Anti-Arthritic and Immunomodulatory Potential of Methanolic, n-Hexane, and Ethyl Acetate Fractions of Bark of Acacia modesta on Complete Freund's Adjuvant-Induced Arthritis in Rats.

Rheumatoid arthritis is an autoimmune disorder and topic of interest for researchers due to its increasing frequency and limited treatment. Acacia modesta Wall is known to treat rheumatic disorders in the traditional system of medicinal plants. Traditional medicines are still required for the treatment of this disease due to the large number of side-effects caused by commercial medicines. In the current study, the antiarthritic potential of methanolic extract (AM-metha), n-hexane (AM-hexa) fraction, and ethyl acetate (AM-etha) fraction of the bark of A. modesta against a complete Freund's adjuvant rat model was evaluated. Evaluation using a digital plethysmometer, macroscopic evaluation, and histopathological evaluation were conducted to determine the paw volume and arthritic scoring. ELISA was performed to assess the PGE2 levels. RT-PCR was used to evaluate the expression levels of MMP2, MMP3, MMP9, NF-κB, IL6, IL1ß, TNFα, and VEGF. Biochemical and hematological analyses were also conducted. GC/MS was also carried out to analyze the presence of medicinal compounds. The data revealed a marked reduction in the paw volume, arthritic scoring, and histopathological parameters, indicating the anti-arthritic potential of the plant. Treatment with plant extracts and fractions markedly down-regulated MMP2, MMP3, MMP9, NF-κB, IL6, IL1ß, TNFα, and VEGF levels. Similarly, PGE2 levels were also found to be ameliorated in the treatment groups, indicating the immunomodulatory property of plant bark. Plant treatment nearly normalized hematological parameters such as counts of WBCs, RBCs, and platelets, along with Hb content, thereby validating the anti-arthritic activity. GC/MS analysis disclosed the presence of strong anti-inflammatory compounds such as lupeol, oleic acid, and squalene. The study showed that A. modesta possesses anti-arthritic and immunomodulatory potential linked to significant down-regulation of pro-inflammatory and inflammatory biomarkers.

Maximizing the extraction yield of plant gum exudate using response surface methodology and artificial neural networking and pharmacological characterization.

Prunus armeniaca gum is used as food additive and ethno medicinal purpose. Two empirical models response surface methodology and artificial neural network were used to search for optimized extraction parameters for gum extraction. A four-factor design was implemented for optimization of extraction process for maximum yield which was obtained under the optimized extraction parameter (temperature, pH, extraction time, and gum/water ratio). Micro and macro-elemental composition of gum was determined by using laser induced breakdown spectroscopy. Gum was evaluated for toxicological effect and pharmacological properties. The maximum predicted yield obtained by response surface methodology and artificial neural network was 30.44 and 30.70% which was very close to maximum experimental yield 30.23%. Laser induced breakdown spectroscopic spectra confirmed the presence Calcium, Potassium, Magnesium, Sodium, Lithium, Carbon, Hydrogen, Nitrogen and Oxygen. Acute oral toxicity study showed that gum is non-toxic up to 2000 mg/Kg body weight in rabbits, accompanied by high cytotoxic effects of gum against HepG2 and MCF-7cells by MTT assay. Overall, Aqueous solution of gum showed various pharmacological activities with significant value of antioxidant, antibacterial, anti-nociceptive, anti-cancer, anti-inflammatory and thrombolytic activities. Thus, optimization of parameters using mathematical models cans offer better prediction and estimations with enhanced pharmacological properties of extracted components.