Intravenous ascorbic acid as an adjuvant to interleukin-2 immunotherapy
Bibliographic record
Abstract
Interleukin-2 (IL-2) therapy has been demonstrated to induce responses in 10-20% of advanced melanoma and renal cell carcinoma patients, which translates into durable remissions in up to half of the responsers. Unfortunately the use of IL-2 has been associated with severe toxicity and death. It has been previously observed and reported that IL-2 therapy causes a major drop in circulating levels of ascorbic acid (AA). The IL-2 induced toxicity shares many features with sepsis such as capillary leakage, systemic complement activation, and a relatively non-specific rise in inflammatory mediators such as TNF-alpha, C-reactive protein, and in advanced cases organ failure. Animal models and clinical studies have shown rapid depletion of AA in conditions of sepsis and amelioration associated with administration of AA (JTM 9:1-7, 2011). In contrast to other approaches to dealing with IL-2 toxicity, which may also interfere with therapeutic effects, AA possesses the added advantage of having direct antitumor activity through cytotoxic mechanisms and suppression of angiogenesis. Here we present a scientific rationale to support the assessment of intravenous AA as an adjuvant to decrease IL-2 mediated toxicity and possibly increase treatment efficacy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".