Chemokines and their receptors: predictors of the therapeutic potential of mesenchymal stromal cells
Bibliographic record
Abstract
Multipotent mesenchymal stromal cells (MSCs) are promising cellular therapeutics for the treatment of inflammatory and degenerative disorders due to their anti-inflammatory, immunomodulatory and regenerative potentials. MSCs can be sourced from a variety of tissues within the body, but bone marrow is the most frequently used starting material for clinical use. The chemokine family contains many regulators of inflammation, cellular function and cellular migration-all critical factors in understanding the potential potency of a novel cellular therapeutic. In this review, we focus on expression of chemokine receptors and chemokine ligands by MSCs isolated from different tissues. We discuss the differential migratory, angiogenetic and immunomodulatory potential to understand the role that tissue source of MSC may play within a clinical context. Furthermore, this is strongly associated with leukocyte recruitment, immunomodulatory potential and T cell inhibition potential and we hypothesize that chemokine profiling can be used to predict the in vivo therapeutic potential of MSCs isolated from new sources and compare them to BM MSCs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".