Tafazzin deficiency in mouse mesenchymal stem cells potentiates their immunosuppression and impairs activated B lymphocyte immune function
Bibliographic record
Abstract
Barth Syndrome (BTHS) is a rare X-linked genetic disorder caused by mutation in the TAFAZZIN gene which encodes the cardiolipin (CL) transacylase tafazzin (Taz). Taz deficiency in BTHS patients results in reduced CL in their tissues and a neutropenia which contributes to the risk of infections. However, the impact of Taz deficiency in other cells of the immune system is poorly understood. Mesenchymal stem cells (MSCs) are well known for their immune inhibitory function. We examined whether Taz-deficiency in murine MSCs impacted their ability to modulate lipopolysaccharide (LPS)-activated wild type (WT) murine B lymphocytes. MSCs from tafazzin knockdown (TazKD) mice exhibited a 50% reduction in CL compared to wild type (WT) MSCs. However, mitochondrial oxygen consumption rate and membrane potential were unaltered. In contrast, TazKD MSCs exhibited increased glycolysis compared to WT MSCs and this was associated with elevated proliferation, phosphatidylinositol-3-kinase expression and expression of the immunosuppressive markers indoleamine-2,3-dioxygenase, cytotoxic T-lymphocyte-associated protein 4, interleukin-10, and cluster of differentiation 59. When co-cultured with LPS-activated WT B cells, TazKD MSCs inhibited B cell proliferation and growth rate and reduced B cell secretion of IgM to a greater extent than B cells co-cultured with WT MSCs. In addition, co-culture of LPS-activated WT B cells with TazKD MSCs induced B cell differentiation toward potent immunosuppressive phenotypes including interleukin-10 secreting plasma cells and B regulatory cells compared to activated B cells co-cultured with WT MSCs. These results indicate that Taz deficiency in MSCs enhances MSCs-mediated immunosuppression of activated B lymphocytes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".