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In vitro and in vivo effects of polyhaemoglobin–tyrosinase on murine B16F10 melanoma

2004· article· en· W2050644093 on OpenAlexaff
Binglan Yu, Thomas Ming Swi Chang

Bibliographic record

VenueMelanoma Research · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsMcGill University
Fundersnot available
KeywordsIn vivoIn vitroTyrosinaseMelanomaChemistryCancer researchPharmacologyMedicineBiologyBiochemistryBiotechnologyEnzyme

Abstract

fetched live from OpenAlex

Melanoma is an increasingly common fatal skin cancer. Many groups are carrying out research on potential treatments for melanoma. One of these approaches has shown that lowering tyrosine can inhibit the growth of melanoma in cell cultures and of B16BL6 melanoma in mice. However, humans cannot tolerate tyrosine-restricted diets for lowering tyrosine because of nausea, vomiting and weight loss. We report here our preparation and characterization of a novel soluble polyhaemoglobin-tyrosinase complex. This preparation prevents native tyrosinase from having adverse effects and from rapid removal after injection. The preparation inhibited murine B16F10 melanoma cell growth in culture and delayed its growth in a mice model. Intravenous injection of the preparation lowers the systemic tyrosine level without causing adverse effects such as vomiting and weight loss in mice. It is therefore possible that this complex could be useful in the treatment of human melanoma.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.319
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2004
Admission routes1
Has abstractyes

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