Angiotensin II‐Induced Vasoconstriction in Skeletal Muscle: Effects of Aging and TNF‐α
Bibliographic record
Abstract
There is increasing evidence that oxidative stress and vascular inflammation contribute to old‐age associated vascular dysfunction. With advancing age there are elevated levels of tumor necrosis factor (TNF)‐α, which, via endothelial vasodilator impairment, may exacerbate the vasoconstrictor responses of angiotensin (ANG)‐II. Purpose To determine whether the proinflammatory cytokine TNF‐α contributes to alterations in ANG II‐mediated vasoconstriction with aging. Methods Pegylated soluble human TNF type 1 receptor (PEG sTNF‐RI; Amgen Inc) was administered (1 mg/kg, s.c., 3x/wk) for 10 wks in eight young (4–6 mo) and seven old (22–24 mo) male Fischer 344 rats to inhibit soluble TNF‐α binding to receptors. At the end of the TNF‐α inhibition period, gastrocnemius muscle arterioles were isolated and concentration response relations to the cumulative addition of ANG II (3x10 −12 to 3x10 −5 M) were determined. Results Chronic TNF‐α inhibition significantly diminished the vasoconstrictor response of arterioles from ~ 60% vasoconstriction in the old untreated animals to ~ 40% in the old treated animals. Furthermore, age‐associated differences (young vs. old) in ANG II mediated vasoconstriction were eliminated with the chronic TNF‐α inhibition. Conclusion With old age there is an enhanced vasoconstriction to ANG II which is due, in part, to diminished endothelial function. Chronic TNF‐α inhibition eliminated age‐related differences in ANG II induced vasoconstriction which suggests that the impaired NOS signaling pathway linked to ANG II receptors with old age may be the result of a proinflammatory state.
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 | 0.000 |
| 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) | 0.000 | 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".