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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).
Methods
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.
Results
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.
Conclusions
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.
Let Q be a quiver of type
$\tilde {A}_n$
. Let
$\alpha =\alpha _1+\alpha _2+\cdots +\alpha _s$
be the canonical decomposition. For the polynomials
$M_Q(\alpha ,q)$
that count the number of isoclasses of representations of Q over
${\mathbb F}_q$
with dimension vector
$\alpha $
, we obtain a precise relation between the degree of
$M_Q(\alpha ,q)$
and that of
$\prod _{i=1}^{s} M_Q(\alpha _i,q)$
for an arbitrary dimension vector
$\alpha $
.
Based on the measurements conducted over the landfast sea ice in Prydz Bay, East Antarctica during the sea-ice growth season in 2016, various parameterization schemes in the high-resolution thermodynamic snow/ice model HIGHTSI are evaluated. The parameterization scheme of turbulent fluxes produces the largest errors compared with the parameterization schemes for other surface heat fluxes. However, the sea-ice thickness simulation is most sensitive to the differences in upward longwave radiation at the surface. In addition, the sea-ice thickness simulation during the growth season is highly sensitive to the oceanic heat flux, and a new oceanic heat flux parameterization scheme based on the bulk method is proposed. The new parameterization scheme is tested in a second year, and it significantly improves the model performance relative to the standard configuration when compared against observations. Finally, the seasonal variation in the heat budget and its influence on the sea-ice thickness variation are analyzed. The net shortwave radiation, sensible heat flux and conductive heat flux (the net longwave radiation and latent heat flux) are found to be the surface heat sources (heat sinks) during the growth season. The larger conductive heat flux and the smaller oceanic heat flux can intensify the growth of sea ice.
The surface spectral albedo was measured over coastal landfast sea ice in Prydz Bay (off Zhongshan Station), East Antarctica from 5 October to 26 November of 2016. The mean albedo decreased from late-spring to early-summer, mainly responding to the change in surface conditions from dry (phase I) to wet (phase II). The evolution of the albedo was strongly influenced by the surface conditions, with alternation of frequent snowfall events and katabatic wind that induce snow blowing at the surface. The two phases and day-to-day albedo variability were more pronounced in the near-infrared albedo wavelengths than in the visible ones, as the near-infrared photons are more sensitive to snow metamorphism, and to changes in the uppermost millimeters and water content of the surface. The albedo diurnal cycle during clear sky conditions was asymmetric with respect to noon, decreasing from morning to evening over full and patchy snow cover, and decreasing more rapidly in the morning over bare ice. We conclude that snow and ice metamorphism and surface melting dominated over the solar elevation angle dependency in shaping the albedo evolution. However, we realize that more detailed surface observations are needed to clarify and quantify the role of the various surface processes.
The surface energy budget over the Antarctic sea ice from 8 April 2016 through 26 November 2016 are presented. From April to October, Sensible heat flux (SH) and subsurface conductive heat flux (G) were the heat source of surface while latent heat flux (LE) and net radiation flux (Rn) were the heat sink of surface. Our results showed larger downward SH (due to the warmer air in our site) and upward LE (due to the drier air and higher wind speed in our site) compared with SHEBA data. However, the values of SH in N-ICE2015 campaign, which located at a zone with stronger winds and more advection of heat in the Arctic, were comparable to our results under clear skies. The values of aerodynamic roughness length (z0m) and scalar roughness length for temperature (z0h), being 1.9 × 10−3 m and 3.7 × 10−5 m, were suggested in this study. It is found that snow melting might increase z0m. Our results also indicate that the value of log(z0h/z0m) was related to the stability of stratification. In addition, several representative parameterization schemes for z0h have been tested and a couple of schemes were found to make a better performance.
Heading errors caused by gyroscope drift affect the positioning precision of pedestrian dead reckoning, and these errors are even greater for smartphone-based reckoning. In this study, an optimised improved heuristic drift elimination (O-iHDE) method is proposed to correct the heading errors on a smartphone gyroscope. Based on an analysis of the improved heuristic drift elimination (iHDE) and enhanced improved heuristic drift elimination (E-iHDE) algorithms, the quaternion method is used to update the attitude and angle threshold judgement conditions, and a method for correcting the quaternion is added to eliminate the heading errors caused by random gyro errors. The analysis of multiple sets of experiments shows that the new method improves the ability to discern and correct the walking route, and the heading accuracy is improved by more than 90%, which extends the effective operation time of pedestrian dead reckoning positioning based on the step-by-step system.
In an effort to improve the reliability of Arctic sea-ice predictions, an ensemble-based Arctic Ice Ocean Prediction System (ArcIOPS) has been developed to meet operational demands. The system is based on a regional Arctic configuration of the Massachusetts Institute of Technology general circulation model. A localized error subspace transform ensemble Kalman filter is used to assimilate the weekly merged CryoSat-2 and Soil Moisture and Ocean Salinity sea-ice thickness data together with the daily Advanced Microwave Scanning Radiometer 2 (AMSR2) sea-ice concentration data. The weather forecasts from the Global Forecast System of the National Centers for Environmental Prediction drive the sea ice–ocean coupled model. The ensemble mean sea-ice forecasts were used to facilitate the Chinese National Arctic Research Expedition in summer 2017. The forecasted sea-ice concentration is evaluated against AMSR2 and Special Sensor Microwave Imager/Sounder sea-ice concentration data. The forecasted sea-ice thickness is compared to the in-situ observations and the Pan-Arctic Ice-Ocean Modeling and Assimilation System. These comparisons show the promising potential of ArcIOPS for operational Arctic sea-ice forecasts. Nevertheless, the forecast bias in the Beaufort Sea calls for a delicate parameter calibration and a better design of the assimilation system.
Considering that traditional visual navigation cannot be utilised in low illumination and sparse feature environments, a novel visual-inertial integrated navigation method using a Structured Light Visual (SLV) sensor for Micro Aerial Vehicles (MAVs) is proposed in this paper. First, the measurement model based on an SLV sensor is studied and built. Then, using the state model based on error equations of an Inertial Navigation System (INS), the measurement model based on the error of the relative motion measured by INS and SLV is built. Considering that the measurements in this paper are mainly related to the position and attitude information of the present moment, the state error accumulation in traditional visual-inertial navigation can be avoided. An Adaptive Sage-Husa Kalman Filter (ASHKF) based on multiple weighting factors is proposed and designed to make full use of the SLV measurements. The results of the simulation and the experiment based on real flight data indicate that high accuracy position and attitude estimations can be obtained with the help of the algorithm proposed in this paper.
Dairy cows with fatty liver or ketosis display decreased insulin sensitivity and defects in the insulin receptor substrate (IRS)/PI3K/AKT signaling pathway. Phosphatase and tensin homolog (PTEN) is a well-known tumor suppressor and also a negative regulator of insulin signaling and peripheral insulin sensitivity. We investigated the hypothesis that PTEN may affect the insulin pathway-mediated hepatic glucose and lipid metabolism in dairy cows. Adenovirus vectors that over-express and silence PTEN were constructed, and then transfected into hepatocytes isolated from calves to investigate the effect of PTEN on PI3K/AKT signaling pathway. PTEN silencing increased the phosphorylation of AKT and the expression of PI3K but decreased the phosphorylation of IRS1, which increased the phosphorylation levels of glycogen synthase kinase-3β (GSK-3β) and expression of sterol regulatory element-binding protein-1c (SREBP-1c). Increased GSK-3β phosphorylation further up-regulated expression of the key enzymes phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6-Pase) involved in gluconeogenesis. Furthermore, the expression of SREBP-1c target gene fatty acid synthase (FAS) also increased significantly. We further showed that PTEN over-expression could reverse the above results. PTEN negatively regulates the enzymes involved in hepatic gluconeogenesis and lipid synthesis, which suggests that PTEN may be a therapeutic target for ketosis and fatty liver in dairy cows.
It is a challenging task to discover information from a large amount of data in an open domain.1 In this paper, an event network framework is proposed to address this challenge. It is in fact an empirical construct for exploring open information, composed of three steps: document event detection, event network construction and event network analysis. First, documents are clustered into document events for reducing the impact of noisy and heterogeneous resources. Secondly, linguistic units (e.g., named entities or entity relations) are extracted from each document event and combined into an event network, which enables content-oriented retrieval. Then, in the final step, techniques such as social network or complex network can be applied to analyze the event network for exploring open information. In the implementation section, we provide examples of exploring open information via event network.
The decrease in summer sea-ice extent in the Arctic Ocean opens shipping routes and creates potential for many marine operations. For these activities accurate predictions of sea-ice conditions are required to maintain marine safety. In an attempt at Arctic sea-ice prediction, the summer of 2010 is selected to implement an Arctic sea-ice data assimilation (DA) study. The DA system is based on a regional Arctic configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter to assimilate Special Sensor Microwave Imager/Sounder (SSMIS) sea-ice concentration operational products from the US National Snow and Ice Data Center (NSIDC). Based on comparisons with both the assimilated NSIDC SSMIS concentration and concentration data from the Ocean and Sea Ice Satellite Application Facility, the forecasted sea-ice edge and concentration improve upon simulations without data assimilation. By the nature of the assimilation algorithm with multivariate covariance between ice concentration and thickness, sea-ice thickness fields are also updated, and the evaluation with in situ observation shows some improvement compared to the forecast without data assimilation.
Dairy cows with fatty liver or ketosis exhibit hyperketonemia, oxidative stress, and a low rate of very low density lipoprotein (VLDL) assembly, and there may be a potential link among these characteristics. Therefore, the objective of this study was to determine the effect of acetoacetic acid (AcAc) on the assembly of VLDL in cow hepatocytes. Cultured cow hepatocytes were treated with different concentrations of AcAc with or without N-acetylcysteine (NAC, an antioxidant). AcAc treatment decreased the mRNA expression and activities of antioxidant enzymes superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px), and significantly increased malondialdehyde (MDA) content, indicative of oxidative stress. Furthermore, AcAc treatment significantly down-regulated the mRNA expression of apolipoprotein B100 (ApoB100), apolipoprotein E (ApoE), and low density lipoprotein receptor (LDLR), which thus decreased VLDL assembly and increased triglyceride (TG) accumulation in these bovine hepatocytes. Importantly, NAC relieved AcAc-induced oxidative stress and increased VLDL assembly. In summary, these results suggest that AcAc-induced oxidative stress affects the assembly of VLDL, which increases TG accumulation in bovine hepatocytes.
Seven-band grouper (Hyporthodus septemfasciatus) is a commercial rocky reef fish in East Asia that has been regarded as a promising species for aquaculture. To investigate the broodstock contributions to offspring for the sustainability of fry production, 62 individuals of H. septemfasciatus from two broodstocks and one offspring population were analysed using fluorescent-AFLP. A total of 602 bands were amplified and 70.10% of them were polymorphic. The numbers of polymorphic loci were 308 (Pbroodstock I = 55.50%) and 356 (Pbroodstock II = 63.12%) in the two broodstocks, and 294 (Poffspring = 52.88%) in the offspring, respectively. The average values of Shannon diversity index (I) and expected heterozygosity (H) were higher in the broodstock (Ibroodstock I = 0.281, Ibroodstock II = 0.244, Hbroodstock I = 0.185, Hbroodstock II = 0.161) than those in the offspring (Ioffspring = 0.243, Hoffspring = 0.161). AMOVA and FST analyses showed that significant genetic differentiation between broodstock and offspring populations, and limited effective broodstock population size has contributed to the offspring. Both STRUCTURE and Principal Coordinates Analysis (PCoA) also showed the three populations composed of two stocks and most offspring individuals (95.0%) only originated from 44.0% of the individuals of broodstock I, which may have negative effects on sustainable fry production. Therefore, genetic variation between broodstock and offspring should be monitored, and large effective size of broodstock should be employed to ensure the success of commercial breeding programmes. Our data provide a useful genetic basis for future planning of sustainable culture and management of H. septemfasciatus.
Dietary isothiocyanates have been shown to possess anti-tumour activity, inhibiting several types of cultured human cancer cell growth. However, there are limited studies on their effects on cancer cell metastasis. Our previous study showed that benzyl isothiocyanate (BITC) and phenethyl isothiocyanate (PEITC) suppressed human lung cancer cell metastasis potential. In the present study, we found BITC (7·5 and 10 μm) and PEITC (12·5 and 20 μm) induced highly metastatic human non-small cell lung cancer L9981 cell apoptosis in a dose-dependent manner. Caspase-3 was activated. They also caused cell cycle arrest at the G2/M phase, via modulation of cyclin B1 expression. The mitogen-activated protein kinase (MAPK) signalling pathway was involved. c-Jun N-terminal kinase, extracellular signal-regulated protein kinase 1/2 and p38 were activated in a dose-dependent manner; activator protein 1 (AP-1) transcriptional activation and cyclin D1 expression were repressed. Apoptosis and MAPK activation were abrogated by anti-oxidant N-acetyl cysteine (NAC), suggesting that cell death signalling was triggered by oxidative stress. Further microarray analysis evaluated the potential targeted genes related to apoptosis and the cell cycle. Our studies suggested that BITC and PEITC suppressed the metastasis potential of highly metastatic lung cancer cells by inducing apoptosis and cell cycle arrest, via targeting the MAPK/AP-1 pathway. This may provide a novel approach for metastasis therapy of lung cancer by dietary isothiocyanates and possibly other types of cancer.