[Retraction]MicroRNA-134 Promotes the Development of Atherosclerosis Via the ANGPTL4/LPL Pathway in Apolipoprotein E Knockout Mice
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
AIMS: Atherosclerosis is the most common cause of cardiovascular disease, such as myocardial infarction and stroke. Previous study revealed that microRNA (miR)-134 promotes lipid accumulation and proinflammatory cytokine secretion through angiopoietin-like 4 (ANGPTL4)/lipid lipoprotein (LPL) signaling in THP-1 macrophages. METHODS: ApoE KO male mice on a C57BL/6 background were fed a high-fat/high-cholesterol Western diet, from 8 to 16 weeks of age. Mice were divided into four groups, and received a tail vein injection of miR-134 agomir, miR-134 antagomir, or one of the corresponding controls, respectively, once every 2 weeks after starting the Western diet. After 8 weeks we measured aortic atherosclerosis, LPL Activity, mRNA and protein levels of ANGPTL4 and LPL, LPL/ low-density lipoprotein receptor related protein 1 Complex Formation, proinflammatory cytokine secretion and lipid levels. RESULTS: Despite this finding, the influence of miR-134 on atherosclerosis in vivo remains to be determined. Using the well-characterized mouse atherosclerosis model of apolipoprotein E knockout, we found that systemic delivery of miR-134 agomir markedly enhanced the atherosclerotic lesion size, together with a significant increase in proinflammatory cytokine secretion and peritoneal macrophages lipid contents. Moreover, overexpression of miR-134 decreased ANGPTL4 expression but increased LPL expression and activity in both aortic tissues and peritoneal macrophages, which was accompanied by increased formation of LPL/low-density lipoprotein receptor-related protein 1 complexes in peritoneal macrophages. However, an opposite effect was observed in response to miR-134 antagomir. CONCLUSIONS: These findings suggest that miR-134 accelerates atherogenesis by promoting lipid accumulation and proinflammatory cytokine secretion via the ANGPTL4/LPL pathway. Therefore, targeting miR-134 may offer a promising strategy for the prevention and treatment of atherosclerotic cardiovascular disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".