Artificial Neural Network is a branch of Artificial intelligence, has been accepted as a new technology in computer science. Neural Networks are currently a 'hot' research area in medicine, particularly in the fields of radiology, urology, cardiology, oncology and etc. It has a huge application in many areas such as education, business; medical, engineering and manufacturing .Neural Network plays an important role in a decision support system. In this paper, an attempt has been made to make use of neural networks in the medical field (carcinogenesis (pre-clinical study)). In carcinogenesis, artificial neural networks have been successfully applied to the problems in both pre-clinical and post-clinical diagnosis. The main aim of research in medical diagnostics is to develop more cost-effective and easy-to-use systems, procedures and methods for supporting clinicians. It has been used to analyze demographic data from lung cancer patients with a view to developing diagnostic algorithms that might improve triage practices in the emergency department. For the lung cancer diagnosis problem, the concise rules extracted from the network achieve an high accuracy rate of on the training data set and on the test data set.
Cell repair/replacing strategies for neurodegenerative diseases such as Parkinson's disease depend on well-characterized dopaminergic neuronal candidates that are healthy and show promising effect on the rejuvenation of degenerated area of the brain. Therefore, it is imperative to develop innovative therapeutic strategies that replace damaged neurons with new/functional dopaminergic neurons. Although several research groups have reported the generation of neural precursors/neurons from human/ mouse embryonic stem cells and mesenchymal stem cells, the latter is considered to be an attractive therapeutic candidate because of its high capacity for self-renewable, no adverse effect to allogeneic versus autologous transplants, high ethical acceptance and no teratoma formation. Therefore, mesenchymal stem cells can be considered as an ideal source for replacing lost cells in degenerative diseases like Parkinson's. Hence, the use of these cells in the differentiation of dopaminergic neurons becomes significant and thrives as a therapeutic approach to treat Parkinson's disease. Here we highlight the basic biology of mesenchymal stem cells, their differentiation potential into dopaminergic neurons and potential use in the clinics.
To control the total treatment cost of textile dye effluent a new advanced combined treatment technology has been investigated. Advanced oxidation processes like ozonation have much potential to degrade dye but its main drawback is high cost. To reduce the cost of ozonation for dye degradation and decolourization, ozonation followed by anaerobic biodegradation using upflow anaerobic sludge blanket (UASB) reactor was carried out. The synthetic textile wastewater containing Reactive Black 5 has been used in this study by this combined treatment process. The system of ozonation and anaerobic treatment by UASB reactor showed that the chemical oxygen demand (COD) reduction has reached to about 90% and dye removal 94% respectively. Combined treatment enhanced the overall color removal up to 10 on platinum cobalt (Pt-Co) scale. Thus the combined treatment process results in high color, COD and total organic carbon (TOC) removal efficiency which would minimize the overall treatment cost. Dye degradation products were analyzed by ion chromatography (IC) and UV-vis spectroscopy.
Although neural stem cells (NSCs) have potential applications in treating neurological disorders, much still needs to be understood about the differentiation biology for their successful clinical translation. In this study, we aimed at deriving NSCs from human umbilical cord blood-derived mesenchymal stem cells (hUCB-MSCs) and explored the role of Notch signaling in the differentiation process. The hUCB-MSCs were characterized as per guidelines of the International Society of Cellular Therapy. NSCs were successfully generated from hUCB-MSCs by using epidermal and fibroblast growth factors under serum-free conditions. The expression of NSC markers (Nestin and Musashi-1) in the neurospheres generated from hUCB-MSCs in the presence or absence of N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butyl ester (DAPT; Notch inhibitor) was immuno-phenotypically characterized by using immunofluorescence. DAPT showed significant (*p < 0.05) downregulated expression of the NSC markers-Nestin and SOX2-at different time points (6 hours, 12 hours, 24 hours, 36 hours, and 5 days) post-treatment. In addition, Mushashi-1 (NSC marker) expression in NSCs was also inhibited after DAPT treatment, which signifies that the process is Notch dependent. These data were further correlated with formation of a reduced average number of neurospheres derived from hUCB-MSCs (2 colonies vs. 11 colonies/field of view) in the presence of DAPT compared with the control (without DAPT). The expression of Notch target genes in NSC cultures (Notch intracellular domain [NICD], HES1, and HES5) was also significantly downregulated after DAPT treatment. In the presence of DAPT, the markers for neuronal (MAP2, NEFH); and glial (GFAP, GLUL, and MBP) lineages were significantly downregulated as seen via immunofluorescence and quantitative polymerase chain reaction, indicating the role of Notch in the tri-differentiation mechanism of NSCs as well. In addition, Notch signaling inhibition induced higher cell death during the lineage commitment of NSCs as measured 3 days (16.9% vs. 8.9%) and 6 days (42.9% vs. 20.8%) postinduction. These results suggest that the efficient derivation of NSCs and their subsequent lineage commitment from hUCB-MSCs requires the Notch signaling pathway.
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