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The membrane transport protein P-glycoprotein (P-gp) is an interesting candidate for individual differences in response to antipsychotics. To present an overview of the current knowledge of P-gp and its interaction with second-generation antipsychotics (SGAs), an internet search for all relevant English original research articles concerning P-gp and SGAs was conducted. Several SGAs are substrates for P-gp in therapeutic concentrations. These include amisulpride, aripiprazole, olanzapine, perospirone, risperidone and paliperidone. Clozapine and quetiapine are not likely to be substrates of P-gp. However, most antipsychotics act as inhibitors of P-gp, and can therefore influence plasma and brain concentrations of other substrates. No information was available for sertindole, ziprasidone or zotepine. Research in animal models demonstrated significant differences in antipsychotic brain concentration and behavior owing to both P-gp knockout and inhibition. Results in patients are less clear, as several external factors have to be accounted for. Patients with polymorphisms which decrease P-gp functionality tend to perform better in clinical settings. There is some variability in the findings concerning adverse effects, and no definitive conclusions can be drawn at this point.

Schizophrenia is a genetically heterogeneous disorder that is associated with several common and rare genetic variants. As technology involved, cost advantages of chip based genotyping was combined with information about rare variants, resulting in the Infinium HumanExome Beadchip. Using this chip, a sample of 493 patients with schizophrenia or schizoaffective disorder and 484 healthy controls was genotyped. From the initial 242901 SNVs, 88306 had at least one minor allele and passed quality control. No variant reached genomewide-significant results (p<10(-8)). The SNP with the lowest p-value was rs1230345 in WISP3 (p = 3.05*10(-6)), followed by rs9311525 in CACNA2D3 (p = 1.03*10(-5)) and rs1558557 (p = 3.85*10(-05)) on chromosome 7. At the gene level, 3 genes were of interest: WISP3, on chromosome 6q21, a signally protein from the extracellular matrix. A second candidate gene is CACNA2D3, a regulator of the intracerebral calcium pathway. A third gene is TNFSF10, associated with p53 mediated apoptosis.

Second-generation antipsychotics (SGA) are known to induce metabolic disturbances. Genetic pathways, such as the IGF pathway could be associated with increased metabolic syndrome (MetS). Additionally, methylation varies as a function of environmental influences and is associated with schizophrenia and MetS. The current study aims to evaluate whether genetic and epigenetic variation in genes of the IGF pathway are associated with metabolic disturbances in patients under treatment with SGAs. Cross-sectional metabolic data from 438 patients with schizophrenia spectrum disorder was analyzed. Using the Sequenom MassARRAY iPLEX platform, 27 SNPs of the and genes and the IGF receptors and were genotyped Methylation status of seven CpG dinucleotides was evaluated using a Sequenom MALDI-TOF spectrometer. There was a significant association between methylation and genotype, but no significant association between genetic or epigenetic variability and metabolic parameters in the present study. Original submitted 28 October 2013; Revision submitted 7 March 2014

Introduction Schizophrenia is a genetically heterogeneous disorder that is associated with several common and rare genetic variants. As technology involved, cost advantages of chip based genotyping was combined with information about rare variants, resulting in the Infinium HumanExome Beadchip. Using this chip, a sample of 493 patients with schizophrenia or schizoaffective disorder and 484 healthy controls was genotyped. Results From the initial 242901 SNVs, 88306 had at least one minor allele and passed quality control. No variant reached genomewide-significant results (p<10-8). The SNP with the lowest p-value was rs1230345 in WISP3 (p = 3.05*10-6), followed by rs9311525 in CACNA2D3 (p = 1.03*10-5) and rs1558557 (p = 3.85*10-05) on chromosome 7. At the gene level, 3 genes were of interest: WISP3, on chromosome 6q21, a signally protein from the extracellular matrix. A second candidate gene is CACNA2D3, a regulator of the intracerebral calcium pathway. A third gene is TNFSF10, associated with p53 mediated apoptosis.

Brain connectivity is disturbed in schizophrenia, both during resting state and during active tasks. Schizophrenia is characterised by a corpus callosum pathology and an inability to suppress overstimulation, both of which relate to this disturbed connectivity. We wanted to verify whether network analysis on EEG sensor level can reveal the corpus callosum pathology in schizophrenia. We measured 62-channel EEG on 46 schizophrenia patients and 43 healthy controls during eyes-closed and eyes-open resting-state, mismatch negativity and visual and auditory oddball. We assessed connectivity through correlation, coherence and directed transfer function (DTF) in the delta, theta, alpha, low- and high beta bands. The coherence and the DTF picked up a consistent pattern of reduced interhemispheric and enhanced intrahemispheric connectivity strength in schizophrenia in the alpha and beta band. This disturbance pattern appeared across all paradigms in the parietal and the occipital region and was generally more pronounced in the right hemisphere. This is the first study to use multiple similarity measures and different tasks to confirm disturbed brain connectivity on EEG sensor level. We hypothesise that the interhemispheric reductions reflect transcallosal disconnection, while the intrahemispheric increases indicate the inability to suppress the response to stimuli.

The γ-secretase complex plays a role in Alzheimer's disease and cancer progression. The development of clinically useful inhibitors, however, is complicated by the role of the γ-secretase complex in regulated intramembrane proteolysis of Notch and other essential proteins. Different γ-secretase complexes containing different Presenilin or Aph1 protein subunits are present in various tissues. Here we show that these complexes have heterogeneous biochemical and physiological properties. Specific inactivation of the Aph1B γ-secretase in a mouse Alzheimer's disease model led to improvements of Alzheimer's disease-relevant phenotypic features without any Notch-related side effects. The Aph1B complex contributes to total γ-secretase activity in the human brain, and thus specific targeting of Aph1B-containing γ-secretase complexes may help generate less toxic therapies for Alzheimer's disease.

Objective: Patients with stage III and high-risk stage II colorectal cancer (CRC) are advised to initiate adjuvant treatment as soon as feasible and certainly before 8 to 12 weeks after resection of the tumor. A protective ileostomy is often constructed during surgery to protect a primary anastomosis \"at risk\", especially in rectal cancer surgery. However, up to 17% of patients with a stoma suffer from high output, a major complication that can prevent adjuvant treatment implementation or completion. To avoid delay or cancellation of adjuvant therapy after CRC resection, effective strategies must be implemented to successfully treat and/or prevent high-output stoma (HOS). Methods: We report two clinical case reports clearly demonstrating the impact and management of HOS in this setting. A review of the available literature and ongoing clinical studies is provided. Results: The clinical cases describe patients with advanced stage CRC and focus on the different strategies for HOS management, presenting their outcome and how each strategy affects the implementation of adjuvant treatment. The patient population with the highest risk of developing HOS is described, along with the rationale for using somatostatin analogs, such as lanreotide, to treat and prevent high output. Conclusion: In patients with CRC and protective ileostomies after primary resection, HOS could be treated with somatostatin analogs in combination with dietary recommendations and Saint Mark's solution. The role of this therapeutic approach as a preventive strategy in patients at high risk of developing HOS, deserves further exploration in a prospective randomized clinical trial.

The γ-secretase complex plays a role in Alzheimer's disease and cancer progression. The development of clinically useful inhibitors, however, is complicated by the role of the γ-secretase complex in regulated intramembrane proteolysis of Notch and other essential proteins. Different γ-secretase complexes containing different Presenilin or Aph1 protein subunits are present in various tissues. Here we show that these complexes have heterogeneous biochemical and physiological properties. Specific inactivation of the Aph1B γ-secretase in a mouse Alzheimer's disease model led to improvements of Alzheimer's disease-relevant phenotypic features without any Notch-related side effects. The Aph1B complex contributes to total γ-secretase activity in the human brain, and thus specific targeting of Aph1B-containing γ-secretase complexes may help generate less toxic therapies for Alzheimer's disease. [PUBLICATION ABSTRACT]

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, our large international expert consortium created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool, which also provides a point of access to explore weaknesses, strengths and specific recommendations for the most common validation metrics. The broad applicability of our framework across domains is demonstrated by an instantiation for various biological and medical image analysis use cases.