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Record W1980102481 · doi:10.1177/1534735405285562

Targeting Angiogenesis With Integrative Cancer Therapies

2006· review· en· W1980102481 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIntegrative Cancer Therapies · 2006
Typereview
Languageen
FieldMedicine
TopicMagnolia and Illicium research
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
FundersHealth CanadaUniversity of Texas MD Anderson Cancer Center
KeywordsAngiogenesisScutellaria baicalensisGinsengTraditional medicinePharmacologyBiologyMedicineCancer researchTraditional Chinese medicine

Abstract

fetched live from OpenAlex

An integrative approach for managing a patient with cancer should target the multiple biochemical and physiological pathways that support tumor development while minimizing normal tissue toxicity. Angiogenesis is a key process in the promotion of cancer. Many natural health products that inhibit angiogenesis also manifest other anticancer activities. The authors will focus on natural health products (NHPs) that have a high degree of antiangiogenic activity but also describe some of their many other interactions that can inhibit tumor progression and reduce the risk of metastasis. NHPs target various molecular pathways besides angiogenesis, including epidermal growth factor receptor (EGFR), the HER-2/neu gene, the cyclooxygenase-2 enzyme, the NF-kB transcription factor, the protein kinases, Bcl-2 protein, and coagulation pathways. The herbalist has access to hundreds of years of observational data on the anticancer activity of many herbs. Laboratory studies are confirming the knowledge that is already documented in traditional texts. The following herbs are traditionally used for anticancer treatment and are antiangiogenic through multiple interdependent processes that include effects on gene expression, signal processing, and enzyme activities: Artemisia annua (Chinese wormwood), Viscum album (European mistletoe), Curcuma longa (turmeric), Scutellaria baicalensis (Chinese skullcap), resveratrol and proanthocyanidin (grape seed extract), Magnolia officinalis (Chinese magnolia tree), Camellia sinensis (green tea), Ginkgo biloba, quercetin, Poria cocos, Zingiber officinale (ginger), Panax ginseng, Rabdosia rubescens (rabdosia), and Chinese destagnation herbs. Quality assurance of appropriate extracts is essential prior to embarking on clinical trials. More data are required on dose response, appropriate combinations, and potential toxicities. Given the multiple effects of these agents, their future use for cancer therapy probably lies in synergistic combinations. During active cancer therapy, they should generally be evaluated in combination with chemotherapy and radiation. In this role, they act as biological response modifiers and adaptogens, potentially enhancing the efficacy of the so-called conventional therapies. Their effectiveness may be increased when multiple agents are used in optimal combinations. New designs for trials to demonstrate activity in human subjects are required. Although controlled trials might be preferred, smaller studies with appropriate end points and surrogate markers for antiangiogenic response could help prioritize agents for the larger resource-intensive phase 3 trials.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.403
Teacher spread0.341 · 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