METHODS: Male Sprague Dawley rats were subjected to permanent bilateral occlusion of common carotid arteries (PBOCCA) or sham surgery. Then, PBOCCA rats received ip injections with, either vehicle (control group), the muscarinic receptor agonist oxotremorine (0.1 mg/kg), or the acetylcholinesterase inhibitor physostigmine (0.1 mg/kg). Cognitive functions were evaluated using a passive avoidance task and the Morris water maze test. In addition, hippocampal LTP was recorded in vivo under anaesthesia.
RESULTS: The PBOCCA rats exhibited significant deficits in passive avoidance retention and spatial learning and memory tests. They also showed a suppression of LTP formation in the hippocampus. Oxotremorine and physostigmine significantly improved the learning and memory deficits as well as the suppression of LTP in PBOCCA rats.
CONCLUSIONS: The present data suggest that the cholinergic system plays an important role in CCH-induced cognitive deficits and could be an effective therapeutic target for the treatment of VaD.
AIM OF THE STUDY: Alzheimer's disease is the most significant type of neurodegenerative disorder plaguing societies globally. Its pathogenesis encompasses the hallmark aggregation of amyloid-beta (Aβ). Of all the Aβ oligomers formed in the brain, Aβ42 is the most toxic and aggressive. Despite this, the mechanism behind this disease remains elusive. In this study, DWE, and its major components, Salvianolic acid A (SalA) and Salvianolic acid B (SalB) were tested for their abilities to attenuate Aβ42's toxic effects.
METHODS: The composition of DWE was determined via Ultra-Performance Liquid Chromatography (UPLC). DWE, SalA and SalB were first verified for their capability to diminish Aβ42 fibrillation using an in vitro activity assay. Since Aβ42 aggregation results in neuronal degeneration, the potential Aβ42 inhibitors were next evaluated on Aβ42-exposed PC12 neuronal cells. The Drosophila melanogaster AD model was then employed to determine the effects of DWE, SalA and SalB.
RESULTS: DWE, SalA and SalB were shown to be able to reduce fibrillation of Aβ42. When tested on PC12 neuronal cells, DWE, SalA and SalB ameliorated cells from cell death associated with Aβ42 exposure. Next, DWE and its components were tested on the Drosophila melanogaster AD model and their rescue effects were further characterized. The UPLC analysis showed that SalA and SalB were present in the brains and bodies of Drosophila after DWE feeding. When human Aβ42 was expressed, the AD Drosophila exhibited degenerated eye structures known as the rough eye phenotype (REP), reduced lifespan and deteriorated locomotor ability. Administration of DWE, SalA and SalB partially reverted the REP, increased the age of AD Drosophila and improved most of the mobility of AD Drosophila.
CONCLUSION: Collectively, DWE and its components may have therapeutic potential for AD patients and possibly other forms of brain diseases.
Results: This review discusses the current status of mesenchymal stem cell (MSC) therapy for SCI, criteria to considering for the application of MSC therapy and novel biological therapies that can be applied together with MSCs to enhance its efficacy. Bone marrow-derived MSCs (BMSCs), umbilical cord-derived MSCs (UC-MSCs) and adipose tissue-derived MSCs (ADSCs) have been trialed for the treatment of SCI. Application of MSCs may minimize secondary injury to the spinal cord and protect the neural elements that survived the initial mechanical insult by suppressing the inflammation. Additionally, MSCs have been shown to differentiate into neuron-like cells and stimulate neural stem cell proliferation to rebuild the damaged nerve tissue.
Conclusion: These characteristics are crucial for the restoration of spinal cord function upon SCI as damaged cord has limited regenerative capacity and it is also something that cannot be achieved by pharmacological and physiotherapy interventions. New biological therapies including stem cell secretome therapy, immunotherapy and scaffolds can be combined with MSC therapy to enhance its therapeutic effects.
METHODS: An initial bibliometric analysis shows that the reviewed papers focused on Electromyogram(EMG), Electroencephalogram(EEG), Electrocardiogram(ECG), and Electrooculogram(EOG). These four categories were used to structure the subsequent content review.
RESULTS: During the content review, we understood that deep learning performs better for big and varied datasets than classic analysis and machine classification methods. Deep learning algorithms try to develop the model by using all the available input.
CONCLUSIONS: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosis.