In the past, several animal disease models were developed to study the molecular mechanism of neurological diseases and discover new therapies, but the lack of equivalent animal models has minimized the success rate. A number of critical issues remain unresolved, such as high costs for developing animal models, ethical issues, and lack of resemblance with human disease. Due to poor initial screening and assessment of the molecules, more than 90% of drugs fail during the final step of the human clinical trial. To overcome these limitations, a new approach has been developed based on induced pluripotent stem cells (iPSCs). The discovery of iPSCs has provided a new roadmap for clinical translation research and regeneration therapy. In this article, we discuss the potential role of patient-derived iPSCs in neurological diseases and their contribution to scientific and clinical research for developing disease models and for developing a roadmap for future medicine. The contribution of humaniPSCs in the most common neurodegenerative diseases (e.g., Parkinson's disease and Alzheimer's disease, diabetic neuropathy, stroke, and spinal cord injury) were examined and ranked as per their published literature on PUBMED. We have observed that Parkinson's disease scored highest, followed by Alzheimer's disease. Furthermore, we also explored recent advancements in the field of personalized medicine, such as the patient-on-a-chip concept, where iPSCs can be grown on 3D matrices inside microfluidic devices to create an in vitro disease model for personalized medicine.
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The platform for precise proteomic profiling of targeted cell populations from heterogeneous tissue sections is developed. We demonstrate a seamless and systematic integration of LCM with an automated cap-IA for the handling of a very small-sized dissected tissues section from the kidney, liver and pancreatic Langerhans islet of rats. Our analysis reveals that the lowest LCM section area ≥ 0.125 mm2 with 10 µm thickness can be optimized for the detection of proteins through LCM-cap-IA integration. We detect signals ranging from a highly-abundant protein, β-actin, to a low-abundance protein, LC-3AB, using 0.125 mm2 LCM section from rat kidney, but, so far, a relatively large section is required for good quality of results. This integration is applicable for a highly-sensitive and accurate assessment of microdissected tissue sections to decipher hidden proteomic information of pure targeted cells. To validate this integration, PCK2 protein expression is studied within Langerhans islets of normal and diabetic rats. Our results show significant overexpression of PCK2 in Langerhans islets of rats with long-term diabetes.
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