A Mini Review of Underutilized Native Plants from East Malaysia’s Rainforestsas Potential Hypertensive Drugs
Bibliographic record
Abstract
Abstract: Hypertension is a risk factor for cardiovascular diseases, which are on the rise throughout the world at an alarming rate. As a result, a variety of techniques to help in the prevention and control of hypertension have been tried, one of which is the use of natural medicines derived from medicinal plants. The relevance of plant-based medicine is now recognised by western countries, as seen by Canada's Natural Health Product Regulations, which were promulgated in January 2004. The Southeast Asian rainforests, notably in East Malaysia, are home to a diverse range of medicinal plant species with endless potential as pharmacological candidates, particularly as antihypertensive agents. The indigenous ethnic groups of East Malaysia have long utilised a broad variety of medicinal plant species to treat hypertension, thanks to their extensive usage of traditional remedies and in-depth understanding of ethnomedicine, which are fundamental elements of their culture. However, scientific understanding of ethnomedicines used to treat hypertension, particularly the processes underlying their antihypertensive action, is inadequate. Based on previous scientific studies, this review aims to address the antihypertensive effects of medicinal plants used by indigenous ethnic groups in East Malaysia, Sabah, in order to provide insights into the mechanisms of the plants' antihypertensive activity for the development of antihypertensive agents from these native plants.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".