Change and significance of the expression of c-kit and SCF following recovery from unilateral testicular torsion in rats
Bibliographic record
Abstract
PURPOSE: To investigate the change in expression levels of c-kit and SCF, and the protective effects of FSH on ischemia-reperfusion injury due to testicular torsion-detorsion. METHODS: 24 adult male SD rats were divided into three groups of 8: control group, testicular torsion group and FSH-treated group. The control group was treated with sham-operation. Animals in the testicular torsion and FSH-treated groups were subjected to unilateral 720 degrees counterclockwise testicular torsion for 2 hours and then reperfusion was allowed after detorsion. The FSH-treated group received intraperitoneal injection of FSH 15min before detorsion. Then, the rats were sacrificed and the testes were harvested. Histopathological changes were observed by light microscope, and the expression levels of c-kit, SCF in testicular tissue in the different groups were detected by Immunohistochemical assay and Quantitative Real-time RT-PCR analysis. Finally, the relative proportions of germ cells were measured by FCM. RESULTS: c-kit and SCF were positive expressed in 52.58% and 61.16% of testicular cells of control tissues, respectively. Decreases of c-kit and SCF positive cells (15.01% and 9.18%) were found in the testicular torsion group. After being treated by FSH, the number of positive cells increased (31.25% and 20.01%). Moreover, the c-kit and SCF mRNA expression was increased dramatically (P < 0.01) in response to FSH stimulation. Furthermore, the number of haploid, diploid and tetraploid cells has also increased significantly in drug-treated testes (P < 0.01). CONCLUSION: The mechanism of tissue damage in the testicular torsion model, includes changes in the expression of c-kit and SCF following torsion. Also, FSH has a protective effect on germ cells after unilateral testicular torsion, which was reflected by increased c-kit and SCF levels.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".