首页|University of Belgrade Reports Findings in Machine Learning (Prefrontal cortical synaptoproteome profile combined with machine learning predicts resilience towa rds chronic social isolation in rats)
University of Belgrade Reports Findings in Machine Learning (Prefrontal cortical synaptoproteome profile combined with machine learning predicts resilience towa rds chronic social isolation in rats)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting out of Belgrade, Serbia, by NewsRx edito rs, research stated, "Chronic social isolation (CSIS) of rats serves as an anima l model of depression and generates CSIS-resilient and CSIS-susceptible phenotyp es. We aimed to investigate the prefrontal cortical synaptoproteome profile of C SIS-resilient, CSIS-susceptible, and control rats to delineate biochemical pathw ays and predictive biomarker proteins characteristic for the resilient phenotype ." Our news journalists obtained a quote from the research from the University of B elgrade, "A sucrose preference test was performed to distinguish rat phenotypes. Class separation and machine learning (ML) algorithms support vector machine wi th greedy forward search and random forest were then used for discriminating CSI S-resilient from CSIS-susceptible and control rats. CSIS-resilient compared to C SIS-susceptible rat proteome analysis revealed, among other proteins, downregula ted glycolysis in- termediate fructose-bisphosphate aldolase C (Aldoc), and upregu lated clathrin heavy chain 1 (Cltc), calcium/calmodulin-dependent protein kinase type II (Cam2a), synaptophysin (Syp) and fatty acid synthase (Fasn) that are in volved in neuronal transmission, synaptic vesicular trafficking, and fatty acid synthesis. Comparison of CSIS-resilient and control rats identified downregulate d mitochondrial proteins ATP synthase subunit beta (Atp5f1b) and citrate synthas e (Cs), and upregulated protein kinase C gamma type (Prkcg), vesicular glutamate transporter 1 (Slc17a7), and synaptic vesicle glycoprotein 2 A (Sv2a) involved in signal transduction and synaptic trafficking. The combined protein difference s make the rat groups linearly separable, and 100% validation accu racy is achieved by standard ML models. ML algorithms resulted in four panels of discriminative proteins."
BelgradeSerbiaEuropeAlgorithmsCy borgsEmerging TechnologiesEnzymes and CoenzymesKinaseMachine LearningS ynthase
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