ASSOCIATIONS BETWEEN CARDIORESPIRATORY FITNESS, BRAIN AGE, AND NEURODEGENERATION AMONG OLDER ADULTS
Bibliographic record
Abstract
Abstract There is growing evidence that CRF mitigates the likelihood of dementia caused by Alzheimer’s disease (AD) and may underlie the cognitive benefits observed from aerobic exercise. Previous evidence further demonstrates neurodegeneration is the biological substrate for cognition deterioration and brain age may protect the brain from the deleterious effects of neurodegeneration. However, little is known about the relationships between CRF, brain age, and neurodegeneration in older adults with amnestic mild cognitive impairment (aMCI). The purpose of this cross-sectional study was to examine associations between CRF, brain age, and neurodegeneration among individuals with aMCI, using baseline data from the Aerobic exercise and Cognitive Training Trial, which examines the cognitive effects and underlying mechanisms of a 6-month ACT in older adults with aMCI. CRF was measured with VO2peak from a symptom-limited peak cycle-ergometer test. Brain age, hippocampal volume, and AD-signature cortical thickness (SCT) were obtained from structural magnetic resonance imaging. Multiple linear regressions were conducted in R (version 4.3.2). The sample (N=134) averaged 73.63 ± 5.81 years of age, 16.98 ± 2.9 years of education, 27.47 ± 5.17 in BMI, and 23.5 ± 2.18 in Montreal Cognitive Assessment scores with 51.5% male and 92.5% White. The mean brain age was 72.37±7.76 years with 2.92± 0.31mm ADSCT and 3164 ±455.51mm3 hippocampal volume. CRF was not associated with brain age and neurodegeneration. A negative association was found between brain age with hippocampal volume (β=-11.37, SE=5.11, p=0.02) and ADSCT (β=-0.01, SE=0.003, p=0.004). To conclude, future studies need to explore other brain indicators related to CRF.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".