Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Objective:To explore the characteristics of brain functional connectivity changes associated with repetitive transcranial magnetic stimulation (rTMS) in adolescents with anhedonia symptoms, and to develop a predictive model of treatment efficacy based on baseline functional connectivity.Methods:A total of 88 adolescents (aged 13-18 years) with major depressive disorder and comorbid anhedonia, diagnosed according to the Diagnostic And Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), were enrolled in a randomized, double-blind, block-design trial. Participants received either active rTMS ( n=44) or sham stimulation ( n=44) for 15 consecutive days with individualized targeting. Resting-state functional magnetic resonance imaging (fMRI) data and clinical assessments were collected before and after the intervention. Brain regions were parcellated using the Brainnetome Atlas to construct whole-brain functional connectivity matrices. Linear mixed-effects models were used to identify functional connections showing significant group×time interaction effects. The percentage change in Snaith-Hamilton Pleasure Scale (SHAPS) scores (ΔSHAPS) served as the dependent variable in multiple regression analyses to examine the explanatory power of connectivity changes for treatment response. A connectome-based predictive modeling (CPM) approach was employed to predict individual treatment responses based on baseline functional connectivity with permutation testing used to validate model robustness. Results:Thirty-one functional connections showing significant group×time interaction ( F=6.67-15.69, all P<0.01) were identified between the active and sham stimulation groups, primarily involving the subcortical network (SCN), dorsal attention network (DAN), limbic network (LN), and default mode network (DMN). Changes in these connections accounted for 53% of the variance in ΔSHAPS (adjusted R2=0.53, F=4.574, P=0.001). The CPM model based on baseline connectivity showed strong predictive performance (10-fold cross-validation: r=0.65, R2=0.40, MAE=0.095, permutation P<0.001; leave-one-out cross-validation: r=0.74, R2=0.52, MAE=0.013, permutation P<0.001). Among the 59 predictive features, those originating from the LN contributed most substantially, particularly cross-network connections with the DMN and SCN. Correlation analyses revealed widespread associations between baseline predictive features and rTMS-induced connectivity changes, including significant negative correlations between baseline LN-DMN connectivity and post-treatment changes in DAN and subcortical connectivity. Conclusion:rTMS significantly alleviates anhedonia symptoms in adolescents with depression and induces widespread reconfiguration of functional connectivity across multiple brain networks. The CPM model based on baseline connectivity features effectively predicts rTMS treatment efficacy for anhedonia, providing new insights for individualized treatment strategies in adolescent depression.

Objective:To explore the characteristics of brain functional connectivity changes associated with repetitive transcranial magnetic stimulation (rTMS) in adolescents with anhedonia symptoms, and to develop a predictive model of treatment efficacy based on baseline functional connectivity.Methods:A total of 88 adolescents (aged 13-18 years) with major depressive disorder and comorbid anhedonia, diagnosed according to the Diagnostic And Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), were enrolled in a randomized, double-blind, block-design trial. Participants received either active rTMS ( n=44) or sham stimulation ( n=44) for 15 consecutive days with individualized targeting. Resting-state functional magnetic resonance imaging (fMRI) data and clinical assessments were collected before and after the intervention. Brain regions were parcellated using the Brainnetome Atlas to construct whole-brain functional connectivity matrices. Linear mixed-effects models were used to identify functional connections showing significant group×time interaction effects. The percentage change in Snaith-Hamilton Pleasure Scale (SHAPS) scores (ΔSHAPS) served as the dependent variable in multiple regression analyses to examine the explanatory power of connectivity changes for treatment response. A connectome-based predictive modeling (CPM) approach was employed to predict individual treatment responses based on baseline functional connectivity with permutation testing used to validate model robustness. Results:Thirty-one functional connections showing significant group×time interaction ( F=6.67-15.69, all P<0.01) were identified between the active and sham stimulation groups, primarily involving the subcortical network (SCN), dorsal attention network (DAN), limbic network (LN), and default mode network (DMN). Changes in these connections accounted for 53% of the variance in ΔSHAPS (adjusted R2=0.53, F=4.574, P=0.001). The CPM model based on baseline connectivity showed strong predictive performance (10-fold cross-validation: r=0.65, R2=0.40, MAE=0.095, permutation P<0.001; leave-one-out cross-validation: r=0.74, R2=0.52, MAE=0.013, permutation P<0.001). Among the 59 predictive features, those originating from the LN contributed most substantially, particularly cross-network connections with the DMN and SCN. Correlation analyses revealed widespread associations between baseline predictive features and rTMS-induced connectivity changes, including significant negative correlations between baseline LN-DMN connectivity and post-treatment changes in DAN and subcortical connectivity. Conclusion:rTMS significantly alleviates anhedonia symptoms in adolescents with depression and induces widespread reconfiguration of functional connectivity across multiple brain networks. The CPM model based on baseline connectivity features effectively predicts rTMS treatment efficacy for anhedonia, providing new insights for individualized treatment strategies in adolescent depression.

Emotional blunting is primarily characterized by a lack of emotional response to positive and negative stimuli, manifesting as a disinterest in surroundings or a cessation of caring about things used to matter. It can significantly and negatively impact patients′ work, social interactions, and family life, consequently leading to declined quality of life and fewer social responsibilities. While emotional blunting gradually attracted researchers′ interest, there is still a lack of clinical knowledge and relevant studies to date. The terms of apathy and emotional blunting have been interchangeably used when describing similar symptoms of affective disorders in previous studies. This article reviews studies on emotional blunting in various mental disorders, including assessment tools, neurobiological mechanisms, and treatment strategies, to provide a more thorough understanding and reference for clinical treatment.

Emotional blunting is primarily characterized by a lack of emotional response to positive and negative stimuli, manifesting as a disinterest in surroundings or a cessation of caring about things used to matter. It can significantly and negatively impact patients′ work, social interactions, and family life, consequently leading to declined quality of life and fewer social responsibilities. While emotional blunting gradually attracted researchers′ interest, there is still a lack of clinical knowledge and relevant studies to date. The terms of apathy and emotional blunting have been interchangeably used when describing similar symptoms of affective disorders in previous studies. This article reviews studies on emotional blunting in various mental disorders, including assessment tools, neurobiological mechanisms, and treatment strategies, to provide a more thorough understanding and reference for clinical treatment.

Transcranial direct current stimulation (tDCS) is a well-tolerated, safe and noninvasive physical brain stimulation method, which has been widely used in the treatment of some common mental disorders and neurological diseases and has achieved certain clinical effects. It is necessary to develop expert consensus on clinical treatment to improve the use norms in related fields. According to the clinical research published before August 2021 and the method of evidence-based medicine, we published an expert consensus on tDCS in the treatment of depressive disorders, schizophrenia, substance use-related disorders, obsessive-compulsive disorder, attention deficit hyperactivity disorder, autism, anxiety disorders, post-traumatic stress disorder, sleep disorders, pain, Parkinson′s disease, stroke, and epilepsy. The consensus also introduced the safety and efficacy of the clinical use of tDCS, and standardized the treatment process and operation technology, aiming to provide guidance for the clinical application of tDCS and promote the standardized development of this treatment technology in the future.

Transcranial direct current stimulation (tDCS) is a well-tolerated, safe and noninvasive physical brain stimulation method, which has been widely used in the treatment of some common mental disorders and neurological diseases and has achieved certain clinical effects. It is necessary to develop expert consensus on clinical treatment to improve the use norms in related fields. According to the clinical research published before August 2021 and the method of evidence-based medicine, we published an expert consensus on tDCS in the treatment of depressive disorders, schizophrenia, substance use-related disorders, obsessive-compulsive disorder, attention deficit hyperactivity disorder, autism, anxiety disorders, post-traumatic stress disorder, sleep disorders, pain, Parkinson′s disease, stroke, and epilepsy. The consensus also introduced the safety and efficacy of the clinical use of tDCS, and standardized the treatment process and operation technology, aiming to provide guidance for the clinical application of tDCS and promote the standardized development of this treatment technology in the future.

Objective:To analyze molecular epidemiological characteristics of drug resistance genes and carbapenem resistance of Pseudomonas aeruginosa (PA) in rural well water. Methods:According to Citation of Natural Mineral Water Inspection (GB 8538-2016), a total of 112 well water samples were tested in Juye county of Shandong province, and PFGE and drug susceptibility test were conducted for the identified PA strains. After PCR identification of carbapenem resistance genes, S1-PFGE and Southern blotting were used to determine the location of drug resistance genes, and combined experiments were used to determine gene transferability. Results:The detection rate of PA in rural well water samples in Juye county of Shandong province was 54.46% (61/112). The 61 strains could be divided into 56 PFGE types. There were 2 strains with 100.00% consistent band types, and there was no obvious predominant band type. The results of drug susceptibility experiments showed that 93.44% (57/61) were multi-drug resistant strains, and there were 2 strains carrying blaVIM-2, both of which were located on the plasmid, and both of them were transferred horizontally with the plasmid. Conclusion:PA carrying carbapenem resistance genes was detected in well water of rural communities in Juye country, and there is the possibility of horizontal transmission of such resistance genes.

Objective: To analyze the etiology and epidemiological characteristics of gastroenteritis virus in foodborne diseases from three cities in Shandong. Methods: From January to December 2017, six sentinel hospitals in Jinan, Yantai and Linyi city of Shandong Province were selected as the research sites. Stool samples of 1 397 diarrhea patients were collected, as well as basic information and clinical symptoms. Duplex quantitative RT-PCR was used to detect Norovirus genogroupⅠ (Nov GⅠ) and genogroupⅡ (Nov GⅡ), Sapovirus (SAV) and Human astrovirus (HAstV), respectively, quantitative RT-PCR was used to detect group A Rotavirus (RVA), and quantitative PCR was used to detect Enteric adenovirus (EAdV). The specific gene of the virus were sequenced and typed. It was compared that the gastroenteritis virus rate in cases with different characteristics and the clinical symptoms difference between the virus positive and negative cases. Results: The median age (P₂₅, P₇₅) was 23 (1, 42) , mainly male, 57.48% with 803 cased and children under 5 years old, 36.36% with 508 cases. The positive rate of gastroenteritis virus was 33.93% (474 cases), and that of Jinan, Linyi and Yantai City were 32.03% (147/459), 41.54% (189/455) and 28.57% (138/483), respectively (P<0.001). Nov GⅡ had the highest positive rate, 16.54% (231 cases), which, mainly GⅡ.P16/GⅡ.2 (48.28%, 56/116), peaked in May (24.75%, 50/202) and June (19.59%, 38/194). In patients of gastroenteritis virus positive, 44.51% (211/474) had vomiting symptoms, higher than that of patients of gastroenteritis virus negative (34.13%, 315/923). The difference was statistically significant (P<0.001). Conclusion In Shandong Province, the majority of gastroenteritis patients were male and children under 5 years old. Nov GⅡ possessed highest epidemic intensity, and peaked in spring and summer. Viral gastroenteritis had atypical clinical symptoms.

Objective:To explore the effects of 5E rehabilitation nursing model on self-management behavior and fatigue symptoms of patients with chronic obstructive pulmonary disease (COPD) .Methods:Totally 110 COPD patients admitted in Yantai Yuhuangding Hospital from October 2018 to September 2019 were selected by convenient sampling, and divided into the control group ( n=53) and the experimental group ( n=57) according to the random number table. Excluding missing patients and patients with incomplete data, finally 48 patients were included in the control group and 51 patients were included in the experimental group. Patients in the control group received routine care and health guidance, while patients in the experimental group received care based on the 5E rehabilitation nursing model. The Self-Management Scale for COPD Patients and the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-F) were used to evaluate the effects of interventions in the two groups. Results:There was no statistically significant difference in the scores of the Self-Management Scale between the two groups before intervention ( P>0.05) ; the scores of all dimensions the Self-Management Scale of the experimental group were higher than those of the control group 12 weeks after discharge, and the differences were statistically significant ( P<0.05) . There was no statistically significant difference in fatigue scores between the two groups before intervention and 12 weeks after discharge ( P>0.05) . Conclusions:The 5E rehabilitation nursing model can improve the self-management behavior of COPD patients, but it cannot ameliorate the fatigue symptoms of patients. Large-sample, multi-center, and long-term research will be further needed in the future to explore the effects of the 5E rehabilitation nursing model on patients' fatigue symptoms.