The devastating effect of exposure to high irradiation dose on liver and the performance of synthesized nano-Hap in relieve the associated symptoms in rats
Bibliographic record
Abstract
Ionizing radiation is one of the environmental factors that may contribute to liver dysfunction through a mechanism involving oxidative stress. This investigation studied the possible therapeutic effects of nano-HAp on hepatotoxicity in rats induced with gamma (γ) radiation. The study was carried out using 3 groups with 10 rats in each. Group 1 comprised the non-irradiated control rats, whereas the rats in groups 2 and 3 received a single dose of 10 Gy γ-radiation. The rats in group 3 were treated with nano-HAp [100 mg·(kg body mass) −1 ] once a week for 2 weeks starting the day after irradiation. The results showed that the rats exposed to γ-radiation had fragmented DNA, and significantly decreased levels of liver tissue enzymes such as paraoxonase 1, gamma glutamyl, alanine aminotransferase (ALT), and aspartate aminotransferase (AST). Pro-inflammatory factors such as interleukin (IL)-2, IL-6, tumor necrosis factor alpha (TNF-α), and interferon gamma (IFN-γ) in tissue were significantly increased compared with the controls. Also, exposure to γ-radiation significantly decreased the activity of superoxide dismutase and glutathione oxidase and increased lipid peroxidation in liver tissue. These effects were accompanied by severe histopathological changes to the hepatocytes. Intravenous injection of nano-HAp after irradiation has significant therapeutic potential against irradiation-induced liver damage because the treatment with nano-HAp restored antioxidant activity in the liver, antagonized the significant changes in the levels of IL-2, IL-6, TNF-α, IFN-γ, and restored the tissue level of paraoxonase 1, gamma glutamyl, ALT, and AST. Administering nano-HAp seemed to relieve the pathological changes induced by γ-radiation. Based on these results, it could be concluded that nano-HAp may have a therapeutic effect against liver dysfunction induced by γ-radiation through antagonizing the generation of free radicals and enhancing the antioxidant defense mechanisms.
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 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 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".