Primary cilium restricts TGF-β/SMAD signaling induced RIBEs in the co-culture model.
Bibliographic record
Abstract
Transforming growth factor β (TGF-β) is the predominant cytokine responding to ionizing radiation and participates in radiation induced bystander effects (RIBEs). Primary cilia (PC) coordinates with multiple signaling pathways, exhibit specialized functions in TGF-β signal transduction. Our previous studies using a medium transfer model revealed that PC modulates RIBEs by restricting TGF-β signaling. To further investigate PC's mechanistic role in RIBEs, proton microbeam radiation (MR) and partial radiation (PR) were used to arrange the co-culture bystander system. Key methodologies included siRNA-mediated PC formation modulation, inhibition of DNA damage response kinases ataxia telangiectasia-mutated gene (ATM), Ataxia telangiectasia and Rad3-related protein (ATR) or DNA-dependent protein kinase (DNApk), and quantitative analysis of γH2AX foci, cell proliferation, and reactive oxygen/nitrogen species (ROS/NO). The results showed that, firstly, PC inhibition in both PR and MR models significantly increased γH2AX foci formation and protein levels within 12 h while suppressing cell proliferation, which were reversed by TGF-β signaling inhibition. Secondly, although inhibition of ATM, ATR, or DNApk reduced γH2AX foci but resulted in decrease of proliferation rate. Scavenging ROS/NO similarly attenuated DNA damage but enhanced cell survival. Third, SMAD2/3 complex inhibition in PC-deficient bystander cells downregulated ATM/ATR expression and reduced intracellular NO/ROS levels. These results demonstrate that TGF-β1 drives RIBEs-associated DNA damage through canonical p-SMAD2/3 signaling, which amplifies ROS/NO production and hyperactivates ATM, ATR or DNApk. Crucially, PC acts as a regulatory role in DNA damages of RIBEs progression.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".