Endoplasmic reticulum stress and steroidogenic dysfunction in Leydig cells: Molecular mechanisms of UPR-mediated testosterone regulation
Bibliographic record
Abstract
This review aims to synthesize current evidence on how endoplasmic reticulum (ER) stress affects steroidogenic function in Leydig cells. It explores the mechanisms by which ER stress activates the unfolded protein response (UPR) and autophagy pathways, ultimately influencing testosterone production and cellular homeostasis. The central research question addresses how ER stress-induced signaling modulates the transcriptional regulation of key steroidogenic enzymes and contributes to age-related declines in androgen synthesis. A comprehensive literature review was conducted using recent findings from molecular, cellular, and animal studies focusing on ER stress signaling in Leydig cells. Studies examining the roles of UPR branches (PERK, IRE1, and ATF6), autophagy pathways, and pharmacological or natural compounds modulating ER stress were analyzed to identify the regulatory mechanisms being involved and potential therapeutic implications. Evidence indicates that unresolved ER stress impairs testosterone biosynthesis by suppressing the expression of genes related to steroidogenesis. Specifically, activations of XBP1, ATF4 and ATF6, as well as their nuclear translocations, may lead to the transcriptional repression of these genes. Conversely, pharmacological ER stress inhibitors and natural antioxidants may restore these protein levels, enhance testosterone production, and improve Leydig cell function. A thorough understanding of the UPR and autophagy in Leydig cells is critical for addressing male reproductive health. ER stress is established as a key factor in the pathophysiology of impaired steroidogenesis. Therefore, targeting these stress response pathways presents a promising strategy for developing novel therapeutic interventions for testosterone deficiency and associated reproductive disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".