MicroRNA Signature and Cellular Characterization of Undifferentiated and Differentiated House Ear Institute-Organ of Corti 1 (HEI-OC1) Cells
Bibliographic record
Abstract
Abstract MicroRNAs (miRNAs) regulate gene expressions and control a wide variety of cellular functions. House Ear Institute-Organ of Corti 1 (HEI-OC1) cells are widely used to screen ototoxic drugs and to investigate cellular and genetic alterations in response to various conditions. HEI-OC1 cells are almost exclusively studied under permissive conditions that promote cell replication at the expense of differentiation. Many researchers suggest that permissive culture condition findings are relevant to understanding human hearing disorders. The mature human cochlea however consists of differentiated cells and lacks proliferative capacity. This study therefore aimed to compare the miRNA profiles and cellular characteristics of HEI-OC1 cells cultured under permissive (P-HEI-OC1) and non-permissive (NP-HEI-OC1) conditions. A significant increase in the level of expression of tubulin β1 class VI(Tubb1), e-cadherin(Cdh1),espin(Espn),and SRY (sex determining region Y)-box2(Sox2)mRNAs was identified in non-permissive cells compared with permissive cells (P < 0.05, Kruskal–Wallis H test, 2-sided). miR-200 family, miR-34b/c, and miR-449a/b functionally related cluster miRNAs, rodent-specific maternally imprinted geneSfmbt2intron 10thcluster miRNAs (-466a/ -467a), and miR-17 family were significantly (P < 0.05, Welch’st-test, 2-tailed) differentially expressed in non-permissive cells when compared with permissive cells. Putative target genes were significantly predominantly enriched in mitogen-activated protein kinase (MAPK), epidermal growth factor family of receptor tyrosine kinases (ErbB), and Ras signaling pathways in non-permissive cells compared with permissive cells. This distinct miRNA signature of differentiated HEI-OC1 cells could help in understanding miRNA-mediated cellular responses in the adult cochlea.
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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".