Mild Reinforcement Learning Deficits in Patients With First-Episode Psychosis

Numerous studies have identified reinforcement learning (RL) deficits in schizophrenia. Most have focused on chronic patients with longstanding antipsychotic treatment, however, and studies of RL in early-illness patients have produced mixed results, particularly regarding gradual/procedural learning. No study has directly contrasted both rapid and gradual RL in first-episode psychosis (FEP) samples. We examined probabilistic RL in 34 FEP patients and 36 controls, using Go/NoGo (GNG) and Gain vs Loss-Avoidance (GLA) paradigms. Our results were mixed, with FEP patients exhibiting greater impairment in the ability to use positive, as opposed to negative, feedback to drive rapid RL on the GLA, but not the GNG. By contrast, patients and controls showed similar improvement across the acquisition. Finally, we found no significant between-group differences in the postacquisition expression of value-based preference in both tasks. Negative symptoms were modestly associated with RL measures, while the overall bias to engage in Go-responding correlated significantly with psychosis severity in FEP patients, consistent with striatal hyperdopaminergia. Taken together, FEP patients demonstrated more circumscribed RL impairments than previous studies have documented in chronic samples, possibly reflecting differential symptom profiles between first-episode and chronic samples. Our finding of relatively preserved gradual/procedural RL, in briefly medicated FEP patients, might suggest spared or restored basal ganglia function. Our findings of preserved abilities to use representations of expected value to guide decision making, and our mixed results regarding rapid RL, may reflect a lesser degree of prefrontal cortical functional impairment in FEP than in chronic samples. Further longitudinal research, in larger samples, is required.postprin

Cognitive and affective perspectives on formation and maintenance of grandiose delusions of a patient with schizophrenia

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Schedule effect and laparoscopic-assisted vaginal hysterectomy

[[abstract]]Background: Prolonged surgical workload and different starting times of laparoscopic-assisted vaginal hysterectomy, (LAVH) might be factors influencing surgical and patient's outcomes. Aims: The aim of this study is to elucidate possible detrimental results of the schedule effect on LAVH. Methods: Retrospective cohort study based on patient charts and hospital's electronic database in a tertiary teaching hospital. A total of 217 consecutive women who underwent LAVH for gynecological diseases were enrolled. Among them, 159 LAVHs performed by four surgeons were divided into three groups according to three different starting times of the operation. Among 159 LAVHs, 110 performed by the same surgeon were divided into three groups in the same way. Variables related to operative and medical outcomes were compared and analysed by one-way ANOVA and chi-squared test. Results: Data on both all women (159 cases) and subgroup women (110 cases) revealed that no statistical significant differences among the three groups including length of hospital stay, shift of serum haemoglobin, shift of serum haematocrit, flatulence-relief time, surgical blood loss, blood transfusion rate, rate of postoperative,e fluid injection over two days after surgery or complication rate. Interestingly, the first LAVH scheduled within the 08.30 to 10.29 hours time slot had the longest mean operation time. LAVHs starting within the 15.30 to 17.29 hours time slot had the shortest mean operation time. Conclusion: The time of day in which LAVH is performed does not have a detrimental effect on outcome. Successful LAVH is dependent on multidisciplinary team work to achieve good surgical and patient outcomes

Incorporating Support Vector Machine for Identifying Protein Tyrosine Sulfation Sites

[[abstract]]Abstract: Tyrosine sulfation is a post-translational modification of many secreted and membrane-bound proteins. It governs protein-protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty-two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five-fold cross-validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in fivefold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 30: 2526-2537, 200

Sustainability of Treatment Effect of a 3-year Early Intervention Programme for First-episode Psychosis in Hong Kong

Parallel Session 1 – Health and Health Services: abstract no. S2published_or_final_versio

Web-Based Psychoeducation Program for Caregivers of First-Episode of Psychosis: An Experience of Chinese Population in Hong Kong

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Flood impact assessment under climate change scenarios in central Taipei area, Taiwan

Providing effective information regarding flood control for responding climate change is essential to future flood risk management for cities. This study simulated and assessed the impacts of flooding for future climate change scenarios in Taipei city, Taiwan. We modelled rainfall events, generated by general circulation models, with different return periods. The flood extents and damage in the Central Taipei Area for the A1B climate change scenarios were compared to the ones, caused by the rainfall events with same return periods, without climate change (baseline scenario). The proposed approach provides potential flooding maps and flood damage assessment for climate change scenarios as useful information for flood risk management in urban areas.The work is supported by the National Science Council, Taiwan (NSC 99-2915-I-002-120) and the CORFU project, funded by the European Commission through Framework Programme 7, Grant Number 244047

Discovering monotonic stemness marker genes from time-series stem cell microarray data

© 2015 Wang et al.; licensee BioMed Central Ltd. Background: Identification of genes with ascending or descending monotonic expression patterns over time or stages of stem cells is an important issue in time-series microarray data analysis. We propose a method named Monotonic Feature Selector (MFSelector) based on a concept of total discriminating error (DEtotal) to identify monotonic genes. MFSelector considers various time stages in stage order (i.e., Stage One vs. other stages, Stages One and Two vs. remaining stages and so on) and computes DEtotal of each gene. MFSelector can successfully identify genes with monotonic characteristics.Results: We have demonstrated the effectiveness of MFSelector on two synthetic data sets and two stem cell differentiation data sets: embryonic stem cell neurogenesis (ESCN) and embryonic stem cell vasculogenesis (ESCV) data sets. We have also performed extensive quantitative comparisons of the three monotonic gene selection approaches. Some of the monotonic marker genes such as OCT4, NANOG, BLBP, discovered from the ESCN dataset exhibit consistent behavior with that reported in other studies. The role of monotonic genes found by MFSelector in either stemness or differentiation is validated using information obtained from Gene Ontology analysis and other literature. We justify and demonstrate that descending genes are involved in the proliferation or self-renewal activity of stem cells, while ascending genes are involved in differentiation of stem cells into variant cell lineages.Conclusions: We have developed a novel system, easy to use even with no pre-existing knowledge, to identify gene sets with monotonic expression patterns in multi-stage as well as in time-series genomics matrices. The case studies on ESCN and ESCV have helped to get a better understanding of stemness and differentiation. The novel monotonic marker genes discovered from a data set are found to exhibit consistent behavior in another independent data set, demonstrating the utility of the proposed method. The MFSelector R function and data sets can be downloaded from: http://microarray.ym.edu.tw/tools/MFSelector/

The Effect of Paternal Age on Relapse in First-Episode Schizophrenia

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