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.

A Multi-Scale Feature Fusion Method Based on U-Net for Retinal Vessel Segmentation.

Computer-aided automatic segmentation of retinal blood vessels plays an important role in the diagnosis of diseases such as diabetes, glaucoma, and macular degeneration. In this paper, we propose a multi-scale feature fusion retinal vessel segmentation model based on U-Net, named MSFFU-Net. The model introduces the inception structure into the multi-scale feature extraction encoder part, and the max-pooling index is applied during the upsampling process in the feature fusion decoder of an improved network.

Identification of characteristic heroin metabolites in urine based on data-mining technology and multivariate statistics analysis combined with a targeted verification approach for distinguishing heroin abusers.

A common phenomenon shows that ingestion of opium poppy shell-containing drugs can result in a "false-positive" urinalysis test result for mandatory or workplace heroin abuse screening. Owing to the short detection window (8 h in urine) of the characteristic heroin metabolite 6-monoacetylmorphine (6-MAM) confirmation or exclusion of heroin abusers still presents major challenges for toxicologists. In this work, we developed an ultra-performance liquid chromatography-time-of-flight mass spectrometry method (UPLC-TOF-MS) with online data acquisition and multiple post-data-mining technologies combined with a multivariate statistical and batch validation analysis workflow to assess the characteristic urine metabolites of heroin abusers.

[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.

Simultaneous Determination of 18 Chemical Constituents in Traditional Chinese Medicine of Antitussive by UPLC-MS-MS.

In this study, a simple, rapid and sensitive liquid chromatography-tandem mass spectrometry (LC-MS-MS) method was developed for the simultaneous determination of 18 compounds, namely, morphine, codeine, tuberostemonine, thebaine, papaverine, scopoletin, liquiritin, narcotine, gynaroside, hyperoside, hesperidin, isoliquiritin, liquiritigenin, luteolin, isoliquiritigenin, apigenin, formononetin and glycyrrhizic acid in traditional Chinese medicine of antitussive. Analytes were chromatographically separated on a Waters C18 column under gradient elution with a mobile phase of water containing 0.1‰ HOAc (A) and methanol (MeOH) containing 0.

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.

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.

[Determination of six active components in three species of genus Swertia by HPLC multiwavelength with detection].

Objective: To develop an HPLC method for the quantification of six active components in three species (Swertia davidi, S. nervosa and S. mussotii) .