Objectives: Whole plants of Boerhavia diffusa L. are widely used medicine in Ghana and other tropical countries, for the treatment of wounds and other ailments. The aim of the study was to determine the ability of sequential extracts of B. diffusa to influence oxidation and wound closure in myoblast cells in vitro.
Methods: Sequential extracts were prepared from the whole plant using four solvents of increasing polarity (hexane, ethyl acetate, methanol and water). Cytotoxicity was determined using the sulforhodamine B staining assay, phase-contrast microscopy, plasDIC microscopy and live-dead staining. Extracts were tested for their ability to reduce 2,2'-azobis(2-amidinopropane) dihydrochloride (AAPH)-induced oxidation and mediate cell migration after artificial wound generation in C2C12 myoblast cells using the scratch wound assay.
Key Findings: All extracts indicated negligible cytotoxicity (IC > 100 μg/ml), and microscopic evaluation showed no difference from negative controls. AAPH induced a 2.87-fold increase in reactive oxygen species compared to the negative control. Pretreatment with 100 μg/ml of the extracts reduced AAPH-induced oxidation to 1.70-fold of the untreated controls (P < 0.001). Wound closures in the methanol and water extract treatments were 18.08% and 20.76% higher than the negative control, respectively (P < 0.01).
Conclusions: These findings indicate that the hexane, methanol and water extracts of B. diffusa whole plant promote artificial wound healing and protection against oxidation in vitro and therefore warrant further research into its mechanisms of wound healing.
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In the current cybersecurity landscape, Distributed Denial of Service (DDoS) attacks have become a prevalent form of cybercrime. These attacks are relatively easy to execute but can cause significant disruption and damage to targeted systems and networks. Generally, attackers perform it to make reprisal but sometimes this issue can be authentic also.
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Department of Pediatrics, Division of Emergency Medicine, University of Texas Southwestern, Children's Medical Center, Dallas, TX, USA.
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Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore, Tamil Nadu 641032 India.
Cross subject Electroencephalogram (EEG) emotion recognition refers to the process of utilizing electroencephalogram signals to recognize and classify emotions across different individuals. It tracks neural electrical patterns, and by analyzing these signals, it's possible to infer a person's emotional state. The objective of cross-subject recognition is to create models or algorithms that can reliably detect emotions in both the same person and several other people.
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