Obesity and ageing: Two sides of the same coin
Bibliographic record
Abstract
Conditions and comorbidities of obesity mirror those of ageing and age-related diseases. Obesity and ageing share a similar spectrum of phenotypes such as compromised genomic integrity, impaired mitochondrial function, accumulation of intracellular macromolecules, weakened immunity, shifts in tissue and body composition, and enhanced systemic inflammation. Moreover, it has been shown that obesity reduces life expectancy by 5.8 years in men and 7.1 years in women after the age of 40. Shorter life expectancy could be because obesity holistically accelerates ageing at multiple levels. Besides jeopardizing nuclear DNA and mitochondrial DNA integrity, obesity modifies the DNA methylation pattern, which is associated with epigenetic ageing in different tissues. Additionally, other signs of ageing are seen in individuals with obesity including telomere shortening, systemic inflammation, and functional declines. This review aims to show how obesity and ageing are "two sides of the same coin" through discussing how obesity predisposes an individual to age-related conditions, illness, and disease. We will further demonstrate how the mechanisms that perpetuate the early-onset of chronic diseases in obesity parallel those of ageing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".