[Simultaneous determination of 7 benzodiazepines in human plasma by UHPLC-MS/MS].

The study was designed to develop the method for determination of 7 benzodiazepines concentration in human plasma. UHPLC-MS/MS was adopted to analyze plasma with protein precipitated by acetonitrile. Citalopram was used as an internal standard. Plasma samples were separated on CORTECS UHPLC C18 column with the mobile phase of aqueous solution (0.01% formic acid) - methanol (0.01% formic acid) at a flow rate of 0.3 m L·min(-1). Multiple reaction monitoring (MRM) mode was performed in combiation with electrospray ionization source operating in the positive ionization mode. The liner calibration curve of midazolam, nitrazepam, estazolam, clonazepam, lorazepam, triazolam and diazepam were obtained in the concentration range of 1.05-840 (r = 0.999 4), 2.06-824 (r = 0.998 1), 2.02-1 616 (r = 0.994 7), 6.18-2 472 (r = 0.997 9), 6.12-2 448 (r = 0.997 4), 3.02-2 416 (r = 0.990 2), 1.02-816 (r = 0.998 8) ng·m L(-1), respectively. The lowest detection limit were 0.02, 0.52, 0.51, 1.55, 0.77, 0.76, 0.02 ng·m L(-1), respectively. The RSD of inter-day and intra-day were less than 10.81%. The relative recovery was 81.46%-106.53%. The method was successfully applied to clinical analysis of blood samples from patients.

Selaginellin M, a new selaginellin derivative from Selaginella pulvinata.

A new selaginellin derivative, selaginellin M (1), together with one known compound, selaginellin E (2), was isolated from Selaginella pulvinata. The structure of the new compound was elucidated and named as (R,S)-4-((4'-hydroxy-4-((2-hydroxyethoxy)methyl))-3-((4-hydroxyphenyl)ethynyl)biphenyl-2-yl)(4-hydroxyphenyl)methylene)cyclohexa-2,5-dienone on the basis of the spectroscopic data including UV, IR, 1D, and 2D NMR as well as HR-ESI-MS analysis.

MPS-Net: Multi-Point Supervised Network for CT Image Segmentation of COVID-19.

The new coronavirus, which has become a global pandemic, has confirmed more than 88 million cases worldwide since the first case was recorded in December 2019, causing over 1.9 million deaths. Since COIVD-19 lesions have clear imaging features on CT images, it is suitable for the auxiliary diagnosis and treatment of COVID-19. Deep learning can be used to segment the lesions areas of COVID-19 in CT images to help monitor the epidemic situation. In this paper, we propose a multi-point supervision network (MPS-Net) for segmentation of COVID-19 lung infection CT image lesions to solve the problem of a variety of lesion shapes and areas. A multi-scale feature extraction structure, a sieve connection structure (SC), a multi-scale input structure and a multi-point supervised training structure were implemented into MPS-Net. In order to increase the ability to segment various lesion areas of different sizes, the multi-scale feature extraction structure and the sieve connection structure will use different sizes of receptive fields to extract feature maps of various scales. The multi-scale input structure is used to minimize the edge loss caused by the convolution process. In order to improve the accuracy of segmentation, we propose a multi-point supervision training structure to extract supervision signals from different up-sampling points on the network. Experimental results showed that the dice similarity coefficient (DSC), sensitivity, specificity and IOU of the segmentation results of our model are 0.8325, 0.8406, 09988 and 0.742, respectively. The experimental results demonstrated that the network proposed in this paper can effectively segment COVID-19 infection on CT images. It can be used to assist the diagnosis and treatment of new coronary pneumonia.

A new flavonoid from Selaginella tamariscina (Beauv.) Spring.

A new flavonoid, 6-(2-hydroxy-5-carboxyphenyl)-apigenin (1), together with two new natural products, 3-(4-hydroxyphenyl)-6,7-dihydroxy coumarin (2), 1-methoxy-3-methylanthraquinone (3) and four known compounds, were isolated from Selaginella tamariscina (BEAUV.) SPRING. The structures of the new isolated compounds were elucidated on the basis of 1D and 2D NMR as well as ESI-HR-MS spectroscopic analysis.