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Record W1604746555 · doi:10.1002/ptr.4880

Neoplasm Prevention and Immuno‐Enhancement Mediated by Daily Consumption of a Proprietary Extract from North American Ginseng by Elderly Mice of a Cancer‐Prone Strain

2012· article· en· W1604746555 on OpenAlexafffund
Durairaj Punithavathi, Sandra C. Miller

Bibliographic record

VenuePhytotherapy Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGinseng Biological Effects and Applications
Canadian institutionsMcGill University
FundersMcGill University
KeywordsCancerGinsengMedicineBone marrowSpleenLeukemiaMouse strainImmune systemNeoplasmImmunologyCancer cellSplenocyteCancer researchInternal medicineBiologyPathologyGene

Abstract

fetched live from OpenAlex

Cells belonging to the innate immune system, known as natural killer (NK) cells, act as the first line of defense against developing neoplasms. We have previously shown in a leukemia-induced tumor model (mouse) that a proprietary extract (CVT-E002), of North American ginseng, administered in the diet, significantly increased the absolute numbers of NK cells, significantly decreased leukemia cells and significantly increased the life span of CVT-E002-fed leukemic mice. In the present study, we assessed the efficacy of this extract to inhibit the spontaneous development of tumors in elderly mice of the cancer-prone C3H strain. Dietary CVT-E002 was fed for approximately a year beginning when mice were almost 2 years of age. Control mice, consuming the same chow without CVT-E002, all developed assorted, palpable tumors between 22 and 33 months, while all mice consuming CVT-E002 remained alive and tumor-free until they were purposely euthanized as healthy animals. The absolute numbers of NK cells at euthanasia, in CVT-E002-consuming mice, were significantly elevated in both the spleen and bone marrow. Given these profoundly positive results and the fact that CVT-E002 already exists in the marketplace under the label Cold-fX®, the potential for cancer prevention in humans becomes apparent.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.364

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 head0.032
GPT teacher head0.359
Teacher spread0.327 · 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 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

Citations6
Published2012
Admission routes2
Has abstractyes

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