Consumption of guava (Psidium guajava L) and noni (Morinda citrifolia L) may protect betel quid-chewing Papua New Guineans against diabetes.
Why this work is in the frame
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Bibliographic record
Abstract
Rapid increase in the incidence of type 2 diabetes (DM2) in Papua New Guinea, coupled with compelling epidemiological evidence supporting a diabetogenic association with betel quid (BQ) chewing has lead us to investigate dietary strategies that might offer protection from developing DM2. We investigated the dietary habits of Kalo residents from coastal Central Province who are avid BQ chewers yet have a relatively low incidence of DM2 compared to the ethnically similar and adjacent Wanigelans who abstain from BQ yet have an unusually high incidence of DM2. In Kalo, guava bud (Psidium guajava L) and noni (Morinda citrifolia L) were consumed much more frequently than in Wanigela, whereas the inverse was observed for mangrove bean (Bruguiera gymnorrhiza (L) Lam.). These plants, along with BQ and its component ingredients areca nut (Areca catechu L) and Piper betle L inflorescence, were assessed for their ability to mediate insulin-dependent and insulin-independent glucose transport in cultured 3T3-L1 adipocytes. A dose-dependent inhibition of glucose uptake from methanolic extracts of BQ, areca nut and P. betle inflorescence supports previous reports of prodiabetic activity. Conversely, guava bud extract displayed significant insulin-mimetic and potentiating activity. Noni fruit, noni leaf, commercial noni juice and mangrove bean all displayed insulin-like activity but had little or no effect on insulin action. Habitual intake of guava and noni is proposed to offer better protection against DM2 development and/or betel quid diabetogenicity than cooked mangrove bean. These findings provide empirical support that DM2 risk reduction can be accomplished using traditional foods and medicines.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it