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The Impact of Graft-Versus-Host Disease on Dendritic Cell Homeostasis and Their Potential Use As Biomarker to Predict the Severity of Chronic Graft-Versus-Host Disease

2015· article· en· W2593845645 on OpenAlexaff
Stéphanie Thiant, Jean Roy, Jessica Trottier, Marie-Pier Giard, Rachel Parat, Denis‐Claude Roy, Martin Guimond

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsImmunologyGraft-versus-host diseaseCD8TransplantationDendritic cellHematopoietic stem cell transplantationMedicineImmune systemT cellBiologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract PURPOSE: Graft-versus-host disease (GVHD) is the principal complication of allogeneic stem cell transplantation (allo-SCT) and occurs when GVHD T cells recognize differences in major and/or minor histocompatibility antigens expressed by recipient cells. Following cytotoxic regimens, the inflammatory milieu represents a fertile ground for alloreactivity and thymic insults resulting from GVHD are largely responsible for thymic dysfunction and immune-incompetence. Studies have also demonstrated that GVHD insult to the peripheral niche is perhaps the most important factor for limiting thymic independent T cell regeneration. Given that patients with chronic GVHD (cGVHD) are profoundly lymphopenic and that dendritic cells (DCs) play a critical role in T cell homeostasis, we postulated that changes in DC counts could precede the development of clinical signs of acute and/or chronic GVHD. METHODS: 44 patients that received HLA-matched allogeneic SCT were included in this study. Controls consist of 15 patients that received autologous SCT and 30 healthy donors. Flow cytometric analysis was used to measure plasmacytoid DCs (pDCs), myeloid DC type 1 (mDC1), mDC2 and mDC3. Blood samples were obtained at day 0, 1 month post-SCT and then every other month until 1 year. The percentage and absolute counts of naïve CD4+ or CD8+ lymphocytes (TNA); (CD3+ CD45RA+ CCR7+), central memory (TCM); (CD3+ CD45RA+ CCR7neg), effector memory (TEM); (CD3+ CD45RAneg CCR7neg) and terminal differentiation (TTD); (CD45RA+ CCR7neg) was determined by flow cytometry. B lymphocytes and regulatory CD4+ T cells were also evaluated. RESULTS: One month after allo-SCT, we found a significant increase in blood DCs followed by a gradual decrease and stabilization by 3 months post-allo-SCT. During the first year, all DC subsets including pDCs, mDC1, mDC2, mDC3 as well as CD4+ and CD8+ T cells were significantly diminished compared to autologous and healthy controls. Plasmacytoid DCs regeneration was in general the most affected and we found a positive correlation between pDC cells count and the number of naïve and central memory CD4+ lymphocytes. Similarly, pDCs counts also correlated with the number of naïve and memory CD8+ T cells. In contrast, effector CD4+ and CD8+ T cell showed a stronger correlation with mDC1. Patients with grade II-IV acute GVHD had lower DC counts compared with mild grade 0-1 aGVHD and a similar trend was also observed during the development of cGVHD, Importantly, loss of pDCs and mDC1 that preceded the development of cGVHD by 1 month was associated with the development of grade 3 cGVHD whereas loss of DCs during cGVHD was associated with milder 0-2 cGVHD. Thus far, our data support a model wherein loss of pDCs and mDC1 could represent potential biomarkers to predict the severity of cGVHD. Disclosures No relevant conflicts of interest to declare.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.258
Teacher spread0.239 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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