Anti‐apoptotic activity of porcine cFLIP in ovarian granulosa cell lines
Bibliographic record
Abstract
In mammalian ovaries, more than 99% of follicles undergo atresia during growth and development. Recently, we found that the expression of cellular FLICE-like inhibitory protein long form (cFLIP(L)) decreased during follicular atresia in granulosa cells of porcine ovaries. In humans and other species, both the short (cFLIP(S)) and long (cFLIP(L)) forms of cFLIP are considered to function as cell survival factors that inhibit death ligand receptor-mediated apoptosis. Since the anti-apoptotic activity of porcine cFLIP (pcFLIP) in granulosa cells had not been determined, we examined the effect of pcFLIP on survival using granulosa-derived cell lines. A human cervix adenocarcinoma cell line, HeLa, human ovarian granulosa tumor cell line, KGN, and porcine granulosa-derived cell line, JC-410, were used. By Western blotting, internal cFLIP(L) was detected in all cell lines, but only trace levels of cFLIP(S) were found in HeLa and KGN cells. To examine the anti-apoptotic activity, pcFLIP(S) or pcFLIP(L) was overexpressed in HeLa and KGN cells. Transfected cells in which pcFLIP(S) or pcFLIP(L) was overexpressed, survived the induction of Fas-mediated apoptosis, while almost all of the cells transfected with empty vector died. Then, we suppressed the expression of porcine cFLIP(S) and/or cFLIP(L) in JC-410 cells using small interfering RNA (siRNA). When both cFLIP(S) and cFLIP(L), or only cFLIP(L) was suppressed, cell viability declined significantly. From the results, we conclude that porcine cFLIP(S) and cFLIP(L) exhibit anti-apoptotic activity in granulosa-derived cells. It was strongly suggested that pcFLIP acts as a survival-promoting factor in granulosa cells and determines whether porcine ovarian follicles survive or undergo atresia.
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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".