Protegrin-1 Regulates Porcine Granulosa Cell Proliferation via the EGFR-ERK1/2/p38 Signaling Pathway in vitro
Bibliographic record
Abstract
Antimicrobial peptides (AMPs) are traditionally known to be essential components in host defense via their broad activities against bacteria, fungi, viruses, and protozoa. Their immunomodulatory properties have also recently received considerable attention in mammalian somatic tissues of various species. However, little is known regarding the role of AMPs in the development and maturation of ovarian follicles. Protegrin-1 (PG-1) is an antimicrobial peptide which is known to have potent antimicrobial activity against both gram positive and negative bacteria. Here we report that the PG-1 is present in the porcine ovarian follicular fluid. Treatment of granulosa cell with PG-1 enhanced granulosa cell proliferation in a dose-dependent manner. This is accompanied by increased expression of cell-cycle progression-related genes such as cyclin D1(CCND1), cyclin D2 (CCND2), and cyclin B1(CCNB1). Additionally, Western blot analysis showed that PG-1 increased phosphorylated epidermal growth factor receptor (EGFR), and the phosphorylated-/total extracellular signal-regulated kinase (ERK)1/2 ratio. Pretreatment with either U0126, a specific ERK1/2 phosphorylation inhibitor, or EGFR kinase inhibitor, AG1478, blocked the PG-1 induced proliferation. Moreover, luciferase reporter assay revealed that ETS domain-containing protein-1 (Elk1) C/EBP homologous protein (CHOP), and the transcription activators downstream of the MAPK pathway, were activated by PG-1. These data collectively suggest that PG-1 may regulate pig granulosa cell proliferation via EGFR-MAPK pathway., Hence, our finding offers insights into the role of antimicrobial peptides on follicular development regulation.
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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".