A Spectroscopy Study of the Brain: Exploring Sex Differences in Healthy Older Adults
Bibliographic record
Abstract
Cognitive decline and aging-related disorders, such as Alzheimer’s, disproportionately affect patients based on sex, but the mechanisms underlying these skewed effects are unknown. This proton magnetic resonance spectroscopy (H-MRS) study seeks to understand if sex disparities in aging exist in neurometabolite concentrations of older adult brains. Sixty-seven participants, ranging from 60 to 85 years of age, underwent the Montreal Cognitive Assessment (MoCA) and H-MRS of the brain. Concentrations of myo-inositol, total creatine, total NAA, and total choline were calculated in the dorsal posterior cingulate cortex, left hippocampal cortex, left medial temporal gyrus, left primary sensorimotor cortex, and right dorsolateral prefrontal cortex. The extensive number of variables inspired dimensionality reduction approaches, such as Principal Component Analysis and Factor Analysis. Each dimension primarily correlated to several metabolites in one brain region. Logistic regression with 10,000 permutation significance tests and multiple regression were conducted with dimension scores to evaluate their relationship with sex, age, and MoCA. Our evidence suggests that a collection of metabolites in the medial temporal gyrus is a reliable predictor of sex. We also found that hippocampal and dorsal posterior cingulate metabolites are associated with age and MoCA, respectively. These three findings emphasize the impact of sex, age, and cognition on neurochemical profiles, specifically in certain brain regions. This work is critical to understanding how sex plays a role in aging and how we can use this knowledge to empower geriatric patients with enhanced diagnostic medicine and personalized care.
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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".