N6‐methyladenosine (m6A) is a well‐known modification of RNA. However, as a key m6A methyltransferase, METTL16 has not been thoroughly studied in gastric cancer (GC). Here, the biological role of ...METTL16 in GC and its underlying mechanism was studied. Immunohistochemistry was used to detect the expression of METTL16 and relationship between METTL16 level and prognosis of GC was analysed. CCK8, colony formation assay, EdU assay and xenograft mouse model were used to study the effect of METTL16. Regulatory mechanism of METTL16 in the progression of GC was studied through flow cytometry analysis, RNA degradation assay, methyltransferase inhibition assay, RT‐qPCR and Western blotting. METTL16 was highly expressed in GC cells and tissues and was associated with prognosis. In vitro and in vivo experiments confirmed that METTL16 promoted proliferation of GC cells and tumour growth. Furthermore, down‐regulation of METTL16 inhibited proliferation by G1/S blocking. Significantly, we identified cyclin D1 as a downstream effector of METTL16. Knock‐down METTL16 decreased the overall level of m6A and the stability of cyclin D1 mRNA in GC cells. Meanwhile, inhibition of methyltransferase activity reduced the level of cyclin D1. METTL16‐mediated m6A methylation promotes proliferation of GC cells through enhancing cyclin D1 expression.
The artificial intelligence (AI) techniques have been widely used in the transient stability analysis of a power system. They are recognized as the most promising approaches for predicting the ...post-fault transient stability status with the use of phasor measurement units data. However, the popular AI methods used for power systems are often "black boxes," which result in the poor interpretation of the model. In this paper, a transient stability prediction method based on extreme gradient boosting is proposed. In this model, a decision graph and feature importance scores are provided to discover the relationship between the features of the power system and transient stability. Meanwhile, the key features are selected according to the feature importance scores to remove redundant variables. The simulation results on the New England 39-bus system have demonstrated the superiority of the proposed model over the prior methods in the computation speed and prediction accuracy. Finally, an algorithm is proposed to interpret the prediction results for a specific fault of the power system, which further improves the interpretability of the model and makes it attractive for real-time transient stability prediction.
While metal is the most common conducting constituent element in the fabrication of metamaterials, graphene provides another useful building block, that is, a truly two-dimensional conducting sheet ...whose conductivity can be controlled by doping. Here we report the experimental realization of a multilayer structure of alternating graphene and Al2O3 layers, a structure similar to the metal-dielectric multilayers commonly used in creating visible wavelength hyperbolic metamaterials. Chemical vapour deposited graphene rather than exfoliated or epitaxial graphene is used, because layer transfer methods are easily applied in fabrication. We employ a method of doping to increase the layer conductivity, and our analysis shows that the doped chemical vapour deposited graphene has good optical properties in the mid-infrared range. We therefore design the metamaterial for mid-infrared operation; our characterization with an infrared ellipsometer demonstrates that the metamaterial experiences an optical topological transition from elliptic to hyperbolic dispersion at a wavelength of 4.5 μm.
Students who wish to learn a specific skill have increasing access to a growing number of online courses and open-source educational repositories of instructional tools, including videos, slides, and ...exercises. Navigating these tools is time-consuming and the search itself can hinder the learning of the skill. Educators are hence interested in aiding students by selecting the optimal content sequence for individual learners, specifically which skill one should learn next and which material one should use to study. Such adaptive selection would rely on pre-knowledge of how the learners’ and the instructional tools’ characteristics jointly affect the probability of acquiring a certain skill. Building upon previous research on Latent Transition Analysis and Learning Trajectories, we propose a multilevel logistic hidden Markov model for learning based on cognitive diagnosis models, where the probability that a learner acquires the target skill depends not only on the general difficulty of the skill and the learner’s mastery of other skills in the curriculum but also on the effectiveness of the particular learning tool and its interaction with mastery of other skills, captured by random slopes and intercepts for each learning tool. A Bayesian modeling framework and an MCMC algorithm for parameter estimation are proposed and evaluated using a simulation study.
Due to the inner deteriorating mechanism or the mutant environmental stress, the degradation systems with multi-phase features have frequently been encountered in engineering practice. The key issue ...for prognostics of such systems is to account for the impact of the changing-point variability and the associated degradation state at this point on the progression of the degradation process. However, current studies usually treat the degradation state at the change point as a fixed value rather a random variable. Thus, it is still challenging to predict the lifetime of such multi-phase degrading systems. To this end, we first formulate a general degradation modeling framework based on a two-phase Wiener process. In prognostics, we take into full account the uncertainty of the degradation state at the changing point and then derive the analytical expressions of the lifetime and remaining useful life under the concept of the first passage time. The derived results are distinguished from existing results limited to the fixed state at the changing point. Furthermore, we extend our approach and results to cases with unit-to-unit variability and multiple phases. To facilitate the model implementation, we propose both offline and online methods for parameter identification, which make full use of the historical data and the in-service data. Finally, a numerical simulation and a practical case study are provided for illustration.
The enantioselective construction of C-CF
R (R: alkyl or fluoroalkyl) bonds has attracted the attention of synthetic chemists because of the importance of chiral fluorinated compounds in life and ...materials sciences. Catalytic asymmetric fluoroalkylation has mainly been realized under organocatalysis and Lewis acid catalysis, with substrates limited to carbonyl compounds. Few examples using transition-metal catalysis exist, owing to side reactions including decomposition and isomerization of fluoroalkylating reagents. Herein we report umpolung asymmetric difluoroallylation of hydrazones with 3-bromo-3,3-difluoropropene (BDFP) under palladium catalysis. Difluoroallylation products having quaternary chiral carbon centers are afforded in good yields with high α/γ- and enantioselectivities. The usefulness of the reaction products is demonstrated and an inner-sphere mechanism of the reaction is proposed. The use of chiral N-heterocyclic carbene as ligand is the key for the selectivities as well as the productivity of the reaction.
Abstract Background A growing number of functional magnetic resonance imaging (fMRI) studies have been conducted in major depressive disorder (MDD) to elucidate reward-related brain functions. The ...aim of this meta-analysis was to examine the common reward network in the MDD brain and to further distinguish the brain activation patterns between positive stimuli and monetary rewards as well as reward anticipation and outcome. Methods A series of activation likelihood estimation (ALE) meta-analyses were performed across 22 fMRI studies that examined reward-related processing, with a total of 341 MDD patients and 367 healthy controls. Results We observed several frontostriatal regions that participated in reward processing in MDD. The common reward network in MDD was characterized by decreased subcortical and limbic areas activity and an increased cortical response. In addition, the cerebellum, lingual gyrus, parahippocampal gyrus and fusiform gyrus preferentially responded to positive stimuli in MDD, while the insula, precuneus, cuneus, PFC and inferior parietal lobule selectively responded to monetary rewards. Our results indicated a reduced caudate response during both monetary anticipation and outcome stages as well as increased activation in the middle frontal gyrus and dorsal anterior cingulate during reward anticipation in MDD. Limitations The reward-related tasks and mood states of patients included in our analysis were heterogeneous. Conclusions Our current findings suggest that there exist emotional or motivational pathway dysfunctions in MDD during reward-related processing. Future studies may be strengthened by paying careful attention to the types of reward used as well as the different components of reward processing examined.
Yunnan Province is located in southwestern China and neighbors the Southeast Asian countries, all of which are dengue-endemic areas. In 2000-2013, sporadic imported cases of dengue fever (DF) were ...reported almost annually in Yunnan Province. During 2013-2015, we confirmed that a large-scale indigenous DF outbreak emerged in cities of Yunnan Province near the China-Myanmar-Laos border.
Epidemiological characteristics of DF in Yunnan Province during 2013-2015 were evaluated by retrospective analysis. A total of 232 dengue virus (DENV)-positive sera were randomly collected for sequence analysis of the capsid/premembrane region of DENV from patients with DF in Yunnan Province. The envelope gene of DENV isolates was also amplified and sequenced. Phylogenetic analyses were performed using the neighbor-joining method with the Tajima-Nei model.
Phylogenetically, all DENV-positive samples could be classified into DENV-1 genotype I and DENV-2 Asian I genotype during 2013-2015 and DENV-4 genotype I in 2015 from Ruili City; and DENV-3 genotype II in 2013 and DENV-2 Cosmopolitan genotype in 2015 from Xishuangbanna Prefecture.
Our results indicated that imported DF from patients from Laos and Myanmar was the primary cause of the DF epidemic in Yunnan Province. Additionally, DENV strains of all four serotypes were identified in indigenous cases in Yunnan Province during the same time period, while the dengue epidemic pattern observed in southwestern Yunnan showed characteristics of a hypoendemic nature: circulation of DENV-1 and DENV-2 over consecutive years.
As one of the most influential international large-scale educational assessments, the Program for International Student Assessment (PISA) provides a valuable platform for the horizontal comparisons ...and references of international education. The cognitive diagnostic model, a newly generated evaluation theory, can integrate measurement goals into the cognitive process model through cognitive analysis, which provides a better understanding of the mastery of students of fine-grained knowledge points. On the basis of the mathematical measurement framework of PISA 2012, 11 attributes have been formed from three dimensions in this study. Twelve test items with item responses from 24,512 students from 10 countries participated in answering were selected, and the analyses were divided into several steps. First, the relationships between the 11 attributes and the 12 test items were classified to form a Q matrix. Second, the cognitive model of the PISA mathematics test was established. The liner logistic model (LLM) with better model fit was selected as the parameter evaluation model through model comparisons. By analyzing the knowledge states of these countries and the prerequisite relations among the attributes, this study explored the different learning trajectories of students in the content field. The result showed that students from Australia, Canada, the United Kingdom, and Russia shared similar main learning trajectories, while Finland and Japan were consistent with their main learning trajectories. The primary learning trajectories of the United States and China were the same. Furthermore, the learning trajectory for Singapore was the most complicated, as it showed a diverse learning process, whereas the trajectory in the United States and Saudi Arabia was relatively simple. This study concluded the differences of the mastery of students of the 11 cognitive attributes from the three dimensions of content, process, and context across the 10 countries, which provided a reference for further understanding of the PISA test results in other countries and shed some evidence for a deeper understanding of the strengths and weaknesses of mathematics education in various countries.
Circular RNAs (circRNAs) play important roles in many biological processes. However, the detailed mechanism underlying the critical roles of circRNAs in cancer remains largely unexplored. We aim to ...explore the molecular mechanisms of circRTN4 with critical roles in pancreatic ductal adenocarcinoma (PDAC).
CircRTN4 expression level was examined in PDAC primary tumors. The oncogenic roles of circRTN4 in PDAC tumor growth and metastasis were studied in mouse tumor models. Bioinformatics analysis, luciferase assay and miRNA pulldown assay were performed to study the novel circRTN4-miRNA-lncRNA pathway. To identify circRTN4-interacting proteins, we performed circRNA-pulldown and mass spectrometry in PDAC cells. Protein stability assay and 3-Dimensional structure modeling were performed to reveal the role of circRTN4 in stabilizing RAB11FIP1.
CircRTN4 was significantly upregulated in primary tumors from PDAC patients. In vitro and in vivo functional studies revealed that circRTN4 promoted PDAC tumor growth and liver metastasis. Mechanistically, circRTN4 interacted with tumor suppressor miR-497-5p in PDAC cells. CircRTN4 knockdown upregulated miR-497-5p to inhibit the oncogenic lncRNA HOTTIP expression. Furthermore, we identified critical circRTN4-intercting proteins by circRNA-pulldown in PDAC cells. CircRTN4 interacted with important epithelial-mesenchymal transition (EMT)- driver RAB11FIP1 to block its ubiquitination site. We found that circRTN4 knockdown promoted the degradation of RAB11FIP1 by increasing its ubiquitination. Also, circRTN4 knockdown inhibited the expression of RAB11FIP1-regulating EMT-markers Slug, Snai1, Twist, Zeb1 and N-cadherin in PDAC.
The upregulated circRTN4 promotes tumor growth and liver metastasis in PDAC through the novel circRTN4-miR-497-5p-HOTTIP pathway. Also, circRTN4 stabilizes RAB11FIP1 to contribute EMT.
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