Long non‐coding <scp>RNA MALAT</scp>1 regulates hyperglycaemia induced inflammatory process in the endothelial cells
Bibliographic record
Abstract
To examine whether the long non-coding RNA (lncRNA) metastasis associated lung adenocarcinoma transcript 1 (MALAT1) is altered in the endothelial cells in response to glucose and the significance of such alteration. We incubated human umbilical vein endothelial cells with media containing various glucose levels. We found an increase in MALAT1 expression peaking after 12 hrs of incubation in high glucose. This increase was associated with parallel increase in serum amyloid antigen 3 (SAA3), an inflammatory ligand and target of MALAT1 and was further accompanied by increase in mRNAs and proteins of inflammatory mediators, tumour necrosis factor alpha (TNF-α) and interleukin 6 (IL-6). Renal tissue from the diabetic animals showed similar changes. Such cellular alterations were prevented following MALAT1 specific siRNA transfection. Results of this study indicate that LncRNA MALAT1 regulates glucose-induced up-regulation of inflammatory mediators IL-6 and TNF-α through activation of SAA3. Identification of such novel mechanism may lead to the development of RNA-based therapeutics targeting MALAT1 for diabetes-induced micro and macro vascular complications.
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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) | 0.002 | 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".