In search of disorders: internalizing symptom networks in a large clinical sample.

Background The co‐occurrence of internalizing disorders is a common form of psychiatric comorbidity, raising questions about the boundaries between these diagnostic categories. We employ network psychometrics in order to: (a) determine whether internalizing symptoms cluster in a manner reflecting DSM diagnostic criteria, (b) gauge how distinct these diagnostic clusters are and (c) examine whether this network structure changes from childhood to early and then late adolescence. Method Symptom‐level data were obtained for service users in publicly funded mental health services in England between 2011 and 2015 (N = 37,162). A symptom network (i.e. Gaussian graphical model) was estimated, and a community detection algorithm was used to explore the clustering of symptoms. Results The estimated network was densely connected and characterized by a multitude of weak associations between symptoms. Six communities of symptoms were identified; however, they were weakly demarcated. Two of these communities corresponded to social phobia and panic disorder, and four did not clearly correspond with DSM diagnostic categories. The network structure was largely consistent by sex and across three age groups (8–11, 12–14 and 15–18 years). Symptom connectivity in the two older age groups was significantly greater compared to the youngest group and there were differences in centrality across the age groups, highlighting the age‐specific relevance of certain symptoms. Conclusions These findings clearly demonstrate the interconnected nature of internalizing symptoms, challenging the view that such pathology takes the form of distinct disorders

Exploring the psychology of suicidal ideation: A theory driven network analysis

Two leading theories within the field of suicide prevention are the interpersonal psychological theory of suicidal behaviour (IPT) and the integrated motivational-volitional (IMV) model. The IPT posits that suicidal thoughts emerge from high levels of perceived burdensomeness and thwarted belongingness. The IMV model is a multivariate framework that conceptualizes defeat and entrapment as key drivers of suicide ideation. We applied network analysis to cross-sectional data collected as part of the Scottish Wellbeing Study, in which a nationally representative sample of 3508 young adults (18–34 years) completed a battery of psychological measures. Network analysis can help us to understand how the different theoretical components interact and how they relate to suicide ideation. Within a network that included only the core factors from both models, internal entrapment and perceived burdensomeness were most strongly related to suicide ideation. The core constructs defeat, external entrapment and thwarted belonginess were mainly related to other factors than suicide ideation. Within the network of all available psychological factors, 12 of the 20 factors were uniquely related to suicide ideation, with perceived burdensomeness, internal entrapment, depressive symptoms and history of suicide ideation explaining the most variance. None of the factors was isolated, and we identified four larger clusters: mental wellbeing, interpersonal needs, personality, and suicide-related factors. Overall, the results suggest that relationships between suicide ideation and psychological risk factors are complex, with some factors contributing direct risk, and others having indirect impact

Analysis of chlorpheniramine in human urine samples using dispersive liquid-liquid microextraction combined with high-performance liquid chromatography

A simple and environmentally friendly microextraction technique was used for determination of chlorpheniramine (CPM), an antihistamine drug, in human urine samples using dispersive liquid-liquid microextraction (DLLME) followed by high performance liquid chromatography with diode array detection (HPLC-DAD). In this extraction technique, an appropriate mixture of acetonitrile (disperser solvent) and carbon tetrachloride (extraction solvent) was rapidly injected into the urine sample containing the target analyte. Tiny droplets of extractant were formed and dispersed into the sample solution and then sedimented at the bottom of the conical test tube by centrifugation. Under optimal conditions, the calibration curve was linear in the range of 0.055-5.5 µg mL-1, with a detection limit of 16.5 ng mL-1. This proposed method was successfully applied to the analysis of real urine samples. Low consumption of toxic organic solvents, simplicity of operation, low cost and acceptable figures of merit are the main advantages of the proposed technique

Effects of vitamin D3, omega-3s, and a simple strength training exercise program on bone health: the DO-HEALTH randomized controlled trial

Evidence on the effects of Vitamin D, omega-3s, and exercise on areal bone mineral density (aBMD) in healthy older adults is limited. We examined whether vitamin D3, omega-3s, or a simple home-based exercise program (SHEP), alone or in combination, over 3 years, improve lumbar spine (LS), femoral neck (FN), or total hip (TH) aBMD assessed by DXA. Areal BMD was a secondary outcome in DO-HEALTH, a 3-year, multicenter, double-blind, randomized 2 × 2 × 2 factorial design trial in generally healthy older adults age ≥ 70 years. The study interventions were vitamin D3 (2000IU/d), omega-3s (1 g/d), and SHEP (3 × 30 min/wk), applied alone or in combination in eight treatment arms. Mixed effects models were used, adjusting for age, sex, BMI, prior fall, study site, and baseline level of the outcome. Main effects were assessed in the absence of an interaction between the interventions. Subgroup analyses by age, sex, physical activity level, dietary calcium intake, serum 25(OH)D levels, and fracture history were conducted. DXA scans were available for 1493 participants (mean age 75 years; 80.4% were physically active, 44% had 25(OH)D levels <20 ng/mL). At the LS and FN sites, none of the treatments showed a benefit. At the TH, vitamin D versus no vitamin D treatment showed a significant benefit across 3 years (difference in adjusted means [AM]: 0.0035 [95% CI, 0.0011, 0.0059] g/cm). Furthermore, there was a benefit for vitamin D versus no vitamin D treatment on LS aBMD in the male subgroup (interaction P = .003; ∆AM: 0.0070 [95% CI, 0.0007, 0.0132] g/cm). Omega-3s and SHEP had no benefit on aBMD in healthy, active, and largely vitamin D replete older adults. Our study suggests a small benefit of 2000 IU vitamin D daily on TH aBMD overall and LS aBMD among men; however, effect sizes were very modest and the clinical impact of these findings is unclear

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype