Abstract 113: Screening of MicroRNAs Expressed in Isolated Cells of Human Abdominal Aortic Aneurysm for the Identification of Potential Biomarkers
Bibliographic record
Abstract
Abdominal aortic aneurysm (AAA) is a vascular asymptomatic disease that is one of the leading causes of death in developed countries. Identifying biomarkers for AAA that can be detected easily in blood, before rupture could be useful. The aim of this study was to investigate the potentiality of miRNAS as biomarkers of AAA by performing a profiling of miRNAs expressed in major cells present in the human AAA tissue. The inflammatory cells as macrophages M1 and M2 and smooth muscle cells (SMC) were located by immunohistochemistry in 20 human AAA biopsies, showing a specific distribution towards the aneurysmal aortic wall. The cells were isolated by laser microdissection (LMD) from 20 human AAA biopsies obtained during surgical repair and control SMC from 14 healthy aortic biopsies harvested during organs multiretrieval. RNA extracted from 2 samples of each LMD isolated cells was screened on human miRNAs microarray. MiRNAs were selected with at least a 2-fold change and a detection value threshold corresponding to the value of miR-29b, described in experimental AAA models. Out of the 850 human miRNAs tested for each sample, 408 were found to be present in AAA. Thirty miRNAs were common to each tested cells. Fifty-three miRNAs were found in SMC, of which 12 were specific to AAA compared to control aortas; 86 miRNAs were found in macrophages, of which 11 were specific to M1 macrophages, 37 to M2 macrophages and 38 common to both subtypes. Ten miRNAs were selected to be validated by quantitative RT-PCR in LMD isolated healthy SMC and aneurysmal SMC, M1 and M2 macrophages. We validated 4 miRNAs to be overexpressed in M1 macrophages and 1 overexpressed in M2 macrophages. Two miRs were validated to be less expressed in aneurysmal SMC compared to SMC from normal aortas. MiR-29b expression was specifically down-regulated in aneurysaml SMC compared to normal SMC. In conclusion, the analysis of isolated cells allows to discriminate the miRNAs specifically expressed in inflammatory and vascular cells in AAA and to determine other miRNAs than those described in experimental AAA models as potential biomarkers of AAA.
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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 | 0.001 |
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".