A multi-module structure labelled molecular network orients the chemical profiles of traditional Chinese medicine prescriptions: Xiaoyao San, as an example.

Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) technology has emerged as a crucial tool for identifying components in traditional Chinese medicine (TCM). However, the characterization of the chemical profiles of TCM prescriptions (TCMPs) which often consist of multiple herbal medicines and contain diverse structural types, presents several challenges, such as component overlapping and time-consuming. In this study, a novel strategy known as the multi-module structure labelled molecular network (MSLMN), which integrates molecular networking, database annotation, and cluster analysis techniques, has been successfully proposed, which facilitates the identification of chemical constituents by leveraging a high-structural similarity ion list derived from the MSLMN. It has been effectively applied to analyze the chemical profile of Xiaoyao San (XYS), a classical TCMP. Through the MSLMN method, a total of 302 chemical constituents were identified, covering nine structural types in XYS. Furthermore, a validated and quantitative analytical method using UHPLC-QqQ-MS/MS technology was developed for 31 identified chemicals, encompassing all eight herbal medicines present in XYS, and the developed analytical approach was applied to investigate the content distribution across 40 different batches of commercially available XYS. In total, the proposed strategy has practical significance for improving the insight into the chemical profile of XYS and serves as a valuable approach for handling complex system data based on UHPLC-MS, particularly for TCMPs.

The role of circadian clock genes in colorectal carcinoma: Novel insights into regulatory mechanism and implications in clinical therapy.

Colorectal cancer (CRC) is a lethal malignancy with limited treatment strategies. Accumulating evidence indicates that CRC tumorigenesis, progression and metastasis are intimately associated with circadian clock, an inherent 24-h cycle oscillation of biochemical, physiological functions in almost every eukaryote. In the present review, we summarize the altered expression level of circadian genes in CRC and the prognosis associated with gene abundance switch. We illustrate the function and potential mechanisms of circadian genes in CRC pathogenesis and progression. Moreover, circadian based-therapeutic strategies including chronotherapy, therapeutics targeting potential circadian components, and melatonin treatment in CRC are also highlighted.

A compounds annotation strategy using targeted molecular networking for offline two-dimensional liquid chromatography-mass spectrometry analysis: Yupingfeng as a case study.

Component overlapping and long-time consumption hinder the data processing of offline two-dimensional liquid chromatography mass spectrometry (offline 2D-LC MS) system. Although molecular networking has been commonly employed in data processing of liquid chromatography mass spectrometry (LC-MS), its application in offline 2D-LC MS is challenged by voluminous and redundant data. In light of this, for the first time, a data deduplication and visualization strategy combining hand-in-hand alignment with targeted molecular networking (TMN) for compounds annotation of offline 2D-LC MS data was developed and applied to the chemical profile of Yupingfeng (YPF), a classical traditional Chinese medicine (TCM) prescription, as a case study. Firstly, an offline 2D-LC MS system was constructed for the separation and data acquisition of YPF extract. Then the data of 12 fractions derived from YPF were deconvoluted and aligned as a whole data file by hand-in-hand alignment, resulting in a 49.2% reduction in component overlapping (from 17951 to 9112 ions) and an improvement in the MS2 spectrum quality of precursor ions. Subsequently, the MS2-similarity adjacency matrix of focused parent ions was computed by a self-building Python script, which realized the construction of an innovative TMN. Interestingly, the TMN was found to be able to efficiently distinguish and visualize the co-elution, in-source fragmentations and multi-type adduct ions in a clustering network. Consequently, a total of 497 compounds were successfully identified depending on only seven TMN analysis guided by product ions filtering (PIF) and neutral loss filtering (NLF) for the targeted compounds in YPF. This integrated strategy improved the efficiency of targeted compound discovery in offline 2D-LC MS data, also shown a huge scalability in accurate compound annotation of complex samples. In conclusion, our study developed available concepts and tools while providing a research paradigm for efficient and rapid compound annotation in complex samples such as TCM prescriptions, with YPF as an example.

A five-dimensional data collection strategy for multicomponent discovery and characterization in Traditional Chinese Medicine: Gastrodia Rhizoma as a case study.

Establishing the identity of bioactive compounds to control the quality of Traditional Chinese Medicines is made more challenging by the complexity of the metabolite matrix, the existence of isomers, and the range of compound concentration and polarity observed between individual samples of the same plant in a multicomponent preparation. In addition, LC-MS analysis has limited capability for the separation and analysis of potentially important trace compounds and isomers, which hinders the comprehensive metabolite characterization of functional foods and Traditional Natural Medicine. To facilitate and improve the chemical composition characterization and enhance metabolite discernment, a comprehensive strategy was developed which integrates ion mobility mass spectrometry (IMS) with offline two-dimensional liquid chromatography based on hydrophilic interaction chromatography (HILIC) and conventional reversed phase (RP) C18 chromatography. Through application of the HILIC × RP offline 2D-LC approach, trace compounds were enriched and separated promoting a more efficient and detailed analysis of the matrix complexity. Comprehensive non-targeted multidimensional data (Rt1D, Rt2D, MS, CCS and MS/MS) and data-independent-acquisition (DIA) mass data of the metabolites in complex food and drug samples were obtained in the IMS-DIA-MS/MS mode on a Waters-SYNAPT G2-Si mass spectrometer with an ESI source. Through the application of high-efficiency neutral loss (NLs) and diagnostic product ions (DPIs) filter strategies, information from DIA mass data permitted the rapid detection and identification of compounds. The identification coverage of metabolites with low-quality MS/MS data was also improved. In the absence of analytical standards, Collision Cross Section (CCS) prediction and matching strategies based on theoretical chemical structures provided a method to distingish isomers. To demonstrate the efficacy of the technique this comprehensive strategy was applied to the compound characterization of Gastrodia Rhizoma (GR). Characterization of 272 compounds was achieved, including 146 unreported compounds. The results affirm that this comprehensive five-dimensional data collection strategy has the capacity to support the in-depth study of the high level of chemical diversity in Traditional Chinese Medicines.

Gastrodia elata Blume Polysaccharides: A Review of Their Acquisition, Analysis, Modification, and Pharmacological Activities.

Gastrodia elata Blume (G. elata) is a valuable Traditional Chinese Medicine (TCM) with a wide range of clinical applications. G. elata polysaccharides, as one of the main active ingredients of G. elata, have interesting extraction, purification, qualitative analysis, quantitative analysis, derivatization, and pharmacological activity aspects, yet a review of G. elata polysaccharides has not yet been published. Based on this, this article summarizes the progress of G. elata polysaccharides in terms of the above aspects to provide a basis for their further research and development.