Ascorbate prevents microvascular dysfunction in the skeletal muscle of the septic rat
Bibliographic record
Abstract
Septic patients have low plasma ascorbate concentrations and compromised microvascular perfusion. The purpose of the present experiments was to determine whether ascorbate improves capillary function in volume-resuscitated sepsis. Cecal ligation and perforation (CLP) was performed on male Sprague-Dawley rats. The concentration of ascorbate in plasma and urine, mean arterial blood pressure, and density of continuously perfused capillaries in the extensor digitorum longus muscle were measured 24 h after surgery. CLP caused a 50% decrease (from 56 +/- 4 to 29 +/- 2 microM) in plasma ascorbate concentration, 1,000% increase (from 46 +/- 13 to 450 +/- 93 microM) in urine ascorbate concentration, 20% decrease (from 115 +/- 2 to 91 +/- 2 mmHg) in mean arterial pressure, and 30% decrease (from 24 +/- 1 to 17 +/- 1 capillaries/mm) in the density of perfused capillaries, compared with time-matched controls. A bolus of intravenous ascorbate (7.6 mg/100 g body wt) administered immediately after the CLP procedure increased plasma ascorbate concentration and restored both blood pressure and density of perfused capillaries to control levels. In vitro experiments showed that ascorbate (100 microM) inhibited replication of bacteria and prevented hydrogen peroxide injury to cultured microvascular endothelial cells. These results indicate that ascorbate is lost in the urine during sepsis and that a bolus of ascorbate can prevent microvascular dysfunction in the skeletal muscle of septic animals. Our study supports the view that ascorbate may be beneficial for patients with septic syndrome.
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) | 0.000 | 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 | 0.001 |
| 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".