Conducted Vasoconstriction Is Reduced in a Mouse Model of Sepsis
Bibliographic record
Abstract
The ability of an arteriole to conduct vasomotor responses along its length contributes to the control of organ perfusion. Sepsis, a systemic inflammatory response to infection, may compromise this control. We aimed to determine whether sepsis, induced by cecal ligation and perforation (CLP), reduces conducted vasoconstriction 24 h post-CLP. We locally stimulated mouse cremaster arterioles with KCl, measured the resulting local and the conducted constriction (500 microm upstream) and, based on these measurements, determined the communication ratio (CR(500)) as an index of the conducted response. Sepsis significantly reduced the CR(500) from 0.75 to 0.20. Based on a mathematical model, this reduction was predicted to have a significant impact on blood flow control. In septic mice, either a 1-hour washout of the cremaster muscle with physiological saline or a treatment of this muscle with the tyrosine kinase inhibitor PP-2 (100 nM) restored the CR(500) to the control level. Treatment of septic arterioles with the nitric oxide synthase inhibitor N(omega)-nitro-L-arginine methyl ester (100 microM) partially restored the CR(500) from 0.2 to 0.4. In control mice, lipopolysaccharide (LPS; 10 microg/ml) superfused over the cremaster muscle for 1 h reduced the CR(500); the nitric oxide (NO) donor S-nitroso-N-acetyl-penicillamine (50 microM) also reduced the CR(500). Thus, LPS and NO could be two factors mediating reduced conduction of vasoconstriction in sepsis. We conclude that sepsis reduces the KCl-induced conducted vasoconstriction in the mouse cremaster muscle by a tyrosine kinase- and nitric oxide- dependent mechanism.
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) | 0.001 | 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) | 0.002 | 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".