Understanding the gut‐brain axis to mitigate cognitive frailty
Bibliographic record
Abstract
Abstract Background Gut microbiota modulation of the brain function may present an opportunity to devise preventive or treatment strategies to manage impairments such as cognitive frailty (CF). This study aims to uncover the relationship between CF, gut microbiota, intestinal permeability and proteome. Method A total of 137 fecal samples of the elderly were collected, and subjected to DNA analysis, and enzyme‐linked immunosorbent assays (ELISA). Plasma samples were subjected to mass spectrometry proteomic analysis. The parameters of the subjects measured include functional reach test (FRT), handgrip strength (HGS), Visual Cognitive Assessment Test (VCAT), Montreal Cognitive Assessment (MoCA), timed up and go (TUG) and UCLA three‐item loneliness scale (UCLA‐3). Result At the genus level, Alistipes which are potential drivers of dysbiosis, are significantly increased in CF subjects. Proteobacteria are also negatively linked to FRT, HGS, VCAT, and MoCA, but positively correlated to TUG and UCLA‐3. Lactoferrin was upregulated in pre‐frail subjects. The plasma apolipoprotein AI (Apo‐AI) was upregulated 5 times in the CF subjects. Conclusion These findings provide evidence for dietary intervention to alter gut microbiota that may modulate cognitive status.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".