FDCNet: Presentation of the Fuzzy CNN and Fractal Feature Extraction for Detection and Classification of Tumors.

The detection of brain tumors using magnetic resonance imaging is currently one of the biggest challenges in artificial intelligence and medical engineering. It is important to identify these brain tumors as early as possible, as they can grow to death. Brain tumors can be classified as benign or malignant. Creating an intelligent medical diagnosis system for the diagnosis of brain tumors from MRI imaging is an integral part of medical engineering as it helps doctors detect brain tumors early and oversee treatment throughout recovery. In this study, a comprehensive approach to diagnosing benign and malignant brain tumors is proposed. The proposed method consists of four parts: image enhancement to reduce noise and unify image size, contrast, and brightness, image segmentation based on morphological operators, feature extraction operations including size reduction and selection of features based on the fractal model, and eventually, feature improvement according to segmentation and selection of optimal class with a fuzzy deep convolutional neural network. The BraTS data set is used as magnetic resonance imaging data in experimental results. A series of evaluation criteria is also compared with previous methods, where the accuracy of the proposed method is 98.68%, which has significant results.

Berberine Inhibits the Gene Expression and Production of Proinflammatory Cytokines by Mononuclear Cells in Rheumatoid Arthritis and Healthy Individuals.

OBJECTIVE: Rheumatoid arthritis (RA) is the most prevalent autoimmune arthritis. Berberine is an alkaloid isolated from Berberis vulgaris, and its anti-inflammatory effect has been identified. METHODS: Twenty newly diagnosed RA patients and 20 healthy controls participated. Peripheral mononuclear cells were prepared and stimulated with bacterial lipopolysachharide (LPS,1 µg/ml), exposed to different concentrations of berberine (10 and 50µM) and dexamethasone (10-7 M) as a reference. The toxicity of compounds was evaluated by WST-1 assay. The expression of TNF-α and IL-1ß was determined by quantitative real-time PCR. Protein level of secreted TNF-α and IL-1ß was measured by using ELISA. RESULTS: Berberine did not have any toxic effect on cells, whereas Lipopolysaccharide (LPS) stimulation caused a noticeable rise in TNF-α and IL-1ß production. Berberine markedly downregulated the expression of both TNF-α and IL-1ß, and inhibited TNF-α and IL-1ß secretion from LPS-stimulated PBMCs. DISCUSSION: This study provided a molecular basis for anti-inflammatory effect of berberine on human mononuclear cells through the suppression of TNF-a and IL-1secretion. Our findings highlighted the significant inhibitory effect of berberine on proinflammatory responses of mononuclear cells from rheumatoid arthritis individuals, which may be responsible for antiinflammatory property of Barberry. We observed that berberine at high concentration exhibited anti-inflammatory effect in PBMCs of both healthy and patient groups by suppression of TNF-a and IL-1cytokines at both mRNA and protein levels. CONCLUSION: Berberine may inhibit the gene expression and production of pro-inflammatory cytokines by mononuclear cells in rheumatoid arthritis and healthy individuals without affecting cell viability. Future studies with a larger sample size are needed to prove the idea.