PI-12Amantadine acetylation as a biomarker for malignancy
Bibliographic record
Abstract
BACKGROUND Since amantadine acetylation occurs only by spermine-spermidine acetyltransferase, and the enzyme is induced in tumor tissue, we hypothesized that amantadine acetylation would serve as a biomarker for malignancy. METHODS We conducted a phase 2 clinical trial to test the hypothesis. We recruited 109 patient volunteers diagnosed with cancer, and at various stages of treatment, who presented to our outpatient clinics. Age ranged from 30–83 yr (median 62 yr) and the majority were male 64M:45F. One hundred patients completed the protocol. Two hr after supper, patients ingested 200 mg of amantadine HCl and urine was collected for the next 12 hr. Seven patients with head and neck cancer also provided a sputum sample 2 hr after amantadine ingestion. Blinded samples were analyzed for amantadine and its acetyl metabolite. RESULTS All specimens contained amantadine, and 9 urine samples contained acetylamantadine, as did 2 sputum samples. Positive sputum samples were not concordant with respective urine samples. Diagnoses for patients positive for acetylamantadine included lung cancer, 4/43, head and neck cancer, 4/12, multiple myeloma, 1/1, pancreatic cancer, 1/2, and a neuroendocrine tumor, 1/1. CONCLUSIONS Initial findings support our hypothesis. Positive sputum samples suggest that timing of specimen collections may be critical, and that sputum may represent a more convenient biological specimen to investigate this metabolic association more critically. Clinical Pharmacology & Therapeutics (2005) 79, P10–P10; doi: 10.1016/j.clpt.2005.12.033
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".