C−N bonds are pervasive throughout organic‐based materials, natural products, pharmaceutical compounds, and agricultural chemicals. Considering the widespread importance of C−N bonds, the development ...of greener and more convenient ways to form C−N bonds, especially in late‐stage synthesis, has become one of the hottest research goals in synthetic chemistry. Copper‐catalyzed radical reactions involving N‐centered radicals have emerged as a sustainable and promising approach to build C−N bonds. As a chemically popular and diverse radical species, N‐centered radicals have been used for all kinds of reactions for C−N bond formation by taking advantage of their inherently incredible reactive flexibility. Copper is also the most abundant and economic catalyst with the most relevant activity for facilitating the synthesis of valuable compounds. Therefore, the aim of the present Review was to illustrate recent and significant advances in C−N bond formation methods and to understand the unique advantages of copper catalysis in the generation of N‐centered radicals since 2016. To provide an ease of understanding for the readers, this Review was organized based on the types of nitrogen sources (amines, amides, sulfonamides, oximes, hydrazones, azides, and tert‐butyl nitrite).
A radical approach: Copper‐catalyzed radical reactions involving N‐centered radicals have emerged as a sustainable and promising approach to build C−N bonds. Therefore, the aim of this Review is to illustrate recent and significant advances in C−N bond formation methods and understand the unique advantages of copper catalysis in the generation of N‐centered radicals since 2016.
This paper completes the implementation of the risk control module of the international trade investment decision-making module through the construction process of the programmed international trade ...investment platform. Combining the decision tree algorithm and logistic regression algorithm to categorize and screen the factors affecting the fluctuation of international trade stock prices to obtain the international trade market fundamentals and technical factors that have a significant impact on international trade stock prices. The Kalman filter model is applied to improve the effective market factors screened so that the factor selection of the international trade investment model is more advantageous. After constructing the platform, in order to reflect its convenience, the RE, OLS, TI, TVD and BC models were used to analyze the export trade efficiency of the home country, respectively. The results show that the degree of facilitation of the host country’s trade and investment platform is positively correlated with the loss of the home country’s export trade efficiency (0.043), which is statistically significant at the 1% significance level, and that the loss of the home country’s export trade efficiency increases by 4.3% for every 1 unit increase in the degree of facilitation of the host country’s trade and investment platform. The construction of the international trade and investment platform increases the facilitation of export trade from trading partner countries to the host country, which indirectly increases the export trade efficiency loss of the home country.
When the self-assembly of block copolymers (BCPs) occurs within a deformable emulsion droplet, BCPs can aggregate into a variety of nanoscaled particles with unique nanostructures and properties ...since the confinement effect can effectively break the symmetry of a structure. On the other hand, the self-assembled BCP particles can serve as the scaffolds to further direct the spatial arrangement of functional inorganic nanoparticles (NPs)
via
co-assembly or
in situ
deposition, thus generating diverse hybrid functional BCP/NP composites with enhanced properties. Here, we summarize the recent progress in the confined self-assembly of BCPs within the emulsion droplet and spatial arrangement of NPs on the resulting BCP scaffolds. This feature article focuses on the influence of multiple factors, including the oil/water interfacial properties, confinement degree, intrinsic properties of BCPs, additives, pH value, and temperature, on the nanostructures of the self-assembled BCP particles as well as the spatial arrangement of NPs on the BCP scaffolds from both experiment and simulation studies.
When the self-assembly of block copolymers (BCPs) occurs within a deformable emulsion droplet, BCPs can aggregate into a variety of nanoscaled particles with unique nanostructures and properties since the confinement effect can effectively break the symmetry of a structure.
Background
Accurate glioma grading plays an important role in the clinical management of patients and is also the basis of molecular stratification nowadays.
Purpose/Hypothesis
To verify the ...superiority of radiomics features extracted from multiparametric MRI to glioma grading and evaluate the grading potential of different MRI sequences or parametric maps.
Study Type
Retrospective; radiomics.
Population
A total of 153 patients including 42, 33, and 78 patients with Grades II, III, and IV gliomas, respectively.
Field Strength/Sequence
3.0T MRI/T1‐weighted images before and after contrast‐enhanced, T2‐weighted, multi‐b‐value diffusion‐weighted and 3D arterial spin labeling images.
Assessment
After multiparametric MRI preprocessing, high‐throughput features were derived from patients' volumes of interests (VOIs). The support vector machine‐based recursive feature elimination was adopted to find the optimal features for low‐grade glioma (LGG) vs. high‐grade glioma (HGG), and Grade III vs. IV glioma classification tasks. Then support vector machine (SVM) classifiers were established using the optimal features. The accuracy and area under the curve (AUC) was used to assess the grading efficiency.
Statistical Tests
Student's t‐test or a chi‐square test were applied on different clinical characteristics to confirm whether intergroup significant differences exist.
Results
Patients' ages between LGG and HGG groups were significantly different (P < 0.01). For each patient, 420 texture and 90 histogram parameters were derived from 10 VOIs of multiparametric MRI. SVM models were established using 30 and 28 optimal features for classifying LGGs from HGGs and grades III from IV, respectively. The accuracies/AUCs were 96.8%/0.987 for classifying LGGs from HGGs, and 98.1%/0.992 for classifying grades III from IV, which were more promising than using histogram parameters or using the single sequence MRI.
Data Conclusion
Texture features were more effective for noninvasively grading gliomas than histogram parameters. The combined application of multiparametric MRI provided a higher grading efficiency. The proposed radiomic strategy could facilitate clinical decision‐making for patients with varied glioma grades.
Level of Evidence: 3
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2018;48:1518–1528
Breast cancer is among the most common malignant cancers in women. B‐cell‐specific Moloney murine leukemia virus integration site 1 (BMI‐1) is a transcriptional repressor that has been shown to be ...involved in tumorigenesis, the cell cycle, and stem cell maintenance. In our study, increased expression of BMI‐1 was found in both human triple negative breast cancer and luminal A‐type breast cancer tissues compared with adjacent tissues. We also found that knockdown of BMI‐1 significantly suppressed cell proliferation and migration in vitro and in vivo. Further mechanistic research demonstrated that BMI‐1 directly bound to the promoter region of CDKN2D/BRCA1 and inhibited its transcription in MCF‐7/MDA‐MB‐231. More importantly, we discovered that knockdown of CDKN2D/BRCA1 could promote cell proliferation and migration after repression by PTC‐209. Our results reveal that BMI‐1 transcriptionally suppressed BRCA1 in TNBC cell lines whereas, in luminal A cell lines, CDKN2D was the target gene. This provides a reference for the precise treatment of different types of breast cancer in clinical practice.
BMI‐1 promotes proliferation and migration via transcriptional inhibition of cyclin‐dependent kinase inhibitor 2D (CDKN2D) in luminal A‐type breast cancer but via transcriptional inhibition of breast cancer susceptibility gene 1 (BRCA1) in TNBC.
Ion channels exhibit strong selectivity for specific ions over others under electrochemical potentials, such as KcsA for K
over Na
. Based on the thermodynamic analysis, this study is focused on ...exploring the mechanism of ion selectivity in nanopores. It is well known that ions must lose part of their hydration layer to enter the channel. Therefore, the ion selectivity of a channel is due to the rearrangement of water molecules when entering the nanopore, which may be related to the hydrophobic interactions between ions and channels. In our recent works on hydrophobic interactions, with reference to the critical radius of solute (Rc), it was divided into initial and hydrophobic solvation processes. Additionally, the different dissolved behaviors of solutes in water are expected in various processes, such as dispersed and accumulated distributions in water. Correspondingly, as the ion approaches the nanopore, there seems to exist the "repulsive" or "attractive" forces between them. In the initial process (<Rc), the energy barrier related to "repulsive" force may be expected as ions enter the channel. Regarding the ion selectivity of nanopores, this may be due to the energy barrier between the ion and channel, which is closely related to the ion size and pore radius. Additionally, these may be demonstrated by the calculated potential mean forces (PMFs) using molecular dynamics (MD) simulations.
Salinization is a global land degradation issue which inhibits microbial activity and plant growth. The effect of salinity on microbial activity and biomass has been studied extensively, but little ...is known about the response of microbes from different soils to increasing salinity although soil salinity may fluctuate in the field, for example, depending on the quality of the irrigation water or seasonally. An incubation experiment with five soils (one non-saline, four saline with electrical conductivity (ECe) ranging from 1 to 50 dS m−1) was conducted in which the EC was increased to 37 ECe levels (from 3 to 119 dS m−1) by adding NaCl. After amendment with 2% (w/w) pea straw to provide a nutrient source, the soils were incubated at optimal water content for 15 days, microbial respiration was measured continuously and chloroform-labile C was determined every three days. Both cumulative respiration and microbial biomass (indicated by chloroform-labile C) were negatively correlated with EC. Irrespective of the original soil EC, cumulative respiration at a given adjusted EC was similar. Thus, microorganisms from previously saline soils were not more tolerant to a given adjusted EC than those in originally non-saline soil. Microbial biomass in all soils increased from day 0 to day 3, then decreased. The relative increase was greater in soils which had a lower microbial biomass on day 0 (which were more saline). Therefore the relative increase in microbial biomass appears to be a function of the biomass on day 0 rather than the EC. Hence, the results suggest that microbes from originally saline soils are not more tolerant to increases in salinity than those from originally non-saline soils. The strong increase in microbial biomass upon pea straw addition suggests that there is a subset of microbes in all soils that can respond to increased substrate availability even in highly saline environments.
► Four saline and one non-saline soil were incubated at different salinities. ► Microbial respiration and biomass were decreased by increasing salinity. ► Respiration was similar at a given adjusted EC irrespective of the original EC.
The linear canonical transform (LCT) has been shown to be one of the most powerful tools in signal processing, and in this paper, we propose an adaptive approach for the computation of the discrete ...LCT (DLCT), termed the sliding discrete linear canonical transform (SDLCT). First, we introduce a scheme for the single-point DLCT, which can effectively calculate a single or a few linear canonical spectra. Second, the SDLCT is proposed based on an iterative algorithm to meet the requirements of online spectral analysis when only a subset of N frequencies are required from an Ñ-point discrete LCT (N ≤ Ñ). The additivity and reversibility properties of the proposed algorithms are also discussed in detail. Third, the DLCT convolution operation is obtained to reduce the spectral leakage of the proposed algorithm, and time-domain windowing is implemented via frequency-domain convolution. Finally, we present two methods to assess performance with regard to computational complexity and precision and to show the correctness of the derived results.
Precise control over the spatial arrangement of inorganic nanoparticles on a large scale is desirable for the design of functional nanomaterials, sensing, and optical/electronic devices. Although ...great progress has been recently made in controlling the organization of nanoparticles, there still remains a grand challenge to arrange nanoparticles into highly-ordered arrays over multiple length scales. Here, we report the directed arrangement of inorganic nanoparticles into arrayed structures with long-range order, up to tens of microns, by using hexagonally-packed cylindrical patterns of block copolymer nanosheets self-assembled within collapsed emulsion droplets as scaffolds. This technique can be used to generate nanoparticle arrays with various nanoparticle arrangements, including hexagonal honeycomb structures, periodic nanoring structures, and their combinations. This finding provides an effective route to fabricate diverse nanoparticle arrayed structures for the design of functional materials and devices.
In the task of image semantic segmentation, most methods do not make full use of features of different scales and levels, but directly upsampling, which will cause some effective information to be ...dismissed as redundant information, thus reducing the accuracy and sensitivity of segmentation of some small categories and similar categories. Therefore, a multi-level feature fusion network (MFFNet) is proposed. MFFNet uses encoder-decoder structure, during the encoding stage, the context information and spatial detail information are obtained through the context information extraction path and spatial information extraction path respectively to enhance the inter-pixel correlation and boundary accuracy. During the decoding stage, a multi-level feature fusion path is designed, and the context information is fused by the mixed bilateral fusion module. Deep information and spatial information are fused by high-low feature fusion module. The global channel-attention fusion module is used to obtain the connections betw
