Psychiatric comorbidity is common in symptom-based diagnoses like autism spectrum disorder (ASD), attention/deficit hyper-activity disorder (ADHD), and obsessive-compulsive disorder (OCD). However, these co-occurring symptoms mediated by shared and/or distinct neural mechanisms are difficult to profile at the individual level. Capitalizing on unsupervised machine learning with a hierarchical Bayesian framework, we derived latent disease factors from resting-state functional connectivity data in a hybrid cohort of ASD and ADHD and delineated individual associations with dimensional symptoms based on canonical correlation analysis. Models based on the same factors generalized to previously unseen individuals in a subclinical cohort and one local OCD database with a subset of patients undergoing neurosurgical intervention. Four factors, identified as variably co-expressed in each patient, were significantly correlated with distinct symptom domains (r = -0.26-0.53, P < 0.05): behavioral regulation (Factor-1), communication (Factor-2), anxiety (Factor-3), adaptive behaviors (Factor-4). Moreover, we demonstrated Factor-1 expressed in patients with OCD and Factor-3 expressed in participants with anxiety, at the degree to which factor expression was significantly predictive of individual symptom scores (r = 0.18-0.5, P < 0.01). Importantly, peri-intervention changes in Factor-1 of OCD were associated with variable treatment outcomes (r = 0.39, P < 0.05). Our results indicate that these data-derived latent disease factors quantify individual factor expression to inform dimensional symptom and treatment outcomes across cohorts, which may promote quantitative psychiatric diagnosis and personalized intervention.
Humans ; Male ; Female ; Attention Deficit Disorder with Hyperactivity ; Obsessive-Compulsive Disorder ; Adult ; Autism Spectrum Disorder ; Bayes Theorem ; Adolescent ; Young Adult ; Magnetic Resonance Imaging ; Middle Aged ; Child ; Brain/metabolism* ; Cohort Studies ; Comorbidity

Objective To explore the immune mechanism of negative results of immune tests of schistosomiasis japonica pa?tients. Methods Totally 142 schistosomiasis patients(positive stool examinations)of Poyang Lake region were tested by ELI?SA method,and the ROC curve was applied to determine the high and low response of the patients. The levels of cellular immu?nity and cytokines of high and low responders were compared. Results Totally eight schistosomiasis patients were found as low responders. Besides SWAP?IgA(t= -1.588,P > 0.1),the levels of isotype antibodies were significantly lower in the low re?sponders compared with those in the high responders(t = -14.517 to -2.866,all P < 0.05). In the low responders,the propor?tion of CD3+T was increased;and the proportions of CD4+T,CD8+T,CD4+CD25+Treg,and the ratio of CD4+/CD8+ were all de?creased,but all of them were not significant(t = -1.72 to 0.974,all P > 0.05)compared with those in the high responders. The differences of IFN?γ and IL?10 between the high and low responders were both not significant(t= -2.426 to 0.216,all P >0.05). Conclusions There is a significant difference between the high and low responders only in the levels of isotype antibod?ies. One of the reasons of low response in the immune tests is the much lower antibody level after the antigen?antibody compound is completely formulated.

Objective To obtain differential expression genes from colorectal cancer cells derived from colo205 for further research. Methods RNA from colo205 cells,CD133+cells and CD133-cells were sequenced and analyzed by bioinformatics software. Results One hundred and twenty four differential expression genes were obtained, which involves 32 metabolic pathways. Conclusions Large quantities of differential genes can be found among different groups of cells derived from colo205 cells , which can provide epigenetic evidence for colorectal cancer research.