Bibliographic record
Abstract
Obesity is emerging as one of the fastest growing pandemics in modern times and is associated with various health related problems.Its prevalence is gradually increased in Bangladesh especially in urban areas.As there is no available reported work and systematically documented data regarding the serum antioxidant and lipid peroxidation levels in Bangladeshi obese patients, so the aim of this study was to examine the relationship between serum antioxidant vitamin C and lipid peroxidation (MDA) levels and thereby, pathophysiological correlation was established.In this study, 100 obese patients and 100 non-obese subjects were recruited.Demographic, anthropometric and clinical data were collected at routine visits.Obesity was determined by the body mass index (BMI).Serum antioxidant vitamin (vitamin C) was determined by UVspectrophotometric method.The study showed that the antioxidant vitamin (C) was comparatively lower (p>0.05) in the obese group than in control subjects and lipid peroxidation (MDA) was significantly higher (p<0.05) in obese group than in the control subjects.Pearson's correlation analysis was carried out to determine the relationship between variables.In the patient groups, there was a positive relationship between Age and BMI (r = 0.010, p = 0.925); Age and MDA (r = 0.078, p = 0.440) but an inverse relationship between Age and Vitamin C (r = -0.052,p = 0.606); BMI and MDA (r = -0.029,p = 0.778); BMI and Vitamin C (r = -0.158,p = 0.117).In the control group, there was a positive relationship between Age and MDA (r = 0.123, p = 0.221); BMI and MDA (r = 0.007, p = 0.942); BMI and Vitamin C (r = 0.152, p = 0.132) but inverse relationship between Age and BMI (r = -0.278,p = 0.005); Age and vitamin C (r = -0.269,p = 0.007).We found decreased serum antioxidant (vitamin C) and elevated lipid peroxidation (MDA) in obese individuals than the controls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.934 | 0.947 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".