Sensitive CE-MS method for monitoring of riociguat and desmethylriociguat levels in human serum

Riociguat is novel antihypertensive drug for treatment of pulmonary hypertension. As such, it is still being tested in many clinical and pharmacokinetic trials. Existing methods that determine serum riociguat and desmethylriociguat (DMR) are based solely on liquid chromatography with mass spectrometry. Therefore, we present a novel capillary electrophoresis with mass spectrometry method (CE-MS) for their determination in human serum as alternative method for ongoing trials. Complete resolution of both analytes was achieved by means of pH optimization of ammonium formate background electrolytes that are fully compatible with ESI/MS detection. Simple liquid-liquid extraction was used as sample pretreatment. The calibration dependence of the method was linear (in the range of 10–1000 ng/mL), with adequate accuracy (90.1–114.9%) and precision (13.4%). LOD and LOQ were arbitrarily set at 10 ng/mL for both analytes. Clinical applicability was validated using serum samples from patients treated with riociguat in pharmacokinetic study and the results corresponded with reference HPLC-MS/MS values. Capillary electrophoresis proved to be sensitive and selective tool for the analysis of riociguat and DMR.     

零维到三维结构中三核铜自旋阻挫簇单元的磁构关系和反对称交换

量子自旋液体是最近几年刚被人们证实除铁磁体、反铁磁体之外的第三种磁性类型,因其有望解释高温超导的运行机制、改变计算机硬盘信息存储方式而在物理、材料等领域备受关注。自旋阻挫作为量子自旋液体的最小单元可能是解开量子自旋液体诸多问题的钥匙,所以在磁学、电学研究领域再一次成为人们研究的热点。基于文献报道的三核铜配合物[Cu3(μ3-OH)(μ-OPz)3(NO3)2(H2O)2]·CH3OH(1),我们合成了三维金属有机框架配合物{[Ag(HOPz)Cu3(μ3-OH)(NO3)3(OPz)2Ag(NO3)]·6H2O}n(2)(HOPz=甲基(2-吡嗪基)酮肟),并从自旋阻挫的角度对二者磁性质进行对比和详细分析。磁化率数据表明自旋间有很强的反铁磁相互作用和反对称交换。通过包含各向同性和反对称交换的哈密顿算符对两者磁学数据进行拟合并研究其磁构关系,所获最佳拟合参数为:配合物1:Jav=-426 cm^-1,g⊥=1.83,g∥=2.00;配合物2:Jav=-401 cm^-1,g⊥=1.85,g∥=2.00。     

A review on machine learning algorithms for the ionic liquid chemical space

There are thousands of papers published every year investigating the properties and possible applications of ionic liquids. Industrial use of these exceptional fluids requires adequate understanding of their physical properties, in order to create the ionic liquid that will optimally suit the application. Computational property prediction arose from the urgent need to minimise the time and cost that would be required to experimentally test different combinations of ions. This review discusses the use of machine learning algorithms as property prediction tools for ionic liquids (either as standalone methods or in conjunction with molecular dynamics simulations), presents common problems of training datasets and proposes ways that could lead to more accurate and efficient models.

In this review article, the authors discuss the use of machine learning algorithms as tools for the prediction of physical and chemical properties of ionic liquids.     

Determination of 5-nitroindazole using silver solid amalgam electrode

Monatshefte für Chemie - Chemical Monthly - The voltammetric behavior of 5-nitroindazole was investigated at polished (p-AgSAE) and at mercury meniscus-modified (m-AgSAE) silver solid amalgam...     

Surface of room temperature ionic liquid [bmim][PF6] studied by polarization- and experimental configuration-dependent sum frequency generation vibrational spectroscopy

Understanding and control of the surface properties such as molecular orientations are of great importance in numerous applications of ionic liquids. However, there remain discrepancies among the previous experimental and theoretical studies on the surface orientation and structures of room temperature ionic liquids(RTIL) systems. In this article, the orientation of 1-butyl-3-methylimidazolium([bmin]) cation at the air/liquid interface of a characteristic RTIL, 1-butyl-3-methylimidazolium hexafluorophosphate([bmim][PF6]), was investigated by the sum frequency generation vibrational spectroscopy(SFG-VS). Detailed polarization and experimental configuration analyses of the SFG-VS spectra showed the possibility of a small spectral splitting in the CH3 symmetric stretching region, which can be further attributed to the probable existence of multiple orientations for the interfacial [bmim] cations. In addition, the(N)–CH3 vibrations were absent, ruling out the prediction by several recent molecular dynamics simulations which state that portions of the [bmim] cations orient with a standing-up(N)–CH3 group at the ionic liquid surface. Hence, new realistic theoretical models have to be developed to reflect the complex nature of the ionic liquid surface.