Progression of age‐associated cognitive impairment correlates with quantitative and qualitative loss of TrkA receptor protein in nucleus basalis and cortex
Bibliographic record
Abstract
A direct correlation between disease progression and reduced expression of TrkA receptor in cholinergic neurons has been documented in neurocognitive pathologies including Alzheimer's disease. We investigated whether reduced expression of TrkA protein might also correlate with the level of cognitive impairment in age-associated cognitive impairment. Quantitative and qualitative measurements of TrkA protein levels in the cortex and nucleus basalis of aged rats that had been well-characterized behaviorally as 'unimpaired', 'mildly impaired' or 'fully impaired' demonstrated significant changes in TrkA expression. In the mildly impaired cognitive state phenotypic silencing of TrkA was detected in neurons expressing TrkA at high density but before cholinergic atrophy or loss of TrkA+ neurons was detected. In the fully impaired cognitive state a significant loss in TrkA+ cholinergic neurons together with a more significant phenotypic silencing of TrkA expression then took place. These data suggest that TrkA+ cholinergic cells are associated with cognition, TrkA could be a biomarker of the cognitive state and phenotypic loss of TrkA precedes neuronal loss and probably sensitizes cells to death. We speculate that neurotrophic deficits may be a shared mechanism for cognitive decline in aging and Alzheimer's disease.
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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 | 0.001 | 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 | 0.001 |
| 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".