miRNA in Circulating Microvesicles as Biomarkers for Age-Related Cognitive Decline
Bibliographic record
Abstract
Community dwelling older individuals from the North Florida region were examined for health status and a comprehensive neuropsychological battery, including the Montreal Cognitive Assessment (MoCA), was performed on each participant. A subpopulation (58 females and 39 males) met the criteria for age (60-89) and no evidence of mild cognitive impairment, with a MoCA score ≥ 23. Despite the stringent criteria for participation, MoCA scores were negatively correlated within the limited age range. Extracellular microvesicles were isolated from the plasma and samples were found to be positive for the exosome marker CD63, with an enrichment of particles within the size range for exosomes. miRNA was extracted and examined using next generation sequencing with a stringent criterion (average of ≥ 10 counts per million reads) resulting in 117 miRNA for subsequent analysis. Characterization of expression confirmed pervious work concerning the relative abundance and overall pattern of expression of miRNA in plasma. Correlation analysis indicated that most of the miRNAs (74 miRNAs) were positively correlated with age (p < 0.01). Multiple regression was employed to identify the relationship of miRNA expression and MoCA score, accounting for age. MoCA scores were negatively correlated with 13 miRNAs. The pattern of expression for cognition-related miRNA did not match that previously described for Alzheimer’s disease. Enrichment analysis was employed to identify miRNA-gene interactions to reveal possible links to brain function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".