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Record W2018665096 · doi:10.1080/10428190500054426

Regression of lymphomatous skin deposits in a chronic lymphocytic leukemia patient treated with the Toll-like receptor-7/8 agonist, imiquimod

2005· article· en· W2018665096 on OpenAlexaff
David Spaner, Richard L. Miller, Jenny Mena, L. Grossman, Vicki Sorrenti, Yonghong Shi

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2005
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsThe Scarborough HospitalGrace (Canada)Sunnybrook Health Science CentreWomen's College HospitalUniversity of Toronto
FundersNational Institute on Aging
KeywordsImiquimodChronic lymphocytic leukemiaMedicineAgonistDermatologyCancer researchToll-like receptorTollLeukemiaReceptorInternal medicineOncologyImmunology

Abstract

fetched live from OpenAlex

The identification of clinically relevant, active immunomodulatory agents is important for developing immunotherapeutic approaches to chronic lymphocytic leukemia (CLL) and other B-cell lymphomas that are not curable with conventional chemotherapy. In this investigation, the imidazoquinoline Toll-like receptor (TLR)-7/8 agonist, imiquimod, was found to mediate the clearance of a lymphomatous skin lesion in a CLL patient. Imidazoquinolines also activated TLR-7/8 signaling pathways, resulting in increased expression of costimulatory molecules on circulating tumor cells. These observations extend the therapeutic spectrum of imiquimod to cutaneous B-cell lymphomas and suggest the use of TLR-7/8 agonists in CLL immunotherapy.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.244
Teacher spread0.235 · 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 designCase report
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

Citations54
Published2005
Admission routes1
Has abstractyes

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