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Despite increasing knowledge on the neuroimaging patterns of eating disorder (ED) symptoms in non-clinical populations, studies using whole-brain machine learning to identify connectome-based neuromarkers of ED symptomatology are absent. This study examined the association of connectivity within and between large-scale functional networks with specific symptomatic behaviors and cognitions using connectome-based predictive modeling (CPM).
CPM with ten-fold cross-validation was carried out to probe functional networks that were predictive of ED-associated symptomatology, including body image concerns, binge eating, and compensatory behaviors, within the discovery sample of 660 participants. The predictive ability of the identified networks was validated using an independent sample of 821 participants.
The connectivity predictive of body image concerns was identified within and between networks implicated in cognitive control (frontoparietal and medial frontal), reward sensitivity (subcortical), and visual perception (visual). Crucially, the set of connections in the positive network related to body image concerns identified in one sample was generalized to predict body image concerns in an independent sample, suggesting the replicability of this effect.
These findings point to the feasibility of using the functional connectome to predict ED symptomatology in the general population and provide the first evidence that functional interplay among distributed networks predicts body shape/weight concerns.
ABSTRACT IMPACT: Screening the effect of thousands of non-coding genetic variants will help identify variants important in the etiology of diseases OBJECTIVES/GOALS: Massively parallel reporter assays (MPRAs) can experimentally evaluate the impact of genetic variants on gene expression. In this study, our objective was to systematically evaluate the functional activity of 3’-UTR SNPs associated with neurological disorders and use those results to help understand their contributions to disease etiology. METHODS/STUDY POPULATION: To choose variants to evaluate with the MPRA, we first gathered SNPs from the GWAS Catalog that were associated with any neurological disorder trait with p-value < 10-5. For each SNP, we identified the region that was in linkage disequilibrium (r2 > 0.8) and retrieved all the common 3’-UTR SNPs (allele-frequency > 0.05) within that region. We used an MPRA to measure the impact of these 3’-UTR variants in SH-SY5Y neuroblastoma cells and a microglial cell line. These results were then used to train a deep-learning model to predict the impact of variants and identify features that contribute to the predictions. RESULTS/ANTICIPATED RESULTS: Of the 13,515 3’-UTR SNPs tested, 400 and 657 significantly impacted gene expression in SH-SY5Y and microglia, respectively. Of the 84 SNPs significantly impacted in both cells, the direction of impact was the same in 81. The direction of eQTL in GTEx tissues agreed with the assay SNP effect in SH-SY5Y cells but not microglial cells. The deep-learning model predicted sequence activity level correlated with the experimental activity level (Spearman’s corr = 0.45). The deep-learning model identified several predictive motifs similar to motifs of RNA-binding proteins. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study demonstrates that MPRAs can be used to evaluate the effect of non-coding variants, and the results can be used to train a machine learning model and interpret its predictions. Together, these can help identify causal variants and further understand the etiology of diseases.
Food pantries play a critical role in combating food insecurity. The objective of the present work was to systematically review and synthesize scientific evidence regarding the effectiveness of food pantry-based interventions in the USA.
Keyword/reference search was conducted in PubMed, Web of Science, Scopus, Cochrane Library and CINAHL for peer-reviewed articles published until May 2018 that met the following criteria. Setting: food pantry and/or food bank in the USA; study design: randomized controlled trial (RCT) or pre–post study; outcomes: diet-related outcomes (e.g. nutrition knowledge, food choice, food security, diet quality); study subjects: food pantry/bank clients.
Fourteen articles evaluating twelve distinct interventions identified from the keyword/reference search met the eligibility criteria and were included in the review. Five were RCT and the remaining seven were pre–post studies. All studies found that food pantry-based interventions were effective in improving participants’ diet-related outcomes. In particular, the nutrition education interventions and the client-choice intervention enhanced participants’ nutrition knowledge, cooking skills, food security status and fresh produce intake. The food display intervention helped pantry clients select healthier food items. The diabetes management intervention reduced participants’ glycaemic level.
Food pantry-based interventions were found to be effective in improving participants’ diet-related outcomes. Interventions were modest in scale and usually short in follow-up duration. Future studies are warranted to address the challenges of conducting interventions in food pantries, such as shortage in personnel and resources, to ensure intervention sustainability and long-term effectiveness.
In order to investigate the benefits of compound waterways more fully, this study reveals vessel navigational mode and traffic conflicts in a compound waterway through a case analysis, following which a type of simplified prototype of a compound waterway is proposed and three key conflict areas are specified. Based on the three key sub-models of slot allocation for vessels in a waterway entrance, traffic flow conversion of a main and auxiliary waterway in a precautionary area, and traffic flow coordination of division and confluence in a Y crossing area, a vessel traffic scheduling optimisation model is presented, with the minimum waterway occupancy time and minimum total waiting time of vessels as the objective. Furthermore, a multi-objective genetic algorithm is proposed to solve the model and a simulation experiment is carried out. By analysing the optimised solution and comparing it with other scheduling schemes in common use, the results indicate that this method can effectively improve navigation safety and efficiency in a compound waterway.
Conventional visual ship tracking methods employ single and shallow features for the ship tracking task, which may fail when a ship presents a different appearance and shape in maritime surveillance videos. To overcome this difficulty, we propose to employ a multi-view learning algorithm to extract a highly coupled and robust ship descriptor from multiple distinct ship feature sets. First, we explore multiple distinct ship feature sets consisting of a Laplacian-of-Gaussian (LoG) descriptor, a Local Binary Patterns (LBP) descriptor, a Gabor filter, a Histogram of Oriented Gradients (HOG) descriptor and a Canny descriptor, which present geometry structure, texture and contour information, and more. Then, we propose a framework for integrating a multi-view learning algorithm and a sparse representation method to track ships efficiently and effectively. Finally, our framework is evaluated in four typical maritime surveillance scenarios. The experimental results show that the proposed framework outperforms the conventional and typical ship tracking methods.
This paper presents a model-based approach for the first time to identify the crack location for the hinge-based planar RRR compliant mechanism, a parallel micro-motion stage driven by piezoelectric (PZT) actuators. However, cracks more likely occur on a flexure hinge because it usually undergoes a periodic deformation in service, which eventually compromises mechanism's performance, positioning accuracy for instance. In this work, the pseudo-rigid-body method is used to develop kinematic and dynamic models of the RRR mechanism both in healthy and damaged conditions, where the crack is considered in terms of the rotational compliance of a flexible hinge. The crack location is determined by measuring PZT elongations, which represents the driving toque deviation because of the crack presence. Numerical simulation is conducted to verify the proposed approach, and the results show good match of the identified crack location with the assumed location. Finally, experiments on the RRR mechanism with a prefabricated crack is performed to further validate the proposed models; the experimental results yield a good consistence.
The duration of untreated psychosis (DUP) has been widely studied. However, for individuals with attenuated psychosis syndrome (APS), it is unclear whether the duration of untreated prodromal symptoms (DUPrS) also has a negative effect on the progression of psychosis. Our aim was to identify demographic and clinical factors contributing to the DUPrS in a large sample of individuals with APS, and to evaluate the association between DUPrS and the conversion to psychosis.
A sample of 391 individuals with APS, who were identified through a structured interview for prodromal syndromes, were included in this study, of whom a total of 334 patients had completed at least a 1-year clinical follow-up. A total of 57 individuals had converted to psychosis.
The average DUPrS was 4.8 months for the whole sample. Individuals with a longer DUPrS were likely to be men, non-local residents, with abnormal thought symptoms, a higher severity level of negative symptoms, the lower severity level of general symptoms, and lower level of general function before the onset of attenuated positive symptoms. A DUPrS of less than 2 months, or more than 6 months, lowered the risk for conversion to psychosis.
Our data suggested that the association between the DUPrS and outcome in individuals with APS were likely to be different, which is either long or short DUPrS was not related to future psychosis onset. Individuals with APS were more likely to have a group of features associated with a longer DUPrS.
Transition metal dichalcogenides such as WS2 show exciting promise in electronic and optoelectronic applications. Significant variations in the transport, Raman, and photoluminescence (PL) can be found in the literature, yet it is rarely addressed why this is. In this report, Raman and PL of monolayered WS2 produced via different methods are studied and distinct features that indicate the degree of crystallinity of the material are observed. While the intensity of the LA(M) Raman mode is found to be a useful indicator to assess the crystallinity, PL is drastically more sensitive to the quality of the material than Raman spectroscopy. We also show that even exfoliated crystals, which are usually regarded as the most pristine material, can contain large amounts of defects that would not be apparent without Raman and PL measurements. These findings can be applied to the understanding of other two-dimensional heterostructured systems.
The introduction of low-temperature fluid into boreholes drilled in ice sheets helps to remove drilling cuttings and to prevent borehole closure through visco-plastic deformation. Only special fluids, or mixtures of fluids, can satisfy the very strict criteria for deep drilling in cold ice. The effects of drilling fluid on the natural environment are analyzed from the following points of view: (1) occupational safety and health; (2) ozone depletion and global warming; (3) chemical pollution; and (4) biological pollution. Traditional low-temperature drilling fluids (kerosene-based fluids with density additives, ethanol and n-butyl acetate) cannot be qualified as intelligent choices from the safety, environmental and technological standpoints. This paper introduces a new type of low-temperature drilling fluid composed of synthetic ESTISOLTM esters, which are non-hazardous substances. ESTISOLTM 140 mixtures with ESTISOLTM 165 or ESTISOLTM F2887 have an acceptable density and viscosity at low temperature. To avoid the potential for biological contamination of the subglacial environment, the borehole drilling fluid should be treated carefully on the surface.
A new strategy using hyperbranched poly(amidoamine)s to functionalize CdTe quantum dots (QDs) has been described. Hyperbranched poly(amidoamine)s with amine terminals (HP-EDAMA1) were synthesized by one-pot polymerization via the coupled-monomer method and subsequently used to functionalize preformed CdTe QDs. Quite different from previous studies in which the photoluminescence of QDs was quenched by further functionalization with tailored ligands, the quantum yield of CdTe/HP-EDAMA1 nanocomposites was 2 times that of pure CdTe QDs without modification. With this versatile method, the photoluminescence quenching of QDs in the modification process by matrix materials can be effectively solved and new QDs/hyperbranched polymer nanocomposites with potential applications in biomedicine might be offered.
We report on the study of single devices of phase-change (Ge2Sb2Te5) memory cells in line cell type devices. Devices were investigated employing an x-ray nanobeam of only about 150 nm diameter, which could be fully contained within the spatial extent of the active area within a single device cell. XANES spectra showing the device in the amorphous and crystalline state have been successfully collected after switching the device in situ at the synchrotron. By monitoring the fluorescence response of the sample constituent materials at a constant photon energy (corresponding to the Ge K-edge absorption edge) as a function of x-ray beam position on the sample 2D maps have been produced.
We introduce a technique to permit x-ray absorption spectroscopy studies focusing on individual phase-change (Ge2Sb2Te5) memory cells in fully integrated PC-RAM structures. Devices were investigated employing an x-ray nanobeam of only about 300 nm diameter, which could be fully contained within the spatial extent of the active area within a single device cell and enabled us to investigate individual devices without interference from non-switching material surrounding the area of interest. By monitoring the fluorescence signals of tungsten and germanium at a photon energy corresponding to the Ge K-edge absorption edge white line position, we were successful in producing 2D area maps of the active cell region, which clearly show the imbedded tungsten heater element and the switched region of the phase change material. Additionally, position dependent changes in the phase change material could be traced by taking an array of XANES spectra at the Ge K-edge on and in the vicinity of individual devices.
The origin of sub-diffraction-limit apertures in Sb-based thin films is discussed. Electromagnetic energy can be channeled by these apertures thus allowing near-field focussing- the Super-RENS effect. The aperture formation within Sb, Sb2Te3, Sb2Te, SbTe and Ge2Sb2Te5 is investigated by time resolved optical pump-probe techniques and found to occur without melting. Density functional calculations have shown that these materials exhibit a thresholdlike change in their optical properties below their melting temperatures. The threshold is shown to be a consequence of thermally induced misalignment of p-orbital bonds. It is the non-linearity of this process that leads to the formation of the sub-diffraction-limit apertures.
Well-aligned ZnO nanowires were synthesized by simple physical vapor deposition using c-oriented ZnO thin films as substrate without catalysts or additives. The synthesized ZnO nanowires have two typical average diameters: 60 nm in majority and 120 nm in minority. They are about 4ím in length and well aligned along the normal direction of the substrate. Most of the synthesized ZnO nanowires are single crystalline in a hexagonal structure and grow along the  direction. The c-oriented ZnO thin films control the growth direction. Photoluminescence spectrum was measured showing a single strong ultraviolet emission (380 nm). Such result indicates that the ZnO nanowire arrays can be applied to excellent optoelectronic devices.
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