Session E8: Not Just for Adults! Evaluating the Efficacy of Multiple Fish Passage Designs at Low-Head Barriers for the Upstream Movement of Juvenile and Adult Trout Salmo Trutta

Abstract: Connectivity in salmonid-streams is vital for juvenile as well as adult trout, yet most upstream passage studies consider only larger adults. Upstream passage of juvenile and adult Salmo trutta at individual and cumulative low-head (\u3c 3 m) barriers on two tributaries of the River Ribble (NW England) was investigated using PIT telemetry during summer/autumn 2013 and 2014. The efficiency of a low-cost baffle fish pass (Servais, 2006) was evaluated for the first time, along with two more traditional poolweir passes, an embedded rock ramp and two culverts. We used a combination of naturally migrating S. trutta and novel innature displacement experiments, where resident fish were displaced from above to below structures and their homing instinct utilised to instigate their ascent of the structure. Each structure was evaluated using several metrics measuring the passage efficiency (PE) and delays incurred before successful passage (time and number of attempts). We show that instigating ascent of a structure through downstream displacement can be successful with up to 91% of displaced fish attempting to pass. Passage efficiencies of up to 82% for the low-cost baffle design were observed, which was comparable to the pool-weir design (up to 84%) and better than the embedded rock ramp (71%). The two culverts had contrasting impacts, with the shorter control (within predicted swim performance) Culvert 1 representing a manmade structure which had little impact on passage efficiency (96% - 100%) and delay metrics compared to Culvert 2 (PE = 41%). Logistic regression demonstrated a strong body-length effect on passage success at passes, with shorter individuals (\u3c 91–132 mm depending on the structure) having a less than 50% probability of successful passage. The study demonstrates the efficacy of three fish passage designs at low-head barriers and the variation in delay that can be incurred even between similarly designed passes

Psychosis and the level of mood incongruence in Bipolar Disorder are related to genetic liability for Schizophrenia

Abstract Importance Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes/mechanisms. Objectives To investigate the relationship between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRS) and psychotic presentations of BD, using clinical descriptions which consider both occurrence and level of mood-incongruent psychotic features. Design Case-control design: using multinomial logistic regression, to estimate differential associations of PRS across categories of cases and controls. Settings & Participants 4399 BDcases, mean [sd] age-at-interview 46[12] years, of which 2966 were woman (67%) from the BD Research Network (BDRN) were included in the final analyses, with data for 4976 schizophrenia cases and 9012 controls from the Type-1 diabetes genetics consortium and Generation Scotland included for comparison. Exposure Standardised PRS, calculated using alleles with an association p-value threshold < 0.05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, adjusted for the first 10 population principal components and genotyping-platform. Main outcome measure Multinomial logit models estimated PRS associations with BD stratified by (1) Research Diagnostic Criteria (RDC) BD subtypes (2) Lifetime occurrence of psychosis.(3) Lifetime mood-incongruent psychotic features and (4) ordinal logistic regression examined PRS associations across levels of mood-incongruence. Ratings were derived from the Schedule for Clinical Assessment in Neuropsychiatry interview (SCAN) and the Bipolar Affective Disorder Dimension Scale (BADDS). Results Across clinical phenotypes, there was an exposure-response gradient with the strongest PRS association for schizophrenia (RR=1.94, (95% C.I. 1.86, 2.01)), then schizoaffective BD (RR=1.37, (95% C.I. 1.22, 1.54)), BD I (RR= 1.30, (95% C.I. 1.24, 1.36)) and BD II (RR=1.04, (95% C.I. 0.97, 1.11)). Within BD cases, there was an effect gradient, indexed by the nature of psychosis, with prominent mood-incongruent psychotic features having the strongest association (RR=1.46, (95% C.I. 1.36, 1.57)), followed by mood-congruent psychosis (RR= 1.24, (95% C.I. 1.17, 1.33)) and lastly, BD cases with no history of psychosis (RR=1.09, (95% C.I. 1.04, 1.15)). Conclusion We show for the first time a polygenic-risk gradient, across schizophrenia and bipolar disorder, indexed by the occurrence and level of mood-incongruent psychotic symptoms

Investigation of relationships between bipolar disorder phenotypes and genome-wide significant loci from PGC2 schizophrenia

Background Schizophrenia (SZ) and Bipolar disorder (BD) show evidence for partial overlap in phenotypic and genetic influences based on family, twins, adoption and Psychiatric Genetic Consortium (PGC) studies. They have lifetime prevalence of about 1% and 2.4%, and heritability estimates of 60-80% and 40-70%, respectively. In the last decade BD has been investigated using dimensional structuring of psychoses based on symptomatic-functional checklists that provides reliable approach to phenotypic assessment. Recent research suggests moving towards developing Phenotype-based Genetic Association Studies. In this approach, patients will only be put into groups consisting of others with symptoms similar to their own. Canonical Correlation Analysis (CCA) is statistical technique designed to identify relationships (usually hidden) between two sets of variables. We use CCA to combine genotypic and phenotypic variables and measure correlation between those sets. This analysis estimates canonical correlation between psychotic symptoms measured using validated item check list (OPCRIT), and genome-wide significant (GWS) loci from PGC2 schizophrenia. Methods For our analysis we used phenotype and genetic data for 5,507 BD cases. Imputation of genetic data was performed with 1000Genomes (Phase 3, 2014) then quality control was applied (INFO>0.8, HWE>1e-6, MAF>0.01). Additional quality control was performed on phenotypic symptom coverage. CCA was employed as implemented in R, using package “CCA” with GWS loci from PGC2 SZ and OPCRIT items. SNPs were standardised and adjusted for 10 population covariates calculated from imputed data using principal component approach prior to CCA. Results Canonical correlation analysis was run on 4422 cases on 89 available GWS PGC2 SZ SNPs or their proxies (with r2>0.6). 60 phenotypic variables were taken from OPCRIT measurements including mood disturbance, biological indices, atypical depression, substance use, psychosis and social functioning. We found no significant canonical correlations indicating absence of hidden sub-clusters at individual symptom level of BD associated with SZ GWS loci. Discussion Our analysis was focused to find correlation from bipolar phenotype by using OPCRIT questionnaire and GWS SZ loci from PGC2. We have shown that there were no significant canonical correlation coefficients suggesting that there is no direct association between SZ associated genetic loci and BP at individual symptom level. CCA is canonical correlation analysis is one of potential of data-driven approaches to identify hidden genotype-phenotype relationships. It provides opportunities to generate and test different hypotheses and understand more about complex architecture of psychiatric disorders. In the next stage we plan to extend our analysis to more fine grained systematic descriptors of BD and test for correlation with genetic profiles from a number of co-morbid disorders, as well as the full range of phenotypic and genetic data that are available

Genome-wide association study of borderline personality disorder reveals genetic overlap with the bipolar disorder, schizophrenia and major depression

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of Bipolar Disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was: (i) to detect genes and gene-sets involved in BOR; and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, Major Depression (MDD) and Schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests,and gene-set-analyses were performed in 998 BOR patients and 1,545 controls. LD score regression was used to detect genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Genebased analysis yielded two significant genes: DPYD (p=4.42x10-7) and PKP4 (p=8.67x10-7); and gene-set-analysis yielded a significant finding for exocytosis (GO:0006887, pFDR=0.019). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [p=2.99x10-3]), SCZ (rg=0.34 [p=4.37x10-5]), and MDD (rg=0.57 [p=1.04x10-3]). Our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies

Heavy Quark Spectroscopy and Matrix Elements: A Lattice Study using the Static Approximation

We present results of a lattice analysis of the $B$ parameter, $B_B$, the decay constant $f_B$, and several mass splittings using the static approximation. Results were obtained for 60 quenched gauge configurations computed at $\beta=6.2$ on a lattice size of $24^3\times48$. Light quark propagators were calculated using the $O(a)$-improved Sheikholeslami-Wohlert action. We find \Bbstat(m_b) = 0.69\er{3}{4} {\rm(stat)}\er{2}{1} {\rm(syst)}, corresponding to \Bbstat = 1.02\er{5}{6}\er{3}{2}, and \fbstat = 266\err{18}{20}\err{28}{27} \mev, f_{B_s}^2 B_{B_s}/f_B^2 B_B = 1.34\er{9}{8}\er{5}{3}, where a variational fitting technique was used to extract \fbstat. For the mass splittings we obtain M_{B_s}-M_{B_d} = 87\err{15}{12}\err{6}{12} \mev, M_{\Lambda_b}-M_{B_d} = 420\errr{100}{90}\err{30}{30} \mev and M_{B^*}^2-M_B^2 = 0.281\err{15}{16}\err{40}{37} \gev^2. We compare different smearing techniques intended to improve the signal/noise ratio. From a detailed assessment of systematic effects we conclude that the main systematic uncertainties are associated with the renormalisation constants relating a lattice matrix element to its continuum counterpart. The dependence of our findings on lattice artefacts is to be investigated in the future.Comment: 40 pages, uuencoded compressed tar file, containing one LaTeX file and 14 postscript files (to be included with epsf). Minor change in the value of the B parameter. Contains corrected value for the B*-B mass splitting. Version accepted for publication in Phys. Rev.

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P &lt; 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P &lt; 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Mastering the Hard Stuff: The History of College Concrete-Canoe Races and the Growth of Engineering Competition Culture

This article details the history of college engineering competitions, originating with student concrete-canoe racing in the 1970s, through today’s multi-million-dollar international multiplicity of challenges. Despite initial differences between engineering educators and industry supporters over the ultimate purpose of undergraduate competitions, these events thrived because they evolved to suit many needs of students, professors, schools, corporations, professional associations, and the engineering profession itself. The twenty-first-century proliferation of university-level competitions in turn encouraged a trickling-down of technical contests to elementary-age children and high schools, fostering the institutionalization of what might be called a competition culture in engineering

The Farsi version of the Hypomania Check-List 32 (HCL-32): Applicability and indication of a four-factorial solution

Background: Data from the Iranian population for hypomania core symptom clusters are lacking. The aim of the present study was therefore to apply the Farsi version of the Hypomania-Check-List 32 (HCL-32), and to explore its factorial structure.Methods: A total of 163 Iranian out-patients took part in the study; 61 suffered from Major Depressive Disorder (MDD), and 102 suffered from Bipolar Disorders (BP). Participants completed the Mood Disorder Questionnaire (MDQ) and the Hypomania Checklist (HCL-32). Exploratory factor analyses were used to examine the properties of the HCL-32. A ROC-curve analysis was performed to calculate sensitivity and specificity.Results: The HCL-32 differentiated between patients with MDD and with BP. Psychometric properties were satisfactory: sensitivity: 73; specificity: 91. MDQ and HCL-32 did correlate highly. No differences were found between patients suffering from BP I and BP II.Discussion: Instead of the two-factorial structure of the HCL-32 reported previously, the present pattern of factorial results suggest a distinction between four factors: two broadly positive dimensions of hypomania ("physically and mentally active"; "positive social interactions") and two rather negative dimensions ("risky behavior and substance use"; "difficulties in social interaction and impatience").Conclusion: The Farsi version of the HCL-32 proved to be applicable, and therefore easy to introduce within a clinical context. The pattern of results suggests a four factorial solution. © 2011 Haghighi et al; licensee BioMed Central Ltd

Genome wide significant locus for Research Diagnostic Criteria Schizoaffective Disorder Bipolar Type.

Studies have suggested that Research Diagnostic Criteria for Schizoaffective disorder Bipolar type (RDC-SABP) might identify a more genetically homogenous subgroup of bipolar disorder. Aiming to identify loci associated with RDC-SABP we have performed a replication study using independent RDC-SABP cases (n=144) and controls (n=6,559), focusing on the 10 loci that P-value <10-5 for RDC-SABP in the Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder sample using ‘researcher-specific SNPs’ represented on the custom array, the ImmunoChip. Combining the WTCCC and replication datasets by meta-analysis (combined RDC-SABP, n=423, Controls, n=9,494) we observed genome wide significance association at one SNP, rs2352974, located within the intron of the gene TRAIP on chromosome 3p21.31. This locus did not reach genome wide significance in bipolar disorder or schizophrenia large psychiatric genomic consortium datasets, suggesting that it may be a relatively specific genetic risk for the bipolar subtype of schizoaffective disorder