Are vitamin D, B12, and folate deficiency associated with depressive disorder? A case-control study.

Background: Depression is a global burden with complex etiopathogenesis. Some nutrients including vitamin D, B12, and folate deficiency have been considered risk factors for depression. Therefore, this study has been contemplated to find out the possible association of vitamin D, B12, and folate deficiency with depression. Method: This study included 81 case subjects with depression and 95 control subjects without any International Classification of Diseases (ICD)-10 diagnosis. The sociodemographic details were collected from each subject. Beck's Depression Inventory (BDI) was administered to identify the severity of depression. The blood samples were collected and measured for vitamin D, B12, and folate along with other laboratory investigations as per exclusion criteria. The data were obtained and analyzed using descriptive and inferential statistics. Results: The mean age ± standard deviation (SD) of the case and control subjects were 34.86 ± 9.25 and 33.49 ± 8.44, respectively, without any significant difference (P > 0.05). The subjects with vitamin D deficiency were found to have four times higher odds (OR 4.703; 95% CI = 2.378-9.300) for depression compared to subjects with sufficient vitamin D levels. In addition, there was a negative correlation between vitamin D levels and the severity of depression as per BDI scoring (r = -.384, P < 0.01). However, there was no significant association identified between the case and control group with respect to serum vitamin B12 and folate levels. Conclusion: The results of the study revealed that vitamin D deficiency has an association with depression. However, further research studies are needed to validate its correlation to the etiopathogenesis of depression.

Musical preferences of Indian children with autism spectrum disorder and acceptability of music therapy by their families: An exploratory study.

Background: Music therapy has been in use for children with autism spectrum disorder (ASD) since the 1940s. However, there is limited scientific evidence on its use in the Indian context. Aim: The present study aims to explore musical preferences of children with ASD and their caregivers' acceptability of music as a form of intervention. Materials and Methods: It is a cross-sectional study of 120 subjects diagnosed with ASD as per the Diagnostic and Statistical Manual of Mental Disorders-5 identified by convenience sampling. A semi-structured interview schedule consisting of 25 objective response questions with multiple choices and 11 open-ended questions (pertaining to music and the use of music) was used to explore caregivers'/parents' thoughts and beliefs. The responses to open-ended questions were collected in narrative mode. A descriptive approach of content analysis was adopted to analyse the data. The data are presented using descriptive statistics. Institutional Ethics Committee's approval was obtained for conducting the study. Results: Most of the children liked (89.2%, n = 107) music and responded (88.3%, n = 106) actively (listen intently/hum or sing or dance along) to music. Most subjects preferred rhythm (65%, n = 78) over melody (15%, n = 18). While 98.3% (n = 118) of the parents were willing to try music therapy for their child, 61% of them (n = 72) asked follow-up questions like - "Is there available data on it?" (n = 12; 10.2%) and "Will it be worth investing our time and efforts on it?" (n = 60; 50.8%). Conclusion: Most of the children including those with auditory sensitivity like music and prefer rhythm over melody. Caregivers possess a positive attitude toward the use of music therapy. However, most of them wish to clarify the scientific basis of the same.

A Feature Extraction Using Probabilistic Neural Network and BTFSC-Net Model with Deep Learning for Brain Tumor Classification.

BACKGROUND AND OBJECTIVES: Brain Tumor Fusion-based Segments and Classification-Non-enhancing tumor (BTFSC-Net) is a hybrid system for classifying brain tumors that combine medical image fusion, segmentation, feature extraction, and classification procedures. MATERIALS AND METHODS: to reduce noise from medical images, the hybrid probabilistic wiener filter (HPWF) is first applied as a preprocessing step. Then, to combine robust edge analysis (REA) properties in magnetic resonance imaging (MRI) and computed tomography (CT) medical images, a fusion network based on deep learning convolutional neural networks (DLCNN) is developed. Here, the brain images' slopes and borders are detected using REA. To separate the sick region from the color image, adaptive fuzzy c-means integrated k-means (HFCMIK) clustering is then implemented. To extract hybrid features from the fused image, low-level features based on the redundant discrete wavelet transform (RDWT), empirical color features, and texture characteristics based on the gray-level cooccurrence matrix (GLCM) are also used. Finally, to distinguish between benign and malignant tumors, a deep learning probabilistic neural network (DLPNN) is deployed. RESULTS: according to the findings, the suggested BTFSC-Net model performed better than more traditional preprocessing, fusion, segmentation, and classification techniques. Additionally, 99.21% segmentation accuracy and 99.46% classification accuracy were reached using the proposed BTFSC-Net model. CONCLUSIONS: earlier approaches have not performed as well as our presented method for image fusion, segmentation, feature extraction, classification operations, and brain tumor classification. These results illustrate that the designed approach performed more effectively in terms of enhanced quantitative evaluation with better accuracy as well as visual performance.

Characteristics of auditory hallucinations in Indian patients with schizophrenia and bipolar affective disorder.

BACKGROUND: Auditory verbal hallucinations are not a unitary phenomenon and can be further differentiated into certain clinical characteristics, viz., frequency, intensity, control, tone, distractibility, distress, and clarity. These clinical characteristics manifest in varying degrees in different psychiatric disorders. AIM: To study the characteristics of auditory hallucinations in Indian patients with schizophrenia and bipolar affective disorder. MATERIALS AND METHODS: By purposive sampling, 140 patients of schizophrenia and bipolar affective disorder each were included in the study. Subjects were assessed cross-sectionally using sociodemographic proforma and characteristics of auditory hallucination scale. RESULTS: Characteristics of auditory hallucinations of schizophrenia patients were significantly different from those of bipolar affective disorder patients in the domains of frequency, intensity, tone, self-control, clarity, distractibility, and distress. CONCLUSION: Characteristics of auditory hallucinations differ in all domains between schizophrenia and bipolar affective disorder.

New initiatives: A psychiatric inpatient facility for older adolescents in India.

CONTEXT: Almost 1/5th of the adolescent population suffers from mental morbidity. In older adolescents, clinical challenges are accompanied by unique psychosocial and developmental needs. Recent legislations in India - the Mental Health Care Act, 2017 and the Juvenile Justice Act, 2015 - mandate specific arrangements and provisions for evaluation and treatment of children and adolescents. A separate inpatient Adolescent Psychiatry Center (APC) was started at National Institute of Mental Health and Neurosciences, Bangalore, in 2016. AIMS: (a) The aim of this study is to present the need for, development, infrastructure and workforce at APC; (b) to describe clinical profile of adolescents admitted to APC and (c) to identify clinical and psychosocial challenges in the management of older adolescents. SETTING AND DESIGN: The paper covers consecutive inpatient admissions over the first 7 months of APC. MATERIALS AND METHODS: Data were gathered from a review of hospital records, staff meetings, and case files. STATISTICAL ANALYSIS: Qualitative data, such as clinical management challenges, are summarized under major emergent themes. Quantitative data are summarized as means with standard deviations and frequencies with percentages. RESULTS: Males, from urban, nuclear family background constituted the majority admissions. Family stressors and risk behaviors were prevalent. Unique clinical challenges included - risk behaviors, issues related to autonomy, conflict with family and conflict with the legal system. CONCLUSIONS: Older adolescents need to be treated in an environment appropriate to their age and developmental stage. Restructuring of spaces, routines, and creative inputs to interventions strategies must be made for healing environments for youngsters. APC could be a model for the development of other similar centers.