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Record W4386945459 · doi:10.1111/bjh.19079

The role of T cells and myeloid‐derived suppressor cells in refractory immune thrombocytopenia

2023· review· en· W4386945459 on OpenAlexaff
Karina Yazdanbakhsh, Drew Provan, John W. Semple

Bibliographic record

VenueBritish Journal of Haematology · 2023
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of Toronto
FundersNational Institutes of HealthNational Heart, Lung, and Blood InstituteVetenskapsrådet
KeywordsImmune systemImmunologyImmune thrombocytopeniaT cellMedicineRefractory (planetary science)PathogenesisMyeloidPlateletMyeloid-derived Suppressor CellImmune toleranceSuppressorBiologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Immune thrombocytopenia (ITP) is characterized by a dysregulated immune response against platelets, affecting both their destruction and production. A role for an abnormal T-cell compartment has been established in ITP pathogenesis and treatments that increase platelet counts in patients with ITP have shown improvements in T-cell profiles. On the other hand, patients who were refractory to treatment appear to retain the T-cell abnormalities as before. Myeloid-derived suppressive cells (MDSCs) are also emerging as key contributors to the immune pathology of ITP and response to treatment. In this review, we will discuss how various treatments affect the T-cell and MDSC compartments in ITP. The review will focus on studies that have examined the underlying mechanisms and/or genetic basis responsible for refractoriness to a given treatment and highlight remaining challenges in identifying factors and mechanisms to predict response to treatment.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.298
Teacher spread0.276 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations22
Published2023
Admission routes1
Has abstractyes

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