Role of the NF‐kB pathway in rats subjected to moderate hemorrhage
Bibliographic record
Abstract
Mechanisms by which hemorrhagic shock leads to hemodynamic disturbances are not fully understood. Nuclear factor kB (NF‐kB) is a nuclear transcription factor that regulates expression of genes critical for the regulation of diseases. We hypothesize that NF‐kB is responsible for the hemodynamic changes associated with hemorrhagic shock in conscious rats. Under isoflurane, catheters were implanted into the aorta to record mean blood pressure (MAP) and heart rate (HR) and in the femoral vein for drug administrations. Cardiac output (CO) was recorded through Doppler flow probe. A blood volume of 2.0 ml/100 g of body weight was withdrawn over a 5‐min to induce moderate hemorrhage. Group 1 (n=6) was subjected to moderate hemorrhage only. Group 2 (n=5) was hemorrhaged in the presence of TPCK, an inhibitor of NF‐kB at 10 mg/kg sc. Our data show that hemorrhagic shock induced decreases in MAP by 30%, HR by 40% whereas CO remained unchanged. Moderate hemorrhage induced significant systemic vasoconstriction. As compared to hemorrhaged animals, TPCK restored MAP to baseline. Furthermore, moderate hemorrhage‐induced systemic vasoconstriction was significantly reduced in the presence of TPCK. Our data suggest that NF‐kB plays a major role in the hemodynamic changes induced by moderate hemorrhage. Development of NF‐kB inhibitors that will be tissue‐specific and/or isoform‐specific as therapeutic agents need to be pursued.
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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) | 0.000 | 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".