Neuroscience
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Peripheral nerve injury (PNI) is a common disease that causes the partial loss of sensory, exercise, and autonomic nervous function. In clinical practice, accurate end-to-end neurorrhaphy of the epineurium without tension is the ideal treatment when there is no nerve defect. We have confirmed that peripheral blood mononuclear cells (PBMCs) can effectively improve nerve regeneration and motor function recovery after PNI. ⋯ We then used TMT labeling quantitative proteomics to explore the underlying mechanism by which PBMCs ameliorated sciatic nerve injury. Results showed that PBMCs regulated 40 differential proteins and the regulated proteins were primarily involved in the complement and coagulation cascade pathways, the notch signaling pathway, the renin angiotensin system, DNA replication, histidine metabolism, β-alanine metabolism, and other types of O-glycan biosynthesis. Immunohistochemical results supported our findings on the changes in expression of Kininogen 1 and Psen1, the relationships between PNI and the notch pathway and the complement and coagulation level pathways.
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Glioblastoma multiforme (GBM) is one of the most common, most formidable, and deadliest malignant types of primary astrocytoma with a poor prognosis. At present, the standard of care includes surgical tumor resection, followed by radiation therapy concomitant with chemotherapy and temozolomide. New developments and significant advances in the treatment of GBM have been achieved in recent decades. ⋯ In this review, we outline some of the most recent literature on the various available treatment options such as surgery, radiotherapy, cytotoxic chemotherapy, gene therapy, immunotherapy, phototherapy, nanotherapy, and tumor treating fields in the treatment of GBM, and we list some of the potential future directions of GBM. The reviewed studies confirm that GBM is a sophisticated disease with several challenges for scientists to address. Hence, more studies and a multimodal therapeutic approach are crucial to yield an effective cure and prolong the survival of GBM patients.
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Early and accurate diagnosis of Alzheimer's disease (AD) and its prodromal period mild cognitive impairment (MCI) is essential for the delayed disease progression and the improved quality of patients' life. The emerging computer-aided diagnostic methods that combine deep learning with structural magnetic resonance imaging (sMRI) have achieved encouraging results, but some of them are limit of issues such as data leakage, overfitting, and unexplainable diagnosis. In this research, we propose a novel end-to-end deep learning approach for automated diagnosis of AD. ⋯ Our approach has been evaluated on two publicly accessible datasets for two classification tasks of AD vs. cognitively normal (CN) and progressive MCI (pMCI) vs. stable MCI (sMCI). The experimental results indicate that our approach outperforms the state-of-the-art approaches, including those using multi-model and three-dimensional (3D) CNN methods. The resultant heatmaps from our approach also highlight the lateral ventricle and some regions of cortex, which have been proved to be affected by AD.
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Somatosensory neurons detect vital information about the environment and internal status of the body, such as temperature, touch, itch, and proprioception. The circuit mechanisms controlling the coding of somatosensory information and the generation of appropriate behavioral responses are not clear yet. ⋯ In this study we describe and validate a rabies tracing approach for mapping mouse spinal circuits receiving sensory input from distinct, genetically defined, modalities. We analyzed the anatomical organization of spinal circuits involved in coding of thermal and mechanical stimuli and showed that somatosensory information from distinct modalities is relayed to partially overlapping ensembles of interneurons displaying stereotyped laminar organization, thus highlighting the importance of positional features and population coding for the processing and integration of somatosensory information.