The brain coordinates motor activity through poorly understood mechanisms, which are difficult to study in animal models or humans. However, the fruit fly exhibits complex behaviors and lends itself to genetic manipulation and brain imaging techniques that can be used to study neural circuits underlying behavior. A critical behavior executed by the fly during development is the ecdysis, or molting, sequence. At the pupal stage, the ecdysis sequence is composed of three stereotyped, serially executed motor programs that are directed by a single, hormonally controlled neural circuit. We have shown that the neurons expressing the Ecdysis Triggering Hormone receptor (ETHR) are responsible for initiating and controlling the ecdysis programs. Our evidence also suggests that a subset of the neurons expressing the Crustacean Cardioactive Peptide receptor (CCAPR) mediate the motor output of the ecdysis neural circuit. In excised brains, the calcium activity of these motor neurons exhibit three phases with characteristics similar to the motor programs of the ecdysis sequence. To more directly compare motor neuron activity with behavior, we are now monitoring muscle and neuronal calcium activity in the same animal. To do so, we have developed transgenic fly lines that express a red fluorescent calcium sensor in the muscles and a green fluorescent calcium sensor in the motor neurons of the CNS. To facilitate comparison of these motor programs with muscle and neuronal calcium activity, we subdivide the activity traces into distinct phases using an algorithm we developed earlier for the analysis of activity in excised brains. This permits a rigorous, quantitative comparison of the muscle and brain patterns of activity with behavior. We are currently integrating this data into our growing systems model of how the brain generates a complex behavior in the fruit fly.

Motor sequences are critical elements of everyday behavior, but how they are produced by central neural circuits is poorly understood. The complexity and scale of the circuitry involved makes motor sequence generation very difficult to study at the cellular level in large, mammalian brains. However, the neural circuits of the fruitfly also drive complex motor sequences, and are small enough to investigate at a brain-wide scale via emerging methods in microscopy. A critical behavioral sequence for the fruitfly, called ecdysis, is required for molting at each developmental stage and consists of three serially executed, stereotyped behavioral programs at the pupal stage. The neural circuit controlling the pupal ecdysis sequence includes approximately 300 peptidergic neurons that express the Ecdysis Triggering Hormone receptor (ETHR) and are activated by peripheral release of Ecdysis Triggering Hormone (ETH). The activation of these neurons leads directly to the three phases of associated motor neuron activity that mediate the ecdysis sequence, and existing data indicate that specific subpopulations are required for each behavioral phase of ecdysis. However, the identities of the individual neurons that control each behavioral phase remain largely unknown, as do the mechanisms by which they regulate motor output. To achieve a detailed cellular-level understanding of the ecdysis circuit, we have built a light-sheet microscope that is capable of imaging the Drosophila pupal CNS rapidly at high resolution. We are currently using calcium biosensors to monitor the neural activity in ETHR-expressing neurons and motor neurons of excised brains in response to ETH. Single-cell activity imaging on the light-sheet microscope confirms that individual neurons respond to ETH with varying onset times and distinct activity profiles that suggest the generation of fictive ecdysis behavior. Analysis of these data, and data collected from other populations of neurons, are being used to generate a predictive model of the circuit underlying the ecdysis sequence with the general goal of understanding how nervous systems orchestrate complex motor sequences in response to input stimuli.

Neural networks are typically defined by their synaptic connectivity, yet synaptic wiring diagrams often provide limited insight into network function. This is due partly to the importance of non-synaptic communication by neuromodulators, which can dynamically reconfigure circuit activity to alter its output. Here, we systematically map the patterns of neuromodulatory connectivity in a network that governs a developmentally critical behavioral sequence in Drosophila. This sequence, which mediates pupal ecdysis, is governed by the serial release of several key factors, which act both somatically as hormones and within the brain as neuromodulators. By identifying and characterizing the functions of the neuronal targets of these factors, we find that they define hierarchically organized layers of the network controlling the pupal ecdysis sequence: a modular input layer, an intermediate central pattern generating layer, and a motor output layer. Mapping neuromodulatory connections in this system thus defines the functional architecture of the network.

Behavior is the result of patterned activity in motor neurons produced by the action of central neural circuits. Abnormalities in these circuits lead to behavioral disorders in a way that is poorly understood because the circuits themselves are complex and highly distributed. The circuits of the fruitfly nervous system are like those found in humans, but the fly nervous system is small enough that brain-wide circuit analysis at subcellular resolution is conceivable with cutting edge microscopy. We are developing a custom dual-view selective plane illumination microscope (diSPIM) for brain-wide imaging in order to characterize the fruit fly neural circuit that drives the ecdysis sequence. This sequence is a hormonally-induced behavioral program that is executed to shed the old exoskeleton. It consists of distinct phases of activity and is governed by ∼300 neurons that express the Ecdysis Triggering Hormone receptor (ETHR). We hypothesize that patterned activity within these neurons drives downstream motor neuron activity to generate the ecdysis sequence. We will use the diSPIM together with recently developed genetic targeting techniques to simultaneously measure Ca2+ activity in ETHR-expressing neurons and motor neurons and create spatiotemporal maps of their activity with subcellular spatial resolution and ∼1 Hz temporal resolution. Collectively, these maps will be used to generate a predictive model of the circuit underlying the ecdysis sequence. Currently, we are constructing and characterizing the diSPIM, testing analysis methods using data collected by conventional confocal microscopy, and generating fly lines that will allow us to simultaneously interrogate the Ca2+ activity in two different populations of neurons.

Genetically encoded effectors are important tools for probing cellular function in living animals, but improved methods for directing their expression to specific cell types are required. Here, we introduce a simple, versatile method for achieving cell-typespecific expression of transgenes that leverages the untapped potential of "coding introns'' (i.e., introns between coding exons). Our method couples the expression of a transgene to that of a native gene expressed in the cells of interest using intronically inserted "plug-and-play'' cassettes (called "Trojan exons'') that carry a splice acceptor site followed by the coding sequences of T2A peptide and an effector transgene. We demonstrate the efficacy of this approach in Drosophila using lines containing suitable MiMIC (Minos-mediated integration cassette) transposons and a palette of Trojan exons capable of expressing a range of commonly used transcription factors. We also introduce an exchangeable, MiMIC-like Trojan exon construct that can be targeted to coding introns using the Crispr/Cas system.

To grow, insects must periodically shed their exoskeletons. This process, called ecdysis, is initiated by the endocrine release of Ecdysis Trigger Hormone (ETH) and has been extensively studied as a model for understanding the hormonal control of behavior. Understanding how ETH regulates ecdysis behavior, however, has been impeded by limited knowledge of the hormone’s neuronal targets. An alternatively spliced gene encoding a G-protein-coupled receptor (ETHR) that is activated by ETH has been identified, and several lines of evidence support a role in ecdysis for its A-isoform. The function of a second ETHR isoform (ETHRB) remains unknown. Here we use the recently introduced “Trojan exon” technique to simultaneously mutate the ETHR gene and gain genetic access to the neurons that express its two isoforms. We show that ETHRA and ETHRB are expressed in largely distinct subsets of neurons and that ETHRA- but not ETHRB-expressing neurons are required for ecdysis at all developmental stages. However, both genetic and neuronal manipulations indicate an essential role for ETHRB at pupal and adult, but not larval, ecdysis. We also identify several functionally important subsets of ETHR-expressing neurons including one that coexpresses the peptide Leucokinin and regulates fluid balance to facilitate ecdysis at the pupal stage. The general strategy presented here of using a receptor gene as an entry point for genetic and neuronal manipulations should be useful in establishing patterns of functional connectivity in other hormonally regulated networks.

The effects of ZNF804A rs1344706, a prominent susceptibility gene for schizophrenia, on gray matter (GM) structure in unmedicated schizophrenia (SZ) patients are still unknown, although several previous studies investigated the effects in medicated SZ patients and healthy controls (HC). Analyzing cortical thickness, surface area, and GM volume simultaneously may provide a more precise and complete picture of the effects. We genotyped 59 unmedicated first episode SZ patients and 60 healthy controls for the ZNF804A single nucleotide polymorphism (SNP) rs1344706, and examined between-group differences in cortical thickness, surface area, and cortical volume using a full-factorial 2 × 2 analysis of variance (ANOVA). We found the risk allele (T) in ZNF804A rs1344706, compared to the non-risk allele (G), was associated with thinner cortex in the bilateral precuneus, left precentral gyrus, and several other regions, associated with a smaller cortical surface area in the left superior parietal, precuneus cortex and left superior frontal, and associated with a lower cortical volume in the left superior frontal, left precentral, and right precuneus in SZ patients. In contrast, in the controls, the T allele was associated with the increased cortical measurements compared to the G allele in the same regions as those mentioned above. ZNF804A rs1344706 has significant, but different, effects on cortical thickness, surface area, and cortical volume in multiple regions of the brain cortex. Our findings suggest that ZNF804A rs1344706 may aggravate the risk for schizophrenia by exerting its effects on cortical thickness, surface area, and cortical volume in these brain regions.

Insects execute a behavioral program, called an ecdysis sequence, to shed their cuticle at each developmental molt. The neural circuit controlling the ecdysis sequence consists of approximately 300 peptidergic neurons that express the Ecdysis Triggering Hormone receptor (ETHR) and are activated by peripheral release of Ecdysis Triggering Hormone (ETH). While several groups of neurons within the network play known roles in the ecdysis sequence, such as those expressing the hormones CCAP and bursicon, the timing of their activity is poorly understood and likely involves regulation by as yet unidentified inhibitory neurons. In general, the patterns of activity within the ecdysis network and how they give rise to motor output remains enigmatic. Using the genetically tractable Drosophila model system, and focusing on the ecdysis sequence executed at the pupal molt, we have investigated the evolution of network activity using Gal4 driver lines to express UAS-RCaMP or UAS-GCaMP6 Ca2+ biosensors in subsets of neurons in the ETHR network or its downstream motor neurons. We are able to elicit the ecdysis sequence in an excised pupal brain by application of exogenous ETH and visualize the neural activity underlying the ecdysis-specific motor patterns in targeted neurons. The quantitative temporal information provided by Ca2+ biosensors, when combined with anatomical data derived from structured illumination and diffraction-limited fluorescence microscopy techniques, provides insights into how the activity patterns of the ETHR circuit are generated.

BACKGROUND:Although many studies have reported that glucose and lipid metabolism disorders are a significant side effect associated with the use of antipsychotic drugs, the characteristics of glucose and lipid metabolism disorders in patients with schizophrenia who are taking antipsychotic drugs remain poorly understood, and the possible effects that antipsychotic discontinuation may have on glucose and lipid metabolism remain unclear.METHODS:The sample consisted of 131 Chinese patients with schizophrenia, including 70 first-episode, drug-naïve patients; 33 patients who had received continuous antipsychotic drug treatment for ≥1 year prior to the beginning of the study; and 28 patients who had discontinued antipsychotic drug treatment for ≥3 months prior to the beginning of study. We compared the glucose and lipid metabolic parameter levels among the three groups of patients with schizophrenia. All assessments were performed upon hospital admission.RESULTS:The characteristics of glucose and lipid metabolism disorders in Chinese patients with schizophrenia who are taking antipsychotic drugs included significant augmentation of the body mass index and waist circumference, significantly higher levels of fasting plasma insulin and insulin resistance, and significantly lower plasma high-density lipoprotein cholesterol levels. Antipsychotic discontinuation appeared to not significantly improve any plasma glucose and lipid metabolic parameter levels.CONCLUSION:The results suggest that antipsychotic drugs aggravate glucose and lipid metabolism disorders and that antipsychotic discontinuation is generally not associated with improvements in the parameters that indicate glucose and lipid metabolism disorders in Chinese patients with schizophrenia.

Altered brain connectivity has been widely considered as a genetic risk mechanism for schizophrenia. Of the many susceptibility genes identified so far, ZNF804A (rs1344706) is the first common genetic variant associated with schizophrenia on a genome-wide level. Previous fMRI studies have found that carriers of rs1344706 exhibit altered functional connectivity. However, the relationship between ZNF804A and white matter structural connectivity in patients of schizophrenia remains unknown. In this study, 100 patients with schizophrenia and 69 healthy controls were genotyped at the single nucleotide polymorphism rs1344706. Diffusion tensor imaging (DTI) was conducted and analyzed with tract-based spatial statistics. Systematic statistical analysis was conducted on multiple diffusion indices, including fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity. Unpaired two-sample t-test revealed significant differences in fractional anisotropy and diffusivity between schizophrenia and control groups. A two-way ANOVA analysis was conducted to assess the main effects of and the interaction between schizophrenia and ZNF804A. Although significant main effects of the diagnosis of schizophrenia were found on radial diffusivity, no association between the ZNF804A (rs1344706) and white matter connectivity was found in the entire group of subjects or in a selected subgroup of age-matched subjects (n=72).

To compare the difference in body mass index (BMI), waist-to-hip ratio (WHR), and glucose and lipid metabolism parameters between drug-naïve, first-episode schizophrenia patients and healthy controls matched for age, ethnicity and gender, we conducted a test including BMI, WHR, and fasting glucose and lipid metabolism parameters in both 70 drug-naïve, first-episode schizophrenia patients, having not a single day of cumulative exposure to antipsychotic medications and 44 normal healthy controls at baseline. Student's t tests (two tailed) were conducted to examine between group differences. We found that drug-naïve first-episode schizophrenia patients had higher insulin, insulin resistance and C-peptide levels, and had lower total cholesterol (TC), high density lipoprotein cholesterol (HDL-c) and apolipoproteinA1 levels. Simultaneously, drug-naïve, first-episode schizophrenia patients show a potential tendency of WHR enlargement, although there were no statistically significant differences between groups (mean=0.82, SD=0.06, for the patients versus mean=0.79, SD=0.06, for the health subjects). These results suggest that drug-naïve, first-episode schizophrenia patients do differ from healthy controls in their fasting glycometabolism parameters and lipid profiles, including fasting plasma levels of insulin, C-peptide, TC, HDL-c, and apolipoproteinA1, and patients are more insulin resistant before the onset of antipsychotic medication treatment.

目的探讨位于锌指蛋白804A（zinc finger protein 804A,ZNF804A）内含子区内的多态位点rs1344706与精神分裂症的关系。方法提取来自广东省的250例精神分裂症患者和201名正常对照基因组DNA,通过聚合酶链反应扩增rs1344706位点前后250bp DNA片段,应用直接测序法确定rs1344706基因型,比较两组间以及按性别分层后两组间rs1344706的等位基因及基因型分布频率。结果患者组携带rs1344706位点C等位基因的频率高于对照组（52.0%vs.44.3%,P=0.025）,但两组间基因型分布差异无统计学意义（P=0.054）;按性别分层后进一步比较,rs1344706在患者组女性和对照组女性之间的C等位基因频率（55.3%vs.41.1%,P=0.007）及基因型分布（P=0.022）差异具有统计学意义,而患者组男性与对照组男性相比,C等位基因频率及基因型分布差异均无统计意义（均P＞0.05）。结论 ZNF804A rs1344706中的C等位基因是广东省汉族女性精神分裂症的风险因子,ZNF804Ars1344706多态性与精神分裂症存在关联。

`The single-nucleotide polymorphism rs1344706 located in the ZNF804A zinc finger protein 804A gene is a well-established genome-wide significant variant for schizophrenia. The aim of this study was to investigate the potential association between this ZNF804A polymorphism and treatment response to atypical antipsychotic. Seventy-one first-episode inpatients with schizophrenia receiving olanzapine, aripiprazole, or quetiapine monotherapy were enrolled. Symptom response to treatment was assessed using the Positive and Negative Syndrome Scale (PANSS) on admission and reassessed after 4 weeks of treatment. Single-nucleotide polymorphism rs1344706 was genotyped by direct sequencing. There was substantial difference in treatment response among patients with 3 different genotypes regarding total PANSS score and positive subscore (for total PANSS score, F = 4.608, df = 2, P = .013; for positive subscore, F = 4.183, df = 2, P = .019). Compared with G homozygotes, T carriers showed significantly less improvement in total PANSS score as well as positive subscore (for total PANSS score, F = 8.724, df = 1, P = .004; for positive subscore, F = 9.392, df = 1, P = .005). Our results suggest that ZNF80A rs1344706 polymorphism may play a role in treatment response to atypical antipsychotic, although replication is required to confirm this finding.

BACKGROUND:The Mood Disorder Questionnaire (MDQ) is a well-recognized screening tool for bipolar disorder, but its Chinese version needs further validation. This study aims to measure the accuracy of the Chinese version of the MDQ as a screening instrument for bipolar disorder (BPD) in a group of patients with a current major depressive episode.METHODS:142 consecutive patients with an initial DSM-IV-TR diagnosis of a major depressive episode were screened for BPD using the Chinese translation of the MDQ and followed up for one year. The final diagnosis, determined by a special committee consisting of three trained senior psychiatrists, was used as a 'gold standard' and ROC was plotted to evaluate the performance of the MDQ. The optimal cut-off was chosen by maximizing the Younden's index.RESULTS:Of the 142 patients, 122 (85.9%) finished the one year follow-up. On the basis of a semi-structured clinical interview 48.4% (59/122) received a diagnosis of unipolar depression (UPD), 36.9% (45/122) BPDII and 14.8% (18/122) BPDI. At the end of the one year follow-up,9 moved from UPD to BPD, 2 from BPDII to UPD, 1 from BPDII to BPDI, the overall rate of initial misdiagnosis was 16.4%. MDQ showed a good accuracy for BPD: the optimal cut-off was 4, with a sensitivity of 0.72 and a specificity of 0.73. When BPDII and BPDI were calculated independently, the optimal cut-off for BPDII was 4, with a sensitivity of 0.70 and a specificity of 0.73; while the optimal cut-off for BPDI was 5, with a sensitivity of 0.67 and a specificity of 0.86.CONCLUSIONS:Our results show that the Chinese version of MDQ is a valid tool for screening BPD in a group of patients with current depressive episode on the Chinese mainland.

Schizophrenia is thought to arise in part from abnormal gray matter (GM), which are partly shared by the relatives of the probands. DISC1 is one of the most promising susceptibility genes of schizophrenia and a SNP rs821597 (A) in the gene was associated with schizophrenia in Han Chinese population. In this study, 61 healthy controls and 72 with schizophrenic patients were genotyped at rs821597, and underwent T1-weighted MRI for the density of GM. The results showed that the risk allele (A) carriers had higher GM density in regional left parahippocampal gyrus and right orbitofrontal cortex in schizophrenic patients, but had reduced GM density of these brain regions in healthy controls. The DISC1 variant rs821597 may confer risk for schizophrenia by its effects on the regional GM in left parahippocampal gyrus and right orbitofrontal cortex with other risk factors for schizophrenia.

Background: ZNF804A gene polymorphism rs1344706, the first genetic risk variant to achieve genome wide significance for schizophrenia, has been linked to neural functional connectivity. Dysconnectivity of WM may be the primary pathological mechanism of schizophrenia. Association of this variant with regional WM density has not been investigated in schizophrenic patients.Methods: 69 healthy controls and 80 patients with schizophrenia underwent genotyping of rs1344706 SNPs, and were examined for WM density (T1-weighted MRI). The association of rs1344706 with WM changes in schizophrenia patients and healthy controls was analyzed using a full-factorial 2 x 2 analysis of variance.Results: 1. There was an interaction on WM density in the left prefrontal lobe between the rs1344706 genotype and schizophrenic diagnosis, where the risk T allele carriers presented higher WM density in the schizophrenia patients and lower WM density in healthy controls in comparison with the non-risk allele carriers.2. The risk allele was associated with an increased WM density of the bilateral hippocampus in both the patients and the healthy group.Limitation: The influence of antipsychotics to the white matter in schizophrenic patients was not fully eliminated.Conclusions: The ZNF804A variant may confer risk for schizophrenia by exerting its effects on the WM in the left prefrontal lobe together with other risk factors for schizophrenia. (C) 2011 Elsevier Inc. All rights reserved.

Background: A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes.Methods: A prospective study was carried out on 394 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted.Results: Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months.Limitations: The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information.Conclusion: Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. (C) 2011 Elsevier B.V. All rights reserved.

Concurrence of psychosis and Dandy–Walker complex (DWC) has been reported in some medical literature. Here, we reported four patients with concurrent psychosis and DWC of all four subtypes. Some clinical features found were juvenile or young adult age onset, high frequency of family history of psychosis, atypical psychotic symptoms, and high prevalence of cognitive deficit and refractoriness to treatment, in line with the cases in previous reports. These findings might help further illuminate the role that the cerebellum plays in the etiology of schizophrenia or bipolar disorder.

AIMS:To evaluate the prevalence of metabolic syndrome (MetS) and its correlates in patients with bipolar disorder (BD) during acute-phase treatment in southern China. METHODS:This study included 148 BD patients presenting with acute mood symptoms and 65 healthy controls at entry. Sociodemographic characteristics were noted for all participants. For patients, lifestyle information (alcohol, smoking, and exercise habits) and clinical characteristics were also collected. Patients were followed up for 6 months after the commencement of pharmacological treatment. Using the Chinese Medical Association Diabetes Branch criteria, MetS prevalence rates were calculated at entry and recalculated for patients at months 1, 3, and 6. RESULTS:At baseline, MetS was presented in 11.5% of the patients; overweight, 34.5%; low high-density lipoprotein cholesterol, 15.5%; hypertriglyceridemia, 29.1%; hypertension, 14.9%; and hyperglycemia, 5.4%. Compared with controls, the patients had a significantly higher prevalence of MetS and all its components except for hyperglycemia (P < 0.05). In the regression analysis, history of hypertension, presence of diabetes, and alcohol drinking were associated with MetS. During the follow-up period, rates of MetS and overweight increased gradually and stably, hypertriglyceridemia and low high-density lipoprotein cholesterol increased significantly in the first month and then remained stable, and hypertension and hyperglycemia remained stable all the time. CONCLUSIONS:These data show that MetS is highly prevalent in Chinese BD patients. Weight gain and dyslipidemia result from a short period of treatment. Early interventions for weight gain and dyslipidemia are warranted.

RIG-I and MDA5 are cytoplasmic sensors that recognize different species of viral RNAs, leads to activation of the transcription factors IRF3 and NF-kappaB, which collaborate to induce type I interferons. In this study, we identified REUL, a RING-finger protein, as a specific RIG-I-interacting protein. REUL was associated with RIG-I, but not MDA5, through its PRY and SPRY domains. Overexpression of REUL potently potentiated RIG-I-, but not MDA5-mediated downstream signalling and antiviral activity. In contrast, the RING domain deletion mutant of REUL suppressed Sendai virus (SV)-induced, but not cytoplasmic polyI:C-induced activation of IFN-beta promoter. Knockdown of endogenous REUL by RNAi inhibited SV-triggered IFN-beta expression, and also increased VSV replication. Full-length RIG-I, but not the CARD domain deletion mutant of RIG-I, underwent ubiquitination induced by REUL. The Lys 154, 164, and 172 residues of the RIG-I CARD domain were critical for efficient REUL-mediated ubiquitination, as well as the ability of RIG-I to induce activation of IFN-beta promoter. These findings suggest that REUL is an E3 ubiquitin ligase of RIG-I and specifically stimulates RIG-I-mediated innate antiviral activity.