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Record W2086624612 · doi:10.1517/14712598.8.2.191

Antigen-specific therapy of rheumatoid arthritis

2008· review· en· W2086624612 on OpenAlexaff
Thomas E. Ichim, Xiufen Zheng, Motohiko Suzuki, Norihiko Kubo, Xusheng Zhang, Marianne Beduhn, Neil H Riordan, Robert D. Inman, Wei‐Ping Min

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2008
Typereview
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity Health NetworkWestern University
FundersNewcastle University
KeywordsImmunotherapyImmunologyMedicineImmune systemAntigenAutoimmunityRheumatoid arthritis

Abstract

fetched live from OpenAlex

BACKGROUND: Immunotherapy offers the promise of antigen-specific suppression of pathological immune responses in conditions such as autoimmunity and organ transplantation. Substantial advances have been made in recent years in terms of understanding basic immunological mechanisms of autoreactivity, as well as clinically implementing immune-based therapies that are antigen nonspecific. OBJECTIVE: To provide an integrated overview of the current state of the art in terms of antigen-specific tolerance induction, as well as to predict future directions for the field. METHODS: Examples of successes and failures of antigen-specific immunotherapy were sought. Particular attention was paid to the well-established collagen II-induced model of arthritis. RESULTS/CONCLUSIONS: Previous failures of antigen-specific immunotherapy were associated with lack of identification of clinically relevant antigens, as well as inappropriate tolerogenic methodologies. The advances in proteomics combined with novel gene-specific immune modulatory techniques place today's translational researchers in a unique position to tackle the problem of antigen-specific immunotherapeutic protocols.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designmedium
models splitAgreement compares identical category sets and study designs across arms.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.185
GPT teacher head0.394
Teacher spread0.208 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
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

Citations13
Published2008
Admission routes1
Has abstractyes

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