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.

Background and aim Cholestasis-associated renal injury or cholemic nephropathy (CN) is a serious clinical problem. Previous studies mentioned that oxidative stress and mitochondrial impairment play a role in CN. There is no specific pharmacological intervention for CN. Metformin is an anti-diabetic drug administered for decades. On the other hand, novel pharmacological properties have emerged for this drug. The effect of metformin on oxidative stress parameters has been well-recognized in different experimental models. It has also been found that metformin positively affected mitochondrial function. The current study aimed to evaluate the effects of metformin in an animal model of CN. Methods Rats underwent bile duct ligation (BDL) and were treated with metformin (250 and 500 mg/kg) for 14 consecutive days. Two weeks after the BDL operations, urine, serum, and kidney samples were collected and analyzed. Results Markers of oxidative stress, including reactive oxygen species (ROS) formation, lipid peroxidation, protein carbonylation, depleted antioxidant capacity, and decreased glutathione (GSH) levels were detected in BDL animals. Moreover, mitochondrial indices, including adenosine triphosphate (ATP) level, dehydrogenase activity, mitochondrial membrane potential, and mitochondrial permeability, were impaired in the kidney of cholestatic rats. Renal histopathological alterations in cholestatic animals included tubular degeneration and interstitial inflammation, cast formation, and fibrosis. It was found that metformin significantly alleviated oxidative stress and improved mitochondrial indices in the kidney of cholestatic rats. Tissue histopathological alterations were also mitigated in metformin-treated groups. Conclusions Metformin could be a candidate for managing CN. The nephroprotective role of metformin is primarily associated with its effects on oxidative stress parameters and mitochondrial function.