Plasma GABA in children and adolescents with mood, behavior, and comorbid mood and behavior disorders: a preliminary study

Plasma GABA concentrations (pGABA) were measured in 115 inpatients (aged 7-17) with child psychiatric disorders. Group mean pGABAs were compared for 38 patients with mood disorders only (MOOD), 29 with behavior disorders only (BEH), 48 with comorbid mood and behavior disorders (MOOD + BEH), and 14 normal controls (CON, aged 14-17). The BEH group was characterized by (a) high mean pGABAs (157 vs. 133 pmol/ml), (b) lower mean pGABAs in BEH subjects who had been receiving pharmacotherapy with SSRIs or other medications (p < 0.026), and (c) decreased pGABA with increasing age (p = 0.019). These features were not found in controls or in groups of patients with mood disorders (MOOD or MOOD + BEH). Elevated mean pGABA in the BEH group appeared specifically in patients with comorbid CD and ADHD, not in patients with ADHD or CD alone (p = 0.004). No patient in BEH (or CON) had pGABA below 100 pmol/ml, but low pGABAs were found in 15% of MOOD patients (who had no behavior disorder) and in 16% of MOOD + BEH patients. Pharmacotherapy did not change pGABAs in the MOOD or the MOOD + BEH groups. No pGABA differences were found among the anxiety disorders, either alone or with mood or behavior comorbidity. The finding that plasma GABA levels are elevated in nonmedicated behavior disorders that present in the absence of mood disorders, and appear to lower following medication treatments, merits increased attention to the pharmacological study of nonaffective behavior disorders.     

Science in the Cloud: Allocation and Execution of Data-Intensive Scientific Workflows

An important challenge for the adoption of cloud computing in the scientific community remains the efficient allocation and execution of data-intensive scientific workflows to reduce execution time and the size of transferred data. The transferred data overhead is becoming significant with emerging scientific workflows that have input/output files and intermediate data products ranging in the hundreds of gigabytes. The allocation of scientific workflows on public clouds can be described through a variety of perspectives and parameters, and has been proved to be NP-complete. This paper proposes an evolutionary approach for task allocation on public clouds considering data transfer and execution time. In our framework, a solution is represented using an allocation chromosome that encodes the allocation of tasks to nodes, and an ordering chromosome that defines the execution order according to the scientific workflow representation. We propose a multi-objective optimization that relies on a cloud cost model and employs tailored evolution operators. Starting from a population of possible solutions, we employ crossover and mutation operators on both chromosomes aiming at optimizing the data transferred between nodes as well as the total workflow runtime. The crossover operators combine parts of solutions to reduce data overhead, whereas the mutation operators swamp between parts of the same chromosome according to pre-defined rules. Our experimental study compares between the proposed approach and current state-of-the art approaches using synthetic and real-life workflows. Our algorithm performs similarly to existing heuristics for small workflows and shows up to 80 % improvements for larger synthetic workflows. To further validate our approach we compare between the allocation and scheduling obtained by our approach with that obtained by popular scientific workflow managers, when real workflows with hundreds of tasks are executed on a public cloud. The results show a 10 % improvement in runtime over existing schedulers, caused by a 80 % reduction in transferred data and optimized allocation and ordering of tasks. This improved data locality has greater impact as it can be employed to improve and study data provenance and facilitate data persistence for scientific workflows.     

Effects of Al:Si and (Al + Na):Si ratios on the properties of the international simple glass,part II: Structure

High-alumina containing high-level waste (HLW) will be vitrified at the Waste Treatment Plant at the Hanford Site. The resulting glasses, high in alumina, will have distinct composition-structure-property (C-S-P) relationships compared to previously studied HLW glasses. These C-S-P relationships determine the processability and product durability of glasses and therefore must be understood. The main purpose of this study is to understand the detailed structural changes caused by Al:Si and (Al + Na):Si substitutions in a simplified nuclear waste model glass (ISG, international simple glass) by combining experimental structural characterizations and molecular dynamics (MD) simulations. The structures of these two series of glasses were characterized by neutron total scattering and ²⁷Al, ²³Na, ²⁹Si, and ¹¹B solid-state nuclear magnetic resonance (NMR) spectroscopy. Additionally, MD simulations were used to generate atomistic structural models of the borosilicate glasses and simulation results were validated by the experimental structural data. Short-range (eg, bond distance, coordination number, etc) and medium-range (eg, oxygen speciation, network connectivity, polyhedral linkages) structural features of the borosilicate glasses were systematically investigated as a function of the degree of substitution. The results show that bond distance and coordination number of the cation-oxygen pairs are relatively insensitive to Al:Si and (Al + Na):Si substitutions with the exception of the B-O pair. Additionally, the Al:Si substitution results in an increase in tri-bridging oxygen species, whereas (Al + Na):Si substitution creates nonbridging oxygen species. Charge compensator preferences were found for Si-[NBO] (Na⁺), ^[3]B-[NBO] (Na⁺), ^[4]B (mostly Ca²⁺), ^[4]Al (nearly equally split Na⁺ and Ca²⁺), and ^[6]Zr (mostly Ca²⁺). The network former-BO-network former linkages preferences were also tabulated; Si-O-Al and Al-O-Al were preferred at the expense of lower Si-O-^[3]B and ^[3]B-O-^[3]B linkages. These results provide insights on the structural origins of property changes such as glass-transition temperature caused by the substitutions, providing a basis for future improvements of theoretical and computer simulation models.     

Comparison of three-dimensional surface scanning techniques for capturing the external ear

Congenital facial anomalies, such as microtia (malformation of the external ear), lead to significant psychosocial effects starting from early childhood. Three-dimensional (3D) scanning and advanced manufacturing are being investigated as a cheaper and more personalised method of fabricating reconstructive treatments for patients compared to traditional approaches. To date, most case studies have used expensive 3D scanners, yet, there is potential for low-cost devices to provide comparable results. This study aimed to investigate these different approaches. Both ears of 16 adult participants were scanned with three devices: Artec Spider (Artec Group), Intel^® RealSense? (Intel), and the Apple iPhone^® 7 (Apple Inc.) combined with photogrammetry using 90, 60 and 30 photographs. The scanning time, processing time, accuracy, completeness, resolution and repeatability of each technique were assessed using the Artec Spider as a reference scanner. Our results show that the iPhone had the longest processing time however, this decreased nine-fold when reducing the number of photos from 90 to 30. There was no significant difference in the accuracy, completeness or repeatability of the iPhone scans with 90 photographs (1.4?±?0.6?mm, 79.9%, 1.0?±?0.1?mm), 60 photographs (1.2?±?0.2, 79.3%, 0.9?±?0.2?mm) or 30 photographs (1.2?±?0.3?mm, 74.3%, 1.0?±?0.2?mm). The Intel RealSesne performed significantly worse in each parameter (1.8?±?03?mm; 46.6%, 1.4?±?0.5). Additionally, the RealSense had significantly lower resolution with not enough detail captured for the application. These results demonstrate that the ear can be accurately 3D scanned using iPhone photographs. We would recommend capturing between 30 and 60 photographs of the ear to create a scan that is accurate but without the downfall of long processing time. Using these methods we aim to provide a more comfortable setting for the patient and a lower-cost and more personalised ear prosthesis.     

Identifying Candidate Protein Markers of Acute Kidney Injury in Acute Decompensated Heart Failure

One-quarter of patients with acute decompensated heart failure (ADHF) experience acute kidney injury (AKI)—an abrupt reduction or loss of kidney function associated with increased long-term mortality. There is a critical need to identify early and real-time markers of AKI in ADHF; however, to date, no protein biomarkers have exhibited sufficient diagnostic or prognostic performance for widespread clinical uptake. We aimed to identify novel protein biomarkers of AKI associated with ADHF by quantifying changes in protein abundance in the kidneys that occur during ADHF development and recovery in an ovine model. Relative quantitative protein profiling was performed using sequential window acquisition of all theoretical fragment ion spectra–mass spectrometry (SWATH–MS) in kidney cortices from control sheep (n = 5), sheep with established rapid-pacing-induced ADHF (n = 8), and sheep after ~4 weeks recovery from ADHF (n = 7). Of the 790 proteins quantified, we identified 17 candidate kidney injury markers in ADHF, 1 potential kidney marker of ADHF recovery, and 2 potential markers of long-term renal impairment (differential abundance between groups of 1.2–2.6-fold, adjusted p < 0.05). Among these 20 candidate protein markers of kidney injury were 6 candidates supported by existing evidence and 14 novel candidates not previously implicated in AKI. Proteins of differential abundance were enriched in pro-inflammatory signalling pathways: glycoprotein VI (activated during ADHF development; adjusted p < 0.01) and acute phase response (repressed during recovery from ADHF; adjusted p < 0.01). New biomarkers for the early detection of AKI in ADHF may help us to evaluate effective treatment strategies to prevent mortality and improve outcomes for patients.     

Measures of larval lake whitefish length and abundance as early predictors of year-class strength in Lake Michigan

Many lake whitefish stocks in Lake Michigan have experienced substantial declines in growth and condition since the 1990s. Reduced growth and condition could result in reduced quality or quantity of eggs produced by spawning females, which in turn could negatively impact recruitment. We evaluated the potential for reduced recruitment by measuring early life stage density and length, and we discuss the utility of these measures as early indicators of lake whitefish year-class strength. Overall, mean larval density (number per 1000 m³ ± SE) in Lake Michigan was greater in 2006 (373.7 ± 28.3) than in 2005 (16.6 ± 24.8); whereas, mean length (mm ± SE) of larval lake whitefish was smaller in 2006 (12.87 ± 0.07) than in 2005 (14.38 ± 0.13). The ratio of zooplankton to fish density did not show an expected relationship with larval fish density or length. Rather, variation in larval density was best explained by a multiple-regression model that included larval length, spring wind intensity, and adult stock density as predictor variables. Our results suggest that the density of larval lake whitefish is not directly regulated by temperature or zooplankton density at the time of emergence, but that a potential for density-dependent regulation exists when larval emergence rates are high. We conclude that the observed declines in growth and condition of adult lake whitefish are not resulting in substantial reductions in recruitment.     

An Intrinsically Fluorescent Recognition Ligand Scaffold Based on Chaperonin Protein and Semiconductor Quantum‐Dot Conjugates

Genetic engineering of a novel protein–nanoparticle hybrid system with great potential for biosensing applications and for patterning of various types of nanoparticles is described. The hybrid system is based on a genetically modified chaperonin protein from the hyperthermophilic archaeon Sulfolobus shibatae. This chaperonin is an 18‐subunit double ring, which self‐assembles in the presence of Mg ions and ATP. Described here is a mutant chaperonin (His‐β‐loopless, HBLL) with increased access to the central cavity and His‐tags on each subunit extending into the central cavity. This mutant binds water‐soluble semiconductor quantum dots, creating a protein‐encapsulated fluorescent nanoparticle. The new bioconjugate has high affinity, in the order of strong antibody–antigen interactions, a one‐to‐one protein–nanoparticle stoichiometry, and high stability. By adding selective binding sites to the solvent‐exposed regions of the chaperonin, this protein–nanoparticle bioconjugate becomes a sensor for specific targets.     

Preface

User Modeling and User-Adapted Interaction -