The Anti-Inflammatory and the Antinociceptive Effects of Mixed Agrimonia pilosa Ledeb. and Salvia miltiorrhiza Bunge Extract.
Jing-Hui FengHyun-Yong KimSu-Min SimGuang-Lei ZuoJeon-Sub JungSeung-Hwan HwangYoun-Gil KwakMin-Jung KimJeong-Hun JoSung-Chan KimSoon-Sung LimHong-Won SuhPublished in: Plants (Basel, Switzerland) (2021)
Arthritis is a common condition that causes pain and inflammation in a joint. Previously, we reported that the mixture extract (ME) from Agrimonia pilosa Ledeb. (AP) and Salvia miltiorrhiza Bunge (SM) could ameliorate gout arthritis. In the present study, we aimed to investigate the potential anti-inflammatory and antinociceptive effects of ME and characterize the mechanism. We compared the anti-inflammatory and antinociceptive effects of a positive control, Perna canaliculus powder (PC). The results showed that one-off and one-week treatment of ME reduced the pain threshold in a dose-dependent manner (from 10 to 100 mg/kg) in the mono-iodoacetate (MIA)-induced osteoarthritis (OA) model. ME also reduced the plasma TNF-α, IL-6, and CRP levels. In LPS-stimulated RAW 264.7 cells, ME inhibited the release of NO, PGE2, LTB4, and IL-6, increased the phosphorylation of PPAR-γ protein, and downregulated TNF-α and MAPKs proteins expression in a concentration-dependent (from 1 to 100 µg/mL) manner. Furthermore, ME ameliorated the progression of ear edema in mice. In most of the experiments, ME-induced effects were almost equal to, or were higher than, PC-induced effects. Conclusions: The data presented here suggest that ME shows anti-inflammatory and antinociceptive activities, indicating ME may be a potential therapeutic for arthritis treatment.
Keyphrases
- anti inflammatory
- rheumatoid arthritis
- diabetic rats
- high glucose
- chronic pain
- oxidative stress
- drug induced
- poor prognosis
- clinical trial
- neuropathic pain
- binding protein
- type diabetes
- machine learning
- metabolic syndrome
- big data
- knee osteoarthritis
- spinal cord injury
- cell cycle arrest
- insulin resistance
- inflammatory response
- uric acid
- spinal cord
- fatty acid
- signaling pathway
- deep learning