Intracellular Calreticulin Regulates Multiple Steps in Fibrillar Collagen Expression, Trafficking, and Processing into the Extracellular Matrix
Bibliographic record
Abstract
Calreticulin (CRT), a chaperone and Ca(2+) regulator, enhances wound healing, and its expression correlates with fibrosis in animal models, suggesting that CRT regulates production of the extracellular matrix. However, direct regulation of collagen matrix by CRT has not been previously demonstrated. We investigated the role of CRT in the regulation of fibrillar collagen expression, secretion, processing, and deposition in the extracellular matrix by fibroblasts. Mouse embryonic fibroblasts deficient in CRT (CRT(-/-) MEFs) have reduced transcript levels of fibrillar collagen I and III and less soluble collagen as compared with wild type MEFs. Correspondingly, fibroblasts engineered to overexpress CRT have increased collagen type I transcript and protein. Collagen expression appears to be regulated by endoplasmic reticulum (ER) calcium levels and intracellular CRT, because thapsigargin treatment reduced collagen expression, whereas addition of exogenous recombinant CRT had no effect. CRT(-/-) MEFs exhibited increased ER retention of collagen, and collagen and CRT were co-immunoprecipitated from isolated cell lysates, suggesting that CRT is important for trafficking of collagen through the ER. CRT(-/-) MEFs also have reduced type I procollagen processing and deposition into the extracellular matrix. The reduced collagen matrix deposition is partly a consequence of reduced fibronectin matrix formation in the CRT-deficient cells. Together, these data show that CRT complexes with collagen in cells and that CRT plays critical roles at multiple stages of collagen expression and processing. These data identify CRT as an important regulator of collagen and suggest that intracellular CRT signaling plays an important role in tissue remodeling and fibrosis.
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 | 0.000 | 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".