Genetically modified autism model monkeys make new achievements.

the Chinese Academy of Sciences Brain Science and Intelligent Technology Excellence Innovation Center, Shanghai Brain Science and Brain Research Center, Neuroscience National Key Laboratory Wang Zheng research team and the Chinese Academy of Sciences Institute of Automation Research team, the first international design of monkey-human cross-species machine learning analysis process, the use of genetically modified macaque model characteristics, the construction of clinical mental illness patients classifier model, and then in-depth analysis of human autism and obsessive-compulsive neuroloop mechanism, for the use of mental illness imagediagnosticThe findings were published online June 17 in the American Journal of Psychiatrynon-human primate model animals and humans in brain structure and function are relatively close, genetically modified primate models can show similar symptompoids to human clinical patients, such as MECP2 over-expression of macaques show repeated stereotyped behavior, social behavior disorders and other autistic symptoms"We are working on the basis of the original innovation work, which in a sense is an extension of the results of the genetically modified autism model macaques, " Wang said"We hope to build a bridge through genetically modified autism model macaques to explore new ideas for clinicaldiagnosisautism-related diseases through magnetic resonance imaging." In an exploration of possible evolutionary conservative characteristics among primate species,Wang Zheng, the team boldly hypothesized that a predictive model of classification of mental illness that can migrate across species, based on conservative brain region functionsthe researchers first used "sparse learning" to screen brain region data from brain function maps from five genetically modified macaques and 11 wild macaques to identify nine core brain regions, and then mapped each of the nine brain regions to the human brain and used functional connections of the brain to form a collection of features to build a sparse logic regression classifier for diagnosis
diagnosis of autism, obsessive-compulsive disorder and attention deficit hyperactivity disorderThe study collected four clinical patient imaging databases from ABIDE-I-ABIDE-II, OCD and ADHD-200by integrating primate models with functional magnetic resonance imaging data from patients with clinical mental illness, the researchers found that classification models based on the characteristics of genetically modified macaques had an 82.14 percent accuracy of the distinction between autistic and normal people in the ABIDE-I data set, and 75.17 percent accuracy for human subjects in the ABIDE-II database, significantly higher than the performance of building classifiers based on the characteristics of autism and obsessive-compulsive disorder patientsWhen the same nine brain regions were extended to obsessive-compulsive imaging data, it was found that the macaque feature-building classification model still achieved 78.36 percent accuracy, significantly higher than the classifier performance based on the characteristics of autistic patientsThese characteristics based on macaque model learning have not significantly improved the classification accuracy of ADHD patients": "The clinical manifestations of autism are diverse, from anxiety to social disorders, to language disorders..The genes behind various symptoms are ever-changing, which is also an important reason for the low accuracy of clinical diagnosisWe hope that this study, based on primate models of a single disease genetic background, will provide a more accurate and objective basis for clinical imagingdiagnosisWang Zheng said(
Bio valleyBioon.com).