Nuclear Factor-κB-Mediated X-Linked Inhibitor of Apoptosis Protein Expression Prevents Rat Granulosa Cells from Tumor Necrosis Factor α-Induced Apoptosis
Bibliographic record
Abstract
Although X-linked inhibitor of apoptosis protein (Xiap) is an important intracellular suppressor of apoptosis in a variety of cell types and is present in ovary, its physiological role in follicular development remains unclear. The purpose of the present studies was to examine the modulatory role of Xiap in the proapoptotic action of tumor necrosis factor-alpha (TNFalpha) in rat granulosa cells. Granulosa cells from equine CG-primed immature rats were plated in RPMI 1640 medium containing 10% FCS and subsequently cultured in serum-free RPMI in the absence or presence of TNFalpha (20 ng/ml), the protein synthesis inhibitor cycloheximide (10 microM), and/or adenoviral Xiap sense or antisense complementary DNA. TNFalpha alone failed to induce granulosa cell death, but in the presence of cycloheximide, it markedly increased the number of apoptotic granulosa cells (as assessed by in situ terminal deoxynucleotidyl transferase-mediated deox-UTPbiotin end labeling and DNA fragmentation analysis). Western analysis indicated that TNFalpha alone increased the Xiap protein level, a response significantly reduced by adenoviral Xiap antisense expression. Down-regulation of Xiap expression by antisense complementary DNA induced granulosa cell apoptosis, which was potentiated by the cytokine. Inhibition of nuclear factor-kappaB activation by N-acetyl-cysteine and SN50 suppressed Xiap protein expression and enhanced apoptosis induced by TNFalpha. The latter phenomenon was readily attenuated by adenoviral Xiap sense expression. In conclusion, these findings suggest that Xiap is an important intracellular modulator of the TNFalpha death signaling pathway in granulosa cells. Its expression is regulated by the TNFalpha via a nuclear factor-kappaB-mediated mechanism.
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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) | 0.001 | 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".