Anti-inflammatory effect of selenium nanoparticles on the inflammation induced in irradiated rats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Selenium (Se) has been reported to possess anti-inflammatory properties, but its bioavailability and toxicity are considerable limiting factors. The present study aimed to investigate the possible anti-inflammatory and analgesic effects of selenium nanoparticles (Nano-Se) on inflammation induced in irradiated rats. Paw volume and nociceptive threshold were measured in carrageenan-induced paw edema and hyperalgesia model. Leukocytic count, tumor necrosis factor-α (TNF-α), prostaglandin E 2 (PGE 2 ), thiobarbituric acid reactive substances (TBAR), and total nitrate/nitrite (NOx) were estimated in the exudate collected from 6 day old air pouch model. Irradiated rats were exposed to 6 Gy gamma (γ)-irradiation. Nano-Se were administered orally in a dose of 2.55 mg/kg once before carrageenan injection in the first model and twice in the second model. The paw volume but not the nociceptive response produced by carrageenan in irradiated rats was higher than that induced in non-irradiated rats. Nano-Se were effective in reducing the paw volume in non-irradiated and irradiated rats but it did not alter the nociceptive threshold. The inflammation induced in irradiated rats increased all the estimated parameters in the exudate whereas; Nano-Se decreased their elevation in non-irradiated and irradiated rats. Nano-Se possess a potential anti-inflammatory activity on inflammation induced in irradiated rats.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it