Expression levels of plasma exosomal miR-124, miR-125b, miR-133b, miR-130a and miR-125b-1-3p in severe asthma patients and normal individuals with emphasis on inflammatory factors
Bibliographic record
Abstract
BACKGROUND: Identification of molecular markers, such as miRNAs is promising for the diagnosis of asthma and its clinical phenotypes. The aim of this study was to examine the changes in the expression of selected microRNAs in plasma exosomal fractions of severe asthma patients. The expression of miRNAs was determined in relation to the changes in inflammatory markers. METHOD: Severe asthma patients (n = 30) and healthy subjects (n = 30) were selected among the individuals referred to asthma and allergy clinic. Blood was collected from each participant to determine the serum high-sensitive C-reactive protein (hs-CRP) and total IgE. The exosomal fraction of plasma was isolated and processed for quantitation of miR-124, miR-125b, miR-133b, miR-130a and miR-125b-1-3p expression using quantitative real time-PCR (qRT-PCR). RESULTS: Serum hs-CRP and total IgE were significantly higher in asthma patients compared to controls. Expression of miR-124, miR-133b, and miR-130a was down-regulated in asthma patients as compared to controls (p < 0.0001). However, the expression of miR-125b was substantially higher in patients compared to controls (p < 0.0001). There was no significant difference in the expression of miR-125b-1-3p in the patients and controls. Data analysis revealed that among the miRNAs, changes in miR-125b in severe asthma patients were highly correlated with the serum levels of hs-CRP and IgE. CONCLUSION: Overexpression of miR-125b in severe asthma which was associated with serum IgE and hs-CRP may suggest that this molecule is linked to inflammatory reactions. Up-regulation of miR-125b together with decreased expression of miR-124, miR-133b, and miR-130a may suggest that this miRNA profile is useful for diagnosis and discrimination of clinical phenotypes of asthma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".