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Vanadium: Possible Use in Cancer Chemoprevention and Therapy

2014· article· en· W2107790677 on OpenAlexvenueno aff
Ladislav Novotný, Samuel B. Kombian

Bibliographic record

VenueJournal of cancer research updates · 2014
Typearticle
Languageen
FieldChemistry
TopicVanadium and Halogenation Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsVanadiumCancerCarcinogenATPaseChemistryEnzymeCancer therapyCancer researchBiologyBiochemistryPharmacologyGenetics

Abstract

fetched live from OpenAlex

Vanadium belongs among the microelements and plays a role in human nutrition. However, it is not regarded as an essential micronutrient. Vanadium affects various biochemical processes and when present in the body, it is capable of interacting with a notable number of enzymes e.g. protein kinases, phosphatases, ATPases, peroxidases, ribonucleases, oxidoreductases and others. It is documented in scientific literature that vanadium takes part in biochemical processes in mammals. Vanadium is not carcinogenic but its presence in cancer cells and its interactions with many key enzymatic processes results in modified expression of p53 and Bax and in down regulation of Bcl2 proteins and in antiproliferative activity. Anti-carcinogenic and anticancer effects of vanadium in various forms have been demonstrated using in vitro and in vivo experiments. Presently, epidemiologic and clinical studies are necessary for developing a clinically useful, vanadium-based anticancer agent/drug for chemoprevention of cancer. This review summarizes recent scientific information on the role and potential use of vanadium in cancer chemoprevention and cancer therapy.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.076
GPT teacher head0.400
Teacher spread0.324 · 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 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

Citations21
Published2014
Admission routes1
Has abstractyes

Explore more

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