Periostin localizes to cells in normal skin, but is associated with the extracellular matrix during wound repair
Bibliographic record
Abstract
Epidermal tissue repair represents a complex series of temporal and dynamic events resulting in wound closure. Matricellular proteins, not normally expressed in quiescent adult tissues, play a pivotal role in wound repair and associated extracellular matrix remodeling by modulating the adhesion, migration, intracellular signaling, and gene expression of inflammatory cells, pericytes, fibroblasts and keratinocytes. Several matricellular proteins show temporal expression during dermal wound repair, but the expression pattern of the recently identified matricellular protein, periostin, has not yet been characterized. The primary aim of this study was to assess whether periostin protein is present in healthy human skin or in pathological remodeling (Nevus). The second aim was to determine if periostin is expressed during dermal wound repair. Using immunohistochemistry, periostin reactivity was detected in the keratinocytes, basal lamina, and dermal fibroblasts in healthy human skin. In pathological nevus samples, periostin was present in the extracellular matrix. In excisional wounds in mice, periostin protein was first detected in the granulation tissue at day 3, with levels peaking at day 7. Periostin protein co-localized with alpha-smooth muscle actin-positive cells and keratinocytes, but not CD68 positive inflammatory cells. We conclude that periostin is normally expressed at the cellular level in human and murine skin, but additionally becomes extracellular during tissue remodeling. Periostin may represent a new therapeutic target for modulating the wound repair 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 | 0.000 |
| 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".