Discovery and identification of interspecies peptide biomarkers in the seahorse species using liquid chromatography tandem mass spectrometry and chemometrics.

Seahorses have important edible and medicinal values including strengthening the body, tonifying the liver and kidneys, and reducing swelling. And there are abundant seahorse species on Earth. Many seahorses have large price differences due to the scarcity of resources, and some seahorses with similar appearances appear to be confused for use. While in market trading, Hippocampus is susceptible to loss of specialized morphology characteristics, making it difficult to distinguish between specific species. Here we report an effective method based on peptide biomarkers for the identification of seahorse species. Peptide biomarkers for each species were predicted using nano-liquid chromatography-tandem mass spectrometry (Nano-LC-MS/MS) combined with chemometrics software. One unique biomarker peptide for each species was synthesized and verified, and finally developed a liquid chromatography tandem mass spectrometry (LC-MS/MS) multiple reaction monitoring method. The results indicate that the method has great potential for species-specific identification of seahorses and their preparations, among others.

Simultaneous determination of four active compounds in Centella asiatica by supramolecular solvent-based extraction coupled with high performance liquid chromatography-tandem mass spectrometry.

In the present study, a new and rapid method for determining four bioactive compounds of Centella asiatica (C. asiatica) in herbs was developed based on high performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). Supramolecular solvent (SUPRAS), formed by n-hexanol, tetrahydrofuran (THF) and water, was used for extracting madecassoside (MS), asiaticoside (AS), asiatic acid (AA) and madecassic acid (MA) from herbs. The sample was extracted with 4 mL of SUPRAS for 5 min. Then centrifugation was performed for phase separation followed by direct analysis by HPLC-MS/MS. Driving forces for the extraction of herbs in the SUPRAS involved both dispersion and hydrogen bond interactions. The effect of the parameters, including compounds of supramolecular solvents, dosage and vortex time, on the extraction efficiency was investigated. The recoveries were carried out at three levels with spiked samples and in the range of 91.6%-99.9%, with relative standard deviations between 1.7%-7.9%. The novel SUPRAS method, coupled with HPLC-MS/MS, was proved to be efficiency, green, and sensitive. It was applied for determination of four target compounds in herbs.

Polycephalums A and B, New Anticoagulant Constituents Isolated from Clinopodium polycephalum.

Two previously undescribed compounds (1 and 2) were isolated from Clinopodium polycephalum, a medicinal plant distributed in southwestern and eastern China. Their structures were elucidated using MS analyses and extensive 2D-homo and heteronuclear NMR data interpretations. Both compounds 1 and 2 could significantly shorten APTT and PT, and their procoagulant effect was comparable to that of positive drugs. At the same time, compound 2 had certain antioxidant activity (IC50 value of 2.25±0.05 µM in ABTS assay).

An Efficiently Doped PEDOT:PSS Ink Formulation via Metastable Liquid-Liquid Contact for Capillary Flow-Driven, Hierarchically and Highly Conductive Films.

With commercial electronics transitioning toward flexible devices, there is a growing demand for high-performance polymers such as poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) (PEDOT:PSS). Previous breakthroughs in promoting the conductivity of PEDOT:PSS, which mainly stem from solvent-treatment and transfer-printing strategies, remain as inevitable challenges due to the inefficient, unstable, and biologically incompatible process. Herein, a scalable fabrication of conducting PEDOT:PSS inks is reported via a metastable liquid-liquid contact (MLLC) method, realizing phase separation and removal of excess PSS simultaneously. MLLC-doped inks are further used to prepare ring-like films through a compromise between the coffee-ring effect and the Marangoni vortex during evaporation of droplets. The specific control over deposition conditions allows for tunable ring-like morphologies and preferentially interconnected networks of PEDOT:PSS nanofibrils, resulting in a high electrical conductivity of 6,616 S cm-1 and excellent optical transparency of the film. The combination of excellent electrical properties and the special morphology enables it to serve as electrodes for touch sensors with gradient pressure sensitivity. These findings not only provide new insight into developing a simple and efficient doping method for commercial PEDOT:PSS ink, but also offer a promising self-assembled deposition pattern of organic semiconductor films, expanding the applications in flexible electronics, bioelectronics as well as photovoltaic devices.

Tunable Berreman mode in highly conductive organic thin films.

The unique performances of Epsilon-near-zero (ENZ) materials allow them to play a crucial role in many optoelectronic devices and have spawned a wide range of inventive uses. In this paper, we found that the modified PEDOT:PSS film formed with a kind of so-called "Metastable liquid-liquid Contact (MLLC)" solution treatment method can achieve a wide tuning of ENZ wavelength from 1270 nm to 1550 nm in the near-infrared region. We further analyzed the variation trend of imaginary permittivity for these samples with different ENZ wavelengths. The Berreman mode was successfully excited by a simple structural design to realize a tunable polarization absorber.

Fingerprint analysis of phenolic acid extract of Salvia miltiorrhiza by digital reference standard analyzer with one or two reference standards.

BACKGROUND: Fingerprint analysis and simultaneous multi-components determination are crucial for the holistic quality control of traditional Chinese medicines (TCMs). Yet, reference standards (RS) are often commercially unavailable and with other shortages, which severely impede the application of these technologies. METHODS: A digital reference standard (DRS) strategy and the corresponding software called DRS analyzer, which supports chromatographic algorithms, spectrum algorithms, and the combination of these algorithms, was developed. The extensive function also enabled the DRS analyzer to recommend the chromatographic column based on big data. RESULTS: Various quality control methods of fingerprints of 11 compounds in polyphenolic acid extract of Salvia miltiorrhiza (S. miltiorrhiza) were developed based on DRS analyzer, involving relative retention time (RRT) method, linear calibration using two reference substances (LCTRS) technique, RRT combined with Photon Diode Array (PDA) method, LCTRS combined with PDA method. Additionally, the column database of samples was established. Finally, our data demonstrated that the DRS analyzer could accurately identify 11 compounds of the samples, using only one or two physical RSs. CONCLUSIONS: The DRS strategy is an automated, intelligent, objective, accurate, eco-friendly, universal, sharing, and promising method for overall quality control of TCMs that requires the usage of fewer RSs.

Application of Chemometric Algorithms in the High-Performance Thin-Layer Chromatography Fingerprint of Traditional Chinese Medicines.

Background: The use of HPTLC fingerprinting for the analysis of traditional Chinese medicines (TCMs) usually involves several image-processing steps. However, these image-processing steps are time consuming. Objective: We describe a new approach that applies artificial neural networks (ANN) directly to raw high-performance thin-layer chromatography HPTLC images. Methods: This approach combines image processing and chemometric modeling and was used to classify TCMs [dried tangerine eel (Chen Pi), green tangerine peel (Qing Pi), immature bitter orange fruit, and bitter orange fruit (Zhi Qiao)]. Images of the plates were processed with Chempattern and chemometric analysis including PCA, PLS-DA, and kNN were carried out all by ChemPattern. Results: The ANN model has an accuracy of 100.00% in all training, validation, and test sets, indicating excellent predictive performance and good generalization ability. The k-nearest neighbors (kNN) and partial least-square discriminant analysis (PLS-DA) models have accuracies of 90.91 and 72.73%, respectively, with the independent test set. The kNN model is also accurate, simple, and can be easily interpreted. Conclusions: HPTLC fingerprinting, combined with advanced image processing and proper chemometric algorithms, is a simple, efficient, and accurate method for the analysis of TCMs. Highlights: HPTLC fingerprints of four TCM crude drugs derived from Citrus spp. were compared by using image analysis algorithms. A new approach that applied ANN directly to raw HPTLC fingerprint images was described. Three image analysis algorithms based on kNN, PLS-DA and ANN are compared in the paper. The ANN model shows excellent predictive performance with high accuracy in test sets.