Adipogenic Constituents from the Bark of Larix laricina (Pinaceae) Used Traditionally by the Cree of Eeyou Istchee (Quebec, Canada) for the Treatment of Type-2 Diabetes
Bibliographic record
Abstract
Diabetes is a growing epidemic worldwide, especially among indigenous populations. Larix laricina was identified through an ethnobotanical survey as a traditional medicine used by Healers and Elders of the Cree of Eeyou Istchee of northern Quebec to treat symptoms of diabetes and subsequent in vitro screening confirmed its potential. We used a bioassay-guided fractionation approach to isolate the active principles responsible for the adipogenic activity of the organic extract (80% EtOH) of the bark of L. laricina . Post-confluent 3T3-L1 cells were differentiated in the presence or absence of the crude extract, fractions or isolates of L. laricina for 7 days, then triglycerides content was measured using AdipoRed reagent. We identified a new cycloartane triterpene (1), which strongly enhanced adipogenesis in 3T3-L1 cells with an EC 50 of 7.7µM. It is responsible for two thirds of the activity of the active fraction of L. laricina . The structure of compound 1 was established on the basis of spectroscopic methods (IR, HREIMS, 1D and 2D NMR) as 23-oxo-3-hydroxycycloart-24-en-26-oic acid. We also identified several known compounds, including three labdane-type diterpenes (2 – 4), two tetrahydrofuran-type lignans (5 – 6), three stilbenes (7 – 9), and taxifolin (10). Compound 2 (epitorulosol) also potentiated adipogenesis (EC 50 8.2µM). This is the first report of antidiabetic principles isolated from L. laricina , therefore increasing the interest in medicinal plants from the Cree pharmacopoeia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".