The Radioprotective Activities of Turpentine-induced Inflammation and α2-Macroglobulin: The Effect of Dexamethasone on the Radioprotective Efficacy of the Inflammation
Bibliographic record
Abstract
This work was aimed at the radioprotective efficacy of turpentine oil (TO), alpha2-Macroglobulin (alpha2-M), Amifostine (Ami) and/or dexamethasone (Dex). These agents were administrated, alone or in combination, prior to irradiation of rats with 6.7 Gy (LD(50/30)). The survival was recorded daily for 4 weeks after irradiation and body weight, peripheral leukocytes and thrombocytes were measured. The plasma concentration of alpha2-M and other acute phase proteins were determined by crossed immunoelectrophoresis. All rats receiving alpha2-M and Ami alone or in combination survived the radiation injury, whereas the rate of survival of TO-treated rats was 90%. Radiation and therapy-induced changes in the expression of acute phase protein genes were atypical for the acute phase reaction. Dex alone was lethal for 45% and 55% of control and irradiated rats, respectively. Pretreatment with 1mg Dex reduced radioprotective efficacy of TO and Ami to 30% and 40%, respectively. Given together TO and Ami provided 70% protection to rats receiving Dex. The TO and alpha2-M enhanced the rate of survival from 50% to 90% and 100%, respectively. In the presence of 1mg Dex the TO-induced radioprotectors and Ami exhibited radiosensitizing rather than radioprotecting activities.
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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) | 0.000 | 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 | 0.000 |
| 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".