Deciphering Stem Cell from Apical Papilla - Macrophage Choreography in Inflammatory Environment using a Novel 3D Organoid
Bibliographic record
Abstract
The aim of this study is twofold: (1) develop and characterize a 3D binary-cells tissue construct to study SCAP (stem-cell-from-apical-papilla) - MQ (macrophage) interaction, and (2) investigate the interactions and cell signaling mechanisms between SCAP-MQ under pro-inflammatory/anti-inflammatory environments in the organoid system. 3D (dimensional) image analysis and cytokine profiles were employed in this investigation. It was demonstrated that the SCAP self-organized as a cap-shaped organoid in the tissue construct. The pro-inflammatory/anti-inflammatory environments influenced SCAP-MQ interactions, resulting in altered cell volume, cell viability, cell morphology and structural organization in 3D tissue construct. The increased cytokine/chemokine profiles at the earlier phase of pro-inflammation, increased ratio of pSTAT6/pSTAT1 and decreased CD206/80 indicated a distinct polarization behavior in macrophages during repair. Conversely, equal ratio of pSTAT6/pSTAT1 and late increase of CD206/80 with amplified secretion of IL-1RA, IL-10 and TGF-1 in the anti-inflammatory environment directed alternative macrophage polarization, while promoting SCAP differentiation and tissue modeling.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".