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Objectives. Schizophrenia (SCZ) is associated with disrupted functional brain connectivity, and antipsychotic medications are the primary and most commonly used treatment for schizophrenia. However, not all patients respond to antipsychotic medications. Methods. The study is aimed at investigating whether the graph-theory-based degree centrality (DC), derived from resting-state functional MRI (rs-fMRI), can predict the treatment outcomes. rs-fMRI data from 38 SCZ patients were collected and compared with findings from 38 age- and gender-matched healthy controls (HCs). The patients were treated with antipsychotic medications for 16 weeks before undergoing a second rs-fMRI scan. DC data were processed using DPABI and SPM12 software. Results. SCZ patients at baseline showed increased DC in the frontal and temporal gyrus, anterior cingulate cortex, and precuneus and reduced DC in bilateral subcortical gray matter structures. However, those abnormalities showed a clear renormalization after antipsychotic medication treatments. Support vector machine analysis using leave-one-out cross-validation achieved a correct classification rate of 84.2% (sensitivity 78.9%, specificity 89.5%, and area under the receiver operating characteristic curve (AUC) 0.925) for differentiating effective subjects from ineffective subjects. Brain areas that contributed most to the classification model were mainly located within the bilateral putamen, left inferior frontal gyrus, left middle occipital cortex, bilateral middle frontal gyrus, left cerebellum, left medial frontal gyrus, left inferior temporal gyrus, and left angular. Furthermore, the DC change within the bilateral putamen is negatively correlated with the symptom improvements after treatment. Conclusions. Our study confirmed that graph-theory-based measures, combined with machine-learning algorithms, can provide crucial insights into pathophysiological mechanisms and the effectiveness of antipsychotic medications.

Despite low-frequency repetitive transcranial magnetic stimulation (rTMS) is effective in treating schizophrenia patients with auditory verbal hallucinations (AVH), the underlying neural mechanisms of the effect still need to be clarified. Using the cerebellar dentate nucleus (DN) subdomain (dorsal and versal DN) as seeds, the present study investigated resting state functional connectivity (FC) alternations of the seeds with the whole brain and their associations with clinical responses in schizophrenia patients with AVH receiving 1 Hz rTMS treatment. The results showed that the rTMS treatment improved the psychiatric symptoms (e.g., AVH and positive symptoms) and certain neurocognitive functions (e.g., visual learning and verbal learning) in the patients. In addition, the patients at baseline showed increased FC between the DN subdomains and temporal lobes (e.g., right superior temporal gyrus and right middle temporal gyrus) and decreased FC between the DN subdomains and the left superior frontal gyrus, right postcentral gyrus, left supramarginal gyrus and regional cerebellum (e.g., lobule 4-5) compared to controls. Furthermore, these abnormal DN subdomain connectivity patterns did not persist and decreased FC of DN subdomains with cerebellum lobule 4-5 were reversed in patients after rTMS treatment. Linear regression analysis showed that the FC difference values of DN subdomains with the temporal lobes, supramarginal gyrus and cerebellum 4-5 between the patients at baseline and posttreatment were associated with clinical improvements (e.g., AVH and verbal learning) after rTMS treatment. The results suggested that rTMS treatment may modulate the neural circuits of the DN subdomains and hint to underlying neural mechanisms for low-frequency rTMS treating schizophrenia with AVH.

Even though the prevalence of benefit finding (BF) has been empirically shown to exist among breast cancer (BC) survivals, how does benefit finding evolve over time remains inadequately investigated. The objective of this cohort study is to examine how BF evolves over time among Chinese breast cancer survivals and determine the demographic, medical and psychosocial factors that can sustain BF increase over time. Participants were 486 women with different stages of breast cancer (stages I, II and III) followed from completion of primary treatment. Analysis were performed on the data collected during 2014–2019. During the assessment, each participant completed self-report questionnaires of characteristics and benefit finding at six time points with the interval of 6 months since BC diagnosis. The relationships between demographic, medical and psychosocial characteristics and benefit finding evolution over time were examined using mixed models. Participants reported mixed results on the evolving patterns of benefit finding: 28% reported an upward trend in BF scoring over time, 49% instead reported an downward trend, and the remaining 23% reported no obvious change. Our study has shown that some well-known covariates of benefit finding, e.g. education, income, and social support, are not associated with BF trends. In comparison, levels of spirituality and disease coping at diagnosis can more reliably predict BF evolution over time. Identifying the sustaining factors of benefit finding in the experience of breast cancer is the key to design effective psycho clinical solutions for patients’ long-term post-traumatic growth. As time goes by, breast cancer patients may experience less benefit finding. Our results strongly indicate that benefit finding can be sustained and increased by encouraging attempts at meaning-making and active disease coping during breast cancer treatment. To the best of our knowledge, this study is among the first to examine the evolution trends of benefit finding over time on breast cancer survivals and determine their psychosocial predictors in developing countries.

Sensitive, rapid and low-cost nucleic acid detection is critical for controlling infectious pathogens. Here, we develop a ready-to-use and multimodal detection based on a rebuilding-free, ultrasensitive and selective strategy named dual hairpin ligation-induced isothermal amplification pro (DHLApro). Taking influenza A, influenza B, MERS-CoV, SARS-CoV-2 as model targets, we demonstrate DHLApro provides ≈zM level ultra-sensitivity, being equaling to 0.45 copy/μL in original sample. By simply changing the recognition module, a set of DHLApro components can be applied to a new target without performance loss. Moreover, DHLApro innovatively allows flexible logic/multiplex assay using one set of primer, for example, the "N pathogens-in-1" OR gate screening and accurate multi-channel multiplex assay. Compared with traditional methods, the cost of this logic/multiplex assay has been largely reduced and the cross-interference between the multiple primer sets is also avoided.

Abnormal concentration of ATP is related to many diseases such as Parkinson's disease, hypoglycaemia, inflammation and cancer. However, most of the reported strategies exhibit moderate sensitivity with ∼nM level detection limit and few of them can distinguish ATP from its analogues, such as GTP, CTP, UTP and adenosine. Herein, we report an ultra-sensitive and selective ATP detection strategy that combines dual hairpin ligation-induced isothermal amplification (DHLA) with ATP-dependent enzymatic reaction. A good linear relationship between Cq value and ATP concentration in the range from 16 fM to 160 nM is acquired. Meanwhile, the strategy can distinguish ATP from its analogues with high selectivity. Furthermore, our proposed strategy has been successfully utilized to detect ATP from colon cell line and cell culture media with great potential applications in cell metabolism and cancer diagnosis.

White matter tracts alterations have been reported in schizophrenia (SZ), but whether such abnormalities are associated with the effects of the disorder itself and/or genetic vulnerability remains unclear. Moreover, the specific patterns of different parts of these altered tracts have been less well studied. Thus, diffusion-weighted images were acquired from 38 healthy controls (HCs), 48 schizophrenia patients, and 33 unaffected first-degree relatives of SZs (FDRs). Diffusion properties of the 25 major tracts automatically extracted with probabilistic tractography were calculated and compared among groups. Regarding the peripheral regions of the tracts, significantly higher diffusivity values in the left superior longitudinal fasciculus (SLF) and the left anterior thalamic radiation (ATR) were observed in SZs than in HCs and unaffected FDRs. However, there were no significant differences between HCs and FDRs in these two tracts. While no main effects of group with respect to the core regions of the 25 tracts survived multiple comparisons correction, FDRs had significantly higher diffusivity values in the left medial lemniscus and lower diffusivity values in the middle cerebellar peduncle than HCs and SZs. These findings enhance the understanding of the abnormal patterns in the peripheral and core regions of the tracts in SZs and those at high genetic risk for schizophrenia. Our results suggest that alterations in the peripheral regions of the left SLF and ATR are features of established illness rather than genetic predisposition, which may serve as critical neural substrates for the psychopathology of schizophrenia.

The biological mediators that support cognitive-control and long-term weight-loss after laparoscopic sleeve gastrectomy (LSG) remain unclear. We measured peripheral appetitive hormones and brain functional-connectivity (FC) using magnetic-resonance-imaging with food cue-reactivity task in 25 obese participants at pre, 1 month, and 6 month after LSG, and compared with 30 normal weight controls. We also used diffusion-tensor-imaging to explore whether LSG increases brain structural-connectivity (SC) of regions involved in food cue-reactivity. LSG significantly decreased BMI, craving for high-calorie food cues, ghrelin, insulin, and leptin levels, and increased self-reported cognitive-control of eating behavior. LSG increased FC between the right dorsolateral prefrontal cortex (DLPFC) and the pregenual anterior cingulate cortex (pgACC) and increased SC between DLPFC and ACC at 1 month and 6 month after LSG. Reduction in BMI correlated negatively with increased FC of right DLPFC-pgACC at 1 month and with increased SC of DLPFC-ACC at 1 month and 6 month after LSG. Reduction in craving for high-calorie food cues correlated negatively with increased FC of DLPFC-pgACC at 6 month after LSG. Additionally, SC of DLPFC-ACC mediated the relationship between lower ghrelin levels and greater cognitive control. These findings provide evidence that LSG improved functional and structural connectivity in prefrontal regions, which contribute to enhanced cognitive-control and sustained weight-loss following surgery.

Background Recent progress in neuroscience research has provided evidence that schizophrenia is a disease that involves dysconnectivity of brain networks. Widespread gray matter loss was commonly observed but how these gray matter abnormalities are characterized at the large-scale network-level in schizophrenia, especially patients with first-episode (FE-SCZ) remains unclear. Methods In this study, gray matter structural network aberrations were investigated by applying structural covariance network analysis to 193 first episode schizophrenia patients and 178 age and gender-matched healthy controls (HCs). The mean gray matter volume in seed regions relating to eight specific networks (visual, auditory, sensorimotor, speech, semantic, default-mode, executive control, and salience) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain gray matter volume and each seed region for FE-SCZ and HCs. Results The auditory network was less extended in FE-SCZ compared with HCs, with a significant decrease in the structural association between the Hesch's gyrus and the middle frontal gyrus and the superior frontal gyrus. Hyperconnectivity was observed in executive control network with a significant increase in the structural association between the dorsal lateral prefrontal cortex and the superior frontal gyrus and supplementary motor area. Conclusion Our research shows that seed based structural covariance analysis can well characterize multiple large-scale networks, the observed changes might underly the hallucinations and cognitive impairments observed in FE-SCZ. Given that these patients were experiencing their first episode of schizophrenia, our findings suggest that such structural network deficits are present at an early stage in this disorder.

Functional constipation (FCon) is a common functional gastrointestinal disorder (FGID); neuroimaging studies have shown brain functional abnormalities in thalamo-cortical regions in patients with FGID. However, association between FCon and topological characteristics of brain networks remains largely unknown. We employed resting-state functional magnetic resonance imaging (RS-fMRI) and graph theory approach to investigate functional brain topological organization in 42 patients with FCon and 41 healthy controls (HC) from perspectives of global, regional and modular levels. Results showed patients with FCon had a significantly lower normalized clustering coefficient and small-worldness, implying decreased brain functional connectivity. Regions showed altered nodal degree and efficiency mainly located in the thalamus, rostral anterior cingulate cortex (rACC), and supplementary motor area (SMA), which are involved in somatic/sensory, emotional processing and motor-control. For the modular analysis, thalamus, rACC and SMA had an aberrant within-module nodal degree and nodal efficiency, and thalamus-related network exhibited abnormal interaction with the limbic network (amygdala and hippocampal gyrus). Nodal degree in the thalamus was negatively correlated with difficulty of defecation, and nodal degree in the rACC was negatively correlated with sensation of incomplete evacuation. These findings indicated that FCon was associated with abnormalities in the thalamo-cortical network.

Mounting evidence suggests that function and connectivity of the striatum is disrupted in schizophrenia1–5. We have developed a new hypothesis-driven neuroimaging biomarker for schizophrenia identification, prognosis and subtyping based on functional striatal abnormalities (FSA). FSA scores provide a personalized index of striatal dysfunction, ranging from normal to highly pathological. Using inter-site cross-validation on functional magnetic resonance images acquired from seven independent scanners (n = 1,100), FSA distinguished individuals with schizophrenia from healthy controls with an accuracy exceeding 80% (sensitivity, 79.3%; specificity, 81.5%). In two longitudinal cohorts, inter-individual variation in baseline FSA scores was significantly associated with antipsychotic treatment response. FSA revealed a spectrum of severity in striatal dysfunction across neuropsychiatric disorders, where dysfunction was most severe in schizophrenia, milder in bipolar disorder, and indistinguishable from healthy individuals in depression, obsessive-compulsive disorder and attention-deficit hyperactivity disorder. Loci of striatal hyperactivity recapitulated the spatial distribution of dopaminergic function and the expression profiles of polygenic risk for schizophrenia. In conclusion, we have developed a new biomarker to index striatal dysfunction and established its utility in predicting antipsychotic treatment response, clinical stratification and elucidating striatal dysfunction in neuropsychiatric disorders. A new cross-validated neuroimaging biomarker that reflects striatal dysfunctioning can be used to distinguish patients with schizophrenia from healthy controls, and is associated with treatment response to antipsychotics.

Obese individuals have shown functional abnormalities in frontal–limbic regions, and bariatric surgery is an effective treatment for morbid obesity. The aim of the study was to investigate how bariatric surgery modulates brain regional activation and functional connectivity (FC) to food cues, and whether the underlying structural connectivity (SC) alterations contribute to these functional changes as well as behavioral changes. A functional magnetic resonance imaging cue-reactivity task with high- (HiCal) and low-calorie (LoCal) food pictures and diffusion tensor imaging (DTI) with deterministic tractography were used to investigate brain reactivity, FC and SC in 28 obese participants tested before and 1 month after laparoscopic sleeve gastrectomy (LSG). Twenty-two obese controls (Ctr) without surgery were also tested at baseline and 1 month later. LSG significantly decreased right dorsolateral prefrontal cortex (DLPFC) activation to HiCal versus LoCal cues and increased FC between DLPFC and ventral anterior cingulate cortex (vACC), which are regions involved in self-regulation of feeding behaviors. LSG also increased SC between DLPFC and ACC as quantified by fractional anisotropy. Increases in SC and FC between DLPFC and ACC were associated with greater reductions in BMI, and SC changes were positively correlated with FC changes. Increased SC between right DLPFC and ACC mediated the relationship between reduced BMI and increased right DLPFC–vACC FC; likewise, increases in right DLPFC–vACC FC mediated the relationship between increased right DLPFC–ACC SC and reduced BMI. LSG might induce weight loss in part by increasing SC and FC between DLPFC and ACC, and thus strengthening top-down control over food intake.

BackgroundPrevious analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.AimsTo identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.MethodWe used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.ResultsWe found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.ConclusionsThese results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.

Little is known about the characteristics of Treatment-Resistant Depression (TRD) in China. In previous studies various identification approaches have led to a wide range of results, and it is unclear how Chinese patients compare to those in other studies.This is a retrospective cohort study using electronic health records (EHR) from two major psychiatric hospitals in China. Adult major depressive disorder (MDD) patients who initiated pharmaceutical treatment during 2010-2018 were enrolled and follow-up was 1 year. TRD was primarily identified by consensus definition of two failures of adequate (≥4 weeks) regimens. Alternative regimens of 2-weeks and 6-weeks duration, and a data-driven definition were also applied.In the two hospitals, 12,257 (mean age: 40.8y, 63.6% female) and 8314 (mean age: 42.4y, 68.4% female) eligible patients were included. The 1-year incidence rate of TRD was estimated to be 5.2%-7.7% using the primary definition. TRD patients had mean treatment duration of 302.5 days and 285.7 days; had 3.6 and 3.7 treatment steps on average; 94.0% and 72.6% were prescribed polypharmacy regimens, which were all marginally greater than that of non-TRD patients. Alternative definitions resulted in a wide range of incidence estimates (0.5%-20.0%).Medications were assumed to be consumed as prescribed and lack of rating scales from EHRs may limit our TRD identification.The incidence of TRD among Chinese MDD patients was comparable to other countries under similar settings and more complex treatment characteristics were observed among TRD patients. Alternative TRD definitions revealed the need for better treatment management in practices.

Auditory verbal hallucinations (AVH) are an important characteristic of schizophrenia. Repeated transcranial magnetic stimulation (rTMS) has been evidence to be effective in treating AVH. We evaluated the topological properties of resting-state functional brain networks in schizophrenia patients with AVH (n = 32) who received 1-Hz rTMS treatment and matched healthy controls (n = 33). The results showed that the psychotic symptoms and certain neurocognitive performances in patients were improved by rTMS treatment. Furthermore, the pretreatment patients showed abnormal global topological metrics compared with the controls, including lower global efficiency (E

Despite evidence of structural brain abnormalities in schizophrenia, the current study aimed to explore the effects of antipsychotic treatment on gray matter (GM) volume using structural magnetic resonance imaging (MRI) and investigate the relationship between brain structure and treatment response. The GM volumes of 33 patients with first-episode schizophrenia were calculated with voxel-based morphometry (VBM), with 33 matched healthy controls. Longitudinal volume changes within subjects after 4-month antipsychotic treatment were also evaluated. Correlation between volumetric changes and clinical symptoms derived from the Positive and Negative Syndrome Scale (PANSS) were further investigated. Compared with healthy controls, decreased GM volumes in the frontal gyrus were observed in schizophrenia patients. After 4-month treatment, patients showed significantly decreased GM volume primarily in the bilateral frontal, temporal and left parietal brain regions. In addition, the GM volume changes of the left postcentral gyrus was positively correlated with negative symptoms improvement, and the correlation analysis revealed the total PANSS scores changes were associated with GM volume changes in the right inferior frontal gyrus and the right superior temporal gyrus. Besides, non-responders had reduced GM volume in the bilateral middle frontal gyrus and the right superior frontal gyrus compared with responders and healthy controls. Our results suggest that the abnormality in the right frontal gyrus exists in the early stage of schizophrenia. Moreover, the relationship between antipsychotics and structural changes was identified. The GM volume might have the potential to reflect the symptom improvement in schizophrenia patients. And MRI may assist in predicting the antipsychotic treatment response in first-episode schizophrenia patients.

Functional constipation (FC) is a common functional gastrointestinal disorder (FGID). Neuroimaging studies on patients with FC showed brain functional abnormalities in regions involved in emotional process modulation, somatic and sensory processing and motor control. Brain structural imaging studies in patients with FGID have also shown disease-related alterations in cortical morphometry, but whether and how FC affects brain structure remains unclear. Structural Magnetic Resonance Imaging and surface-based morphometry analysis were used to investigate the impact of FC on cortical morphometry in 29 patients with FC and 29 healthy controls (HC). Results showed that patients with FC compared to HC had significantly decreased cortical thickness in the left middle frontal gyrus (MFG), dorsomedial (DMPFC) and ventromedial prefrontal gyrus (VMPFC), right dorsal anterior cingulate cortex (dACC), left orbitofrontal cortex (OFC), posterior cingulate cortex (PCC)/precuneus, middle temporal gyrus (MTG), and supplementary motor area (SMA) (P

Objective We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs. Methods Resting-state functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female). Results Compared with healthy controls, SZ at baseline showed lower clustering coefficient (Cp) and local network efficiency (Eloc), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of Cp was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes. Conclusion The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, Cp, the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ.

The “hunger” hormone ghrelin regulates food-intake and preference for high-calorie (HC) food through modulation of the mesocortico-limbic dopaminergic pathway. Laparoscopic sleeve gastrectomy (LSG) is an effective bariatric surgery to treat morbid obesity. We tested the hypothesis that LSG-induced reductions in appetite and total ghrelin levels in blood are associated with reduced prefrontal brain reactivity to food cues. A functional magnetic resonance imaging (fMRI) cue-reactivity task with HC and low-calorie (LC) food pictures was used to investigate brain reactivity in 22 obese participants tested before and one month after bariatric surgery (BS). Nineteen obese controls (Ctr) without surgery were also tested at baseline and one-month later. LSG significantly decreased (1) fasting plasma concentrations of total ghrelin, leptin and insulin, (2) craving for HC food, and (3) brain activation in the right dorsolateral prefrontal cortex (DLPFC) in response to HC vs. LC food cues (P(FWE) < 0.05). LSG-induced reduction in DLPFC activation to food cues were positively correlated with reduction in ghrelin levels and reduction in craving ratings for food. Psychophysiological interaction (PPI) connectivity analyses showed that the right DLPFC had stronger connectivity with the ventral anterior cingulate cortex (vACC) after LSG; and changes in BMI were negatively correlated with changes in connectivity between the right DLPFC and vACC in the LSG group only. These findings suggest that LSG-induced weight-loss may be related to reductions in ghrelin, possibly leading to decreased food craving and hypothetically reducing DLPFC response to the HC food cues.

OBJECTIVE Functional constipation (FC) is a common gastrointestinal disorder. Anxiety and/or depressive disorders are common in patients with FC (FCAD). Brain dysfunction may play a role in FC, but the contribution of comorbid anxiety and/or depression in patients with FC is poorly understood. METHODS Sixty-five FC patients and 42 healthy controls (HCs) were recruited, and a hierarchical clustering algorithm was used to classify FC patients into FCAD and patients without anxiety/depressive status (FCNAD) based on neuropsychological assessment. Resting-state functional magnetic resonance imaging measures including fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity were used to investigate brain functional differences. RESULTS Thirty-seven patients were classified as FCAD, and 28 patients were classified as FCNAD; as compared with HC, both groups showed decreased activity (fALFF) in the perigenual anterior cingulate cortex (pACC), dorsomedial prefrontal cortex (DMPFC), and precuneus; enhanced precentral gyrus-thalamus connectivity and attenuated precuneus-thalamus connectivity in FCAD/FCNAD highlighted the thalamus as a critical connectivity node in the brain network (pFWE < .05). In comparison with FCNAD/HC, the FCAD group also had decreased fALFF in the orbitofrontal cortex (OFC) and thalamus, and increased OFC-hippocampus connectivity. In the FCNAD group, brain activities (pACC/DMPFC) and connection (precuneus-thalamus) had correlations only with symptoms; in the FCAD group, brain activities (OFC, pACC/DMPFC) and connectivities (OFC-hippocampus/precentral gyrus-thalamus) showed correlations with both constipation symptoms and anxiety/depressive status ratings. Mediation analysis indicated that the relationship between abdominal distension and OFC activity was completely mediated by anxiety in FCAD. CONCLUSIONS These findings provide evidence of differences in brain activity and functional connectivity between FCAD and FCNAD, potentially providing important clues for improving treatment strategies.

Two different but interacting neural systems exist in the human brain: the task positive networks and task negative networks. One of the most important task positive networks is the central executive network (CEN), while the task negative network generally refers to the default mode network (DMN), which usually demonstrates task-induced deactivation. Although previous studies have clearly shown the association of both the CEN and DMN with major depressive disorder (MDD), how the causal interactions between these two networks change in depressed patients remains unclear. In the current study, 99 subjects (43 patients with MDD and 56 healthy controls) were recruited with their resting-state fMRI data collected. After data preprocessing, spectral dynamic causal modeling (spDCM) was used to investigate the causal interactions within and between the DMN and CEN. Group commonalities and differences in causal interaction patterns within and between the CEN and DMN in patients and controls were assessed by a parametric empirical Bayes (PEB) model. Both subject groups demonstrated significant effective connectivity between regions of the CEN and DMN. In particular, we detected inhibitory influences from the CEN to the DMN with node-level PEB analyses, which may help to explain the anticorrelations between these two networks consistently reported in previous studies. Compared with healthy controls, patients with MDD showed increased effective connectivity within the CEN and decreased connectivity from regions of the CEN to DMN, suggesting impaired control of the DMN by the CEN in these patients. These findings might provide new insights into the neural substrates of MDD.

Highlights • Schizophrenia classification was studied using a large sample data from eight sites. • Both brain images and genetic factors were used as features for classification. • Machine learning methods and leave-one-site-out cross-validation were performed., Previous brain structural magnetic resonance imaging studies reported that patients with schizophrenia have brain structural abnormalities, which have been used to discriminate schizophrenia patients from normal controls. However, most existing studies identified schizophrenia patients at a single site, and the genetic features closely associated with highly heritable schizophrenia were not considered. In this study, we performed standardized feature extraction on brain structural magnetic resonance images and on genetic data to separate schizophrenia patients from normal controls. A total of 1010 participants, 508 schizophrenia patients and 502 normal controls, were recruited from 8 independent sites across China. Classification experiments were carried out using different machine learning methods and input features. We tested a support vector machine, logistic regression, and an ensemble learning strategy using 3 feature sets of interest: (1) imaging features: gray matter volume, (2) genetic features: polygenic risk scores, and (3) a fusion of imaging features and genetic features. The performance was assessed by leave-one-site-out cross-validation. Finally, some important brain and genetic features were identified. We found that the models with both imaging and genetic features as input performed better than models with either alone. The average accuracy of the classification models with the best performance in the cross-validation was 71.6%. The genetic feature that measured the cumulative risk of the genetic variants most associated with schizophrenia contributed the most to the classification. Our work took the first step toward considering both structural brain alterations and genome-wide genetic factors in a large-scale multisite schizophrenia classification. Our findings may provide insight into the underlying pathophysiology and risk mechanisms of schizophrenia.

Background Functional constipation (FCon) is a common functional gastrointestinal disorder (FGID) with a high prevalence in clinical practice. Previous studies have identified that FCon is associated with functional and structural alterations in the primary brain regions involved in emotional arousal processing, sensory processing, somatic/motor-control, and self-referential processing. However, whether FCon is associated with abnormal structural connectivity (SC) among these brain regions remains unclear. Methods We selected the brain regions with functional and structural abnormalities as seed regions and employed diffusion tensor imaging (DTI) with probabilistic tractography to investigate SC changes in 29 patients with FCon and 31 healthy controls (HC). Key results Results showed lower fractional anisotropy (FA) in the fibers connecting the thalamus, a region involved in sensory processing, with the amygdala (AMY), hippocampal gyrus (HIPP), precentral (PreCen) and postcentral gyrus (PostCen), supplementary motor area (SMA) and precuneus in patients with FCon compared with HC. FCon had higher mean diffusivity (MD) and radial diffusivity (RD) in the thalamus connected to the AMY and HIPP. In addition, FCon had significantly increased RD of the thalamus-SMA tract. Sensation of incomplete evacuation was negatively correlated with FA of the thalamus-PostCen and thalamus-HIPP tracts, and there was a negative correlation between difficulty of defecation and FA of the thalamus-SMA tract. Conclusions and inferences These findings reflected that FCon is associated with alterations in SC between the thalamus and limbic/parietal cortex, highlighting the integrative role of the thalamus in brain structural network.

Objective The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients. Methods We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS). Results We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS. Conclusions Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia.

Background The association between abnormal gut microbiome composition and depression is well established. However, the composition and functional capacity of the gut microbiota regarding depressed women has been poorly addressed. Methods Stool samples from 62 female patients with major depressive disorder (MDD) and 46 healthy controls (Con) were analyzed by 16S rRNA gene sequencing; Twenty fecal samples from the patient group and 21 fecal samples from the Con group were further analyzed by shotgun metagenomic sequencing. Psychiatric symptoms and psychological, social, and professional functioning was also assessed. Results Phylum Bacteroidetes, proteobaeteria, and Fusobacteria were greatly enriched in patients with MDD, while the Firmicutes and Actinobacteria phyla were consistently higher in Con. Notably, 18 microbial markers were identified on a random forest model and achieve an area under the curve of 0.92 between patients with MDD and the Con group. Forty-five species and their associated function were identified with statistically significant differences between patients with MDD and the Con group. Limitations The number of recruited samples, especially samples enrolled for shotgun metagenomic sequencing was relatively small, and the stool samples were collected only at baseline, making it difficult to establish a causal association between changes in gut microbiota compositions and disease remission. Conclusions This study characterizes the gut microbiota and their related function in female MDD. The gut microbiota-based biomarkers may be helpful in diagnosis and the altered gut microbial metabolites may contribute to the pathogenesis of MDD in women, representing potential microbial targets.

As a Public Health Emergency of International Concern declared by WHO, the current outbreak of coronavirus disease (COVID-19) in China has captured the world's attention.(1).

The root of Codonopis bulleynana Forest ex Diels (cbFeD), a tonic food widely used in Yunnan Province of China, was found to have a wide range of pharmacological effects. The present study was designed to investigate the anti-fibrotic effect of water extracts of cbFeD in chronic liver injury mice model induced by carbon tetrachloride (CCl

Multimodal neuroimaging features provide opportunities for accurate classification and personalized treatment options in the psychiatric domain. This study aimed to investigate whether brain features predict responses to the overall treatment of schizophrenia at the end of the first or a single hospitalization. Structural and functional magnetic resonance imaging (MRI) data from two independent samples (N = 85 and 63, separately) of schizophrenia patients at baseline were included. After treatment, patients were classified as responders and non-responders. Radiomics features of gray matter morphology and functional connectivity were extracted using Least Absolute Shrinkage and Selection Operator. Support vector machine was used to explore the predictive performance. Prediction models were based on structural features (cortical thickness, surface area, gray matter regional volume, mean curvature, metric distortion, and sulcal depth), functional features (functional connectivity), and combined features. There were 12 features after dimensionality reduction. The structural features involved the right precuneus, cuneus, and inferior parietal lobule. The functional features predominately included inter-hemispheric connectivity. We observed a prediction accuracy of 80.38% (sensitivity: 87.28%; specificity 82.47%) for the model using functional features, and 69.68% (sensitivity: 83.96%; specificity: 72.41%) for the one using structural features. Our model combining both structural and functional features achieved a higher accuracy of 85.03%, with 92.04% responder and 80.23% non-responders to the overall treatment to be correctly predicted. These results highlight the power of structural and functional MRI-derived radiomics features to predict early response to treatment in schizophrenia. Prediction models of the very early treatment response in schizophrenia could augment effective therapeutic strategies.

Background: Although antipsychotic monotherapy is recommended as the main treatment for schizophrenia, antipsychotic polypharmacy is not rare in practice. However, longitudinal data on antipsychotic polypharmacy in schizophrenia treatment are limited. Methods: This longitudinal database study described antipsychotic polypharmacy in the treatment of schizophrenia in real-world settings in China and Japan. We retrieved information about antipsychotic treatment for schizophrenia from January 2010 to December 2014 from two hospital Electronic Medical Records databases in China and one claims database, Japan Medical Data Centre in Japan. Eligible patients had a diagnosis of schizophrenia (International Classification of Diseases, Tenth Revision F20.x) and at least one prescription for first or second generation antipsychotics. Antipsychotic polypharmacy was defined as having more than one antipsychotic medication overlapping for ⩾60 days. The Japan Medical Data Centre study cohort was further stratified by employees (insurance beneficiaries) and their dependents. Results: The study cohorts comprised 11,961 patients from China and 25,034 (10,661 employee sub-cohort and 14,373 dependent sub-cohort) from 14 days Japan Medical Data Centre in Japan. Most patients were prescribed monotherapy (87.3% in China and 80.1% in Japan), of which oral second-generation antipsychotics were the majority (78.9% in China and 65.8% in Japan). The prevalence rate of antipsychotic polypharmacy was 12.7% in China and 19.9% in Japan (13.7% in employees vs 24.5% in dependents). The most common combinations were two oral antipsychotics. Combinations of more than two drugs were uncommon in China (0.3%) but were prescribed for 5.3% of patients in Japan. Among patients treated with monotherapy, 12.6/100 person-years (11.8%) in China and 9.6/100 person-years (11.0%) in Japan switched to antipsychotic polypharmacy during follow-up. Younger patients were more likely to switch to antipsychotic polypharmacy than older patents in all study cohorts. Conclusion: The observed rates of antipsychotic polypharmacy ranged from 12.7% in China to 19.9% in Japan. Switching from monotherapy to antipsychotic polypharmacy was most likely to occur in younger patients with schizophrenia.

Background In the past decades, substantial effort has been made to explore the genetic influence on brain structural/functional abnormalities in schizophrenia, as well as cognitive impairments. In this work, we aimed to extend previous studies to explore the internal mediation pathway among genetic factor, brain features and cognitive scores in a large Chinese dataset. Methods Gray matter (GM) volume, fractional amplitude of low-frequency fluctuations (fALFF), and 4522 schizophrenia-susceptible single nucleotide polymorphisms (SNP) from 905 Chinese subjects were jointly analyzed, to investigate the multimodal association. Based on the identified imaging-genetic pattern, correlations with cognition and mediation analysis were then conducted to reveal the potential mediation pathways. Findings One linked imaging-genetic pattern was identified to be group discriminative, which was also associated with working memory performance. Particularly, GM reduction in thalamus, putamen and bilateral temporal gyrus in schizophrenia was associated with fALFF decrease in medial prefrontal cortex, both were also associated with genetic factors enriched in neuron development, synapse organization and axon pathways, highlighting genes including CSMD1, CNTNAP2, DCC, GABBR2 etc. This linked pattern was also replicated in an independent cohort (166 subjects), which although showed certain age and clinical differences with the discovery cohort. A further mediation analysis suggested that GM alterations significantly mediated the association from SNP to fALFF, while fALFF mediated the association from SNP and GM to working memory performance. Interpretation This study has not only verified the impaired imaging-genetic association in schizophrenia, but also initially revealed a potential genetic-brain-cognition mediation pathway, indicating that polygenic risk factors could exert impact on phenotypic measures from brain structure to function, thus could further affect cognition in schizophrenia.

Laparoscopic sleeve gastrectomy (LSG) is an effective bariatric surgery to treat obesity, and involves removal of the gastric fundus where ghrelin is mainly produced. Ghrelin stimulates appetite and regulates food intake through its effect on the hypothalamus and hippocampus (HIPP). While ghrelin’s role on the hypothalamus has been explored, little is known about its role on HIPP. We tested the hypothesis that LSG-induced reductions in ghrelin levels would be associated with changes in HIPP activity. Brain activity was measured with amplitude of low-frequency fluctuations (ALFF) captured with resting-state functional magnetic resonance imaging (fMRI) in 30 obese participants, both before and after 1-month of LSG, and in 26 obese controls without surgery that were studied at baseline and 1-month later. A two-way analysis of variance (ANOVA) was performed to model the group and time effects on ALFF and resting-state functional connectivity. One-month post-LSG there were significant decreases in appetite, body mass index (BMI), fasting plasma ghrelin and leptin levels, anxiety, and ALFF in HIPP and ALFF increases in posterior cingulate cortex (PCC, PFWE

Many studies have focused on patients with schizophrenia with or without auditory verbal hallucinations (AVHs), but due to the complexity of schizophrenia, biologically based diagnosis of patients with schizophrenia remains unsolved. The objectives of this study are to classify between first-episode drug-naïve patients with schizophrenia and healthy controls, and to classify between patients with and without AVHs. Resting state fMRI data from 41 patients with schizophrenia (22 with and 19 without AVHs) and 23 normal controls (NC) were included to compute functional connectivity between brain regions. Classifiers based on support vector machine (SVM) were developed to classify patients with schizophrenia from NC, as well as between the two subgroups of patients. The classification accuracy was evaluated with a leave-one-out cross-validation (LOOCV) strategy. The accuracy in discriminating both subgroups of patients from NC was 81.3%, with 92.0% (sensitivity) and 65.2% (specificity) for the patients and NC, respectively. The classification accuracy in discriminating patients with and without AVHs was 75.6%, with 77.3% (sensitivity) and 73.9% (specificity) for patients with and without AVHs, respectively. The results suggest that functional connectivity provided good discriminative power not only for identifying patients with schizophrenia among NC, but also in discriminating patients with schizophrenia with and without AVHs., Highlights • Normal controls, schizophrenia patients with and without AVHs were successfully classified. • Using LOOCV, the classifier achieved an accuracy of groups of 81.3% for all the three groups of subjects. • Patients with AVHs were differentiated with those without AVHs with an accuracy of 75.6%. • The proposed may help with the clinical diagnosis of schizophrenia patients.

The goal of the study was to investigate cerebral blood flow (CBF) and its connectivity (an across-subject covariance measure) patterns of schizophrenia (SZ) patients with auditory verbal hallucinations (AVHs). A total of demographically matched 25 SZ patients with AVHs, 25 without AVHs, and 25 healthy controls (HCs) underwent resting state perfusion imaging using a pulsed arterial spin labeling sequence. CBF and its connectivity were analyzed and then CBF topological properties were calculated. AVHs patients exhibited decreased CBF in the bilateral superior and middle frontal gyri and postcentral gyri, and right supplementary motor area compared with SZ patients without AVHs. SZ patients without AVHs showed reduced CBF in the left middle frontal gyrus relative to HCs. Moreover, AVHs groups showed distinct connectivity pattern, an intermediate level between HCs and patients without AVHs in the global efficiency. Our study demonstrates aberrant CBF in the brain regions associated with inner speech monitoring and language processing in SZ patients with AVHs. The complex network measures showed by CBF-derived functional connectivity indicate dysconnectivity between different functional units within the network of AVHs in SZ. Our findings might shed light on the neural underpinnings behind AVHs in this devastating disease at the level of CBF and its connectivity.

Numerous antidepressants are available for the treatment of the major depressive disorder (MDD). Unfortunately, the disadvantages of these antidepressive medications, including inadequate treatment response, the therapeutic lag between drug administration and the onset of symptoms alleviation, and the safety consideration limit their clinical use and accelerate the exploration of advanced antidepressants with novel action mechanisms/newer targets, with fewer side effects. In this chapter, a series of compounds showing clinical potent in the treatment of MDD has been reviewed based on their reported results from different phase clinical trials. Although the majority of these strategies currently only lead to a systematic approach in the aspects of treatment resistant depression, some of them would be a routine clinical practice which is usable in the treatment of MDD, such as ketamine. Additionally, beyond the mechanism of action for novel therapeutic molecules involving glutamatergic, opiate, cholinergic receptors, and neuroplasticity, some supplemental procedures such as polyunsaturated fatty acids were also included in this chapter due to their solid property against MDD.

Investigations of brain structure in schizophrenia using magnetic resonance imaging (MRI) have identified variations in regional grey matter (GM) volume throughout the brain but the results are mixed. This study aims to investigate whether the inconsistent voxel-based morphometry (VBM) findings in schizophrenia are due to the use of different software packages. T1 MRI images were obtained from 86 first-episode schizophrenia (FESZ) patients and 86 age- and gender-matched Healthy controls (HCs). VBM analysis was carried out using FMRIB software library (FSL) 5.0 and statistical parametric mapping 8 (SPM8). All images were processed using the default parameter settings as provided by these software packages. FSL-VBM revealed widespread GM volume reductions in FESZ patients compared with HCs, however, for SPM-VBM, only increased and circumscribed GM volume changes were found, both software revealed increased GM volume within cerebellum. Significant correlations between Positive and Negative Syndrome Scale (PANSS) and GM volume were mainly found in frontal regions. Algorithms of GM tissue segmentation, image registration and statistical strategies might contribute to these disparate results.

Rapid endothelialization on small diameter artificial blood vessels is an effective strategy to facilitate long-term patency and inhibit thrombosis. The gene delivery can enhance the proliferation and migration of endothelial cells (ECs), which is beneficial for rapid endothelialization. REDV-G-TAT-G-NLS-Cys (abbreviated as TP-G) peptide could weakly condense pEGFP-ZNF580 (pZNF580) and transfect ECs, but its transfection efficiency was still very low because of its low positive charge, low stability and weak endosome escape ability. In order to develop more stable and efficient gene carriers with low cytotoxicity, in the present study, we conjugated different amounts of TP-G peptide onto poly(lactide-co-glycolide)-g-polyethylenimine (PLGA-g-PEI) amphiphilic copolymers via a hetero-poly(ethylene glycol) spacer (OPSS-PEG-NHS). The TP-G peptide and PEI could cooperatively and strongly condense pZNF580. The carrier’s cytotoxicity was reduced by the introduction of poly(ethylene glycol) spacer. They condensed pZNF580 to form gene complexes (PPP-TP-G/pZNF580) with suitable size and positive zeta potential for gene delivery. The transfected ECs promoted their migration ability as demonstrated by cell migration assay. The results of cellular uptake and confocal laser scanning microscopy showed significantly high internalization efficiency, endosomal/lysosomal escape and nucleus location of pZNF580 by this multifunctional TP-G peptide sequence conjugated gene delivery system. Furthermore, several inhibitors were used to study the cellular uptake pathways of PPP-TP-G/pZNF580 complexes. The results showed that PPP-TP-G2/Cy5-oligonucleotide complexes exhibited the optimized endocytosis pathways which facilitated for cellular uptake. In conclusion, the multifunctional TP-G peptide conjugated gene carriers could promote the transfection efficiency due to the multifunction of REDV, cell-penetrating peptide and nuclear localization signal in the peptide sequence, which could be a suitable gene carrier for endothelialization.

BackgroundSchizophrenia is a complex mental disorder with high heritability and polygenic inheritance. Multimodal neuroimaging studies have also indicated that abnormalities of brain structure and function are a plausible neurobiological characterisation of schizophrenia. However, the polygenic effects of schizophrenia on these imaging endophenotypes have not yet been fully elucidated.AimsTo investigate the effects of polygenic risk for schizophrenia on the brain grey matter volume and functional connectivity, which are disrupted in schizophrenia.MethodGenomic and neuroimaging data from a large sample of Han Chinese patients with schizophrenia (N = 509) and healthy controls (N = 502) were included in this study. We examined grey matter volume and functional connectivity via structural and functional magnetic resonance imaging, respectively. Using the data from a recent meta-analysis of a genome-wide association study that comprised a large number of Chinese people, we calculated a polygenic risk score (PGRS) for each participant.ResultsThe imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal grey matter volume and hippocampus–medial prefrontal cortex functional connectivity, both of which were lower in the people with schizophrenia than in the controls. We also found that the observed neuroimaging measures showed weak but similar changes in unaffected first-degree relatives of patients with schizophrenia.ConclusionsThese findings suggested that genetically influenced brain grey matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.

BACKGROUND: Obesity is associated with decreased brain gray- (GM)/white-matter (WM) volumes in regions. Laparoscopic-sleeve-gastrectomy (LSG) is an effective bariatric surgery associated with neuroplastic changes in patients with obesity at 1-month-post-LSG. OBJECTIVE: To investigate whether LSG can induce sustained neuroplastic recovery of brain structural abnormalities, and whether structural changes are accompanied by functional alterations. SETTING: University hospital, longitudinal study. METHODS: Structural MRI/voxel-based morphometry-analysis were employed to assess GM/WM volumes in 30 obese participants at pre-LSG, 1-/3-month-post-LSG. One-way-ANOVA modeled time effects on GM/WM volumes, and then alterations in resting-state-functional-connectivity (RSFC) were assessed. RESULTS: Significant time effects on GM volumes were in caudate (F=11.20), insula (INS, F=10.11), posterior cingulate cortex (PCC, F=13.32) and inferior frontal gyrus (IFG, F=12.18), and on WM volumes in anterior cingulate cortex (ACC, F=15.70), PCC (F=15.56) and parahippocampus (PHIPP, F=17.96, P(FDR)

Background Associations between abnormal gut microbiome compositions and anxiety-like behaviors are well established. However, it is unknown whether the gut microbiome composition is associated with the severity of generalized anxiety disorder (GAD) and relief from clinical symptoms in patients. Methods Stool samples from 36 patients with active GAD (A-GAD group) and 24 matched healthy control subjects (HC group) were analyzed by 16S rRNA gene sequencing. Anxiety was assessed with the Hamilton Anxiety Rating Scale and the Self-rating Anxiety Scale, and global assessments of functioning were performed at baseline and 1 month after drug treatment. Results Gut microbiome compositions were altered in A-GAD patients, with fewer operational taxonomic units and lower fecal bacterial α-diversity. Specifically, Firmicutes and Tenericutes abundances were lower in A-GAD patients, and several genera were differentially represented in the A-GAD and HC groups. The abundances of Eubacterium_coprostanoligenes_group, Ruminococcaceae_UCG-014, and Prevotella_9 correlated negatively with the anxiety severity and positively with anxiety reduction, whereas the abundances of Bacteroides and Escherichia-Shigella were positively associated with anxiety severity. Sex, smoking, and alcohol intake influenced the gut microbiome composition. Limitations The sample sizes were small and the stool samples were collected only at baseline; therefore, a causal association between changes in intestinal flora and disease remission was not established. Moreover, the effects of different drugs on gut microbiome composition were not investigated. Conclusions Altered gut microbiome composition may contribute to GAD pathogenesis and remission.

The anti-depressant effect of repetitive transcranial magnetic stimulation (rTMS), a clinically-useful treatment for depression, is associated with changes to the endocannabinoid system (ECS). However, it is currently unknown whether different frequencies of rTMS alter the ECS differently. To test this, rats exposed to chronic unpredictable stress (CUS) were treated with rTMS at two different frequencies (5 (high) or 1 Hz (low), 1.26 Tesla) for 7 consecutive days. Twenty-four hours after the final rTMS treatment, we evaluated depressive-like behaviors and the expression of several synaptic proteins and ECS-related proteins in the hippocampus. In addition, we knocked-down diacylglycerol lipase alpha (DAGLα) and cannabinoid type 1 receptor (CB1R), two important components of the ECS, and measured depressive-like behaviors and synaptic protein expression following rTMS. Furthermore, we measured the expression levels of several components of the ECS system in hippocampal-derived astrocytes and neurons exposed to repetitive magnetic stimulation (rMS) with different parameters (5 or 1 Hz, 0.84 or 1.26 Tesla). Interestingly, we found that only high-frequency rTMS ameliorated depressive-like behaviors and normalized the expression of hippocampal synaptic proteins in CUS-treated rats; this effect was eliminated by knockdown of DAGLα or CB1R. Moreover, we found that rMS at 5 Hz increased the expression of DAGLα and CB1R in hippocampal astrocytes and neurons. Collectively, our results suggest that high-frequency rTMS exerts its anti-depressant effect by up-regulating DAGLα and CB1R.

Objective A serious issue in psychiatric practice is a lack of specific, objective biomarker to assist clinicians in establishing differential diagnosis and improving individualized treatment. Major depression disorder (MDD) is characterized by poorer ability in processing of facial emotional expressions. Approach Applying a portable neuroimaging system using near-infrared spectroscopy, we investigated the prefrontal cortex hemodynamic activation changes during facial emotion recognition and rest periods for 27 MDD patients compared with 24 healthy controls (HC). Main results The hemodynamic changes in the left prefrontal cortex for the MDD group showed significant differences in the median values and the Mayer wave power ratios of the oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) during the emotional face recognition compared with the HC subjects, indicating the abnormal oxidative metabolism and weaker local hemodynamic oscillations for the MDD. The mean cross wavelet coefficients and the average wavelet coherence coefficient between oxy-Hb and deoxy-Hb over the left prefrontal cortex, and also between the bilateral oxy-Hb in the MDD patients were significantly lower than the HC group, demonstrating abnormal locally functional connectivity over the left prefrontal cortex, and the inter-hemispheric connection between the bilateral prefrontal cortices. Significance These results suggested that the hemodynamic changes over the left prefrontal cortex and between the bilateral prefrontal cortices detected by fNIRS could provide reliable predictors for the diagnosis of the depression in clinic, and also supported the rationale for use of transcranial magnetic stimulation over the left dorsolateral prefrontal cortex to restore excitability of prefrontal cortex that exhibits diminished regulation of emotion-generative systems in the MDD patients.

Heterogeneous findings across studies of structural abnormality in schizophrenia (SZ) have impeded the development a unified theory of white matter pathology. As a cardinal symptom of SZ, auditory verbal hallucination (AVH) has been suspected to be associated with improper communication among several brain regions, which might indicated white matter pathology. Participants comprised 25 first-episode (FE) patients with AVH, 25 patients without AVH and 25 healthy subjects. Diffusion tensor imaging (DTI) measures were calculated using the TBSS of FSL. Voxel-based ANOVA tests were performed among the three groups and threshold-free cluster enhancement (TFCE) method correction was used for multiple comparisons. Voxel-based one-way ANOVA showed significant group effects for fractional anisotropy (FA) and radial diffusivity (RD) values. Post-hoc t-tests indicated that schizophrenia patients had lower FA and higher RD values in the internal capsule and anterior corona radiata than control subjects. Post-hoc analyses exhibited more widespread fiber disruptions in AVH patients than non-AVH patients. These results hinted on the important role of projection fiber disruption in schizophrenia patients. In addition, the current study also suggested that direct comparison between studies using patients with different symptom profiles should be interpreted with caution.

Functional constipation (FC) is a common functional gastrointestinal disorder (FGID) with a higher prevalence in clinical practice. The primary brain regions involved in emotional arousal regulation, somatic, sensory and motor control processing have been identified with neuroimaging in FGID. It remains unclear how these factors interact to influence the baseline brain activity of patients with FC. In the current study, we combined resting-state fMRI (RS-fMRI) with Granger causality analysis (GCA) to investigate the causal interactions of the brain areas in 14 patients with FC and in 26 healthy controls (HC). Our data showed significant differences in baseline brain activities in a number of major brain regions implicated in emotional process modulation (i.e. dorsal anterior cingulate cortex-dACC, anterior insula-aINS, orbitofrontal cortex-OFC, hippocampus-HIPP), somatic and sensory processing, and motor control (i.e., supplementary motor area-SMA, precentral gyrus-PreCen) (P

Obesity-related brain structural abnormalities have been reported extensively, and bariatric surgery (BS) is currently the most effective intervention to produce sustained weight reduction in overtly obese (OB) people. It is unknown whether BS can repair the brain circuitry abnormalities concomitantly with long-term weight loss.In order to investigate whether BS promotes neuroplastic structural recovery in morbidly OB patients, we quantified fractional anisotropy (FA), mean diffusivity (MD) and gray (GM) and white (WM) matter densities in 15 morbidly OB patients and in 18 normal weight (NW) individuals. OB patients were studied at baseline and also 1 month after laparoscopic sleeve gastrectomy surgery.Two-sample t-test between OB (baseline) and NW groups showed decreased FA values, GM/WM densities and increased MD value in brain regions associated with food intake control (that is, caudate, orbitofrontal cortex, body and genu of corpus callosum) and cognitive-emotion regulation (that is, inferior frontal gyrus, hippocampus, insula, external capsule) (P0.05, family-wise error correction). Paired t-test in the OB group between before and after surgery showed that BS generated partial neuroplastic structural recovery in the OB group, but the differences had relative less strength and smaller volume (P0.001).This study provides the first anatomical evidence for BS-induced acute neuroplastic recovery that might in part mediate the long-term benefit of BS in weight reduction. It also highlights the importance of this line of gut-brain axis research employing the combined BS and neuroimaging model for identifying longitudinal changes in brain structure that correlated with obesity status.

Aim The aim of this study was to determine the efficacy and safety of cranial electrotherapy stimulation (CES) as an add-on treatment for TD. Methods A randomized, double-blind, sham-controlled trial was conducted at an outpatient, single-center academic setting. A total of 62 patients aged 6–17 years with TD and lack of clinical response to 4 weeks’ pharmacotherapy were enrolled. Patients were divided randomly into 2 groups and given 4 weeks’ treatment, including 30 min sessions of active CES (500 μA–2 mA) or sham CES (lower than 100 μA) per day for 40 d on weekdays. Change in Yale Global Tic Severity Scale (YGTSS), Clinical Global Impression-severity of illness-severity (CGI-S) and Hamilton Anxiety Scale-14 items (HAMA-14) were performed at baseline, week 2, week 4. Adverse events (AEs) were also evaluated. Results 53 patients (34 males and 9 females) completed the trial, including 29 in the active CES group and 24 in the sham CES group. Both groups showed clinical improvement in tic severities compared to baseline respectively at week 4. Participants receiving active CES showed a reduction of 31.66 % in YGTSS score, compared with 23.96 % in participants in sham CES group, resulting in no significant difference between the two groups (t = 1.54, p = 0.13). Conclusion Four-week’s treatment of CES for children and adolescents with TD is effective and safe, but the improvement for tic severity may be related to placebo effect.

AIM Transcutaneous electrical acupoint stimulation (TEAS) has the potential to alleviate post-traumatic stress disorder (PTSD). The purpose of this study was to determine whether adding TEAS to sertraline or cognitive behavioral therapy (CBT) could improve the anti-PTSD efficacy. METHODS In this randomized controlled trial, 240 PTSD patients (60 in each group) were assigned to receive simulated TEAS combined with sertraline (group A) or with CBT (group B), active TEAS combined with CBT (group C), or active TEAS combined with CBT plus sertraline (group D) for 12 weeks. The outcomes were measured using the Clinician-Administered PTSD Scale, PTSD Check List-Civilian Version, and 17-item Hamilton Rating Scale for Depression. RESULTS While PTSD symptoms reduced over time in all patients, groups C and D had markedly greater improvement in both PTSD and depressive measures than groups A and B in all post-baseline measurement points, with moderate to very large effect sizes of 0.484-2.244. Groups C and D also had a significantly higher rate than groups A and B on clinical response (85.0% and 95.0% vs 63.3% and 60.0%, P

Obesity-related brain gray (GM) and white matter (WM) abnormalities have been reported in regions associated with food-intake control and cognitive-emotional regulation. Bariatric surgery (BS) is the most effective way to treat obesity and induce structural recovery of GM/WM density and WM integrity. It is unknown whether the surgery can promote structural changes in cortical morphometry along with weight-loss. Structural Magnetic Resonance Imaging and surface-based morphometry analysis were used to investigate BS-induced alterations of cortical morphometry in 22 obese participants who were tested before and one month post-BS, and in 21 obese controls (Ctr) without surgery who were tested twice (Baseline and One-month). Results showed that fasting plasma ghrelin, insulin, and leptin levels were significantly reduced post-BS (P

Understanding the neural substrates of depression is crucial for diagnosis and treatment. Here, we review recent studies of functional and effective connectivity in depression, in terms of functional integration in the brain. Findings from these studies, including our own, point to the involvement of at least four networks in patients with depression. Elevated connectivity of a ventral limbic affective network appears to be associated with excessive negative mood (dysphoria) in the patients; decreased connectivity of a frontal-striatal reward network has been suggested to account for loss of interest, motivation, and pleasure (anhedonia); enhanced default mode network connectivity seems to be associated with depressive rumination; and diminished connectivity of a dorsal cognitive control network is thought to underlie cognitive deficits especially ineffective top-down control of negative thoughts and emotions in depressed patients. Moreover, the restoration of connectivity of these networks-and corresponding symptom improvement-following antidepressant treatment (including medication, psychotherapy, and brain stimulation techniques) serves as evidence for the crucial role of these networks in the pathophysiology of depression.

Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with synchronous changes in both functional and structural regions, especially the basal ganglia network, salience network (SAN), and the frontoparietal network. Such a multimodal coalteration was also replicated in another independent Chinese sample (40 SZs, 66 HCs). Our results on auditory verbal hallucination (AVH) also provide evidence for the hypothesis that prefrontal hypoactivation and temporal hyperactivation in SZ may lead to failure of executive control and inhibition, which is relevant to AVH. In addition, impaired working memory performance was found associated with GM reduction and FA decrease in SZ in prefrontal and superior temporal area, in both discovery and replication datasets. In summary, by leveraging multiple imaging and clinical information into one framework to observe brain in multiple views, we can integrate multiple inferences about SZ from large-scale population and offer unique perspectives regarding the missing links between the brain function and structure that may not be achieved by separate unimodal analyses.