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Record W3005889406

The immunological and vascular effects of IL-6 signalling in transplant arteriosclerosis

2019· dissertation· en· W3005889406 on OpenAlexfundno aff
Ashani Montgomery

Bibliographic record

VenueSummit (Simon Fraser University) · 2019
Typedissertation
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsnot available
FundersSimon Fraser UniversityHeart and Stroke Foundation of Canada
KeywordsArteriosclerosisImmunologySignallingMedicineSignalling pathwaysBiologyInternal medicineReceptorCell biology
DOInot available

Abstract

fetched live from OpenAlex

Transplant arteriosclerosis (TA) is a pathological vascular condition that is a main cause of chronic rejection and eventual failure of cardiac transplants.TA is caused by the activation of T cells towards allogeneic antigens expressed by vascular cells, which results in T cell-mediated injury and dysfunction of allograft arteries.T cells also support the activation and secretion of donor specific antibodies (DSAs) by B cells that contribute to the pathogenesis of TA.Interleukin-6 (IL-6) is secreted within hours of surgical transplantation and plays an important role in activation of allogeneic immune responses and regulation of vascular processes that influences TA.There are two main mechanisms by which IL-6 can signal to cells, classic and trans, that are distinguished by whether it binds to membrane bound or soluble forms of its receptor (IL-6R).In classic signalling IL-6 binds to IL-6R on the surface of cells.In trans-signaling IL-6 binds to soluble IL-6R.In both scenarios, the IL-6/IL-6R complex associates with the signalling subunit gp130 on cell membranes to transduce intracellular signalling events.Interestingly, IL-6 classic and trans-signalling have distinct biological outcomes.I examined the mechanism by which IL-6 classic and trans signalling contributes to immune activation in TA and characterized the biological outcomes of IL-6 signalling in endothelial cells.IL-6 classic and trans signalling were redundant for the activation of peripheral T cells that cause TA.However, eliminating IL-6R expression in T cells significantly reduced the development of DSAs in the serum of graft recipients, suggesting that IL-6 classic signalling in T cells may be required for antibody-mediated pathology in TA.In addition to activating immune cells, IL-6 acts on endothelial cells to induce inflammation and protect the vasculature from injury.IL-6 trans signalling in ECs significantly induced STAT-3, ERK1/2 and Akt activation.This signalling mechanism was needed for ICAM upregulation and the secretion of inflammatory cytokines by IL-6, indicating that IL-6 trans-signaling drives inflammatory activation of ECs.IL-6 classic signalling induced ERK1/2 and Akt activation but not STAT3 and was sufficient to stimulate the secretion of IL-8 and to protect ECs from cell death caused by serum deprivation but did not induce other inflammatory processes in ECs.My results suggest that IL-6 trans and classic signalling differentially affect inflammatory and survival responses in endothelial cells, which may have implications for understanding the vascular effects of IL-6R blockade in patients.Overall, my findings provide new insight into the immune and vascular effects of IL-6 in transplantation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · 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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.227
Teacher spread0.216 · 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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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