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Development of a Modified Skin Explant Assay to Study Treg Suppression of Th17 Cell Mediated GvHD in the Skin

2008· article· en· W2572005821 on OpenAlexaff
Raewyn Broady, Sarah Q. Crome, Jessie Z. Yu, Jan Dutz, Megan K. Levings

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFOXP3ImmunologyCytotoxic T cellCD8Adoptive cell transferImmune systemT cellGraft-versus-host diseaseIL-2 receptorHaematopoiesisImmune toleranceBiologyProinflammatory cytokineCytokineTransplantationStem cellMedicineIn vitroInflammationCell biologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Acute graft versus host disease (aGVHD) following haematopoietic stem cell transplantation (HCT) occurs when donor T cells infused with the graft recognise and react to histo-incompatible recipient antigens causing tissue damage. Historically, the inflammatory response in aGVHD was attributed to alloreactive CD4+ T helper and CD8+ cytotoxic T cells and alterations in cytokine production. Recently, a new CD4+ T cell subset, characterised by IL-17 production has been identified. TH17 cells produce high levels of proinflammatory cytokines, including IL-17A, IL-17F, and IL-22, and have been implicated in solid organ rejection and more recently a number of murine studies suggest that Th17 cells play a role in the development of aGVHD. It is well known that FOXP3+ regulatory T cells (Tregs) are critical for the maintenance of self-tolerance, and control the immune response to alloantigens. Murine studies have shown that adoptive transfer of these cells can prevent acute GVHD whereas selective depletion leads to an increased severity. In humans, Tregs also appear to control acute GVHD as they occur at a lower frequency in the peripheral blood patients with aGVHD compared to patients without GVHD. These findings have led to active interest into the use of these cells to prevent or decrease GVHD following allogeneic HCT. It has been reported that in vitro, Th17 cells are resistant to Treg cell mediated suppression of proliferation and IL-17 production, suggesting that the effector functions of Th17 cells might not be susceptible to Treg-cell-mediated inhibition. If true, this would suggest that Treg-based therapies might not be effective at limiting Th17-cell-mediated tissue damage. However, there is currently no evidence regarding whether Treg cells affect the phenotype or function of Th17 cells in tissues. Understanding the interactions between suppressive Tregs and pro-inflammatory T effectors in tissues that are targets of aGVHD, such as the skin, is critical to better define the potential of Tregs as adoptive therapy for the prevention or treatment of aGVHD. In order to address this question, we developed two methods to generate human Th17 cells, one based on over-expression of RORC2 and the other on sorting CCR4+CCR6+CD4+ T cells. We found that ectopic expression of RORC induces a cytokine and chemokine receptor profile analogous to in vivo differentiated Th17 cells. Although expression of RORC2 made CD4+ T cells resistant to Treg-cell mediated suppression of proliferation and IL-17 production, production of IFN-g, TNF-a and IL-6 could be suppressed in these Th17-like cells. In order to further delineate the functional consequence of the interaction between Treg and Th17 cells in tissues we developed a modified the human skin explant model that involves culture of 4 mm punch biopsies of skin with ex vivo Th17 cells (CCR4+CCR6+CD4+ T cells), RORC2 transduced CD4+ T cells, or controls, in the presence or absence of Treg and grading the graft-versus-host reactivity (grades I–IV) histopathologically. Preliminary data suggest that Th17 cells cause significant tissue destruction in this skin explant model, and experiments are ongoing to determine whether Treg cells can counteract these effects.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.021
GPT teacher head0.227
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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
Published2008
Admission routes1
Has abstractyes

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