In vitro and in vivo enzyme studies of polyhemoglobin‐tyrosinase
Bibliographic record
Abstract
Melanoma is now the fifth most common type of cancer in North America. At present, there is no optimal treatment for this cancer. However, the lowering of the tyrosine level can inhibit the growth of melanoma. Unfortunately, this diet restriction cannot be humanly tolerated and causes vomiting, nausea, and severe body weight loss. To prevent these problems, we are studying a new approach involving the preparation intermolecularly crosslinked hemoglobin and tyrosinase for intravenous injection. In this article we describe the method of preparation and the structural and functional properties of polyhemoglobin-tyrosinase. We evaluate the effects of varying glutaraldehyde ratio, crosslinking time, and enzyme concentration on the enzyme activity of polyhemoglobin-tyrosinase. We also optimize the molecular weight distribution of polyhemoglobin-tyrosinase. The stability of polyhemoglobin-tyrosinase at 37 degrees C is much more stable when compared to noncrosslinked tyrosinase solution. Animal studies show that a higher degree of polymerization correlates with a longer circulation time of polyhemoglobin-tyrosinase, and the optimal crosslinking time is 24 hours. One intravenous injection of polyhemoglobin-tyrosinase lowers the plasma tyrosine to about 10% of its original level within one hour.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".