The Immunomodulatory and Therapeutic Effects of Mesenchymal Stromal Cells for Acute Lung Injury and Sepsis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is increasingly recognized that immunomodulation represents an important mechanism underlying the benefits of many stem cell therapies, rather than the classical paradigm of transdifferentiation and cell replacement. In the former paradigm, the beneficial effects of cell therapy result from paracrine mechanism(s) and/or cell-cell interaction as opposed to direct engraftment and repair of diseased tissue and/or dysfunctional organs. Depending on the cell type used, components of the secretome, including microRNA (miRNA) and extracellular vesicles, may be able to either activate or suppress the immune system even without direct immune cell contact. Mesenchymal stromal cells (MSCs), also referred to as mesenchymal stem cells, are found not only in the bone marrow, but also in a wide variety of organs and tissues. In addition to any direct stem cell activities, MSCs were the first stem cells recognized to modulate immune response, and therefore they will be the focus of this review. Specifically, MSCs appear to be able to effectively attenuate acute and protracted inflammation via interactions with components of both innate and adaptive immune systems. To date, this capacity has been exploited in a large number of preclinical studies and MSC immunomodulatory therapy has been attempted with various degrees of success in a relatively large number of clinical trials. Here, we will explore the various mechanism employed by MSCs to effect immunosuppression as well as review the current status of its use to treat excessive inflammation in the context of acute lung injury (ALI) and sepsis in both preclinical and clinical settings.
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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) | 0.003 | 0.001 |
| 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) | 0.000 | 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 it