Mesenchymal Stromal Cells Improve Salivary Function and Reduce Lymphocytic Infiltrates in Mice with Sjögren's-Like Disease
Bibliographic record
Abstract
BACKGROUND: Non-obese diabetic (NOD) mice develop Sjögren's-like disease (SS-like) with loss of saliva flow and increased lymphocytic infiltrates in salivary glands (SGs). There are recent reports using multipotent mesenchymal stromal cells (MSCs) as a therapeutic strategy for autoimmune diseases due to their anti-inflammatory and immunomodulatory capabilities. This paper proposed a combined immuno- and cell-based therapy consisting of: A) an injection of complete Freund's adjuvant (CFA) to eradicate autoreactive T lymphocytes, and B) transplantations of MSCs to reselect lymphocytes. The objective of this was to test the effectiveness of CD45(-)/TER119(-) cells (MSCs) in re-establishing salivary function and in reducing the number of lymphocytic infiltrates (foci) in SGs. The second objective was to study if the mechanisms underlying a decrease in inflammation (focus score) was due to CFA, MSCs, or CFA+MSCs combined. METHODOLOGY/PRINCIPAL FINDINGS: Donor MSCs were isolated from bones of male transgenic eGFP mice. Eight week-old female NOD mice received one of the following treatments: insulin, CFA, MSC, or CFA+MSC (combined therapy). Mice were followed for 14 weeks post-therapy. CD45(-)/TER119(-) cells demonstrated characteristics of MSCs as they were positive for Sca-1, CD106, CD105, CD73, CD29, CD44, negative for CD45, TER119, CD11b, had high number of CFU-F, and differentiated into osteocytes, chondrocytes and adipocytes. Both MSC and MSC+CFA groups prevented loss of saliva flow and reduced lymphocytic infiltrations in SGs. Moreover, the influx of T and B cells decreased in all foci in MSC and MSC+CFA groups, while the frequency of Foxp3(+) (T(reg)) cell was increased. MSC-therapy alone reduced inflammation (TNF-α, TGF-β), but the combination of MSC+CFA reduced inflammation and increased the regenerative potential of SGs (FGF-2, EGF). CONCLUSIONS/SIGNIFICANCE: The combined use of MSC+CFA was effective in both preventing saliva secretion loss and reducing lymphocytic influx in salivary glands.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".