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Record W2127496998 · doi:10.1186/1752-153x-3-13

Antioxidant activity of noni juice in heavy smokers

2009· article· en· W2127496998 on OpenAlexaff
Mian-Ying Wang, M. Nawal Lutfiyya, Vicki Weidenbacher-Hoper, Gary L. Anderson, Chen X. Su, Brett J. West

Bibliographic record

VenueChemistry Central Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicMorinda citrifolia extract uses
Canadian institutionsUniversity of ManitobaWinnipeg Regional Health Authority
Fundersnot available
KeywordsChemistryAntioxidantPlaceboIn vivoMorindaPlacebo groupPharmacologyTraditional medicineBiochemistryMedicineBiotechnology

Abstract

fetched live from OpenAlex

BACKGROUND: Noni (Morinda citrifolia) juice has demonstrated antioxidant activity in vitro and in vivo. To evaluate this activity in humans, noni juice from Tahiti (TNJ) was evaluated in a 30 day, double-blind, and placebo controlled clinical trial with 285 current heavy smokers. Research participants were randomly assigned to three daily treatment groups: 118 mL placebo, 29.5 mL TNJ, and 118 mL TNJ. Plasma superoxide anion radicals (SAR) and lipid hydroperoxide (LOOH) levels were measured pre and post-intervention. RESULTS: After 30 days, mean SAR decreased from 0.26 +/- 0.14 to 0.19 +/- 0.10 micromol/mL in the 29.5 mL dose group (P < 0.01) and from 0.26 +/- 0.22 to 0.18 +/- 0.11 micromol/mL in the 118 mL dose group (P < 0.001). LOOH levels decreased from 0.53 +/- 0.19 to 0.40 +/- 0.10 micromol/mL in the 29.5 mL dose group (P < 0.001) and from 0.55 +/- 0.21 to 0.40 +/- 0.14 micromol/mL in the 118 mL dose group (P < 0.001). No significant reductions in SAR or LOOH levels were observed in the placebo group. CONCLUSION: The results suggest an antioxidant activity from noni juice in humans exposed to tobacco smoke, thereby replicating the results found previous chemical and in vivo tests.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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 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

Citations62
Published2009
Admission routes1
Has abstractyes

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