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Record W1968962176 · doi:10.1007/s12079-010-0107-x

B cell block: is rituximab a new possible treatment for systemic sclerosis?

2010· article· en· W1968962176 on OpenAlexaff
Andrew Leask

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2010
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsWestern University
Fundersnot available
KeywordsRituximabMedicineCD20ImmunologyAntibodyImmune systemAutoimmune diseaseProinflammatory cytokineDiseaseInternal medicineInflammation

Abstract

fetched live from OpenAlex

There is no treatment for fibrotic diseases, including the autoimmune disease systemic sclerosis (sclerderma, SSc). Although broad spectrum immune suppressants have little to no effect on the fibrosis in SSc, agents targeting specific proinflammatory agents are currently being considered as possible therapeutic approaches to combating SSc. B cells are lymphocytes that proliferate and secrete antibody molecules which drive the autoimmune response. CD20 is a B cell marker; the agent rituximab is an antibody against CD20. In a recent report by Bosello and colleagues (Arthritis Res. Ther. 12(2): R54, 2010), rituximab was tolerated in SSc patients and appeared to result in an improvement of the skin score and of clinical symptoms of SSc. This report is one of a series of recent studies suggesting that rituximab may be a possible treatment for SSc. This commentary summarizes these observations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.063
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.279
Teacher spread0.238 · 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 teacher head, 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

Citations3
Published2010
Admission routes1
Has abstractyes

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