Potentiation of photodynamic therapy of cancer by complement: the effect of γ-inulin
Bibliographic record
Abstract
Host response elicited by photodynamic therapy (PDT) of cancerous lesions is a critical contributor to the clinical outcome, and complement system has emerged as its important element. Amplification of complement action was shown to improve tumour PDT response. In search of a clinically relevant complement activator for use as a PDT adjuvant, this study focused on gamma-inulin and examined its effects on PDT response of mouse tumours. Intralesional gamma-inulin (0.1 mg mouse(-1)) delivered immediately after PDT rivaled zymosan (potent classical complement activator) in delaying the recurrence of B16BL6 melanomas. This effect of gamma-inulin was further enhanced by IFN-gamma pretreatment. Tumour C3 protein levels, already elevated after individual PDT or gamma-inulin treatments, increased much higher after their combination. With fibrosarcomas MCA205 and FsaR, adjuvant gamma-inulin proved highly effective in reducing recurrence rates following PDT using four different photosensitisers (BPD, ce6, Photofrin, and mTHPC). At 3 days after PDT plus gamma-inulin treatment, over 50% of cells found at the tumour site were CTLs engaged in killing specific targets via perforin-granzyme pathway. This study demonstrates that gamma-inulin is highly effective PDT adjuvant and suggests that by amplifying the activation of complement system, this agent potentiates the development of CTL-mediated immunity against PDT-treated tumours.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".