The MEK-ERK Signaling Pathway Is a Negative Regulator of Cartilage-specific Gene Expression in Embryonic Limb Mesenchyme
Bibliographic record
Abstract
The extracellular signal-regulated kinase (ERK) mitogen-activated protein kinase pathway, also known as the MEK-ERK kinase cascade, has recently been implicated in the regulation of embryonic cartilage differentiation. However, its precise role in this complex process remains controversial. To more thoroughly examine the role of the MEK-ERK kinase cascade in chondrogenesis, we analyzed the effects of two structurally different pharmacological inhibitors of MEK, the upstream kinase activator of ERK, on chondrocyte differentiation in micromass cultures of embryonic chick limb mesenchyme cells. We found that the MEK inhibitors, U0126 and PD98059, promote increased accumulation of cartilage-characteristic mRNA transcripts for type II collagen, aggrecan, and the transcription factor, Sox9. PD98059 treatment stimulated increased deposition of sulfated glycosaminoglycan into both Alcian blue-stainable cartilage matrix and the surrounding culture medium, whereas U0126 elevated glycosaminoglycan secretion into the medium fraction alone. Both MEK inhibitors increased total type II collagen protein accumulation in micromass culture and elevated the activity of a transfected type II collagen enhancer-luciferase reporter gene. Thus, pharmacological MEK inhibition induced increased expression of multiple chondrocyte differentiation markers. Conversely, transfection of limb mesenchyme cells with a constitutively active MEK1 plasmid resulted in a prominent decrease in the activity of a co-transfected type II collagen enhancer-luciferase reporter gene. Collectively, these findings support the hypothesis that signaling through the MEK-ERK kinase cascade may function as an important inhibitory regulator of embryonic cartilage differentiation.
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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".