Molecular and cell biology of porcine HSP47 during wound healing: complete cDNA sequence and regulation of gene expression
Bibliographic record
Abstract
Heat shock protein (HSP) 47 is a major stress-inducible protein that is localized to the endoplasmic reticulum of avian and mammalian cells and is thought to act as a molecular chaperone specific for the processing of procollagen. However, limited information is available regarding the regulation of HSP47 during wound healing. Using a polymerase chain reaction strategy, screening of a cDNA library, and RACE-polymerase chain reaction approaches, the sequence of a full-length porcine HSP47 cDNA has been identified. The cDNA contained 2096 bp that encodes for an 18 amino acid signal peptide and a mature protein coding region consisting of 401 amino acid residues. It also included 108 bp of the 5' noncoding region and a 731-bp 3' noncoding region. The deduced amino acid is 83% identical to chicken, 87% identical to mouse, 88% identical to rat, and 91% identical to human HSP47. It also shares between 26% and 30% identity with different members of the serine protease inhibitor superfamily. The protein contains a RDEL endoplasmic reticulum retention signal, and two potential glycosylation sites. All of these features are characteristic of HSP47 in higher vertebrates. Heat shock treatment of porcine fibroblasts led to up-regulation of HSP47 at both the transcriptional and translational levels. HSP47 protein levels were also up-regulated during skin wound healing in a pig model. Moreover, a higher molecular weight complex at approximately 140 Kda containing HSP47 was detected at the stage of healing that was coincident with the maximal transcriptional expression of HSP47 during wound healing in this animal model. Further investigation of how HSP47 is regulated during normal and abnormal skin wound healing may lead to new therapeutic approaches to improve the healing process.
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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 | 0.001 |
| 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) | 0.002 | 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".