Intact Memory in TGF-β1 Transgenic Mice Featuring Chronic Cerebrovascular Deficit: Recovery with Pioglitazone
Bibliographic record
Abstract
The roles of chronic brain hypoperfusion and transforming growth factor-beta 1 (TGF-β1) in Alzheimer's disease (AD) are unresolved. We investigated the interplay between TGF-β1, cerebrovascular function, and cognition using transgenic TGF mice featuring astrocytic TGF-β1 overexpression. We further assessed the impact of short, late therapy in elderly animals with the antioxidant N-acetyl-L-cysteine (NAC) or the peroxisome proliferator-activated receptor-γ agonist pioglitazone. The latter was also administered to pups as a prophylactic 1-year treatment. Elderly TGF mice featured cerebrovascular dysfunction that was not remedied with NAC. In contrast, pioglitazone prevented or reversed this deficit, and rescued the impaired neurovascular coupling response to whisker stimulation, although it failed to normalize the vascular structure. In aged TGF mice, neuronal and cognitive indices--the stimulus-evoked neurometabolic response, cortical cholinergic innervation, and spatial memory in the Morris water maze--were intact. Our findings show that impaired brain hemodynamics and cerebrovascular function are not accompanied by memory impairment in this model. Conceivably in AD, they constitute aggravating factors against a background of aging and underlying pathology. Our data further highlight the ability of pioglitazone to protect the cerebrovasculature marked by TGF-β1 increase, aging, fibrosis, and antioxidant resistance, thus of high relevance for AD patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".