Recent progress on the role of cellular communication network factors (CCN) 3, 4 and 6 in regulating adiposity, liver fibrosis and pancreatic islets
Bibliographic record
Abstract
CCN/WISP (cellular communication network factors, or Wnt-inducted secreted proteins) family of proteins consists of six extracellular matrix (ECM)-associated proteins that regulate development, cell adhesion and proliferation, ECM remodeling, inflammation, and tumorigenesis. In the last two decades, metabolic regulation by these matricellular proteins has been studied extensively, several excellent reviews have covered the roles of CCN1, -2 and - 5. In this brief review, we will focus on those lesser-known members and more recent discoveries, together with other recent articles presenting a more complete picture of the current state of knowledge. We have found that CCN2, -4, and - 5 promote pancreatic islet function, while CCN3 plays a unique and negative role. CCN3 and - 4 are pro-adiposity leading to insulin resistance, but CCN5 and - 6 are anti-adiposity. While CCN2 and - 4 promote tissue fibrosis and inflammation, all other four members are clearly anti-fibrotic. As for cellular signaling, they are known to interact with integrins, other cell membrane proteins and ECM thereby regulate Akt/protein kinase B, myocardin-related transcription factor (MRTF), and focal adhesion kinase. Yet, a cohesive mechanism of action to comprehensively explain those major functions is still lacking.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".