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Fulltext Comparative Assessment of the Effects of Hatha Yoga and Physical Exercise on Biochemical Functions in Perimenopausal Women

Chaturvedi A, Nayak G, Nayak AG, Rao A

J Clin Diagn Res, 2016 Aug;10(8):KC01-4.
PMID: 27656468 DOI: 10.7860/JCDR/2016/18891.8389

INTRODUCTION: Menopause is a transitional phase in which some women experience discomfort, while others may exhibit variety of symptoms. The power of yoga therapy in relieving stress, enhancing health, improving fitness and managing symptoms of a variety of disorders is remarkable.
AIM: The current study was designed to study the effect of Hatha yoga therapy and regular physical exercise on the Fasting Blood Sugar (FBS), Glycated Haemoglobin (GHB), Thyroid Stimulating Hormone (TSH), serum cortisol and total plasma thiol levels in perimenopausal women.
MATERIALS AND METHODS: The study included 216 women with perimenopausal symptoms, 111 in test group (Hatha yoga) and 105 in control group (physical exercise). The duration of intervention was 45 minutes every day for 12 weeks. Blood samples were collected in the pre and post intervention period. Statistical significance was defined as p<0.05.
RESULTS: FBS and GHB (p≤0.05) showed a significant decrease after yoga therapy. Cortisol levels significantly (p≤0.05) increased in the post intervention period in the control group. However, it is maintained in the test group between the two time periods. The total plasma thiols level showed a rise in the post intervention period, significant rise (p≤0.001) in control group but not significant in the test group. The TSH levels were not altered in any group.
CONCLUSION: It is concluded that exercise helps in maintaining the sugar levels but calming effects of yoga practice is important in relieving stress and enhancing health in perimenopausal women.
Reduced Serum Levels of Cluster of Differentiation 200 in Alcohol-Dependent Patients

Chaturvedi A, Rao G, Praharaj SK, Guruprasad KP, Pais V

Alcohol Alcohol, 2020 Jun 25;55(4):391-394.
PMID: 32363396 DOI: 10.1093/alcalc/agaa033

AIM: Chronic alcohol consumption can activate and dysregulate the neuroimmune system which leads to neuroinflammation. Neuroimmune regulatory proteins (NIReg) (e.g. Cluster of Differentiation 200 (CD200)) are the regulators of innate immune response and are responsible for silencing the innate immunity and suppression of inflammation. In this study, we explored the changes of serum levels of CD200 in patients with alcohol dependence at baseline, after one-week alcohol withdrawal and after one-month of alcohol abstinence.
METHODS: Seventeen patients with alcohol dependence admitted for de-addiction treatment and 12 healthy controls were enrolled in the study. Blood samples were collected at baseline, after one-week, and after one-month, and CD200 levels were measured using enzyme-linked immunosorbent assay kit and compared with the healthy controls.
RESULTS: The serum level of the neuroimmune regulatory protein CD200 in alcohol dependent group (at baseline) was significantly lower compared to healthy controls (p=0.003), and increased after one-week, and one-month period.
CONCLUSION: The present study indicates that decrease of CD200 serum levels in alcohol dependent patients and its rise during alcohol withdrawal and abstinence may provide a preliminary evidence of the role of neuroimmune regulatory proteins in neuroadaptation during alcohol withdrawal.
Fulltext Enhancing communication skills among residents in India: An interprofessional education approach

Bhatia JK, Chaturvedi A, Datta K, Ciraj AM

Med J Armed Forces India, 2021 Feb;77(Suppl 1):S115-S121.
PMID: 33612941 DOI: 10.1016/j.mjafi.2020.12.027

BACKGROUND: Interprofessional education (IPE) provides opportunities to postgraduates to develop communication skills which are vital for interactions with patients, their relatives, colleagues, paramedical and nursing staff. There is a need to develop an innovative IPE based module on communication skills for postgraduates stressing upon the existing lacunae and requirements detected by a validated assessment tool. We assessed the residents' appraisal of communication skills by a validated questionnaire to identify key areas to improve their communication skills and to determine perceptions of all the stakeholders i.e. faculty, nursing staff and paramedical staff.
METHODS: A descriptive correlational design using an online self-administered questionnaire on a sample of a total of 200 participants comprising residents, paramedical staff, nursing staff and faculty of tertiary care hospital. Study was approved by the Institutional Ethical Committee. Data was analysed by SPSS Version 22.0 used. (p value
Forecasting deep learning-based risk assessment of vector-borne diseases using hybrid methodology

Nanda AK, Thilagavathy R, Gayatri Devi GSK, Chaturvedi A, Jalda CS, Inthiyaz S

Technol Health Care, 2024 Jun 21.
PMID: 38968030 DOI: 10.3233/THC-240046

BACKGROUND: Dengue fever is rapidly becoming Malaysia's most pressing health concern, as the reported cases have nearly doubled over the past decade. Without efficacious antiviral medications, vector control remains the primary strategy for battling dengue, while the recently introduced tetravalent immunization is being evaluated. The most significant and dangerous risk increasing recently is vector-borne illnesses. These illnesses induce significant human sickness and are transmitted by blood-feeding arthropods such as fleas, parasites, and mosquitos. A thorough grasp of various factors is necessary to improve prediction accuracy and typically generate inaccurate and unstable predictions, as well as machine learning (ML) models, weather-driven mechanisms, and numerical time series.
OBJECTIVE: In this research, we propose a novel method for forecasting vector-borne disease risk using Radial Basis Function Networks (RBFNs) and the Darts Game Optimizer (DGO) algorithm.
METHODS: The proposed approach entails training the RBFNs with historical disease data and enhancing their parameters with the DGO algorithm. To prepare the RBFNs, we used a massive dataset of vector-borne disease incidences, climate variables, and geographical data. The DGO algorithm proficiently searches the RBFN parameter space, fine-tuning the model's architecture to increase forecast accuracy.
RESULTS: RBFN-DGO provides a potential method for predicting vector-borne disease risk. This study advances predictive demonstrating in public health by shedding light on effectively controlling vector-borne diseases to protect human populations. We conducted extensive testing to evaluate the performance of the proposed method to standard optimization methods and alternative forecasting methods.
CONCLUSION: According to the findings, the RBFN-DGO model beats others in terms of accuracy and robustness in predicting the likelihood of vector-borne illness occurrences.
Fulltext Proteomic Analysis of the Human Anterior Pituitary Gland

Yelamanchi SD, Tyagi A, Mohanty V, Dutta P, Korbonits M, Chavan S, et al.

OMICS, 2018 12;22(12):759-769.
PMID: 30571610 DOI: 10.1089/omi.2018.0160

The pituitary function is regulated by a complex system involving the hypothalamus and biological networks within the pituitary. Although the hormones secreted from the pituitary have been well studied, comprehensive analyses of the pituitary proteome are limited. Pituitary proteomics is a field of postgenomic research that is crucial to understand human health and pituitary diseases. In this context, we report here a systematic proteomic profiling of human anterior pituitary gland (adenohypophysis) using high-resolution Fourier transform mass spectrometry. A total of 2164 proteins were identified in this study, of which 105 proteins were identified for the first time compared with high-throughput proteomic-based studies from human pituitary glands. In addition, we identified 480 proteins with secretory potential and 187 N-terminally acetylated proteins. These are the first region-specific data that could serve as a vital resource for further investigations on the physiological role of the human anterior pituitary glands and the proteins secreted by them. We anticipate that the identification of previously unknown proteins in the present study will accelerate biomedical research to decipher their role in functioning of the human anterior pituitary gland and associated human diseases.