Oxidative Stress after Subarachnoid Hemorrhage in <i>gp91<sup>phox</sup></i> Knockout Mice
Bibliographic record
Abstract
BACKGROUND: Oxidative stress largely contributes to early brain injury after subarachnoid hemorrhage (SAH). One of the major sources of reactive oxygen species is NADPH oxidase, upregulated after SAH. We hypothesized that NADPH oxidase-induced oxidative stress plays a major causative role in early brain injury after SAH. METHODS: Using gp91phox knockout (ko) and wild-type (wt) mice, we studied early brain injury in the endovascular perforation model of SAH. Mortality rate, cerebral edema, oxidative stress, and superoxide production were measured at 24 h after SAH. Neurological evaluation was done at 23 h after SAH surgery. RESULTS: Genotyping confirmed the existence of a nonfunctional gp91phox gene in the ko mice. CBF measurements did not show differences in SAH-induced acute ischemia between ko and wt mice. SAH caused a significant increase of water content in the ipsilateral hemisphere as well as an increase of Malondialdehyde (MDA) levels and superoxide production. There were no significant differences in post-SAH mortality rate, brain water content and the intensity of the oxidative stress between knockout and wild type groups of mice. CONCLUSIONS: Our results suggest that gp91phox is not critically important to the early brain injury after SAH. An adaptive compensatory mechanism for free radical production in knockout mice is discussed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".