Inflammation Differentially Modulates the Biological Features of Adult Derived Human Liver Stem/Progenitor Cells
Bibliographic record
Abstract
The progression of mesenchymal stem cell-based therapy from concept to cure closely depends on the optimization of conditions that allow a better survival and favor the cells to achieve efficient liver regeneration. We have previously demonstrated that adult-derived human liver stem/progenitor cells (ADHLSC) display significant features that support their clinical development. The current work aims at studying the impact of a sustained pro-inflammatory environment on the principal biological features of ADHLSC in vitro. METHODS: ADHLSC from passages 4-7 were exposed to a cocktail of inflammatory cytokines for 24 h and 9 days and subsequently analyzed for their viability, expression, and secretion profiles by using flow cytometry, RT-qPCR, and antibody array assay. The impact of inflammation on the hepatocytic differentiation potential of ADHLSC was also evaluated. RESULTS: ADHLSC treated with a pro-inflammatory cocktail displayed significant decrease of cell yield at both times of treatment while cell mortality was observed at 9 days post-priming. After 24 h, no significant changes in the immuno-phenotype of ADHLSC expression profile could be noticed while after 9 days, the expression profile of relevant markers has changed both in the basal conditions and after inflammation treatment. Inflammation cocktail enhanced the release of IL-6, IL-8, CCL5, monocyte-chemo-attractant protein-2 and 3, CXCL1/GRO, and CXCL5/ENA78. Furthermore, while IP-10 secretion was increased after 24 h priming, granulocyte macrophage colony-stimulating factor enhanced secretion was noticed after 9 days treatment. Finally, priming of ADHLSC did not affect their potential to differentiate into hepatocyte-like cells. CONCLUSION: These results indicate that ADHLSCs are highly sensitive to inflammation and respond to such signals by adjusting their gene and protein expression. Accordingly, monitoring the inflammatory status of patients at the time of cell transplantation, will certainly help in enhancing ADHLSC safety and efficiency.
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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 | 0.000 | 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) | 0.000 | 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".