Differential brain volume between obese and underweight cognitively normal older adults with frailty in the JPSC-AD
Bibliographic record
Abstract
Frailty is common in older adults; however, the central nervous system mechanisms underlying the differences between obesity and underweight remain unclear. This study investigated brain volume in frail, cognitively normal, community-dwelling older adults across three body mass index (BMI) groups: low (< 18.5), intermediate (18.5-24.9), and high (≥ 25.0). Whole and regional brain volumes were measured and analyzed. Among 3,627 participants, those in the high BMI group (n = 1,134) had significantly lower multivariate-adjusted total brain volume (66.8% vs. 67.3%, p < 0.001) and gray matter volume (36.1% vs. 36.6%, p < 0.001) than participants in the intermediate BMI group (n = 2,274). Volume differences were observed in the frontal, parietal, temporal, and cingulate cortices, as well as the hippocampal gyrus; amygdala; superior, middle, and inferior temporal gyri; temporal pole; parahippocampal gyrus; and cuneus. Compared with the intermediate BMI group, the low BMI group (n = 219) presented a significantly lower volume in the middle temporal gyrus (1.91% vs. 1.95%, p = 0.008). These findings indicate that older adults with frailty experience differences in brain volume, with atrophy patterns differing based on BMI. Therefore, the central nervous system dysfunction may play a role in the mechanisms underlying frailty.
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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 | 0.001 |
| 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".