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Record W2116155140 · doi:10.1017/s146239941100202x

Towards new therapeutic approaches for malignant melanoma

2011· review· en· W2116155140 on OpenAlexafffund
Ivan Pacheco, Cristina Buzea, Victor A. Tron

Bibliographic record

VenueExpert Reviews in Molecular Medicine · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsQueen's University
FundersCanadian Institutes of Health ResearchMelanoma Research Alliance
KeywordsMelanomaCancer researchCancerDiseaseMedicineComputational biologyBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Recent progress in understanding the molecular mechanisms of the initiation and progression of melanoma has created new opportunities for developing novel therapeutic modalities to manage this potentially lethal disease. Although at first glance, melanoma carcinogenesis appears to be a chaotic system, it is indeed, arguably, a deterministic multistep process involving sequential alterations of proto-oncogenes, tumour suppressors and miRNA genes. The scope of this article is to discuss the most recent and significant advances in melanoma molecular therapeutics. It is apparent that using single agents targeting solely individual melanoma pathways might be insufficient for long-term survival. However, the outstanding results on melanoma survival observed with novel selective inhibitors of B-RAF, such as PLX4032 give hope that melanoma can be cured. The fact that melanoma develops acquired resistance to PLX4032 emphasises the importance of simultaneously targeting several pathways. Because the most striking feature of melanoma is its unsurpassed ability to metastasise, it is important to implement newer systems for drug delivery adapted from research on stem cells and nanotechnology.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.150
GPT teacher head0.355
Teacher spread0.205 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations45
Published2011
Admission routes2
Has abstractyes

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