Combined Effects of Defatted Hydrolyzed Collagen from Salmon Skin and Vitamin C on Proliferation and Migration of Human Fibroblast Cell
Bibliographic record
Abstract
Skin injury causes fibroblast dysfunction and lowers collagen production. Safe, functional ingredients such as vitamin C (Vit C) and fish hydrolyzed collagen (HC) have been used to alleviate this problem. Defatted HC from salmon (Oncorhynchus nerka) skin could be a potential functional ingredient with skin nourishment activity. This study aimed to investigate the combined effects of HC and Vit C on the proliferation and migration of human dermal fibroblast (HDF). Molecular weight ranging from 102 Da to 10,175 Da and high imino acid content were found in HC. HC (0–800 µg/mL) or vitamin C (Vit C) (0.01–100 µg/mL) was applied for HDF treatment. Higher cell proliferation was found by adding HC at 50 µg/mL or Vit C at 0.01 µg/mL compared to the control and those treated with both compounds at other levels (p < 0.05). Cells treated with HC (50 µg/mL) combined with Vit C (0.01 µg/mL) (HC+Vit C) showed higher proliferation, migration, and lamellipodia formation of HDF cells than those treated with HC or Vit C alone. Moreover, all the samples tested could stimulate the proliferation and migration of HDF cells via FAK/Akt and ERK/p38 MAPK signaling pathways. Thus, HC combined with Vit C could be a promising functional ingredient for skin nourishment and would healing.
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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".