A thermally stable lipase (EC 3.1.1.3.) was first identified in rice (Oryza sativa) bran, and the enzyme was purified to homogeneity using octyl-Sepharose chromatography. The enzyme was purified to 7.6-fold with the final specific activity of 0.38 mol min Ϫ1 mg Ϫ1 at 80°C using [9,10-3 H]triolein as a substrate. The purified enzyme was found to be a glycoprotein of 9.4 kD. Enzyme showed a maximum activity at 80°C and at pH 11.0. The protein was biologically active and retained most of its secondary structure even at 90°C as judged by the enzymatic assays and far-ultraviolet circular dichroism spectroscopy, respectively. Differential scanning calorimetric studies indicated that the transition temperature was 76°C and enthalpy 1.3 ϫ 10 5 Calorie mol Ϫ1 at this temperature. The purified lipase also exhibited phospholipase A 2 activity. Colocalization of both the hydrolytic activities in reverse-phase high-performance liquid chromatography and isoelectric focusing showed that the dual activity was associated with a single protein. Further, a direct interaction between both the substrates and the purified protein was demonstrated by photoaffinity labeling, using chemically synthesized analogs of triolein and phosphatidylcholine (PC). Apparent K m for triolein (6.71 mm) was higher than that for PC (1.02 mm). The enzyme preferentially hydrolyzed the sn-2 position of PC, whereas it apparently exhibited no positional specificity toward triacylglycerol. Diisopropyl fluorophosphate inhibited both lipase and phospholipase activities of the purified enzyme. This enzyme is a new member from plants in the family of lipases capable of hydrolyzing phospholipids.

Background: Heart rate variability (HRV) is a used to assess autonomic nervous system input to the heart. Studies on the impact of HRV on underweight are limited. Aims/Objectives: To evaluate HRV in age matched young adults of different BMI category. Methodology: This cross-sectional study was done among healthy young adult volunteers between 18 and 25 years of age. Anthropometric variables were measured. ECG was recorded in lead II configuration for 5 minutes. Heart rate variability was analysed with Kubios HRV analyzer. Results: HRV indices were reduced in underweight (UW), overweight (OW) and obese group compared to normal weight (NW) BMI group. Second order polynomial regression between BMI and HF log power in both genders shows an inverted U-shaped relationship with BMI. The association between BMI, waist circumference and body fat (percentage) with HRV indices shows a significant relation to heart rate variability among which waist circumference (WC) shows a greater association with HRV indices than BMI. Comparison of HRV parameters among men and women of different BMI group shows female had greater heart rate variability compared to males across BMI Conclusions: underweight individual also have increased cardiovascular risk like obese group and abdominal obesity is better indicator of cardiovascular risk than BMI.

BackgroundExcessive body fat, or obesity, is a worldwide epidemic and a major contributor to the development of dementia. AimThe research aimed to determine how obesity affected healthcare professionals' memory performance. Materials and MethodA total of 474 participants (both male and female) were recruited in this study by random sampling method from three different health institutions. Participants were categorized into overweight, normal weight, and obese groups based on their body mass index (BMI) as per the WHO guidelines and for body fat participants. The memory function test was done using the Gilewski MJ scale. General frequency of forgetting, mnemonic usage, retrospective functioning, and seriousness of forgetting were measured and compared across the BMI and %body fat groups. ResultsThe percentage of body fat of males and females was 38.19% and 42.26%. Statistically, a significant difference (p<0.05) was observed among the male and female BMI and percentage of body fat. The results showed that there was a significant difference between memory scale parameters and percentage BMI. Statistically, a significant difference was observed in the level of general frequency of forgetting among participants with different percentages of BMI (p<0.05). Similar, results were also observed in the level of seriousness of forgetting, retrospective functioning, and mnemonics usage with different % BMI (p<0.05). The findings showed a positive correlation between BMI and %body fat on the scale of general frequency of forgetting and seriousness of forgetting whereas, a negative correlation was observed on the scale of retrospective functioning and mnemonics usage. ConclusionMemory loss is one of the disorders that obesity is linked to more frequently. A focus on keeping a healthy weight may help prevent the development of future diseases.

Background: Obesity has been a major concern due to its increasing prevalence and associated metabolic complications. Body mass index (BMI) assesses general obesity, but it does not distinguish between muscle and fat accumulations, so using only BMI can lead to an erroneous result. Waist circumference (WC), a marker of central obesity, predicted mortality risk better than BMI. However, WC can be affected by abdominal distension, is time-consuming, and may not be culture-sensitive. Neck circumference (NC) is devoid of these disadvantages and is believed to be an index of upper body fat distribution. This study aimed to assess the association of neck circumference with general and central obesity and to identify the cut-off points for evaluating obesity in young adults using NC. Material and Methods: Height, weight, waist, and hip circumference were measured to determine BMI and waist-hip ratio. NC was measured at the level of the mid-cervical spine and mid-anterior neck in a standing position with the arms hanging freely. For males with a laryngeal prominence, NC was measured just below the prominence. Results: In total, 357 (170 male and 187 female) young, healthy Indian adults aged 18–25 participated. Neck circumference (NC) is significantly associated with BMI and WC in both genders. We found the best cut-off for male and female participants to be ≥34 cm and ≥30.5 cm, with a sensitivity of 88.3% and 84.4% for assessing obesity. Conclusion: NC may be a better alternative to BMI and WC as a marker to assess obesity since it is more practical, simple, inexpensive, time-saving, and less invasive.

Introduction: Obesity is considered to be a risk factor for a variety of cardiovascular conditions. Various markers for obesity are used to evaluate effect of obesity on cardiovascular autonomic activity. In light of conflicting reports on effect of obesity on heart rate variability (HRV), use of obesity indices, and the effect of physical activity on HRV, we evaluated autonomic activity in young Indian obese adults using revised Indian and World Health Organization (WHO) body mass index (BMI) guidelines for obesity, waist circumference (WC), and waist–hip ratio (WHR) taking into consideration the level of physical activity. Methods: The study was conducted on 91 young healthy adults. Height, weight, waist, and hip circumference were recorded to determine BMI and WHR. Five-minute electrocardiogram (ECG) was recorded for assessment of HRV. Physical activity was assessed by the WHO Global Physical Activity Questionnaire (GPAQ). Results: Waist circumference showed a negative correlation with the time domain parameters of HRV and high frequency normalized units (HFnu) while a positive correlation with low frequency normalized units (LFnu). In multiple linear regression analysis, time domain indices, HFnu and total power decreased while LFnu increased with an increase in WC. The result was supported by the similar effect of waist–hip ratio categories on HRV in analysis of covariance (ANCOVA). Physical activity had no effect on HRV. Conclusion: Central obesity parameters are better predictors of effect of obesity on HRV independent of the effect of physical activity.