ABSTRACT
Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI’s role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O’Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient’s prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.
ABSTRACT
Background: Alzheimer's Disease [AD] is a neurodegenerative disorder, which is the most common cause of dementia in the elderly. Accumulation of beta-amyloid plaques outside neurons is the most important pathological hallmark of AD, which is produced by cleavage of amyloid precursor protein by the Alzheimer's beta-secretase [BACE1]. Since BACE1 is a key enzyme in the formation of beta-amyloid peptides, the purpose of this study was to assess the association between polymorphisms of G/C [rs638405] BACE1 gene with sporadic AD in Khuzestan, Isfahan and Fars provinces in Iran
Methods: Genotypes were determined by the PCRRestriction Fragment Length Polymorphism [PCRRFLP] technique in two groups including 89 sporadic AD patients and 73 healthy subjects
Results: The findings of the BACE1 G/C [rs638405] polymorphism revealed that there was no significant difference between AD patients and controls in men group; however, there was a weak difference in the frequency of CC genotype between patients and controls in women group [?2=3.333, df=1, p=0.068]
Conclusion: The results of this study suggest that the G/C [rs638405] polymorphism of BACE1 gene might not be related with sporadic AD in Khuzestan, Isfahan and Fars provinces in Iran. However, our results do not support a genetic risk factor of this polymorphism for developing AD in male group of this study