Effect of Long-Term Treatment with Fluoxetine, Clomipramine and St. John's Wort Extract on Bone Turnover in Female Irradiated Rats
Bibliographic record
Abstract
Aim: The study aimed at evaluating the bone turnover rate in irradiated female rats treated daily with fluoxetine, clomipramine or St. John’s wort extract for 8 weeks. Material and Methods: 40 rats were randomly classified into 5 experimental groups: normal, irradiated control, irradiated fluoxetine, irradiated clomipramine and irradiated St. John’s wort extract treated groups. The irradiated animals were exposed to a total dose of 15 Gy, fractionated over 5 weeks to small doses each of 1 Gy (day after day). Bone turnover rate biomarkers [serum osteocalcin (OC), urinary hydroxyproline/ creatinine ratio (Hpr/ Cr), urinary calcium/creatinine ratio (Ca/Cr)], hypothalamic pituitary adrenal [serum corticosterone], thyroid activities [serum thyroxin (T4) and thyrotrophin (TSH)], antioxidant [serum total antioxidant capacity (TAC) and malondialdehyde (MDA)] and pro-inflammatory biomarkers [serum tumor necrosis factor-alpha (TNF-α)] were done after 8 weeks from the 1st exposure to radiation. Histopathological investigations were also performed. Results: The present results revealed that irradiation induced a significant decrease in serum OC by 43.6%, and a significant increase of Hpr/ Cr and Ca/Cr by 186.4% and 192.4%, respectively. Irradiated rats showed also a significant increase in serum corticosterone, TNF-α and MDA as well as a significant decrease in serum T4, TSH levels and TAC. Treatment of irradiated rats with St. John’s wort extract, fluoxetine or clomipramine ameliorated most of the changes caused by bone-irradiation. The latter findings were confirmed by histological examination of bone tissue. Conclusions: St. John’s wort extract offers a therapeutic potential on bone comparable to traditional antidepressants like fluoxetine or clomipramine in irradiated female 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.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".