Childhood IQ and risk of bipolar disorder in adulthood: prospective birth cohort study

Background: Intellectual ability may be an endophenotypic marker for bipolar disorder. Aims: Within a large birth cohort, we aimed to assess whether childhood IQ (including both verbal IQ (VIQ) and performance IQ (PIQ) subscales) was predictive of lifetime features of bipolar disorder assessed in young adulthood. Method: We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a large UK birth cohort, to test for an association between measures of childhood IQ at age 8 years and lifetime manic features assessed at age 22–23 years using the Hypomania Checklist-32 (HCL-32; n=1881 individuals). An ordinary least squares linear regression model was used, with normal childhood IQ (range 90–109) as the referent group. We adjusted analyses for confounding factors, including gender, ethnicity, handedness, maternal social class at recruitment, maternal age, maternal history of depression and maternal education. Results: There was a positive association between IQ at age 8 years and lifetime manic features at age 22–23 years (Pearson's correlation coefficient 0.159 (95% CI 0.120–0.198), P>0.001). Individuals in the lowest decile of manic features had a mean full-scale IQ (FSIQ) which was almost 10 points lower than those in the highest decile of manic features: mean FSIQ 100.71 (95% CI 98.74–102.6) v. 110.14 (95% CI 107.79–112.50), P>0.001. The association between IQ and manic features was present for FSIQ, VIQ and for PIQ but was strongest for VIQ. Conclusions: A higher childhood IQ score, and high VIQ in particular, may represent a marker of risk for the later development of bipolar disorder. This finding has implications for understanding of how liability to bipolar disorder may have been selected through generations. It will also inform future genetic studies at the interface of intelligence, creativity and bipolar disorder and is relevant to the developmental trajectory of bipolar disorder. It may also improve approaches to earlier detection and treatment of bipolar disorder in adolescents and young adults

Occurrence of Paraleucilla magna Klautau et al., 2004 (porifera : Calcarea) in Malta

The calcareous sponge Paraleucilla magna, first recorded from the Mediterranean in 2001 (southern Tyrrhenian, southern Adriatic and northwest Ionian coasts of Italy), is recorded from Malta (Central Mediterranean) where it was found forming part of the fouling community on small, surface marker-buoys around a fish-farm in Marsaxlokk Bay.peer-reviewe

Diarrhetic shellfish toxin monitoring in commercial wild harvest bivalve shellfish in new south wales, Australia

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. An end-product market survey on biotoxins in commercial wild harvest shellfish (Plebidonax deltoides, Katelysia spp., Anadara granosa, Notocallista kingii) during three harvest seasons (2015–2017) from the coast of New South Wales, Australia found 99.38% of samples were within regulatory limits. Diarrhetic shellfish toxins (DSTs) were present in 34.27% of 321 samples but only in pipis (P. deltoides), with two samples above the regulatory limit. Comparison of these market survey data to samples (phytoplankton in water and biotoxins in shellfish tissue) collected during the same period at wild harvest beaches demonstrated that, while elevated concentrations of Dinophysis were detected, a lag in detecting bloom events on two occasions meant that wild harvest shellfish with DSTs above the regulatory limit entered the marketplace. Concurrently, data (phytoplankton and biotoxin) from Sydney rock oyster (Saccostrea glomerata) harvest areas in estuaries adjacent to wild harvest beaches impacted by DSTs frequently showed elevated Dinophysis concentrations, but DSTs were not detected in oyster samples. These results highlighted a need for distinct management strategies for different shellfish species, particularly during Dinophysis bloom events. DSTs above the regulatory limit in pipis sampled from the marketplace suggested there is merit in looking at options to strengthen the current wild harvest biotoxin management strategies

Theoretical optimal trajectories for reducing the environmental impact of commercial aircraft operations

This work describes initial results obtained from an ongoing research involving the development of optimization algorithms which are capable of performing multi-disciplinary aircraft trajectory optimization processes. A short description of both the rationale behind the initial selection of a suitable optimization technique and the status of the optimization algorithms is firstly presented. The optimization algorithms developed are subsequently utilized to analyze different case studies involving one or more flight phases present in actual aircraft flight profiles. Several optimization processes focusing on the minimization of total flight time, fuel burned and oxides of nitrogen (NOx) emissions are carried out and their results are presented and discussed. When compared with others obtained using commercially available optimizers, results of these optimization processes show atisfactory level of accuracy (average discrepancies ~2%). It is expected that these optimization algorithms can be utilized in future to efficiently compute realistic, optimal and ‘greener’ aircraft trajectories, thereby minimizing the environmental impact of commercial aircraft operations

Investigating whether adverse prenatal and perinatal events are associated with non-clinical psychotic symptoms at age 12 years in the ALSPAC birth cohort

Background. Non-clinical psychosis-like symptoms (PLIKS) occur in about 15% of the population. It is not clear whether adverse events during early development alter the risk of developing PLIKS. We aimed to examine whether maternal infection, diabetes or pre-eclampsia during pregnancy, gestational age, perinatal cardiopulmonary resuscitation or 5-min Apgar score were associated with development of psychotic symptoms during early adolescence. Method. A longitudinal study of 6356 12-year-old adolescents who completed a semi-structured interview for psychotic symptoms in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Prenatal and perinatal data were obtained from obstetric records and maternal questionnaires completed during pregnancy. Results. The presence of definite psychotic symptoms was associated with maternal infection during pregnancy [adjusted odds ratio (OR) 1.44, 95% confidence interval (CI) 1.11–1.86, p=0.006], maternal diabetes (adjusted OR 3.43, 95% CI 1.14–10.36, p=0.029), need for resuscitation (adjusted OR 1.50, 95% CI 0.97–2.31, p=0.065) and 5-min Apgar score (adjusted OR per unit decrease 1.30, 95% CI 1.12–1.50, p<0.001). None of these associations were mediated by childhood IQ score. Most associations persisted, but were less strong, when including suspected symptoms as part of the outcome. There was no association between PLIKS and gestational age or pre-eclampsia. Conclusions. Adverse events during early development may lead to an increased risk of developing PLIKS. Although the status of PLIKS in relation to clinical disorders such as schizophrenia is not clear, the similarity between these results and findings reported for schizophrenia indicates that future studies of PLIKS may help us to understand how psychotic experiences and clinical disorders develop throughout the life-course

Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods

We present a hierarchical Bayesian method for atmospheric trace gas inversions. This method is used to estimate emissions of trace gases as well as "hyper-parameters" that characterize the probability density functions (PDFs) of the a priori emissions and model-measurement covariances. By exploring the space of "uncertainties in uncertainties", we show that the hierarchical method results in a more complete estimation of emissions and their uncertainties than traditional Bayesian inversions, which rely heavily on expert judgment. We present an analysis that shows the effect of including hyper-parameters, which are themselves informed by the data, and show that this method can serve to reduce the effect of errors in assumptions made about the a priori emissions and model-measurement uncertainties. We then apply this method to the estimation of sulfur hexafluoride (SF6) emissions over 2012 for the regions surrounding four Advanced Global Atmospheric Gases Experiment (AGAGE) stations. We find that improper accounting of model representation uncertainties, in particular, can lead to the derivation of emissions and associated uncertainties that are unrealistic and show that those derived using the hierarchical method are likely to be more representative of the true uncertainties in the system. We demonstrate through this SF6 case study that this method is less sensitive to outliers in the data and to subjective assumptions about a priori emissions and model-measurement uncertainties than traditional methods