Transcriptional Profile of Cytokines, Regulatory Mediators and TLR in Mesenchymal Stromal Cells after Inflammatory Signaling and Cell-Passaging
Bibliographic record
Abstract
Adult human subcutaneous adipose tissue (AT) harbors a rich population of mesenchymal stromal cells (MSCs) that are of interest for tissue repair. For this purpose, it is of utmost importance to determine the response of AT-MSCs to proliferative and inflammatory signals within the damaged tissue. We have characterized the transcriptional profile of cytokines, regulatory mediators and Toll-like receptors (TLR) relevant to the response of MSCs. AT-MSCs constitutively present a distinct profile for each gene and differentially responded to inflammation and cell-passaging. Inflammation leads to an upregulation of IL-6, IL-8, IL-1β, TNFα and CCL5 cytokine expression. Inflammation and cell-passaging increased the expression of HGF, IDO1, PTGS1, PTGS2 and TGFβ. The expression of the TLR pattern was differentially modulated with TLR 1, 2, 3, 4, 9 and 10 being increased, whereas TLR 5 and 6 downregulated. Functional enrichment analysis demonstrated a complex interplay between cytokines, TLR and regulatory mediators central for tissue repair. This profiling highlights that following a combination of inflammatory and proliferative signals, the sensitivity and responsive capacity of AT-MSCs may be significantly modified. Understanding these transcriptional changes may help the development of novel therapeutic approaches.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".