs as key regulatory factors operating at the transcriptional and post-transcriptional levels, respectively. Molecular docking simulations led to the proposal of 10 top-ranked repurposable drug molecules (Rapamycin, Ivermectin, Everolimus, Quercetin, Estradiol, Entrectinib, Nilotinib, Conivaptan, Radotinib, and Venetoclax) as potential treatment options for COVID-19 in individuals with comorbid asthma. Validation analysis demonstrated that Rapamycin effectively inhibited ICAM1 expression in the HDM-stimulated mice group (p < 0.01). This study unveils the common pathogenesis and genetic signature underlying asthma and SARS-CoV-2 infection, delineated by the interaction networks of ACE2-related host factors. These findings provide valuable insights for the design and discovery of drugs aimed at more effective therapeutics within the context of lung disease comorbidities.

An inappropriate decline in ribosome levels drives a diverse set of neurodevelopmental disorders.

Many neurodevelopmental defects are linked to perturbations in genes involved in housekeeping functions, such as those encoding ribosome biogenesis factors. However, how reductions in ribosome biogenesis can result in tissue and developmental specific defects remains a mystery. Here we describe new allelic variants in the ribosome biogenesis factor AIRIM primarily associated with neurodevelopmental disorders. Using human cerebral organoids in combination with proteomic analysis, single-cell transcriptome analysis across multiple developmental stages, and single organoid translatome analysis, we identify a previously unappreciated mechanism linking changes in ribosome levels and the timing of cell fate specification during early brain development. We find ribosome levels decrease during neuroepithelial differentiation, making differentiating cells particularly vulnerable to perturbations in ribosome biogenesis during this time. Reduced ribosome availability more profoundly impacts the translation of specific transcripts, disrupting both survival and cell fate commitment of transitioning neuroepithelia. Enhancing mTOR activity by both genetic and pharmacologic approaches ameliorates the growth and developmental defects associated with intellectual disability linked variants, identifying potential treatment options for specific brain ribosomopathies. This work reveals the cellular and molecular origins of protein synthesis defect-related disorders of human brain development. Highlights: AIRIM variants reduce ribosome levels specifically in neural progenitor cells. Inappropriately low ribosome levels cause a transient delay in radial glia fate commitment.Reduced ribosome levels impair translation of a selected subset of mRNAs.Genetic and pharmacologic activation of mTORC1 suppresses AIRIM-linked phenotypes.