Normoxic Expression of Hypoxia‐Inducible Factor 1 in Rat Leydig Cells In Vivo and In Vitro
Bibliographic record
Abstract
Hypoxia-inducible factors (HIF) are transcription factors that serve essential regulatory roles in cellular and molecular responses to oxygen debt. HIFs are composed of hypoxia-dependent α subunits (1α, 2α, 3α) and an oxygen-independent β subunit. Previously we demonstrated that HIF-1, the master regulator of hypoxic responses, is expressed in the adult rat testis. We hypothesized that HIF-1 is involved in regulating responses to oxygen tension in the testis. Goals of this study were to determine if HIF-2α and HIF-3α are expressed in rat testis, identify testis cell types that express HIF-1α, and examine patterns of testicular HIF-1α protein expression under conditions of ischemia and hypoxia in vivo and in vitro. Reverse transcriptase polymerase chain reaction revealed that mRNA for Hif-1α, Hif-2α, and Hif-3α is expressed in the testis. The HIF-1α protein is the predominant subunit in testis. HIF-1α protein was abundant in normoxic testis, and its levels remained unchanged following ischemia created by surgically induced testicular torsion and reperfusion. Immunoblot and immunocytochemical experiments demonstrated that Leydig cells are the major source of HIF-1α in normoxic and hypoxic testes. To examine potential mechanisms of testicular HIF-1 stabilization, nuclear proteins from Leydig cells cultured in 5% or 21% oxygen, or cells cultured with H₂O₂, were analyzed by immunoblotting. Levels of HIF-1α were significantly diminished in 5% or 21% oxygen cultures compared with freshly isolated cells. Treating Leydig cells with H₂O₂ as a source of reactive oxygen species did not affect HIF-1α levels. High levels of constitutively expressed HIF-1α in normoxic Leydig cells suggest potentially unique roles for HIF-1 in Leydig cell responsiveness to oxygen.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".