Identification of miR-141 as a Regulator of Epidermal Homeostasis
Bibliographic record
Abstract
MicroRNAs, small endogenous noncoding RNAs, are involved in the regulation of epidermal homeostasis. Among them, miR-203 was the most described and expressed in human epidermis, promoting keratinocyte (KC) differentiation by repressing genes involved in proliferation. To identify other microRNAs involved in this process, the miRNomes of normal human KCs cultured in monolayer (2-dimensional) or in 3-dimensional reconstructed skin were compared. Besides miR-203, miR-141 was one of the most expressed microRNAs in 3-dimensional culture and was overexpressed in 3-dimensional versus 2-dimensional condition, that is, during KC differentiation. Functional experiments revealed that, mostly expressed in the basal layer, miR-141 decreased KC proliferation and clonogenicity while promoting differentiation. Target prediction algorithm coupled with transcriptomic data of KCs overexpressing miR-141 as well as 3' untranslated region luciferase assays highlighted CCND2 mRNA as a direct target of miR-141, leading to its downregulation by miR-141 overexpression. Finally, CCND2 silencing decreased KC proliferation and induced differentiation, revealing that miR-141 action was mediated by CCND2. MiR-141 features were also compared with those of miR-203 in parallel experiments. Although miR-141 displayed functions similar to those of miR-203, it exhibited different localization and targets, suggesting a joint participation of miR-141 and miR-203 in engaging and maintaining KC toward differentiation, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".