Molecular genetics of the chromosome 11q22-24 schizophrenia susceptibility region

Linkage analyses of multiply affected schizophrenic families have confirmed the involvement of the chromosome 11q22-24 region in the aetiology of schizophrenia, with LOD scores of 3.4 and 3.1. As a result, a genetic association study was performed to fine map this area by detecting linkage disequilibrium between DNA markers and the genetic disorder. This was done using the University College London (UCL) sample of 496 cases and 488 supernormal controls. Seven microsatellite or SNP markers localised within or near the FXYD6 gene showed empirically significant allelic associations with schizophrenia. Confirmation was then performed by the study of an Aberdeen sample consisting of 858 cases and 591 controls. Here, two of the SNPs replicated association with schizophrenia. Sequencing of the FXYD6 gene led to the discovery of several mutations including a rare non-database SNP, which was found at a significantly higher frequency in the selected high risk haplotype schizophrenic patients, when compared to the randomly chosen control individuals. However, a genetic association test of this SNP was found to be negatively associated to schizophrenia when genotyping in the whole UCL case-control sample. FXYD6 encodes for the protein phosphohippolin and functions by modulating the kinetic properties of Na,K-ATPase to the specific requirements of a given tissue, cell type or physiological state. Phosphohippolin is predominantly expressed in the brain, with strong expression in the hippocampus and the cerebellum. The prominent levels of FXYD6 expression in regions of the brain thought to be involved in schizophrenia provide strong support that the FXYD6 gene increases genetic susceptibility to schizophrenia. Further confirmations involving FXYD6 to schizophrenia are essential in other case-control samples. In addition, aetiological base pair changes in FXYD6 or in associated promoter/control regions that cause an abnormal function or expression of phosphohippolin require detection

Sensing and modeling human networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2004.Includes bibliographical references (p. 101-105).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Knowledge of how groups of people interact is important in many disciplines, e.g. organizational behavior, social network analysis, knowledge management and ubiquitous computing. Existing studies of social network interactions have either been restricted to online communities, where unambiguous measurements about how people interact can be obtained (available from chat and email logs), or have been forced to rely on questionnaires, surveys or diaries to get data on face-to-face interactions between people. The aim of this thesis is to automatically model face-to-face interactions within a community. The first challenge was to collect rich and unbiased sensor data of natural interactions. The "sociometer", a specially designed wearable sensor package, was built to address this problem by unobtrusively measuring face-to-face interactions between people. Using the sociometers, 1518 hours of wearable sensor data from 23 individuals was collected over a two-week period (66 hours per person). This thesis develops a computational framework for learning the interaction structure and dynamics automatically from the sociometer data. Low-level sensor data are transformed into measures that can be used to learn socially relevant aspects of people's interactions - e.g. identifying when people are talking and whom they are talking to. The network structure is learned from the patterns of communication among people. The dynamics of a person's interactions, and how one person's dynamics affects the other's style of interaction are also modeled. Finally, a person's style of interaction is related to the person's role within the network. The algorithms are evaluated by comparing the output against hand-labeled and survey data.by Tanzeem Khalid Choudhury.Ph.D

1-Gb/s Transmission Over a Phosphorescent White LED by Using Rate-Adaptive Discrete Multitone Modulation

Light-emitting diodes (LEDs), which will be increasingly used in lighting technology, will also allow for distribution of broadband optical wireless signals. Visible-light communication (VLC) using white LEDs offers several advantages over the RF-based wireless systems, i.e., license-free spectrum, low power consumption, and higher privacy. Mostly, optical wireless can provide much higher data rates. In this paper, we demonstrate a VLC system based on a white LED for indoor broadband wireless access. After investigating the nonlinear effects of the LED and the power amplifier, a data rate of 1 Gb/s has been achieved at the standard illuminance level, by using an optimized discrete multitone modulation technique and adaptive bit- and power-loading algorithms. The bit-error ratio of the received data was 1.5 10^(-3), which is within the limit of common forward error correction (FEC) coding. These results twice the highest capacity that had been previously obtained

3.4 Gbit/s Visible Optical Wireless Transmission Based on RGB LED

In this paper, we experimentally realized a gigabit-class indoor visible light communication system using commercially available RGB White LED and exploiting an optimized DMT modulation. We achieved data rate of 1.5 Gbit/s with single channel and 3.4 Gbit/s by implementing WDM transmission at standard illumination levels. In both experiments, the resulting bit error ratios were below the FEC limit. To the best of our knowledge, these values are the highest ever achieved in VLC systems

A Visible Light Localization Aided OpticalWireless System

We report about a Line of Sight Optical Wireless Communication (LoS OWC) system aided by a simplified Visible Light localization algorithm for tracking purposes. We show experimentally that by combining the LoS OWC system with the localization algorithm it is possible to provide a gross datarate exceeding 300 Mb/s over a 90 degrees illumination angle by using a RGB visible-light LED at 90 cm distance

Evidence for the association of the DAOA (G72) gene with schizophrenia and bipolar disorder but not for the association of the DAO gene with schizophrenia

Background: Previous linkage and association studies have implicated the D-amino acid oxidase activator gene (DAOA)/G30 locus or neighbouring region of chromosome 13q33.2 in the genetic susceptibility to both schizophrenia and bipolar disorder. Four single nucleotide polymorphisms (SNPs) within the D-amino acid oxidase (DAO) gene located at 12q24.11 have also been found to show allelic association with schizophrenia.Methods: We used the case control method to test for genetic association with variants at these loci in a sample of 431 patients with schizophrenia, 303 patients with bipolar disorder and 442 ancestrally matched supernormal controls all selected from the UK population.Results: Ten SNPs spanning the DAOA locus were genotyped in these samples. In addition three SNPs were genotyped at the DAO locus in the schizophrenia sample. Allelic association was detected between the marker rs3918342 (M23), 3' to the DAOA gene and both schizophrenia (chi(2) = 5.824 p = 0.016) and bipolar disorder (chi(2) = 4.293 p = 0.038). A trend towards association with schizophrenia was observed for two other DAOA markers rs3916967 (M14, chi(2) = 3.675 p = 0.055) and rs1421292 (M24; chi(2) = 3.499 p = 0.062). A test of association between a three marker haplotype comprising of the SNPs rs778293 (M22), rs3918342 (M23) and rs1421292 (M24) and schizophrenia gave a global empirical significance of p = 0.015. No evidence was found to confirm the association of genetic markers at the DAO gene with schizophrenia.Conclusion: Our results provide some support for a role for DAOA in susceptibility to schizophrenia and bipolar disorder

Failure to confirm allelic and haplotypic association between markers at the chromosome 6p22.3 dystrobrevin-binding protein 1 (DTNBP1) locus and schizophrenia

Background: Previous linkage and association studies may have implicated the Dystrobrevin-binding protein 1 (DTNBP1) gene locus or a gene in linkage disequilibrium with DTNBP1 on chromosome 6p22.3 in genetic susceptibility to schizophrenia.Methods: We used the case control design to test for of allelic and haplotypic association with schizophrenia in a sample of four hundred and fifty research subjects with schizophrenia and four hundred and fifty ancestrally matched supernormal controls. We genotyped the SNP markers previously found to be significantly associated with schizophrenia in the original study and also other markers found to be positive in subsequent studies.Results: We could find no evidence of allelic, genotypic or haplotypic association with schizophrenia in our UK sample.Conclusion: The results suggest that the DTNBP1 gene contribution to schizophrenia must be rare or absent in our sample. The discrepant allelic association results in previous studies of association between DTNBP1 and schizophrenia could be due population admixture. However, even positive studies of European populations do not show any consistent DTNBP1 alleles or haplotypes associated with schizophrenia. Further research is needed to resolve these issues. The possible confounding of linkage with association in family samples already showing linkage at 6p22.3 might be revealed by testing genes closely linked to DTNBP1 for allelic association and by restricting family based tests of association to only one case per family

Effectiveness of interventions to address obesity and health risk behaviours among people with severe mental illness in low- and middle-income countries (LMICs): a systematic review and meta analysis

Abstract Introduction People with severe mental illness (SMI) are more likely to have obesity and engage in health risk behaviours than the general population. The aims of this study are (1) evaluate the effectiveness of interventions that focus on body weight, smoking cessation, improving sleeping patterns, and alcohol and illicit substance abuse; (2) Compare the number of interventions addressing body weight and health risk behaviours in low- and middle-income countries (LMICs) v. those reported in published systematic reviews focusing on high-income countries (HICs). Methods Intervention studies published up to December 2020 were identified through a structured search in the following database; OVID MEDLINE (1946–December 2020), EMBASE (1974–December 2020), CINAHL (1975–2020), APA PsychoINFO (1806–2020). Two authors independently selected studies, extracted study characteristics and data and assessed the risk of bias. and risk of bias was assessed using the Cochrane risk of bias tool V2. We conducted a narrative synthesis and, in the studies evaluating the effectiveness of interventions to address body weight, we conducted random-effects meta-analysis of mean differences in weight gain. We did a systematic search of systematic reviews looking at cardiometabolic and health risk behaviours in people with SMI. We compared the number of available studies of LMICs with those of HICs. Results We assessed 15 657 records, of which 9 met the study inclusion criteria. Six focused on healthy weight management, one on sleeping patterns and two tested a physical activity intervention to improve quality of life. Interventions to reduce weight in people with SMI are effective, with a pooled mean difference of −4.2 kg (95% CI −6.25 to −2.18, 9 studies, 459 participants, I2 = 37.8%). The quality and sample size of the studies was not optimal, most were small studies, with inadequate power to evaluate the primary outcome. Only two were assessed as high quality (i.e. scored ‘low’ in the overall risk of bias assessment). We found 5 reviews assessing the effectiveness of interventions to reduce weight, perform physical activity and address smoking in people with SMI. From the five systematic reviews, we identified 84 unique studies, of which only 6 were performed in LMICs. Conclusion Pharmacological and activity-based interventions are effective to maintain and reduce body weight in people with SMI. There was a very limited number of interventions addressing sleep and physical activity and no interventions addressing smoking, alcohol or harmful drug use. There is a need to test the feasibility and cost-effectiveness of context-appropriate interventions to address health risk behaviours that might help reduce the mortality gap in people with SMI in LMICs

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO