MétaCan
Menu
Back to cohort
Record W1876311751 · doi:10.4049/jimmunol.164.5.2457

IL-10 Contributes to the Inhibition of Contact Hypersensitivity in Mice Treated with Photodynamic Therapy

2000· article· en· W1876311751 on OpenAlexaff
G Simkin, Jing-Song Tao, Julia G. Levy, David W. C. Hunt

Bibliographic record

VenueThe Journal of Immunology · 2000
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsSt. Paul's HospitalUniversity of British ColumbiaQLT (Canada)
Fundersnot available
KeywordsVerteporfinPhotodynamic therapyIn vitroSpleenChemistryPharmacologyKnockout mouseImmunologyRatónMedicineReceptorBiochemistry

Abstract

fetched live from OpenAlex

We have explored the effect of photodynamic therapy (PDT) with verteporfin on the induction and expression of contact hypersensitivity (CHS) to 2,4-dinitrofluorobenzene (DNFB) in normal mice and IL-10-deficient mice. Our results indicate that DNFB sensitized mice given PDT with verteporfin and whole body red light irradiation exhibited a significant reduction in CHS compared with control animals. Administration of rIL-12 reversed the effect(s) of PDT as did treatment of mice with anti-IL-10-neutralizing Ab. Knockout mice deficient in IL-10 were found to be resistant to the inhibitory effects of PDT. In vitro proliferative responses using spleen cells from DNFB-sensitized and PDT-treated mice showed a significantly lower response to DNBS as compared with cells from DNFB-sensitized mice or DNFB and PDT-treated IL-10-deficient mice. Finally, naive mice exposed to PDT exhibited an increase in skin IL-10 levels, which peaked between 72 and 120 h post-PDT. Together these data support the role of IL-10 as a key modulator in the inhibition of the CHS response by whole body PDT.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.269
Teacher spread0.258 · 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 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

Citations47
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of ImmunologySame topicPhotodynamic Therapy Research StudiesFrench-language works237,207