Simultaneous Determination of Six Immunosuppressants in Human Whole Blood by HPLC-MS/MS Using a Modified QuEChERS Method

A high-performance liquid chromatography-tandem mass spectrometry method was established for the simultaneous determination of mycophenolic acid, mycophenolate mofetil, tacrolimus, rapamycin, everolimus and pimecrolimus in human whole blood by optimizing the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) preparation method. Whole blood was extracted into ethyl acetate, salted out with anhydrous magnesium sulfate, and purified with ethylenediamine-N-propyl silane adsorbent. The supernatant was evaporated under nitrogen until dry and finally reconstituted in methanol. Chromatographic separation was performed on an Agilent Poroshell 120 EC-C18 column in methanol (mobile phase A)-water (optimized for 0.1% acetic acid and 10 mM ammonium acetate, mobile phase B) at a 0.3 mL·min⁻¹ flow rate. Electrospray ionization and positive ion multiple reaction monitoring were used for detection. The time for of analysis was 13 min. The calibration curves range of tacrolimus, rapamycin, everolimus and pimecrolimus were in the range of 1–100 ng·mL⁻¹, mycophenolate mofetil in the range of 0.1–10 ng·mL⁻¹ and mycophenolic acid at 10–1000 ng·mL⁻¹. All correlation coefficients were >0.993. The coefficients of variation (CV, %) for inter-day and intra-day precision were less than 10%, while the spiked recoveries were in the range of 92.1% to 116%. Our method was rapid, sensitive, specific, and reproducible for the simultaneous determination of six immunosuppressants in human whole blood. Importantly, our approach can be used to monitor drug concentrations in the blood to facilitate disease treatment.     

Cu(ii)/SPDO complex catalyzed asymmetric Baeyer–Villiger oxidation of 2-arylcyclobutanones and its application for the total synthesis of eupomatilones 5 and 6

A novel classical kinetic resolution of 2-aryl-substituted or 2,3-disubstituted cyclobutanones of Baeyer–Villiger oxidation catalyzed by a Cu(ii)/SPDO complex is reported for the first time, producing normal lactones in excellent enantioselectivities (up to 96% ee) and regioselectivities (up to >20/1), along with unreacted ketones in excellent enantioselectivities (up to 99% ee). The current transformation features a wide substrate scope. Moreover, catalytic asymmetric total syntheses of natural eupomatilones 5 and 6 are achieved in nine steps from commercially available 3-methylcyclobutan-1-one.

A novel classical kinetic resolution of Baeyer–Villiger oxidation catalyzed by a Cu(ii)/SPDO complex with excellent enantioselectivity, regioselectivity and wide substrate scope is reported for the first time and explore the synthetic application.     

Asymmetric synthesis of chromanone lactones via vinylogous conjugate addition of butenolide to 2-ester chromones

Chiral chromanone lactones are a class of natural products with important biological activity. We report a direct diastereo- and enantioselective vinylogous conjugate addition of butenolide to 2-ester substituted chromones. The transformation proceeded well in the presence of as low as 1 mol% of a chiral N,N′-dioxide/Sc^III complex, 3 Å MS and a catalytic amount of hexafluoroisopropanol (HFIP). The scope of Michael acceptors includes a variety of substituted chromones at different positions, and the desired chromanone lactones upon reduction are afforded in good yield and diastereoselectivity, and excellent enantioselectivity (up to 99% ee). The strategy could be used in the concise synthesis of blennolide C and gonytolide A, C and G.

We report a direct, diastero- and enantioselective vinylogous 1,4-addition of butanolide to 2-ester chromones. A chiral Sc^III complex enabled the reaction to proceed smoothly to give a variety of chraomanone lactones.     

ZnO纳米钉的制备和光学性质研究

通过化学气相沉积(CVD)方法在Si(100)衬底上制备出新型的ZnO纳米钉结构.X射线衍射(XRD)结果表明纳米钉是六角纤锌矿结构.纳米钉顶部对角线在450～750 nm之间,纳米钉长度为几个微米.研究了不同气氛下退火样品的可见发光性质,认为绿光发射来自于导带电子和反位氧中空穴的辐射复合.     

Improved Stretchable and Sensitive Fe Nanowire-Based Strain Sensor by Optimizing Areal Density of Nanowire Network

Flexible strain sensors, when considering high sensitivity and a large strain range, have become a key requirement for current robotic applications. However, it is still a thorny issue to take both factors into consideration at the same time. Here, we report a sandwich-structured strain sensor based on Fe nanowires (Fe NWs) that has a high GF (37–53) while taking into account a large strain range (15–57.5%), low hysteresis (2.45%), stability, and low cost with an areal density of Fe NWs of 4.4 mg/cm². Additionally, the relationship between the contact point of the conductive network, the output resistance, and the areal density of the sensing unit is analyzed. Microscopically, the contact points of the conductive network directly affect the sensor output resistance distribution, thereby affecting the gauge factor (GF) of the sensor. Macroscopically, the areal density and the output resistivity of the strain sensor have the opposite percolation theory, which affects its linearity performance. At the same time, there is a positive correlation between the areal density and the contact point: when the stretching amount is constant, it theoretically shows that the areal density affects the GF. When the areal density reaches this percolation threshold range, the sensing performance is the best. This will lay the foundation for rapid applications in wearable robots.     

Structural and Functional Analysis of the Pyridoxal Phosphate Homeostasis Protein YggS from Fusobacterium nucleatum

Pyridoxal 5′-phosphate (PLP) is the active form of vitamin B6, but it is highly reactive and poisonous in its free form. YggS is a PLP-binding protein found in bacteria and humans that mediates PLP homeostasis by delivering PLP to target enzymes or by performing a protective function. Several biochemical and structural studies of YggS have been reported, but the mechanism by which YggS recognizes PLP has not been fully elucidated. Here, we report a functional and structural analysis of YggS from Fusobacterium nucleatum (FnYggS). The PLP molecule could bind to native FnYggS, but no PLP binding was observed for selenomethionine (SeMet)-derivatized FnYggS. The crystal structure of FnYggS showed a type III TIM barrel fold, exhibiting structural homology with several other PLP-dependent enzymes. Although FnYggS exhibited low (<35%) amino acid sequence similarity with previously studied YggS proteins, its overall structure and PLP-binding site were highly conserved. In the PLP-binding site of FnYggS, the sulfate ion was coordinated by the conserved residues Ser201, Gly218, and Thr219, which were positioned to provide the binding moiety for the phosphate group of PLP. The mutagenesis study showed that the conserved Ser201 residue in FnYggS was the key residue for PLP binding. These results will expand the knowledge of the molecular properties and function of the YggS family.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.