Follistatin Is a Potential Novel Therapeutic Agent for Essential Hypertension
Bibliographic record
Abstract
Background: Follistatin (FST) is an inhibitor of several members of the profibrotic TGFb superfamily. It is highly effective at neutralizing activins, without activity against TGFb1 itself. Activins are known to induce inflammation, oxidative stress and fibrosis, all of which contribute to the vascular dysfunction characteristic of hypertension (HTN). We previously showed that FST inhibits kidney fibrosis, improves kidney function and lowers blood pressure (BP) in a hypertensive chronic kidney disease mouse model. While this is a model of secondary HTN, here we seek to analyze the efficacy of FST in improving BP and vascular structure and function in a model of essential HTN. Methods: Telemeters were implanted in the abdominal aorta of spontaneously hypertensive rats (SHR), a model of essential HTN, and normotensive control Wistar Kyoto (WKY) rats for wireless BP monitoring. Rats were treated with 0.075mg/kg FST or vehicle IP every other day from 12-20 weeks of age (8 weeks). BP was recorded weekly. First branch mesenteric arteries were harvested for analysis of vascular function using myography, assessed for oxidative stress by DHE, or formalin fixed for IHC. Results: By the end of the study, FST significantly lowered both systolic and diastolic BP in SHRs (200 +/- 9 over 132 +/- 4 mmHg in control and 189 +/- 2 over 123 +/- 2 mmHg in FST-treated SHRs, P < 0.04 and P < 0.03 respectively). SHR vessels showed increased contractility with the a1 adrenergic agonist phenylephrine, which was attenuated by FST. Impaired endothelium-dependent relaxation in SHR vessels was also improved by FST. Structurally, FST-treated vessels had less collagen deposition, assessed by Trichrome, which was accompanied by a reduction in medial thickness. Increased oxidative stress seen in SHR vessels was inhibited by FST. Conclusions: FST lowers BP in SHR with established HTN, at least in part by reducing vascular oxidative stress and medial thickening. This manifests as improved vascular function, with decreased hypersensitivity to contractile agents and improved endothelial function. Future work will identify the effects of FST on inflammation, and the role of specific activins in essential HTN. Funding: Private Foundation Support
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".