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The Impact of Complement Activation on Tumor Oxygenation During Photodynamic Therapy<sup>†</sup>

2007· article· en· W2070019224 on OpenAlexaff
Ivana Cecić, Andrew I. Minchinton, Mladen Korbelik

Bibliographic record

VenuePhotochemistry and Photobiology · 2007
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsPhotodynamic therapyPhotosensitizerComplement systemCancer researchOxygenationOxygen tensionChemistryImmunologyOxygenMedicineInternal medicinePhotochemistryAntibody

Abstract

fetched live from OpenAlex

The response to photodynamic therapy (PDT) mediated by photosensitizer Photofrin was examined with Lewis lung carcinomas growing in either complement-proficient C57BL/6 (B6) or complement-deficient complement C3 knockout (C3KO) mice. The results reveal that Photofrin-PDT was more effective in attaining cures of tumors in C3KO than in B6 hosts. Colony-forming ability of cells from tumors excised immediately after Photofrin-PDT confirmed that the direct cell killing effect was more pronounced in C3KO than in B6 hosts. In contrast, PDT mediated by photosensitizer benzoporphyrin derivative (BPD) produced higher cure rates of tumors in B6 hosts than those in C3KO hosts. Determination of tumor C3 levels by ELISA showed that Photofrin-PDT induced markedly more pronounced complement activation than BPD-PDT. Measurements of tumor oxygen tension immediately after PDT by Eppendorf pO2 histograph showed that Photofrin-PDT induced a marked decline in the oxygenation of tumors growing in B6 mice that was much less pronounced in C3KO hosts. With BPD-PDT the oxygen tensions in tumors in B6 and C3KO hosts decreased to a similar extent. This study indicates that complement activation in PDT-treated tumors that varies with different photosensitizers is an important determinant of tumor oxygen limitation effects directly associated with photodynamic action.

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)0.001
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 score0.072
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.337
Teacher spread0.319 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

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