DNA damage and protein oxidation associated with ageing correlate with cognitive dysfunction in a Malaysian population
Bibliographic record
Abstract
Ageing is associated with increased oxidative stress accompanied by cognitive decline. The aim of this study was to evaluate oxidative stress biomarkers and their possible relationship with cognitive performances during ageing among the Malay population. Approximately 160 healthy Malay adults aged between 28 and 79 years were recruited around Selangor and Klang Valley. Cognitive function was assessed by Montreal Cognitive Assessment (MoCA), forward digit span (FDS), backward digit span (BDS), digit symbol, Rey Auditory Verbal Learning Test immediate recalled [RAVLT(I)] and delayed recalled [RAVLT(D)], and visual reproduction immediate recalled (VR-I) and delayed recalled (VR-II). DNA damage, plasma protein carbonyl and malondialdehyde (MDA) levels were also determined. Cognitive function test showed significant lower scores of MoCA, BDS, RAVLT(I), RAVLT(D), digit symbol, VR-I, and VR-II in the older age group (60 years old) compared with the 30-, 40-, and 50-year-old group. The extent of DNA damage was sequential with age: 60 > 50 > 40 > 30, whereas protein carbonyl was higher in 40-, 50-, and 60-year-old groups compared with the youngest group (30 years old). However, the MDA level was observed unchanged in all age groups. Approximately 21.88% of the participants had cognitive impairment. Multiple logistic regression analysis revealed that DNA damage and protein carbonyl levels are predictors for cognitive impairment in healthy Malays. In conclusion, cognitive decline occurred in healthy adult Malay population at an early age of 30 years old with corresponding higher DNA damage and protein oxidation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".