No abstract

The Glu298Asp polymorphism of NOS3 associates with CSFP.

Uncertainty about Coronavirus disease 2019 (COVID-19) and resulting lockdown caused widespread panic, stress, and anxiety. Yoga is a known practice that reduces stress and anxiety and may enhance immunity. This study aimed to (1) investigate that including Yoga in daily routine is beneficial for physical and mental health, and (2) to evaluate lifestyle of Yoga practitioners that may be instrumental in coping with stress associated with lockdown. This is a pan-India cross-sectional survey study, which was conducted during the lockdown. A self-rated scale, COVID Health Assessment Scale (CHAS), was designed by 11 experts in 3 Delphi rounds (Content valid ratio = 0.85) to evaluate the physical health, mental health, lifestyle, and coping skills of the individuals. The survey was made available digitally using Google forms and collected 23,760 CHAS responses. There were 23,290 valid responses (98%). After the study's inclusion and exclusion criteria of yogic practices, the respondents were categorized into the Yoga (n = 9,840) and Non-Yoga (n = 3,377) groups, who actively practiced Yoga during the lockdown in India. The statistical analyses were performed running logistic and multinomial regression and calculating odds ratio estimation using R software version 4.0.0. The non-Yoga group was more likely to use substances and unhealthy food and less likely to have good quality sleep. Yoga practitioners reported good physical ability and endurance. Yoga group also showed less anxiety, stress, fear, and having better coping strategies than the non-Yoga group. The Yoga group displayed striking and superior ability to cope with stress and anxiety associated with lockdown and COVID-19. In the Yoga group, participants performing meditation reportedly had relatively better mental health. Yoga may lead to risk reduction of COVID-19 by decreasing stress and improving immunity if specific yoga protocols are implemented through a global public health initiative.

Introduction: Evidence-based information about cerebrospinal fluid (CSF) levels of biomarkers in patients with amyotrophic lateral sclerosis (ALS) is limited. Methods: Vascular endothelial growth factor (VEGF) and its receptor vascular endothelial growth factor receptor 2 (VEGFR2), optineurin (OPTN), monocyte chemoattractant protein-1 (MCP-1), angiogenin (ANG), and TAR DNA-binding protein (TDP-43) were quantified by enzyme-linked immunoassay in the CSF of 54 patients with sporadic ALS and 32 controls in a case-control study design.

Amyotrophic Lateral Sclerosis (ALS) is a degenerative disorder of motor neurons which leads to complete loss of movement in patients. The only FDA approved drug Riluzole provides only symptomatic relief to patients. Early Diagnosis of the disease warrants the importance of diagnostic and prognostic models for predicting disease and disease progression respectively. In the present study we represent the predictive statistical model for ALS using plasma and CSF biomarkers. Forward stepwise (Binary likelihood) Logistic regression model is developed for prediction of ALS. The model has been shown to have excellent validity (94%) with good sensitivity (98%) and specificity (93%). The area under the ROC curve is 99.3%. Along with age and BMI, VEGF (Vascular Endothelial Growth Factor), VEGFR2 (Vascular Endothelial Growth Factor Receptor 2) and TDP43 (TAR DNA Binding Protein 43) in CSF and VEGFR2 and OPTN (Optineurin) in plasma are good predictors of ALS.