A medical unsupervised domain adaptation framework based on Fourier transform image translation and multi-model ensemble self-training strategy.

PURPOSE: Well-established segmentation models will suffer performance degradation when deployed on data with heterogeneous features, especially in the field of medical image analysis. Although researchers have proposed many approaches to address this problem in recent years, most of them are feature-adaptation-based adversarial networks, the problems such as training instability often arise in adversarial training. To ameliorate this challenge and improve the robustness of processing data with different distributions, we propose a novel unsupervised domain adaptation framework for cross-domain medical image segmentation. METHODS: In our proposed approach, Fourier transform guided images translation and multi-model ensemble self-training are integrated into a unified framework. First, after Fourier transform, the amplitude spectrum of source image is replaced with that of target image, and reconstructed by the inverse Fourier transform. Second, we augment target dataset with the synthetic cross-domain images, performing supervised learning using the original source set labels while implementing regularization by entropy minimization on predictions of unlabeled target data. We employ several segmentation networks with different hyperparameters simultaneously, pseudo-labels are generated by averaging their outputs and comparing to confidence threshold, and gradually optimize the quality of pseudo-labels through multiple rounds self-training. RESULTS: We employed our framework to two liver CT datasets for bidirectional adaptation experiments. In both experiments, compared to the segmentation network without domain alignment, dice similarity coefficient (DSC) increased by nearly 34% and average symmetric surface distance (ASSD) decreased by about 10. The DSC values were also improved by 10.8% and 6.7%, respectively, compared to the existing model. CONCLUSION: We propose a Fourier transform-based UDA framework, the experimental results and comparisons demonstrate that the proposed method can effectively diminish the performance degradation caused by domain shift and performs best on the cross-domain segmentation tasks. Our proposed multi-model ensemble training strategy can also improve the robustness of the segmentation system.

Disentangled representation and cross-modality image translation based unsupervised domain adaptation method for abdominal organ segmentation.

PURPOSE: Existing medical image segmentation models tend to achieve satisfactory performance when the training and test data are drawn from the same distribution, while they often produce significant performance degradation when used for the evaluation of cross-modality data. To facilitate the deployment of deep learning models in real-world medical scenarios and to mitigate the performance degradation caused by domain shift, we propose an unsupervised cross-modality segmentation framework based on representation disentanglement and image-to-image translation. METHODS: Our approach is based on a multimodal image translation framework, which assumes that the latent space of images can be decomposed into a content space and a style space. First, image representations are decomposed into the content and style codes by the encoders and recombined to generate cross-modality images. Second, we propose content and style reconstruction losses to preserve consistent semantic information from original images and construct content discriminators to match the content distributions between source and target domains. Synthetic images with target domain style and source domain anatomical structures are then utilized for training of the segmentation model. RESULTS: We applied our framework to the bidirectional adaptation experiments on MRI and CT images of abdominal organs. Compared to the case without adaptation, the Dice similarity coefficient (DSC) increased by almost 30 and 25% and average symmetric surface distance (ASSD) dropped by 13.3 and 12.2, respectively. CONCLUSION: The proposed unsupervised domain adaptation framework can effectively improve the performance of cross-modality segmentation, and minimize the negative impact of domain shift. Furthermore, the translated image retains semantic information and anatomical structure. Our method significantly outperforms several competing methods.

Prolactin levels influenced by antipsychotic drugs in schizophrenia: A systematic review and network meta-analysis.

Prolactin increase is a common side effect in antipsychotic treatment of schizophrenia, which crucially impacts drug choice and treatment compliance. As previous reviews by our group on this topic have included only few Chinese studies, we aimed to compare and rank antipsychotics based on broader evidence. This systematic review pooled data of 92 included studies from previous systematic review by Huhn et al. and 38 newly-added studies from Chinese-database search, including Chinese databases of China National Knowledge Infrastructure (CNKI), WANFANG DATA, WEIPU Journal Net (VIP) and Sino Biomedicine Service System (SinoMed) up to 20 May 2020. We conducted both network meta-analysis (NMA) and pairwise meta-analysis. The primary outcome was prolactin increase (continuous data). We calculated mean differences (MDs) for prolactin level with 95% confidence intervals (CIs) using random-effects model as primary analysis. 130 RCTs with 25,610 participants were included. Newer antipsychotics (risperidone, amisulpride and paliperidone) and older antipsychotics (chlorpromazine, haloperidol and sulpride) increase prolactin levels with large effect sizes. The SMD results were not identical to the MD results because consistency and heterogeneity assumption was tested to be different in calculations. Sensitivity analyses removing two studies with massive baseline imbalance or removing Chinese studies with high risk of bias did not affect the result. In contrast to a previous review clozapine and zotepine were no longer associated with decreased prolactin levels compared to placebo. Risperidone's ranking has more implications supported by CINeMA. This NMA draws the conclusion with larger sample size and extends evidence to more literature in this field.

The role of circulating blood microRNA-374 and microRNA-10 levels in the pathogenesis and therapeutic mechanisms of major depressive disorder.

Compelling recent evidence suggests that microRNAs (miRNAs) regulate specific mRNA transcripts at the transcriptomic level and coordinately influence complex regulatory networks, which may play a crucial role in the pathogenesis of major depressive disorder (MDD) and the treatment effects of antidepressants. To evaluate the possible involvement of miRNAs in the pathophysiology and therapeutic response of MDD, we conducted a miRNA expression array analysis of the peripheral blood mononuclear cells (PBMCs) of 5 depressed patients and 5 healthy controls (HCs). Subsequently, we chose 2 miRNAs for validation with real-time PCR (RT-PCR) analysis pre- and post-treatment in another group of 25 MDD patients and 25 HCs. In the array, 5 miRNAs were differentially expressed in medication-naïve MDD patients compared to HCs, of which 2 miRNAs were upregulated and 3 were downregulated. Furthermore, in comparison with HCs, MDD patients showed significantly lower expression levels of miR-374b and miR-10a before treatment. After 8 weeks of antidepressant treatment, both miR-374b and the miR-10a expression levels in MDD patients were significantly elevated only in responders. In conclusion, these results indicate the involvement of miR-374b and miR-10a in the biological mechanisms and therapeutic response of MDD, and provide new insights for exploring miRNAs as potential biomarkers for MDD.

A Preliminary Investigation on Plasma Cell Adhesion Molecules Levels by Protein Microarray Technology in Major Depressive Disorder.

Objectives: Major depressive disorder (MDD) is a serious mental disorder, and there is a great difficulty to diagnose and treat. Hitherto, relatively few studies have explored the correlation between the levels of plasma cell adhesion molecules and MDD. Methods: Thirty outpatients with acute episodes of MDD in Shanghai Mental Health Center and 34 healthy volunteers from the community were recruited as subjects. Protein microarray technology was applied to compared the differences in plasma levels of 17 kinds of adhesion molecular proteins between the two groups. Meanwhile, the diagnostic value of different proteins in depression was discussed by using the receiver operating characteristic curve. Results: The levels of Carcinoembryonic Antigen Related Cell Adhesion Molecule-1(CEACAM-1) and Neural Cell Adhesion Molecule (NrCAM) in MDD patients were significantly higher than those in healthy controls (P < 0.05). The area under ROC curve of CEACAM-1 combined with NrCAM was 0.723, with the sensitivity 0.800 and the specificity 0.676. Conclusion: The plasma levels of CEACAM-1 and NrCAM were significantly up-regulated in MDD, and their combined application was of potential diagnostic value, deserving to expand the sample size for further verification.

Sequential Multiple-Assignment Randomized Trials to Compare Antipsychotic Treatments (SMART-CAT) in first-episode schizophrenia patients: Rationale and trial design.

Accumulated studies have investigated pharmacological interventions for first-episode schizophrenia (FES) patients. However, studies on subsequent treatment steps, which are essential to guide clinicians, are largely missing. This Sequential Multiple-Assignment Randomized Trials comparing Antipsychotic Treatments (SMART-CAT) program intends to evaluate the effectiveness of commonly used antipsychotic drugs in FES patients. The major goals of this study are to examine: 1) what would be the optimal subsequent sequential treatment if the first antipsychotic drug failed; 2) whether clozapine could be used in those first-trial failed and have superior efficacy compared to other atypical antipsychotics. In this article we will report the detail protocol of SMART-CAT. The SMART-CAT is a randomized controlled clinical multicenter trial in which 9 institutions in China will participate. A total of 720 FES patients will be enrolled and followed up for 12 months in this study. The trial includes three treatment phases (each phase lasting for 8 weeks) and a naturalistic follow-up phase; participants who do well on an assigned treatment will remain on that treatment for the duration of the 12-month treatment period, while non-responders will move to the next phase of the study to receive a new treatment. Phase 1 is a randomized controlled trial; patients will be randomly assigned to one of the treatments with oral olanzapine, risperidone, amisulpride, aripiprazole or perphenazine. Subjects who fail to respond after 8 weeks will enter the phase 2 randomization. Phase 2 is an equipoise-stratified randomization trial, and patients will be randomly assigned to oral olanzapine, amisulpride or clozapine for 8 weeks. Subjects who fail to respond after phase 2 will enter an open label trial (phase 3); patients who receive clozapine in phase 2 and fail to respond will be assigned to an extended clozapine treatment or modified electroconvulsive therapy add-on therapy (Phase 3A). Patients who were not assigned to clozapine in phase 2 will be assigned to treatment with clozapine or another SGAs not previously used in phase 1 and 2 (Phase 3B). The primary outcome for the treatment phase is the treatment efficacy rate, which is defined as at least 40% reduction in Positive and Negative Syndrome Scale (PANSS) total score. We hypothesize that clozapine is more therapeutically effective than any other SGAs to patients who failed to meet efficacy criteria in Phase 1, and earlier treatment with clozapine can improve the functional outcomes of schizophrenia patients. As for the naturalistic follow-up phase, time to all-cause treatment failure, marked by its discontinuation is selected as the primary outcome, since it reflects both efficacy and side effects. The all-cause discontinuation is defined as discontinuing for any reasons, including poor efficacy, intolerance of adverse reactions, poor compliance and other reasons. The results of the SMART-CAT trial will provide evidence for the selection of antipsychotics in FES patients who fail to respond to the first trial of an antipsychotic drug. It will also provide evidence for the efficacy and safety of using clozapine in the early phase of schizophrenia treatment by comparing with other SGAs. The study is based on the combination of sequential therapy and dynamic therapy, which can be more suitable to assess the effectiveness of treatment options in the real-world clinical setting. As a result, we hope that this study can provide guidance for an optimal treatment algorithm in first-episode schizophrenia patients. Trial registration: ID NCT03510325 in ClinicalTrials.gov.

Neurochemical and brain functional changes in the ventromedial prefrontal cortex of first-episode psychosis patients: A combined functional magnetic resonance imaging-proton magnetic resonance spectroscopy study.

OBJECTIVE: Previous studies showed alterations of brain function in the ventromedial prefrontal cortex of schizophrenia patients. Also, neurochemical changes, especially GABA level alteration, have been found in the medial prefrontal cortex of schizophrenia patients. However, the relationship between GABA level in the ventromedial prefrontal cortex and brain functional activity in schizophrenia patients remains unexplored. METHODS: In total, 23 drug-naïve, first-episode psychosis patients and 26 matched healthy controls completed the study. The single voxel proton magnetic resonance spectroscopy data were acquired in ventromedial prefrontal cortex region, which was used as the seed region for resting-state functional connectivity analysis. The proton magnetic resonance spectroscopy data were processed to quantify the concentrations of GABA+, glutamine and glutamate, and N-acetylaspartate in ventromedial prefrontal cortex. Spearman correlation analysis was used to examine the relationship between metabolite concentration, functional connectivity and clinical variables. Pearson correlation analysis was used to examine the relationship between GABA+ concentration and functional connectivity value. RESULTS: In first-episode psychosis patients, GABA+ level in ventromedial prefrontal cortex was higher and was positively correlated with ventromedial prefrontal cortex-left middle orbital frontal cortex functional connectivity. N-acetylaspartate level was positively correlated with positive symptoms, and the functional connectivity between ventromedial prefrontal cortex and left precuneus was negatively associated with negative symptoms of first-episode psychosis patients. CONCLUSION: Our results indicated that ventromedial prefrontal cortex functional connectivity changes were positively correlated with higher local GABA+ level in first-episode psychosis patients. The altered neurochemical concentration and functional connectivity provide insights into the pathology of schizophrenia.

Replicated risk CACNA1C variants for major psychiatric disorders may serve as potential therapeutic targets for the shared depressive endophenotype.

Genome-wide association studies (GWASs) have reported numerous associations between risk variants and major psychiatric disorders (MPDs) including schizophrenia (SCZ), bipolar disorder (BPD), major depressive disorder (MDD) and others. We reviewed all of the published GWASs, and extracted the genome-wide significant (p<10-6) and replicated associations between risk SNPs and MPDs. We found the associations of 6 variants located in 6 genes, including L type voltage-gated calcium channel (LTCCs) subunit alpha1 C gene (CACNA1C), that were genome-wide significant (2.0×10 -8 ≤p≤1.0×10 -6 ) and replicated at single-point level across at least two GWASs. Among them, the associations between MPDs and rs1006737 within CACNA1C are most robust. Thus, as a next step, the expression of the replicated risk genes in human hippocampus was analyzed. We found CACNA1C had significant mRNA expression in human hippocampus in two independent cohorts. Finally, we tried to elucidate the roles of venlafaxine and ω-3 PUFAs in the mRNA expression regulation of the replicated risk genes in hippocampus. We used cDNA chip-based microarray profiling to explore the transcriptome-wide mRNA expression regulation by ω-3 PUFAs (0.72/kg/d) and venlafaxine (0.25/kg/d) treatment in chronic mild stress (CMS) rats. ω-3 PUFAs and venlafaxine treatment elicited significant CACNA1C up-regulation. We concluded that CACNA1C might confer the genetic vulnerability to the shared depressive symptoms across MPDs and CACNA1C might be the therapeutic target for depressive endophenotype as well.

Detection Study of Bipolar Depression Through the Application of a Model-Based Algorithm in Terms of Clinical Feature and Peripheral Biomarkers.

Objectives: The nature of the diagnostic classification of mood disorder is a typical dichotomous data problem and the method of combining different dimensions of evidences to make judgments might be more statistically reliable. In this paper, we aimed to explore whether peripheral neurotrophic factors could be helpful for early detection of bipolar depression. Methods: A screening method combining peripheral biomarkers and clinical characteristics was applied in 30 patients with major depressive disorder (MDD) and 23 patients with depressive episode of bipolar disorder. By a model-based algorithm, some information was extracted from the dataset and used as a "model" to approach penalized regression model for stably differential diagnosis for bipolar depression. Results: A simple and efficient model of approaching the diagnosis of individuals with depressive symptoms was established with a fitting degree (90.58%) and an acceptable cross-validation error rate. Neurotrophic factors of our interest were successfully screened out from the feature selection and optimized model performance as reliable predictive variables. Conclusion: It seems to be feasible to combine different types of clinical characteristics with biomarkers in order to detect bipolarity of all depressive episodes. Neurotrophic factors of our interest presented its stable discriminant potentiality in unipolar and bipolar depression, deserving validation analysis in larger samples.

Cost-effectiveness of olanzapine in the first-line treatment of schizophrenia in China.

OBJECTIVES: This study aimed to analyze (1) the cost-effectiveness of olanzapine orally disintegrating tablet (ODT) compared to olanzapine standard oral tablet (SOT) and (2) the cost-effectiveness of olanzapine-SOT compared to aripiprazole-SOT for patients with schizophrenia in China. METHODS: A microsimulation model was adapted from a healthcare payers' perspective. The model ran over a 1-year time horizon, using quarterly cycles. The costs of adverse events were acquired through a clinical expert panel. The average bidding prices in China of olanzapine-ODT, olanzapine-SOT, aripiprazole-SOT, and other switch alternatives were used. Inpatient and outpatient medical costs were sourced from the Urban Employee Basic Medical Insurance database in Tianjin. Additionally, adherence, efficacy, safety, and utility data were taken from the literature. Uncertainty of parameters were assessed through one-way and probabilistic sensitivity analyses. RESULTS: The total annual costs per patient in aripiprazole-SOT arm, olanzapine-SOT arm, and olanzapine-ODT arm are USD 2,296.05, USD 1,940.05, and USD 2,292.81, respectively. The average number of relapses per patient in 1 year in the aripiprazole-SOT arm, olanzapine-SOT arm, and olanzapine-ODT arm, are 0.734, 0.325, and 0.198, respectively. The quality-adjusted life years (QALYs) gained per patient in 1 year in the aripiprazole-SOT arm, olanzapine-SOT arm, and olanzapine-ODT arm are 0.714, 0.737, and 0.758, respectively. Consequently, (1) the incremental cost-effectiveness ratios (ICERs) of administrating olanzapine-ODT over olanzapine-SOT are USD 2,791.96 per relapse avoided and USD 16,798.39 per QALY gained; and (2) the ICERs of using olanzapine-SOT over aripiprazole-SOT are USD -870.39 per relapse avoided and USD -15,477.93 per QALY gained. All ICERs are under the willingness-to-pay threshold in China of USD 25,772.67. The sensitivity analyses confirmed the robustness of the results. CONCLUSION: As the first-line treatment for schizophrenia in China, olanzapine-ODT is cost-effective compared to olanzapine-SOT and olanzapine-SOT is cost-effective compared to aripiprazole-SOT.

Macrophage migration inhibitory factor mediates metabolic dysfunction induced by atypical antipsychotic therapy.

Atypical antipsychotics are highly effective antischizophrenic medications but their clinical utility is limited by adverse metabolic sequelae. We investigated whether upregulation of macrophage migration inhibitory factor (MIF) underlies the insulin resistance that develops during treatment with the most commonly prescribed atypical antipsychotic, olanzapine. Olanzapine monotherapy increased BMI and circulating insulin, triglyceride, and MIF concentrations in drug-naive schizophrenic patients with normal MIF expression, but not in genotypic low MIF expressers. Olanzapine administration to mice increased their food intake and hypothalamic MIF expression, which led to activation of the appetite-related AMP-activated protein kinase and Agouti-related protein pathway. Olanzapine also upregulated MIF expression in adipose tissue, which reduced lipolysis and increased lipogenic pathways. Increased plasma lipid concentrations were associated with abnormal fat deposition in liver and skeletal muscle, which are important determinants of insulin resistance. Global MIF-gene deletion protected mice from olanzapine-induced insulin resistance, as did intracerebroventricular injection of neutralizing anti-MIF antibody, supporting the role of increased hypothalamic MIF expression in metabolic dysfunction. These findings uphold the potential pharmacogenomic value of MIF genotype determination and suggest that MIF may be a tractable target for reducing the metabolic side effects of atypical antipsychotic therapy.

A compromise solution between overlapping and overlooking DSM personality disorders in Chinese psychiatric practice.

OBJECTIVE: This study aimed to examine the overlaps between the Diagnostic and Statistical Manual-5 (DSM-5) Personality Disorders (PDs) in a high-risk clinical population and to explore a transitional model for implementing DSM-5 PDs. METHOD: A sample population of 982 outpatients with at least one diagnosed PD was selected from 3,075 outpatients of the Shanghai Mental Health Center. The diagnostic process comprised of a personality diagnostic questionnaire and a structured clinical interview. RESULTS: 685 (22.3%) patients were diagnosed with at least one of six PDs (antisocial, avoidant, borderline, narcissistic, obsessive-compulsive, and schizotypal) under the alternative DSM-5 model for personality disorders proposed in Section III of the DSM-5. Nearly 20.3% of the subjects with PD met criteria for at least two PDs (of the 685 PD patients/6 PD model). Cluster and principal component analyses suggest a transitional model for the 7 specific PD categories (among the 722 PD patients, the overlapping rate was 24.1%) will be more appropriate for PD diagnosis in China. CONCLUSIONS: Using the simplified PD categories in the alternative DSM-5 model for personality disorders will reduce the overlaps in PD diagnoses in Chinese psychiatric practice, and should be preferred over the DSM-5 PD diagnostic system.

Using 'WeChat' online social networking in a real-world needs analysis of family members of youths at clinical high risk of psychosis.

OBJECTIVE: The argument surrounding the safety and effectiveness of interventions for the population of individuals at a clinical high risk of developing psychosis has been ongoing for the past 30 years. However, few studies have assessed the needs of this special young population, who are struggling with the recent onset of psychotic symptoms. METHOD: The sample consisted of 171 family members of 108 clinical high-risk individuals included from the ShangHai at Risk for Psychosis research programme. A 'WeChat' group was established to provide mutual support. There were 22,007 valid messages sent within the group between 1 April 2015 and 27 June 2016. Chat records were subsequently analysed to determine the needs of families during intervention at the early stages of psychosis. RESULTS: Families of clinical high-risk individuals were highly involved in the entire medical process, and the major concerns of the families of clinical high-risk individuals focused on both functional recovery and medication. The themes of 'take medication', 'go to school' and 'study in school' were often discussed within the group. CONCLUSION: A family-focused intervention targeting functional recovery and real-time professional explanations of medication would meet the major needs of families of Chinese clinical high-risk individuals.

Research Progress in Biological Studies of Schizophrenia in China in 2017.

Schizophrenia is a severe mental disorder and its etiology and pathological mechanism are unknown. This article mainly introduces the progress of biological studies of schizophrenia in China in 2017, including neuroimaging, genetics, and immunology studies. It also introduces the research progress of high-risk psychotic syndrome and physiotherapy.

Is Depression the Result of Immune System Abnormalities?

The etiology of Major Depressive Disorder (MDD) is still unclear. We reviewed the literature for the relationship between inflammatory signaling and cytokines in the pathogenesis of MDD. In addition, we provid evidence for adjunctive treatment using anti-inflammatory drugs to improve the therapeutic effect and prognosis. Finally, we explore the possible relationship between the pathogenesis of MDD and immune disturbances.

The Use of Psychotropic Drugs During Pregnancy.

Patients with severe psychotic disorders face at least two challenges during pregnancy: the genetic risk of psychotic disorders and the risk of teratogenicity caused by psychotropic drugs. This paper reviewed the relevant literature regarding the issues surrounding use of antipsychotics, antidepressants in pregnant patients. The latest treatment guidelines and FDA recommendations are introduced.

Efficacy and tolerability of escitalopram in treatment of major depressive disorder with anxiety symptoms: a 24-week, open-label, prospective study in Chinese population.

BACKGROUND: Significant anxiety symptoms are associated with poor clinical course and outcome in major depressive disorder (MDD). This single-arm, open-label study aimed to evaluate the efficacy and tolerability of escitalopram treatment in patients with MDD and anxiety symptoms. METHODS: Adult patients with MDD and anxiety symptoms (Montgomery-Asberg Depression Rating Scale [MADRS] ≥22 and Hamilton Anxiety Rating Scale [HAM-A] ≥14) were enrolled and received escitalopram (10-20 mg/day) treatment for 24 weeks. Symptom status was assessed by MADRS, 17-item-Hamilton Depression Rating Scale, HAM-A, and Clinical Global Impression Scale at baseline and the following visits. Quality of life was assessed by Short Form-12, and safety was evaluated by adverse events, laboratory investigations, vital signs, and physical findings. RESULTS: Overall, 200 of 318 (66.2%) enrolled patients completed the 24-week treatment. The remission (MADRS ≤10 and HAM-A ≤7) rate in the full analysis set (N=285) was 73.3% (95% confidence interval: 67.80, 78.38) at week 24. Mean (± standard deviation) MADRS total score was 33.4 (±7.13) and HAM-A score was 27.6 (±7.26) at baseline, which reduced to 6.6 (±10.18) and 6.0 (±8.39), respectively, at week 24. Patients with higher baseline depression and anxiety level took longer to achieve similar remission rates. Overall, 80 of the 302 (26.5%) patients included in the safety set reported at least 1 treatment-emergent adverse event (TEAE). Most frequently reported TEAEs (>2%) were headache (4.0%), nasopharyngitis (3.6%), nausea (3.0%), and dizziness (2.6%). Serious TEAEs were reported by 1.3% patients; no deaths were reported. CONCLUSION: Escitalopram 10-20 mg/day was effective and well-tolerated in the long-term treatment of MDD with anxiety symptoms in adult Chinese population.

Resting-state functional connectivity changes within the default mode network and the salience network after antipsychotic treatment in early-phase schizophrenia.

OBJECTIVE: Abnormal resting-state functional connectivity (FC), particularly in the default mode network (DMN) and the salience network (SN), has been reported in schizophrenia, but little is known about the effects of antipsychotics on these networks. The purpose of this study was to examine the effects of atypical antipsychotics on DMN and SN and the relationship between these effects and symptom improvement in patients with schizophrenia. METHODS: This was a prospective study of 33 patients diagnosed with schizophrenia and treated with antipsychotics at Shanghai Mental Health Center. Thirty-three healthy controls matched for age and gender were recruited. All subjects underwent functional magnetic resonance imaging (fMRI). Healthy controls were scanned only once; patients were scanned before and after 6-8 weeks of treatment. RESULTS: In the DMN, the patients exhibited increased FC after treatment in the right superior temporal gyrus, right medial frontal gyrus, and left superior frontal gyrus and decreased FC in the right posterior cingulate/precuneus (P<0.005). In the SN, the patients exhibited decreased FC in the right cerebellum anterior lobe and left insula (P<0.005). The FC in the right posterior cingulate/precuneus in the DMN negatively correlated with the difference between the Clinical Global Impression (CGI) score pre/post-treatment (r=-0.564, P=0.023) and negative trends with the difference in the Positive and Negative Syndrome Scale (PANSS) total score pre/post-treatment (r=-0.475, P=0.063) and the difference in PANSS-positive symptom scores (r=-0.481, P=0.060). CONCLUSION: These findings suggest that atypical antipsychotics could regulate the FC of certain key brain regions within the DMN in early-phase schizophrenia, which might be related to symptom improvement. However, the effects of atypical antipsychotics on SN are less clear.

Impaired cue identification and intention retrieval underlie prospective memory deficits in patients with first-episode schizophrenia.

OBJECTIVE: Schizophrenia is associated with impairment in prospective memory, the ability to remember to carry out an intended action in the future. It has been established that cue identification (detection of the cue event signaling that an intended action should be performed) and intention retrieval (retrieval of an intention from long-term memory following the recognition of a prospective cue) are two important processes underlying prospective memory. The purpose of this study was to examine prospective memory deficit and underlying cognitive processes in patients with first-episode schizophrenia. METHODS: This study examined cue identification and intention retrieval components of event-based prospective memory using a dual-task paradigm in 30 patients with first-episode schizophrenia and 30 healthy controls. All participants were also administered a set of tests assessing working memory and retrospective memory. RESULTS: Both cue identification and intention retrieval were impaired in patients with first-episode schizophrenia compared with healthy controls ( ps < 0.05), with a large effect size for cue identification (Cohen's d = 0.98) and a medium effect size for intention retrieval (Cohen's d = 0.62). After controlling for working memory and retrospective memory, the difference in cue identification between patients and healthy controls remained significant. However, the difference in intention retrieval between the two groups was no longer significant. In addition, there was a significant inverse relationship between cue identification and negative symptoms ( r = -0.446, p = 0.013) in the patient group. CONCLUSION: These findings suggest that both cue identification and intention retrieval in event-based prospective memory are impaired in patients with first-episode schizophrenia. Cue identification and intention retrieval could be potentially used as biomarkers for early detection and treatment prognosis of schizophrenia. In addition, addressing cue identification deficit through cognitive enhancement training may potentially improve negative symptoms as well.