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Record W7036624828

Comprehensive study of the immunomodulatory properties of bone marrow-derived mesenchymal stromal cells

2011· other· en· W7036624828 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2011
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicFossil Insects in Amber
Canadian institutionsnot available
Fundersnot available
KeywordsMesenchymal stem cellImmune systemStromal cellPriming (agriculture)Peripheral blood mononuclear cellT cellIn vivoCell growthCell
DOInot available

Abstract

fetched live from OpenAlex

Over the course of the last decade, mesenchymal stromal cells (MSC) have made a remarkable entry in the field of cell-based immunotherapy. In vitro, MSC were shown to modulate the immune response, either by acting as an immunosuppressant on several immune cells, or upon IFN-γ stimulation, as an antigen presenting cell (APC) for the priming of CD4+ T cells. Although a vast array of in vivo experiments in animals and humans has undeniably proven the immunological properties of MSC, the exact mechanisms by which MSC mediate their effects remain unclear. In Chapter 1, I presented a succinct review of the literature in regards to the characteristics of MSC. In Chapter 2, I addressed the immunosuppressive mechanisms of human MSC toward T cell proliferation. Using an in vitro proliferation assay, I demonstrated that human MSC suppressed T cell proliferation through the expression indoleamine 2,3-dioxygenase (IDO) induced following IFN-γ priming. In addition, MSC derived from different donors were shown to suppress T cell proliferation at variable degrees, which corresponded to their individual expression level of IDO. The use of whole peripheral blood mononuclear cells (PBMC) as opposed to purified T cells revealed the role played by monocytes in the suppression of T cell proliferation by MSC. Factors secreted by MSC in addition to the enzymatic activity of IDO induced the differentiation of monocytes into immunosuppressive M2 macrophages. Stimulation by IFN-γ not only triggered the immunosuppressive mechanisms of MSC but also induced APC-like properties in MSC. In Chapter 3, I investigated the molecular mechanisms implicated in the modulation of IFN-γ-inducible expression of MHC class II molecules and mediated antigen presentation in MSC. I demonstrated that IFN-γ mediated the transcriptional activation of the class II transactivator gene (CIITA), which is responsible for the upregulation of MHC class II molecules on both mouse and human MSC, and that TGF-β counter-acted the effect of IFN-γ by inhibiting the transcription of CIITA. In addition, cell culture density also modulated MHC class II-mediated antigen presentation differentially in mouse and human MSC. In Chapter 4, I examined the capacity of mouse MSC to cross-present exogenously acquired antigens as part of their APC-like features. I demonstrated that cross-presentation by mouse MSC was induced by IFN-γ and dependent on MHC class I machinery molecules, TAP complex and proteasome. I also demonstrated using an in vivo immune reconstitution assay, that mouse MSC can prime CD8+ T cells against a specific antigen, a characteristic of professional APC. Finally, I investigated in Chapter 5 the immunological impact of TLR expression and signaling in human and mouse MSC. I demonstrated that TLR activation in MSC induced the expression of chemokines and cytokines, which created an attractive inflammatory milieu for immune cells. I concluded by demonstrating that MSC differ from classic APC in that they did not express IL-12p70, an essential cytokine involved in both innate and adaptive immunity, in response to TLR activation. The findings in this thesis illustrate the complexity of the mechanisms by which MSC modulate the immune system. Their response to environment clues such as inflammation and pathogens activate either their suppressive or stimulatory immune functions, depending on the situation. Overall, these findings help optimize the utilization of MSC in cell-based immunotherapy.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.131
Teacher spread0.123 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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