Soluble mediators from human neural stem cells play a critical role in suppression of T‐cell activation and proliferation
Bibliographic record
Abstract
Human neural stem cells (hNSCs) can control inflammation in the central nervous system, although the underlying mechanisms are not understood fully. We investigated the immunomodulatory effect of hNSCs on human T cells and the underlying mechanisms. Culture supernatant from an immortalized hNSC cell line, HB1.F3, which has a therapeutic effect on acute stroke and intracerebral hemorrhage, suppressed the proliferation of allogeneically or mitogenically stimulated human peripheral T cells, including the CD3(+)CD103(+) subpopulation. CFSE labeling and flow cytometry showed that the suppression of proliferation was caused by cell cycle arrest and induction of apoptosis. The lack of significant change in caspase-8 levels and the significant reduction in Bcl-2 expression in the affected T cells suggest that the intrinsic pathway plays a major role in soluble-factor-mediated T-cell apoptosis. The addition of culture supernatant from hNSCs to activated T cells reduced the expression of the activation markers CD69 and CD25 at 24 hr after activation, but at 48 hr only CD69 was down-regulated. A cytometry bead assay showed that the secretion of interleukin (IL)-2 decreased significantly, whereas that of IL-4, IL-10, tumor necrosis factor-alpha, and interferon-gamma increased. These results show that hNSCs can negatively affect human peripheral T cells by suppressing their activation and proliferation through soluble mediators, suggesting that hNSCs have a bystander immunomodulatory effect on T cells.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".