Ascorbate Inhibits Reduced Arteriolar Conducted Vasoconstriction in Septic Mouse Cremaster Muscle
Bibliographic record
Abstract
OBJECTIVE: The mechanism of neuronal nitric oxide synthase (nNOS)-dependent reduction in arteriolar conducted vasoconstriction in sepsis, and the possible protection by antioxidants, are unknown. The authors hypothesized that ascorbate inhibits the conduction deficit by reducing nNOS-derived NO production. METHODS: Using intravital microscopy and the cecal ligation and perforation (CLP) model of sepsis (24 h), arterioles in the cremaster muscle of male C57BL/6 wild-type mice were locally stimulated with KCl to initiate conducted vasoconstriction. The authors used the ratio of conducted constriction (500 microm upstream) to local constriction as an index of conduction (CR500). Cremaster muscle NOS enzymatic activity and protein expression, and plasma nitrite/nitrate levels were determined in control and septic mice. Intravenous ascorbate bolus (200 mg/kg in 0.1 ml of saline) was given early (0 h) or delayed at 23 h post CLP. RESULTS: Sepsis reduced CR500 from 0.73 +/- 0.03 to 0.21 +/- 0.03, increased nNOS activity from 87 +/- 9 to 220 +/- 29 pmol/mg/h and nitrite/nitrate from 16 +/- 1 to 39 +/- 3 microM, without affecting nNOS protein expression. Ascorbate at 0 and 23 h prevented/reversed the conduction deficit and the increases in nNOS activity and nitrite/nitrate level. NO donor SNAP (S-nitroso-N-acetylpenicillamine) reestablished the conduction deficit in ascorbate-treated septic mice. Superoxide scavenger MnTBAP (Mn(III)tetrakis(4-benzoic acid)porphyrin chloride) did not affect this deficit. CONCLUSION: These data indicate that early and delayed intravenous boluses of ascorbate prevent/reverse sepsis-induced deficit in arteriolar conducted vasoconstriction in the cremaster muscle by inhibiting nNOS-derived NO production.
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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 | 0.000 | 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 | 0.001 |
| 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".