<i>NRAS</i> promotes the proliferation of melanocytes to increase melanin deposition in Rex rabbits
Bibliographic record
Abstract
Melanocytes play a major role in the formation of mammalian fur color and are regulated by several genes. Despite playing the pivotal role in the study of melanoma, the mechanistic role of NRAS (neuroblastoma RAS viral oncogene homolog) in the formation of mammalian epidermal color is still elusive. First of all, the expression levels of NRAS mRNA and protein in the dorsal skin of different colored Rex rabbits were detected by qRT-PCR and Western blot. Then, the subcellular localization of NRAS was identified in melanocytes by indirect immunofluorescence. Next, the expression of NRAS was overexpressed and knocked down in melanocytes, and its efficiency was verified by qRT-PCR and Western blot. Subsequently, NaOH, CCK-8, and Annexin V-FITC were used to verify the changes in melanin content, proliferation, and apoptosis in melanocytes. Finally, we analyzed the regulation of NRAS on other genes ( MITF, TYR, DCT, PMEL, and CREB) that affect melanin production. In silico studies showed NRAS as a stable and hydrophilic protein, and it is localized in the cytoplasm and nucleus of melanocytes. The mRNA and protein expression levels of NRAS were significantly different in skin of different colored Rex rabbits, and the highest level was found in black skin ( P < 0.01). Moreover, the NRAS demonstrated impact on the proliferation, apoptosis, and melanin production of melanocytes ( P < 0.05), and the strong correlation of NRAS with melanin-related genes was evidently observed ( P < 0.05). Our results suggested that NRAS can be used as a gene that regulates melanin production and controls melanocyte proliferation and apoptosis, providing a new theoretical basis for studying the mechanism of mammalian fur color formation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".