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Record W4213217853 · doi:10.3747/co.v15i2.238

Chinese Medicine and Biomodulation in Cancer Patients—Part Two

2008· article· en· W4213217853 on OpenAlexaffvenue
Stephen M. Sagar, Ryan Wong

Bibliographic record

VenueCurrent Oncology · 2008
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsJuravinski Cancer Centre
Fundersnot available
KeywordsMedicineTraditional Chinese medicineImmune systemCancerImmunopotentiatorAdverse effectDiseaseInnate immune systemTraditional medicineBioinformaticsImmunologyPharmacologyInternal medicineAlternative medicineBiologyPathology

Abstract

fetched live from OpenAlex

Traditional Chinese Medicine (TCM) is a whole system containing therapeutic interventions that individually induce biomodulation at the physiologic, chemical, and molecular levels. The theory of TCM proposes a synergy between specific interventions selected as part of a care plan based on TCM diagnostic theory. Combining TCM with the modern practice of oncology seems, in conjunction with biomedical interventions (surgery, radiotherapy, chemotherapy, and pharmaceuticals), to have potential advantages through the synergy of biomodulation. Biomodulation approaches are broadly categorized as modification of tumour response and reduction of adverse effects; modulation of immunity; prevention of cancer progression; and enhancement of symptom control. Although the database of preclinical studies is rapidly expanding, good-quality clinical trials are notably scarce. Laboratory studies suggest that some herbs increase the effectiveness of conventional chemotherapy without increasing toxicity. A healthy immune system is necessary for control of malignant disease, and the immune suppression associated with cancer contributes to its progression. Many Chinese herbs contain glycoproteins and polysaccharides (among them, constituents of Coriolus versicolor, Ganoderma lucidum, Grifola frondosa, Astragalus membranaceus, Panax ginseng, and various other medicinal mushrooms) that can modulate metastatic potential and the innate immune system. Phytochemicals such as specific polysaccharides have been shown to boost the innate immune system, especially through interaction with Toll-like receptors in mucosa-associated lymphoid tissue. This intervention can potentially improve the effectiveness of new anticancer vaccines. An increase in virus-associated cancers presents a major public health problem that requires novel therapeutic strategies. A number of herbal therapies have both antiviral activity and the ability to promote immunity, possibly inhibiting the initiation and promotion of virus-associated cancers. The mechanisms learned from basic science should be applied to clinical trials both of specific interventions and of whole-system care plans that safely combine the TCM approach with the conventional biomedical model. In Western medicine, the combination of TCM herbs with drug therapies is controversial, given lack of knowledge concerning whether a drug is favourably enhanced or whether adverse effects occur. Using initial data from the preclinical studies, future clinical research needs to evaluate the combinations, some of which are showing favourable synergy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.124
GPT teacher head0.472
Teacher spread0.348 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations7
Published2008
Admission routes2
Has abstractyes

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