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Evidence of executive dysfunction in autism spectrum disorders (ASD) across development remains mixed and establishing its role is critical for guiding diagnosis and intervention. The primary objectives of this meta-analysis is to analyse executive function (EF) performance in ASD, the fractionation across EF subdomains, the clinical utility of EF measures and the influence of multiple moderators (for example, age, gender, diagnosis, measure characteristics). The Embase, Medline and PsychINFO databases were searched to identify peer-reviewed studies published since the inclusion of Autism in DSM-III (1980) up to end of June 2016 that compared EF in ASD with neurotypical controls. A random-effects model was used and moderators were tested using subgroup analysis. The primary outcome measure was Hedges' g effect size for EF and moderator factors. Clinical sensitivity was determined by the overlap percentage statistic (OL%). Results were reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 235 studies comprising 14 081 participants were included (N, ASD=6816, Control=7265). A moderate overall effect size for reduced EF (Hedges' g=0.48, 95% confidence interval (CI) 0.43-0.53) was found with similar effect sizes across each domain. The majority of moderator comparisons were not significant although the overall effect of executive dysfunction has gradually reduced since the introduction of ASD. Only a small number of EF measures achieved clinical sensitivity. This study confirms a broad executive dysfunction in ASD that is relatively stable across development. The fractionation of executive dysfunction into individual subdomains was not supported, nor was diagnostic sensitivity. Development of feasible EF measures focussing on clinical sensitivity for diagnosis and treatment studies should be a priority.

Met is a receptor tyrosine kinase that promotes cancer progression. In addition, Met has been implicated in resistance of tumors to various targeted therapies such as epidermal growth factor receptor inhibitors in lung cancers, and has been prioritized as a key molecular target for cancer therapy. However, the underlying mechanism of resistance to Met-targeting drugs is poorly understood. Here, we describe screening of 1310 genes to search for key regulators related to drug resistance to an anti-Met therapeutic antibody (SAIT301) by using a small interfering RNA-based synthetic lethal screening method. We found that knockdown of 69 genes in Met-amplified MKN45 cells sensitized the antitumor activity of SAIT301. Pathway analysis of these 69 genes implicated fibroblast growth factor receptor (FGFR) as a key regulator for antiproliferative effects of Met-targeting drugs. Inhibition of FGFR3 increased target cell apoptosis through the suppression of Bcl-xL expression, followed by reduced cancer cell growth in the presence of Met-targeting drugs. Treatment of cells with the FGFR inhibitors substantially restored the efficacy of SAIT301 in SAIT301-resistant cells and enhanced the efficacy in SAIT301-sensitive cells. In addition to FGFR3, integrin β3 is another potential target for combination treatment with SAIT301. Suppression of integrin β3 decreased AKT phosphorylation in SAIT301-resistant cells and restored SAIT301 responsiveness in HCC1954 cells, which are resistant to SAIT301. Gene expression analysis using CCLE database shows that cancer cells with high levels of FGFR and integrin β3 are resistant to crizotinib treatment, suggesting that FGFR and integrin β3 could be used as predictive markers for Met-targeted therapy and provide a potential therapeutic option to overcome acquired and innate resistance for the Met-targeting drugs.

Observation window is an important component for visual observation during cryogenic wind tunnel testing. However, the change of temperature and pressure in the wind tunnel may lead to thermal stress and deformation of the observation window, threatening the safety of observation window. On this account, aiming to improve observation window structure, the temperature and stress fields of observation window for continuous transonic cryogenic wind tunnel were investigated by a fluid-solid-thermal coupling finite element method in this work. A numerical calculation model of cryogenic observation window was established based on the designed boundary and initial conditions. A fluid-solid-thermal coupling analysis was carried out to investigate the temperature and stress fields, respectively. Finally, taking the flow rate of nitrogen as the variable and the surface temperature of outer plexiglass as the optimization objective, the heat exchange parameter of the observation window was optimized. The obtained results showed that when the flow rate of nitrogen was 20 m·s − 1 (the mass flow of nitrogen was equal to 0.00291 kg·s − 1 ), the temperature of the outer plexiglass was 289.6 K after 10,800 s, which was 1.3 K higher than the dew point temperature. This can ensure clear observation through the cryogenic observation window. This work provides the guidance and reference for the heating gas consumption of cryogenic wind tunnel.

Tanshinones and phenolic acids are the major bioactive constituents in the traditional medicinal crop Salvia miltiorrhiza; however, transcription factors (TFs) are seldom investigated with regard to their regulation of the biosynthesis of these compounds. Here a complete overview of the APETALA2/ethylene‐responsive factor (AP2/ERF) transcription factor family in S. miltiorrhiza is provided, including phylogeny, gene structure, conserved motifs, and gene expression profiles of different organs (root, stem, leaf, flower) and root tissues (periderm, phloem, xylem). In total, 170 AP2/ERF genes were identified and divided into five relatively conserved subfamilies, including AP2 (25 genes), DREB (61 genes), ethylene responsive factor (ERF; 79 genes), RAV (4 genes), and Soloist (1 gene). According to the distribution of bioactive constituents and the expression patterns of AP2/ERF genes in different organs and root tissues, the genes related to the biosynthesis of bioactive constituents were selected. On the basis of quantitative real‐time polymerase chain reaction (qRT‐PCR) analysis, coexpression analysis, and the prediction of cis‐regulatory elements in the promoters, we propose that two genes (Sm128 and Sm152) regulate tanshinone biosynthesis and two genes (Sm008 and Sm166) participate in controlling phenolic acid biosynthesis. The genes related to tanshinone biosynthesis belong to the ERF‐B3 subgroup. In contrast, the genes predicted to regulate phenolic acid biosynthesis belong to the ERF‐B1 and ERF‐B4 subgroups. These results provide a foundation for future functional characterization of AP2/ERF genes to enhance the biosynthesis of the bioactive compounds of S. miltiorrhiza.

We report an in-plane optical spectroscopy study on the iron-selenide superconductor K 0.75 Fe 1.75 Se 2 . The measurement revealed the development of a sharp reflectance edge below T c at frequency much smaller than the superconducting energy gap on a relatively incoherent electronic background, a phenomenon which was not seen in any other Fe-based superconductors so far investigated. Furthermore, the feature could be noticeably suppressed and shifted to lower frequency by a moderate magnetic field. Our analysis indicates that this edge structure arises from the development of a Josephson-coupling plasmon in the superconducting condensate. Together with the transmission electron microscopy analysis, our study yields compelling evidence for the presence of nanoscale phase separation between superconductivity and magnetism. The results also enable us to understand various seemingly controversial experimental data probed from different techniques.

Drought and tropical storm (TS) are associated with water deficit and surplus, respectively. Soil moisture is a key component in the hydrological cycle that plays an important role in monitoring drought and reflects the infiltrated or stored water due to TS rainfall. Therefore, soil moisture information can be used for the assessment of whether TS can ameliorate severe drought conditions. Here, we use downscaled 1 km Soil Moisture Active Passive data set generated at the Center for Complex Hydrosystems Research at the University of Alabama, and Hurricane Database 2nd generation to examine the coincidence of extreme events between agricultural droughts and Atlantic TS in the contiguous United States from 2015 to 2019. The Cumulative Distribution Function (CDF) matching approach is employed to correct the bias using the root zone soil moisture data provided by the North American Land Data Assimilation System Phase 2 (NLDAS‐2), and then weekly Standardized Soil Moisture Index is calculated for characterization of agricultural drought. As a result, we estimate the frequency of TS impacted regions in the US, the ratio of droughts ameliorated and exacerbated by TS, and the regions where TS highly affect the offset of drought. Our findings indicate detailed spatial information of the offset of drought conditions based on a high‐resolution data set and provide potential information in terms of mitigating drought and TS for the future. Key Points Agricultural drought in the contiguous United States was identified by high‐resolution standardized soil moisture index Drought in the East Coast are likely to get exacerbated due to climate condition although tropical storm (TS) landfall Drought in the Gulf of Mexico are rarely affected by TS

Background/Objectives: Although there is an increasing trend of dietary supplement (DS) use, few researches have evaluated nutrient intake from DS. This study aimed to establish a nutrient database (NDB) for DS and estimate the effect of DS on total nutrient intake by Korean adults. Subjects/Methods: The NDB for DS was established using the label information of products reported in the Korea National Health and Nutrition Examination Survey (KNHANES) IV. Of the 16 031 participants who were ⩾20 years old, 2053 products were reported as being taken by 5606 subjects. But nutrient composition could be identified by searching product name only in 1158 products consumed by 3844 subjects (DS users). Total nutrient intake of DS users was obtained by combining intakes from diet and DS. Results: Dietary supplement use was higher in women, in middle-aged people and in those with higher education and low smoking and drinking preferences. Nutrients obtained from food were higher in DS users than in nonusers for most nutrients, particularly in women. When total nutrient intake was evaluated in DS users, the percentage of subjects whose intake was below the estimated average requirement for Koreans decreased for several vitamins and minerals, but the percentage of subjects whose intake was above the tolerable upper intake levels increased for vitamin A, vitamin C and iron. Conclusions: The newly developed NDB for DS will be an important resource for more accurate assessment of nutrient intake as well as evaluation of the relationship between nutrition and health. Further research is needed to update a more comprehensive NDB applicable to diverse populations.

In order to overcome the problems existing in the traditional mechanical fault diagnosis, and to improve the accuracy of mechanical fault diagnosis, an optimization method of mechanical fault diagnosis based on artificial intelligence technology is proposed in this paper. The optimization method combines a variety of current popular high and new technologies, such as artificial intelligence technology, expert system and artificial neural network technology. at the same time, the optimization method also breaks the traditional mechanical fault diagnosis mode based on fuzzy set theory. Based on this, the optimization method also makes an in-depth analysis and research on artificial intelligence technology, which promotes the application and development of artificial intelligence technology, and expands the application scope and application field of artificial intelligence technology. The research results show that the optimization method can scientifically overcome the problems existing in the traditional mechanical fault diagnosis, and can improve the accuracy and scientificalness in the process of mechanical fault diagnosis, so it has strong feasibility.

The preadipocyte-to-adipocyte differentiation (adipogenesis) is a key process in fat mass increase and thus it is regarded as a compelling target for preventing or treating obesity. Of adipogenic hormone receptors, peroxisome proliferator-activated receptor gamma (PPAR γ ) has crucial roles in adipogenesis and lipid accumulation within adipocytes. Here we demonstrate that the NEDD8 (neuronal precursor cell expressed, developmentally downregulated 8)-based post-translation modification (neddylation) of PPAR γ is essential for adipogenesis. During adipogenesis, NEDD8 is robustly induced in preadipocytes and conjugates with PPAR γ , leading to PPAR γ stabilization. When the neddylation process was blocked by NEDD8-targeting siRNAs (or viral vectors) or an inhibitor MLN4924, adipocyte differentiation and fat tissue development were substantially impaired. We also demonstrate that MLN4924 effectively prevents the high-fat diet-induced obesity and glucose intolerance in mice. This study provides a better understanding of how the PPAR γ signaling pathway starts and lasts during adipogenesis and a potential anti-obesity strategy that targets the neddylation of PPAR γ .

The biggest factors, which lower the machining accuracy of machine tools for advanced manufacturing, are thermal deformation and chatter vibration. In this article, we introduce the development case of a device and technology that can automatically compensate thermal deformation errors of machine during long-time processing on the machine tool’s CNC(Computerized Numerical Controller) in real time. In machine processing, the data acquisition of temperature signal in real time and auto-compensation of the machine origin of machine tools depending on thermal deformation have significant influence on improving the machining accuracy and the rate of operation. Thus, we attempts to introduce the related contents of the development we have made in this article: The development of a device that embedded the acquisition part of temperature data, linear regression to get compensation value, compensation model of neural network and a system that compensates the machine origin of machine tool automatically during manufacturing process on the CNC.