Anti-Melanogenesis Effects of a Cyclic Peptide Derived from Flaxseed via Inhibition of CREB Pathway
Bibliographic record
Abstract
Linosorbs (Los) are cyclic peptides from flaxseed oil composed of the LO mixture (LOMIX). The activity of LO has been reported as being anti-cancer and anti-inflammatory. However, the study of skin protection has still not proceeded. In particular, there are poorly understood mechanisms of melanogenesis to LO. Therefore, we investigated the anti-melanogenesis effects of LOMIX and LO, and its activity was examined in mouse melanoma cell lines. The treatment of LOMIX (50 and 100 μg/mL) and LO (6.25-50 μM) suppressed melanin secretion and synthesis, which were 3-fold increased, in a dose-dependent manner, up to 95%. In particular, [1-9-NαC]-linusorb B3 (LO1) and [1-9-NαC]-linusorb B2 (LO2) treatment (12.5 and 25 μM) highly suppressed the synthesis of melanin in B16F10 cell lines up to 90%, without toxicity. LOMIX and LOs decreased the 2- or 3-fold increased mRNA levels, including the microphthalmia-associated transcription factor (MITF), Tyrosinase, tyrosinase-related protein 1 (TYRP1), and tyrosinase-related protein 2 (TYRP2) at the highest concentration (25 μM). Moreover, the treatment of 25 μM LO1 and LO2 inhibited the expression of MITF and phosphorylation of upper regulatory proteins such as CREB and PKA. Taken together, these results suggested that LOMIX and its individual LO could inhibit melanin synthesis via downregulating the CREB-dependent signaling pathways, and it could be used for novel therapeutic materials in hyperpigmentation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".