The role and possible mechanism of lncRNA AC092159.2 in modulating adipocyte differentiation
Bibliographic record
Abstract
Obesity is a major risk factor for metabolic diseases, while adipocyte differentiation is closely related to obesity occurrence. Long noncoding RNAs (lncRNAs) are a unique class of transcripts in regulation of various biological processes. Using lncRNA microarray, we found lncRNA AC092159.2 was highly expressed in differentiated HPA-v and located ~247 bp upstream of the TMEM18, which was associated with BMI and obesity. We aimed to explore the role of AC092159.2 in adipogenesis and the underlying mechanisms. The effects of AC092159.2 gain- and loss-of-function on HPA-v adipogenesis were determined with lentivirus and siRNA-mediated cell transduction, respectively. Lipid accumulation was evaluated by oil red O staining; the expression of AC092159.2, TMEM18 and several adipogenesis makers in HPA-v were analyzed by qPCR/Western blot. We found that the expression of AC092159.2 gradually increased during HPA-v differentiation, and its expression in omental adipose tissue was positively related with BMI among 48 human subjects. Overexpression of AC092159.2 promoted adipocytes differentiation while knockdown of it led to an adipogenic defect. Moreover, the expression of AC092159.2 and TMEM18 were positively correlated during adipogenic differentiation. AC092159.2 overexpression boosted TMEM18 expression while AC092159.2 knockdown restrained TMEM18 expression. Further rescue experiments showed that TMEM18 knockdown partially restrained adipogenic differentiation in AC092159.2 overexpressed HPA-v and adipogenic defect caused by AC092159.2 knockdown could be rescued by TMEM18 overexpression. Luciferase reporter assays revealed that AC092159.2 had a transcriptional activation effect on TMEM18. We concluded that lncRNA AC092159.2 promoted human adipocytes differentiation possibly by regulating TMEM18.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".