Nuclear Factor κB-Mediated Induction of Flice-Like Inhibitory Protein Prevents Tumor Necrosis Factor α-Induced Apoptosis in Rat Granulosa Cells1
Bibliographic record
Abstract
The purpose of the present studies was to examine the role and regulation of the antiapoptotic Flice-like inhibitory protein (FLIP) in rat granulosa cells by tumor necrosis factor alpha (TNFalpha) in vitro. Granulosa cells from immature rats primed with eCG were cultured in serum-free RPMI in the absence or presence of TNFalpha (20 ng/ml), cycloheximide (CHX, 10 microg/ml), SN50 (a specific inhibitor of nuclear factor kappaB [NFkappaB] translocation, 100 or 200 microg/ml), or a combination of these. (SM50, a mutated inactive peptide of SN50, was used as control.) Inhibitor kappaB (IkappaB; total and phosphorylated forms) and NFkappaB binding abilities were measured by Western blot and electrophoretic mobility shift assay, respectively. Apoptosis was assessed by in situ TUNEL assay, whereas FLIP mRNA levels were determined by semiquantitative reverse transcriptase-polymerase chain reaction. TNFalpha alone failed to induce granulosa cell death but significantly increased the apoptotic cell number in the presence of cycloheximide. TNFalpha significantly up-regulated the expression of the short form of FLIP (FLIP(S)) but not the long form (FLIP(L)). TNFalpha induced IkappaB phosphorylation and NFkappaB activation. SN50, but not SM50, attenuated TNFalpha-induced FLIP(S) expression and enhanced TNFalpha-induced apoptosis. Down-regulation of TNFalpha-induced FLIP(S) by FLIP(S) antisense expression enhanced TNFalpha-induced apoptosis. A full length of rat FLIP(S), with high homology to mouse FLIP(S) (85%), had been cloned and sequenced. These findings suggest that, in addition to its proapoptotic function, TNFalpha can induce an intracellular survival factor for the maintenance of follicular development. TNFalpha-induced, NFkappaB-mediated FLIP(S) expression is a determinant of granulosa cell fate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".