Epidermal ROCK2 induces AKT1/GSK3β/β-catenin, NFκB and dermal tenascin C; but enhanced differentiation and p53/p21 inhibit papilloma
Bibliographic record
Abstract
ROCK2 roles in epidermal differentiation and carcinogenesis have been investigated in mice expressing an RU486-inducible, 4HT-activated ROCK2 transgene (K14.creP/lslROCKer). RU486/4HT-mediated ROCKer activation induced epidermal hyperplasia similar to cutaneous oncogenic rasHa (HK1.ras); however ROCKer did not elicit papillomas. Instead, anomalous basal-layer ROCKer expression corrupted normal ROCK2 roles underlying epidermal rigidity/stiffness and barrier maintanance, resulting in premature keratin K1, loricrin and filaggrin expression. Also, hyperproliferative/stress-associated keratin K6 was reduced; possibly reflecting altered ROCK2 roles in epidermal rigidity and keratinocyte flexibility/migration during wound healing. Consistent with increased proliferation, K14.creP/lslROCKer hyperplasia displayed supra-basal-to-basal increases in activated p-AKT1, inactivated p-GSK3β ser9 and membranous/nuclear β-catenin expression together with weak NFκB, which were absent in equivalent HK1.ras hyperplasia. Furthermore, ROCKer-mediated increases in epidermal rigidity via p-MypT1 inactivation/elevated MLC, coupled to anomalous β-catenin expression, induced tenascin C-positive dermal fibroblasts. Alongside an altered ECM, these latent tenascin C-positive dermal fibroblasts may become putative pre-cancer-associated fibroblasts (pre-CAFs) and establish a susceptibility that subsequently contributes to tumour progression. However, anomalous differentiation was also accompanied by an immediate increase in basal-layer p53/p21 expression; suggesting that while ROCK2/AKT1/β-catenin activation increased keratinocyte proliferation resulting in hyperplasia, compensatory p53/p21 and accelerated differentiation helped inhibit papillomatogenesis.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".