<i>Cistanche tubulosa</i>ethanol extract mediates rat sex hormone levels by induction of testicular steroidgenic enzymes
Bibliographic record
Abstract
CONTEXT: Plants of the genus Cistanche Hoffmg. et Link (Orobanchaceae) are usually used as ethno-medicine in Eastern Asia. Pharmacology studies have shown that Cistanche possesses an androgen-like effect; however, the exact mechanism is unclear. OBJECTIVE: The present study determines the effect of ethanol extract of Cistanche tubulosa (Schenk) R. Wight stem (CTE) on hormone levels and testicular steroidogenic enzymes in rats. MATERIALS AND METHODS: Phenylethanoid glycoside content of CTE was detected by UV spectrophotometry. Rats were fed with different doses of CTE (0.2, 0.4, and 0.8 g/kg) by intragastric administration for 20 d. Sperm parameters were measured by staining and counting method. The level of progesterone and testosterone in serum was quantified by radioimmunoassay. The expression levels of cholesterol side-chain cleavage enzyme (CYP11A1), 17α-hydroxylase/17, 20-lyase (CYP17A1), and a liver metabolic enzyme (CYP3A4) in the microsome were assessed by immunohistochemical staining or/and western blot analysis. RESULTS: The study illustrates that the administration of CTE (0.4 and 0.8 g/kg) increased sperm count (2.3- and 2.7-folds) and sperm motility (1.3- and 1.4-folds) and decreased the abnormal sperm (0.76- and 0.6-folds). The serum level of progesterone and testosterone in rats was also increased by CTE administration (p < 0.05). Results of immunohistochemistry and western blot analysis confirmed that the expression of CYP11A1, CYP17A1, and CYP3A4 was enhanced by CTE (p < 0.05). It was also found that high-dose of CTE can cause mild hepatic edema. CONCLUSION: Our results suggest that the increase in sex hormone levels could be mediated by the induction of testicular steroidogenic enzymes.
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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) | 0.002 | 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".