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A Mini Review of Underutilized Native Plants from East Malaysia’s Rainforestsas Potential Hypertensive Drugs

2022· review· en· W4280643258 on OpenAlexaboutno aff
Fong Tyng Chee, Su Na Chin, Fui Fui Lem

Bibliographic record

VenueThe Natural Products Journal · 2022
Typereview
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsnot available
Fundersnot available
KeywordsEthnomedicineIndigenousRainforestMedicinal plantsTraditional medicineEthnic groupMedicineNative plantGeographyBiologyIntroduced speciesEcologyPolitical science

Abstract

fetched live from OpenAlex

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.318
Teacher spread0.257 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations0
Published2022
Admission routes1
Has abstractyes

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