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1.
Fluorescent-based single-strand conformation polymorphism (F-SSCP) analysis with capillary electrophoresis (CE) is the most common method for the detection of mutation because of its high sensitivity and resolution. In this study, we prepared an inexpensive linear polyacrylamide (LPA), and successfully applied it to CE-SSCP analysis and tandem CE-SSCP/heteroduplex analysis (HA) of the P53 gene on an ABI capillary genetic analyzer. A comparison of the sieving capabilities of a homemade LPA and commercial polydimethylacrylamide (PDMA) demonstrates that the homemade LPA has a higher resolution, a shorter analysis time, and is more suitable for tandem SSCP/HA than commercial PDMA. To show the usefulness, mutations of P53 gene exon 7 - 8 in 37 tumor samples were investigated by using homemade LPA. The results indicate that 10 mutations were found in 9 of 37 cases; the majority of P53 mutations were missense mutations, and 70% were located in exon 7, which plays an important role in neoplastic progression in human tumorigenesis.  相似文献   
2.
A novel microphase‐inversion method was proposed for the preparation of TiO2–SiO2/poly(methyl methacrylate) core–shell nanocomposite particles. The inorganic–polymer nanocomposites were first synthesized via a free‐radical copolymerization in a tetrahydrofuran solution, and the poor solvent was added slowly to induce the microphase separation of the nanocomposite and result in the formation of nanoparticles. The average particle sizes of the microspheres ranged from 70 to 1000 nm, depending on the reaction conditions. Transmission electron microscopy and scanning electron microscopy indicated a core–shell morphology for the obtained microspheres. Thermogravimetric analysis and X‐ray photoelectron spectroscopy measurements confirmed that the surface of the nanocomposite microspheres was polymer‐rich, and this was consistent with the core–shell morphology. The influence of the synthetic conditions, such as the inorganic composition and the content of the crosslinking monomer, on the particle properties was studied in detail. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 3911–3920, 2006  相似文献   
3.
Amphotericin B (AMB) is an antifungal drug used for serious fungal infections. However, AMB has adverse reactions such as nephrotoxicity, which limit the clinical application of AMB alone or in combination with other antifungal drugs. Nano or micro drug delivery systems (DDS) have been proven to be effective in reducing the toxic and side effects of drugs. Further, the combination of AMB with other compounds with antifungal activity, such as curcumin (CM), may enhance the synergistic effects. Herein, AMB and CM were co-loaded into porous poly (lactic-co-glycolic acid) (PLGA) microparticles (MPs) to prepare AMB/CM-PLGA MPs. The AMB/CM-PLGA MPs showed a remarkably reduced hemolysis (62.2 ± 0.6%) compared to AMB (80.9 ± 1.1%). The nephrotoxicity of AMB/CM-PLGA MPs is significantly lower than that of AMB. In vitro, AMB/CM-PLGA MPs had better inhibitory effects on the adhesion and biofilm formation of Candida albicans compared with AMB. Experiments on mice infected with C. albicans showed that AMB/CM-PLGA MPs have a better therapeutic effect than AMB in vivo. In summary, AMB/CM-PLGA MPs may be a novel and promising therapeutic candidate for fungal infection.  相似文献   
4.
An N-heterocyclic carbene(NHC)-catalyzed enantioselective Mannich reaction of the remote γ-carbon of cyclopropylcarbaldehydes is disclosed for the first time. Diastereo-and enantiomerically enriched multicyclic δ-lactam compound is afforded as the main product from 8 possible stereo-specific isomers through dynamic kinetic asymmetric transformation(DYKAT) processes. Multiple chiral functional molecules can be afforded from the lactam products through simple protocols with retentions of the optical purities.  相似文献   
5.
6.
Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.  相似文献   
7.
Matrine is a traditional botanical pesticide with a broad-spectrum biological activity that is widely applied in agriculture. Halopyrazole groups are successfully introduced to the C13 of matrine to synthesize eight new derivatives with a yield of 78–87%. The insecticidal activity results show that the introduction of halopyrazole groups can significantly improve the insecticidal activity of matrine on Plutella xylostella, Mythimna separata and Spodoptera frugiperda with a corrected mortality rate of 100%, which is 25–65% higher than matrine. The fungicidal activity results indicate that derivatives have a high inhibitory effect on Ceratobasidium cornigerum, Cibberella sanbinetti, Gibberrlla zeae and Collectot tichum gloeosporioides. Thereinto, 4-Cl-Pyr-Mat has the best result, with an inhibition rate of 23–33% higher than that of matrine. Therefore, the introduction of halogenated pyrazole groups can improve the agricultural activity of matrine.  相似文献   
8.
A convenient and regioselective sulfonylation/cyclization of 1,6-enynes with arylazo sulfones has been developed to access a series of sulfonylated γ-butyrolactams.The present reaction could be efficiently conducted under catalyst-and additive-free conditions,in which C-S and C-C bonds were selectively constructed in one-pot procedure.  相似文献   
9.
Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins. Herein we report the formation and crystal structure of a planar square tetranuclear silver cluster when silver ions were mixed with human copper chaperone Atox1. Quantum chemical studies reveal that two Ag 5s1 electrons in the tetranuclear silver cluster fully occupy the one bonding molecular orbital, with the assumption that this Ag4 cluster is Ag42+, leading to extensive electron delocalization over the planar square and significant stabilization. This bonding pattern of the tetranuclear silver cluster represents an aromatic all-metal structure that follows a 4n + 2 electron counting rule (n = 0). This is the first time an all-metal aromatic silver cluster was observed in a protein.

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins.  相似文献   
10.
Drug–drug interactions (DDIs) can trigger unexpected pharmacological effects on the body, and the causal mechanisms are often unknown. Graph neural networks (GNNs) have been developed to better understand DDIs. However, identifying key substructures that contribute most to the DDI prediction is a challenge for GNNs. In this study, we presented a substructure-aware graph neural network, a message passing neural network equipped with a novel substructure attention mechanism and a substructure–substructure interaction module (SSIM) for DDI prediction (SA-DDI). Specifically, the substructure attention was designed to capture size- and shape-adaptive substructures based on the chemical intuition that the sizes and shapes are often irregular for functional groups in molecules. DDIs are fundamentally caused by chemical substructure interactions. Thus, the SSIM was used to model the substructure–substructure interactions by highlighting important substructures while de-emphasizing the minor ones for DDI prediction. We evaluated our approach in two real-world datasets and compared the proposed method with the state-of-the-art DDI prediction models. The SA-DDI surpassed other approaches on the two datasets. Moreover, the visual interpretation results showed that the SA-DDI was sensitive to the structure information of drugs and was able to detect the key substructures for DDIs. These advantages demonstrated that the proposed method improved the generalization and interpretation capability of DDI prediction modeling.

SA-DDI is designed to learn size-adaptive molecular substructures for drug–drug interaction prediction and can provide explanations that are consistent with pharmacologists.  相似文献   
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