Transforming growth factor-β1 induces cerebrovascular dysfunction and astrogliosis through angiotensin II type 1 receptor-mediated signaling pathways
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Transgenic mice constitutively overexpressing the cytokine transforming growth factor-β1 (TGF-β1) (TGF mice) display cerebrovascular alterations as seen in Alzheimer's disease (AD) and vascular cognitive impairment and dementia (VCID), but no or only subtle cognitive deficits. TGF-β1 may exert part of its deleterious effects through interactions with angiotensin II (AngII) type 1 receptor (AT1R) signaling pathways. We test such interactions in the brain and cerebral vessels of TGF mice by measuring cerebrovascular reactivity, levels of protein markers of vascular fibrosis, nitric oxide synthase activity, astrogliosis, and mnemonic performance in mice treated (6 months) with the AT1R blocker losartan (10 mg/kg per day) or the angiotensin converting enzyme inhibitor enalapril (3 mg/kg per day). Both treatments restored the severely impaired cerebrovascular reactivity to acetylcholine, calcitonin gene-related peptide, endothelin-1, and the baseline availability of nitric oxide in aged TGF mice. Losartan, but not enalapril, significantly reduced astrogliosis and cerebrovascular levels of profibrotic protein connective tissue growth factor while raising levels of antifibrotic enzyme matrix metallopeptidase-9. Memory was unaffected by aging and treatments. The results suggest a pivotal role for AngII in TGF-β1-induced cerebrovascular dysfunction and neuroinflammation through AT1R-mediated mechanisms. Further, they suggest that AngII blockers could be appropriate against vasculopathies and astrogliosis associated with AD and VCID.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 it