MétaCan
Menu
Back to cohort
Record W2123235650 · doi:10.1097/moh.0b013e32833eaef3

Recent progress in understanding the pathogenesis of immune thrombocytopenia

2010· review· en· W2123235650 on OpenAlexaff
John W. Semple, Drew Provan, Marie Garvey, John Freedman

Bibliographic record

VenueCurrent Opinion in Hematology · 2010
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsSt. Michael's HospitalCanadian Blood Services
Fundersnot available
KeywordsPathogenesisImmunologyAutoimmunityImmune systemPlateletMolecular mimicryMechanism (biology)Immune thrombocytopeniaMedicineCytokineBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Immune thrombocytopenia (ITP) is a bleeding disorder in which both antibody and cell-mediated autoimmune responses are directed against an individual's own platelets and/or megakaryocytes, leading to either enhanced platelet destruction and/or reduced platelet production, respectively. The cause of this platelet-specific autoimmunity remains unknown, but there has been a constant stream of recent publications that suggest ITP is the result of T-cell dysregulation. RECENT FINDINGS: In the last 18 months, a rich tapestry of studies has emerged that seems to clarify some immunopathologic issues in ITP while raising new questions related to ITP pathogenesis. The current view on the immunopathogenic mechanisms associated with ITP appears to particularly concentrate on how incompetent CD4+ T-regulatory cells (Tregs) allow autoimmune effector mechanisms to proceed and cause thrombocytopenia. There is a parallel body of recent literature focusing on molecular mimicry mechanisms, B-cell abnormalities, abnormal cytokine patterns and genetic studies in ITP. Of interest, one can recognize inter-relationships between these immune dysregulations. SUMMARY: This article will discuss the literature from the past 18 months pertaining to these observations and will show that whereas many of the T-cell defects have been clarified, new questions have also come to light and more immunopathological research is warranted.

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)0.001
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.190
GPT teacher head0.430
Teacher spread0.241 · 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

Citations87
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in HematologySame topicPlatelet Disorders and TreatmentsFrench-language works237,207