Evaluation of DNA methylation status of toll‐like receptors 2 and 4 promoters in Behcet's disease
Bibliographic record
Abstract
BACKGROUND: Altered innate immune function plays an important role in the initiation of inflammatory response in Behcet's disease (BD). Toll-like receptors (TLRs) are the master regulators of the innate immune system. Because the role of TLRs remains unknown in the pathogenesis of BD, the present study aimed to evaluate the expression levels and methylation status of the TLR2 and TLR4 promoters in patients with BD. METHODS: In the present study, Iranian Azeri BD patients (n = 47) with an active (n = 22) and inactive (n = 25) period, and healthy controls (n = 61), were matched according to age, sex and ethnicity. TLR2 and TLR4 genes promoter CpG islands were predicted with the Eukaryotic Promoter Database (https://epd.vital-it.ch). Methylated DNA immunoprecipitation (MeDIP) was conducted. RESULTS: The results showed that mRNA of TLR4 was significantly increased in the peripheral blood mononuclear cells (PBMCs) of BD patients with an active phase compared to the control group. Differences in mRNA of TLR4 between the inactive BD and control groups were not significant. Differences in TLR2 mRNA levels in the PBMCs of the active and inactive phase BD and control groups were not significant. The methylation rate of TLR4 gene promoter was significantly lower in the active and inactive BD groups compared to the control group. The difference between the active and inactive BD groups was not significant. There was no significant difference in the methylation rates of the TLR2 gene between studied groups. CONCLUSIONS: Our preliminary findings suggest that the hypomethylation of TLR4 gene may be involved in the pathogenesis of BD via increasing TLR4 expression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".