Dysregulation of Mesenchymal Stromal Cell Antioxidant Responses in Progressive Multiple Sclerosis
Bibliographic record
Abstract
The potential of autologous cell-based therapies including those using multipotent mesenchymal stromal cells (MSCs) is being investigated for multiple sclerosis (MS) and other neurological conditions. However, the phenotype of MSC in neurological diseases has not been fully characterized. We have previously shown that MSC isolated from patients with progressive MS (MS-MSC) have reduced expansion potential, premature senescence, and reduced neuroprotective potential in vitro. In view of the role of antioxidants in ageing and neuroprotection, we examined the antioxidant capacity of MS-MSC demonstrating that MS-MSC secretion of antioxidants superoxide dismutase 1 (SOD1) and glutathione S-transferase P (GSTP) is reduced and correlates negatively with the duration of progressive phase of MS. We confirmed reduced expression of SOD1 and GSTP by MS-MSC along with reduced activity of SOD and GST and, to examine the antioxidant capacity of MS-MSC under conditions of nitrosative stress, we established an in vitro cell survival assay using nitric oxide-induced cell death. MS-MSC displayed differential susceptibility to nitrosative stress with accelerated senescence and greater decline in expression of SOD1 and GSTP in keeping with reduced expression of master regulators of antioxidant responses nuclear factor erythroid 2-related factor 2 and peroxisome proliferator-activated receptor gamma coactivator 1-α. Our results are compatible with dysregulation of antioxidant responses in MS-MSC and have significant implications for development of autologous MSC-based therapies for MS, optimization of which may require that these functional deficits are reversed. Furthermore, improved understanding of the underlying mechanisms may yield novel insights into MS pathophysiology and biomarker identification. Stem Cells Translational Medicine 2018;7:748-758.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".