hsa_circ_0001818 regulates the function of macrophages in sepsis by inhibiting miR-17-3p, miR-433-3p, and miR-642a-5p
Bibliographic record
Abstract
Sepsis is a leading cause of death due to severe infections. Macrophages are important players in regulating the development of sepsis. Notably, hsa_circ_0001818 is highly expressed in the serum exosomes of sepsis patients and has shown potential as a diagnostic marker for the condition. However, its regulatory role in sepsis remains unclear. Here, we reported that hsa_circ_0001818 expression in macrophages is increased in sepsis. After hsa_circ_0001818 silencing, the apoptotic rate and release of inflammatory cytokines decreased, while phagocytic function of macrophages increased. In contrast, after hsa_circ_0001818 overexpression, the apoptotic rate and the release of inflammatory factors increased, whereas phagocytic function of macrophages decreased. In addition, mechanistic studies and rescue experiments confirmed that hsa_circ_0001818 adsorbs miR-17-3p, miR-433-3p, and miR-642a-5p as sponges, competitively inhibiting the expression of downstream target genes and regulating macrophage function. That is, hsa_circ_0001818 increased the apoptosis rate of macrophages through the miR-17-3p/caspase-3 (CASP3) axis, inhibited the phagocytic function of macrophages by adsorbing miR-433-3p and miR-642a-5p, and increased the secretion level of macrophage inflammatory factors by regulating the zinc finger and BTB domain-containing 20 (ZBTB20)/nuclear factor kappa-B (NF-κB) axis through miR-433-3p and miR-642a-5p. This study revealed the important role of hsa_circ_0001818 in sepsis and provided a new theoretical basis for the precise treatment of sepsis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".