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Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Predicting transition from clinical high risk (CHR) to first episode psychosis has proven difficult. Assessment of oxidative stress biomarkers and the niacin skin flush response (NSFR) may improve prediction accuracy.
To predict transition to psychosis based on combined clinical and blood biomarker.
To analyse data from patients in placebo group of a 12-week trial of omega-3 fatty acid supplementation in CHR. Transition likelihood ratios (LRs) for baseline historical risks, clinical assessments (PANSS subscales and total, GAF), NSFR and blood markers (nervonic acid, superoxide dismutase, glutathione) were calculated. Variables with the highest positive and lowest negative LRs were included in an odds ratio form of Bayes’ rule transition prediction models. Model accuracy was calculated by area under the receiver operating curves (AUROC) of each model.
1-year transition to psychosis was 28% (n=40). Historical data showed no predictability (sensitivity 30%, specificity 100% (AUROC)=0.688, p=0.085). Clinical assessments alone produced a sensitivity of 30% at a specificity of 95% (AUROC=0.83, p<0.0001). The biomarker panel alone predicted transition with 40% sensitivity and 100% specificity (AUROC=0.73, p=0.03). Combining history and clinical assessment provided no improvement above clinical data alone (sensitivity = 30%, specificity = 100%, AUROC=0.85, p< 0.0001). The combination of history, clinical assessment and biomarkers identified transition with a sensitivity of 60% and specificity of 100% (AUROC=0.87, p< 0.0001).
Probabilistic models combining biomarkers and clinical data are able to target high-risk subgroups within CHR and may help to personalise treatment.
This work is part of the interlaboratory collaboration to study the stability of organic solar cells containing PCDTBT polymer as a donor material. The varieties of the OPV devices with different device architectures, electrode materials, encapsulation, and device dimensions were prepared by seven research laboratories. Sets of identical devices were aged according to four different protocols: shelf lifetime, laboratory weathering under simulated illumination at ambient temperature, laboratory weathering under simulated illumination, and elevated temperature (65 °C) and daylight outdoor weathering under sunlight. The results generated in this study allow us to outline several general conclusions related to PCDTBT-based bulk heterojunction (BHJ) solar cells. The results herein reported can be considered as practical guidance for the realization of stabilization approaches in BHJ solar cells containing PCDTBT.
A rapid low-pressure plasma sintering process of inkjet-printed silver nanoparticles is reported, yielding a conductivity of 11.4% of bulk silver within 1 min of plasma exposure and a final conductivity up to 40% of bulk silver for longer sintering times. The maximum processing temperature did not exceed 70 °C, which enabled the use of cost-effective polyethylene terephthalate (PET) foils. Fully functional radio-frequency identification (RFID) tags were prepared with inkjet-printed antennas, which showed similar results as screen-printed devices. The inkjet-printed antennas require significantly less materials, hence thinner layers, than the screen-printed references.
In this study the strain states in alternating multilayers of an extrinsic O2− ion conductor yttria stabilized zirconia (YSZ) and an insulator RE2O3 (RE = Er, Y) are investigated as a function of the layer thickness. Multilayers with narrow columnar crystallites and coherent phase boundaries were grown by pulsed laser deposition (PLD). A detailed strain analysis is performed by X-Ray Diffraction XRD, measuring distinct reflections in and perpendicular to the interface planes. Because of small columnar crystallites in the layers, the interfacial strain decays by shear with increasing distance from the interface. The extent of the strained interface regions in the YSZ layers is estimated from XRD data. By using a quantitative analytical model based on the pressure dependence of the free migration enthalpy for vacancies the results are compared to former published experimental data on O2− ion conductivity and diffusion.
A modified critical point model dielectric function for graphene is derived here and used to analyze spectroscopic ellipsometry data obtained over a wide spectral range from 3 to 9 eV. Critical point and exciton resonance energies are extracted and discussed. Our findings indicate that epitaxial graphene on SiC to exhibits equivalent exciton behavior to that of suspended graphene. We further apply our model dielectric function to evaluate dielectric function data for highly oriented pyrolytic graphite reported in the literature. Excellent agreement is found between the critical point model developed here and the literature data even for the low energy spectral range up to 1 eV.
We report on mid-infrared (600 – 4000 cm-1), refection-type optical-Hall effect measurements on epitaxial graphene grown on C-face silicon carbide and present Landau-level transition features detected at 1.5 K as a function of magnetic field up to 8 Tesla. The Landau-level transitions are detected in reflection configuration at oblique incidence for wavenumbers below, across and above the silicon carbide reststrahlen range. Small Landau-level transition features are enhanced across the silicon carbide reststrahlen range due to surface-guided wave coupling with the electronic Landau-level transitions in the graphene layer. We analyze the spectral and magnetic-field dependencies of the coupled resonances, and compare our findings with previously reported Landau-level transitions measured in transmission configuration [4,5,6]. Additional features resemble transitions previously assigned to bilayer inclusion , as well as graphite . We discuss a model description to account for the electromagnetic polarizability of the graphene layers, and which is sufficient for quantitative model calculation of the optical-Hall effect data.
In view of the complexity of thin-film solar cells, which are comprised of a multitude of layers, interfaces, surfaces, elements, impurities, etc., it is crucial to characterize and understand the chemical and electronic structure of these components. Because of the high complexity of the Cu2ZnSn(S,Se)4 compound semiconductor absorber material alone, this is particularly true for kesterite-based devices. Hence, this paper reviews our recent progress in the characterization of Cu2ZnSnS4 (CZTS) thin films. It is demonstrated that a combination of different soft x-ray spectroscopies is an extraordinarily powerful method for illuminating the chemical and electronic material characteristics from many different perspectives, ultimately resulting in a comprehensive picture of these properties. The focus of the article will be on secondary impurity phases, electronic structure, native oxidation, and the CZTS surface composition.
We demonstrate that the anisotropic optical response of metal (cobalt) slanted columnar thin films (STF) at THz frequencies strongly depends on the dielectric properties of the dielectric ambient surrounding the slanted columnar thin films. An effective medium dielectric function approach is used to describe the combined optical response of metal slanted columnar thin film and dielectric ambient. Our observations indicate that metal (cobalt) slanted columnar thin films can be used as sensors which will enable detection and characterization of minute amounts of dielectrics at THz frequencies, such as for flow-based detection of liquid chemical constituents.
Young people who are born very preterm exhibit a narrower arterial tree as compared with people born at term. We hypothesized that such arterial narrowing occurs as a direct result of premature birth. The aim of this study was to compare aortic and carotid artery growth in infants born preterm and at term. Observational and longitudinal cohort study of 50 infants (21 born very preterm, all appropriate for gestational age, 29 controls born at term) was conducted. Diameters of the upper abdominal aorta and common carotid artery were measured with ultrasonography at three months before term, at term and three months after term-equivalent age. At the first assessment, the aortic end-diastolic diameter (aEDD) was slightly larger in very preterm infants as compared with fetal dimensions. Fetal aortic EDD increased by 2.6 mm during the third trimester, whereas very preterm infants exhibited 0.9 mm increase in aEDD during the same developmental period (P < 0.001 for group difference). During the following 3-month period, aortic growth continued unchanged (+0.9 mm) in very preterm infants, whereas postnatal growth in term controls slowed down to +1.3 mm (P < 0.001 v. fetal aortic growth). At the final examination, aEDD was 22% and carotid artery EDD was 14% narrower in infants born preterm compared with controls, also after adjusting for current weight (P < 0.01). Aortic and carotid artery growth is impaired after very preterm birth, resulting in arterial narrowing. Arterial growth failure may be a generalized vascular phenomenon after preterm birth, with implications for cardiovascular morbidity in later life.
Constraint sets can become inconsistent in different contexts. For example, during a configuration session the set of customer requirements can become inconsistent with the configuration knowledge base. Another example is the engineering phase of a configuration knowledge base where the underlying constraints can become inconsistent with a set of test cases. In such situations we are in the need of techniques that support the identification of minimal sets of faulty constraints that have to be deleted in order to restore consistency. In this paper we introduce a divide and conquer-based diagnosis algorithm (FastDiag) that identifies minimal sets of faulty constraints in an overconstrained problem. This algorithm is specifically applicable in scenarios where the efficient identification of leading (preferred) diagnoses is crucial. We compare the performance of FastDiag with the conflict-directed calculation of hitting sets and present an in-depth performance analysis that shows the advantages of our approach.
Background: In contrast to a wealth of research on the treatment of Obsessive Compulsive Disorder (OCD), there is a relative paucity of work examining how OCD begins. Available data suggest that there is often a slow progression from the onset of symptoms to meeting criteria for a diagnosis of OCD. Aims: The current study sought to add to existing data documenting the slow-development of OCD, and to extend previous findings by examining potential moderators of this symptom phase and to examine patients’ explanations for the transition from symptoms to disorder. Method: One hundred and ninety-nine individuals with OCD reported on the start of their symptoms and the disorder via an internet-based survey. Results: Over two-thirds of respondents reported that the development of their OCD was gradual. Further, participants reported having experienced obsessions and/or compulsions for an average of 5 years before experiencing full-blown OCD. This extended symptom phase was observed in individuals with early- and late-onset OCD, with an even more protracted symptom phase in the later group. Female gender and onset of compulsions prior to obsessions were also associated with slower progression to full-blown OCD. Finally, explanations for the transition from symptoms to disorder suggest that changes in daily routines and general stress may be particularly important in this transition for individuals that develop clinical OCD at age 18 or later. Conclusions: Existence of a protracted symptom phase may present opportunities for elucidating risk factors for OCD disease progression and a window of opportunity for indicated prevention programs.
We present a technique to find threshold values that allows the user to separate signal from noise in fluorescence grey-level images. It can be classified as a purely comparative method based upon the amount of “Mutual Information” between two or more florescence images, and we apply it to stacks of such images produced using the newly-developed MELK technology. Our results are compared to results obtained by another research group using a quite different (completely independent and more technology-based) approach; and also to results obtained using Otsu's Thresholding Method, yet another completely distinct approach invented to separate foreground and background in a grey-level image, based on minimising “intra-class variance” [9,10]. The remarkably good agreement found suggests that our proposed comparative information based method not only accounts for the biological mechanisms governing cellular protein networks very well, but also (and probably much more importantly) shows that cells actually organise the spatial structure of their protein networks in a highly non-random fashion as might be expected – and thereby try to optimise their “mutual information content”, and thus most probably their efficiency.