Knockdown of circular RNA FSCN1 impairs dendritic cell immune function through regulating the NFKB and Foxo3 signaling pathways
Bibliographic record
Abstract
Abstract Circular RNAs (circRNAs) that are a new class of endogenously expressed non-coding RNAs produced from back splicing with a covalently closed loop structure have been emerging as an important gene regulator in the physiological and pathological development of cells. It remains unknown about roles of circRNAs in DCs. The objective of the study is to investigate the impact of circular RNA FSCN1 (circFSCN1) on dendritic cell immune function. Bone marrow derived dendritic cells were cultured in vitro and circRNA expression was detected by circRNA microarrays and qRT-PCR. The effect of circFSCN1 on DCs was studied. We found that the expression profiles of circRNAs were significantly different in mature immunogenic DCs v.s immature immunosuppressive DCs. circFSCN1 was the most significantly highly expressed in mature DCs compared with immature DCs. Treatment with immunosuppressive cytokines TGF β and GDF15 reduced circFSCN1 expression in DCs. Knockdown of circFSCN1 using siRNA reduced the phosphorylation of Rel Ap65, but increased phosphorylated Foxo3. Silencing of circFSCN1 impaired DCs to activate T cells, changed inflammatory cytokine production and enhanced Treg generation whereas circFSCN1 siRNA did not affect DC maturation. In conclusion, it is a first report to demonstrate that circFSCN1 is essential for DC immune response.
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) | 0.001 | 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".