Mechanism of Action of an Environmentally Relevant Organochlorine Mixture in Repressing Steroid Hormone Biosynthesis in Leydig Cells
Bibliographic record
Abstract
Within Leydig cells, steroidogenesis is induced by the pituitary luteinizing hormone (LH). The binding of LH to its receptor increases cAMP production, which then activates the expression of genes involved in testosterone biosynthesis. One of these genes codes for the steroidogenic acute regulatory (STAR) protein. STAR is part of a complex that shuttles cholesterol, the precursor of all steroid hormones, through the mitochondrial membrane where steroidogenesis is initiated. Organochlorine chemicals (OCs) are environmental persistent organic pollutants that are found at high concentrations in Arctic areas. OCs are known to affect male reproductive health by decreasing semen quality in different species, including humans. We previously showed that an environmentally relevant mixture of OCs found in Northern Quebec disrupts steroidogenesis by decreasing STAR protein levels without affecting the transcription of the gene. We hypothesized that OCs might affect STAR protein stability. To test this, MA-10 Leydig cell lines were incubated for 6 h with vehicle or the OCs mixture in the presence or absence of 8Br-cAMP with or without MG132, an inhibitor of protein degradation. We found that MG132 prevented the OC-mediated decrease in STAR protein levels following 8Br-cAMP stimulation. However, progesterone production was still decreased by the OC mixture, even in the presence of MG132. This suggested that proteins involved in steroid hormone production in addition to STAR are also affected by the OC mixture. To identify these proteins, a whole cell approach was used and total proteins from MA-10 Leydig cells exposed to the OC mixture with or without stimulation with 8Br-cAMP were analyzed by 2D SDS-PAGE and LC-MS/MS. Bioinformatics analyses revealed that several proteins involved in numerous biological processes are affected by the OC mixture, including proteins involved in mitochondrial transport, lipid metabolism, and steroidogenesis.
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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".