Combretum micranthum G. Don (Combretaceae): A Review on Traditional Uses, Phytochemistry, Pharmacology and Toxicology.
Yoro TineMadieye SeneCheikhouna GayeAlioune DialloBenjamin NdiayeIdrissa NdoyeAlassane WelePublished in: Chemistry & biodiversity (2024)
Combretum micranthum (Combretaceae) is a medicinal plant widely known and used in Africa to treat a variety of conditions such as diabetes, fever, coughs, bronchitis, diarrhea, pain, malaria and liver disorders, among others. Due to its wide traditional use, in this review, published scientific reports on its composition and pharmacological properties were explored by conducting a literature search of databases. To date, 155 organic compounds including 34 flavonoids, 16 phenolic acids, 14 alkaloids, 15 fatty acids, 14 terpenoids/steroids, 24 amino acids, 8 carbohydrate substances and 30 other organic compounds have been identified from this plant. In addition to these organic compounds, 6 minerals (potassium nitrate, calcium, magnesium, potassium, sodium, iron and zinc) have also been reported. In vitro and in vivo studies have shown that these phytochemicals and plant extracts have a wide range of pharmacological potential, including antibacterial, antiviral, antioxidant, antidiabetic, anti-inflammatory, analgesic, antihypertensive, nephroprotective, hepatoprotective, anxiolytic, anti-cholinesterase and antidiarrheal activities. Additionally, no harmful effects have been revealed through studies. Thus, this study could constitute a valuable reference for the valorization of C. micranthum in the pharmaceutical industry.
Keyphrases
- anti inflammatory
- fatty acid
- water soluble
- drinking water
- type diabetes
- cardiovascular disease
- neuropathic pain
- chronic pain
- amino acid
- systematic review
- blood pressure
- case control
- nitric oxide
- oxidative stress
- pain management
- cell wall
- metabolic syndrome
- emergency department
- randomized controlled trial
- adipose tissue
- clostridium difficile
- big data
- spinal cord injury
- spinal cord
- adverse drug
- machine learning
- iron deficiency
- insulin resistance
- artificial intelligence
- drug induced
- electronic health record
- oxide nanoparticles