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Record W2123516682 · doi:10.1080/10739680590896036

Therapeutic Intervention in Inflammatory Diseases: A Time and Place for Anti‐Adhesion Therapy

2005· review· en· W2123516682 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrocirculation · 2005
Typereview
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineAdhesionCell adhesion moleculeInflammationClinical trialDiseaseIntervention (counseling)ImmunologyPathologyChemistry

Abstract

fetched live from OpenAlex

The recruitment of leukocytes from the blood into tissue is central to the development and maintenance of the majority of inflammatory diseases. This multistep process requires a series of leukocyte-endothelial adhesive interactions, involving several families of adhesion molecules. Molecules that block these interactions have been targeted as potential therapeutic treatments for acute and chronic inflammatory diseases. However, many of the anti-adhesion therapy clinical trials have yielded disappointing outcomes. This review discusses some of the animal models that raise questions about the suitability of anti-adhesion therapy to treat certain inflammatory diseases. The authors suggest that it is crucial to understand the underlying mechanisms and time lines of leukocyte recruitment in each affected tissue and inflammatory disease to develop more effective anti-adhesion therapy.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.045
GPT teacher head0.373
Teacher spread0.327 · 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