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The nonvolatile and volatile compounds in the peels of 13 Citrus reticulata cultivars (4 mandarins, 5 tangerines, and 4 hybrids) and 5 Citrus sinensis (sweet oranges) cultivars were analyzed.Initially, 66 volatile compounds were detected using gas chromatog.-mass spectrometry (GC-MS).Tangerines were distinguished from other citrus cultivars (mandarins, sweet oranges, hybrids) by having higher volatile oil extraction rates and higher relative contents of o-Cymene, α-Terpinene, D-α-Pinene, Terpinolene, γ-Terpinene, L-β-Pinene, and 3-Thujene.Addnl., 115 nonvolatile compounds were tentatively identified using ultraperformance liquid chromatog.-Q-Exactive Orbitrap tandem mass spectrometry (UPLC-Q-Exactive Orbitrap-MS).C. sinensis contained fewer compounds than did C. reticulata.Pterostilbene was detected in all tangerines but not in mandarins and hybrids, suggesting its potential as a marker compound for differentiating tangerines from other C. reticulata.Lastly, a high-performance liquid chromatog.-photodiode array (HPLC-PDA) was used to quantify 9 major nonvolatile components.Heat map and principal component anal. showed that the contents of tangerines differed from other cultivars (sweet oranges, mandarins, and hybrids).It may be caused by the higher content of synephrine, nobiletin, tangeretin, and 5-hydroxy-6,7,8,3′,4′-pentamethoxyflavone in tangerines.The study may obtain information for the application of different types of C. reticulata (tangerines, mandarins, or hybrids) and C. sinensis peels, thereby promoting their recycling.

01 Dec 2024·Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Application of artificial intelligence combined with near infrared spectroscopy in the continuous counter-current extraction process of Angelica dahurica formula granules

Article

Author: Lin, Boran ; Huang, Shouyao ; Yang, Chunguo ; Zang, Hengchang ; Li, Lian ; Nie, Lei ; Ma, Xiaobo ; Wang, Haowei ; Zhang, Mengyu ; Wu, Aoli

The establishment of near infrared (NIR) spectroscopy model mostly relies on chemometrics, and spectral analysis combined with artificial intelligence (AI) provides a new way of thinking for pharmaceutical quality inspection, new algorithms such as back propagation artificial neural networks (BP-ANN) and swarm intelligence optimization algorithms such as sparrow search algorithm (SSA) provide core technical support. In order to explore the application of AI in the pharmaceutical field, in this study, Angelica dahurica formula granules with a relatively complex system were selected as the research object. Quantitative analysis models were established by using partial least squares regression (PLSR) with a micro-NIR spectrometer, and BP-ANN modeling results were compared. For the best PLSR models of six characteristic components in the continuous counter-current extract of Angelica dahurica, R²_v of imperatorin was lower than 0.90, and the RPD values of imperatorin, phellopterin, and isoimperatorin were even lower than 1. When the prediction model established by SSA-BP-ANN was used for quantitative analysis, R²_v of six components were all higher than 0.92, and the RPD values all higher than 1.5, which proved that the BP-ANN method was better than PLSR. This study confirmed that in the continuous counter-current extraction progress of Angelica dahurica formula granules, the use of micro-NIR spectrometer combined with AI could realize the rapid prediction of the contents of six characteristic components. The comparison results provided a scientific reference for the process analysis and on-line monitoring in the production process of traditional Chinese medicine by micro-NIR spectrometer combined with AI.

13 Aug 2024·Analytical Chemistry

Enhanced Recognition of a Herbal Compound Epiberberine by a DNA Quadruplex-Duplex Structure

Article

Author: Wang, Zi ; Shao, Yong ; Lu, Rongguang ; Xu, Yingyi ; Shu, Zhiyu ; Ni, Jie ; Krishna, Manchugondanahalli S. ; Lian, Yun ; Sun, Dongmei ; Liu, Jingyan ; Vandana, J. Jeya ; Xu, Yunong ; Stjepanovic, Goran ; Deng, Liping ; Zhou, Fangyu ; Wu, Song ; Chen, Gang ; Wang, Anni ; Xiong, Chi ; Cheng, Gui-Juan ; Jiang, Cheng ; Mai, Xinyi ; Huang, Shaohui ; Bai, Shiyao ; Chiang, Ying-Chih ; Zhan, Xuan ; Li, Yuqing

The small molecule epiberberine (EPI) is a natural alkaloid with versatile bioactivities against several diseases including cancer and bacterial infection. EPI can induce the formation of a unique binding pocket at the 5' side of a human telomeric G-quadruplex (HTG) sequence with four telomeric repeats (Q4), resulting in a nanomolar binding affinity (K_D approximately 26 nM) with significant fluorescence enhancement upon binding. It is important to understand (1) how EPI binding affects HTG structural stability and (2) how enhanced EPI binding may be achieved through the engineering of the DNA binding pocket. In this work, the EPI-binding-induced HTG structure stabilization effect was probed by a peptide nucleic acid (PNA) invasion assay in combination with a series of biophysical techniques. We show that the PNA invasion-based method may be useful for the characterization of compounds binding to DNA (and RNA) structures under physiological conditions without the need to vary the solution temperature or buffer components, which are typically needed for structural stability characterization. Importantly, the combination of theoretical modeling and experimental quantification allows us to successfully engineer Q4 derivative Q4-ds-A by a simple extension of a duplex structure to Q4 at the 5' end. Q4-ds-A is an excellent EPI binder with a K_D of 8 nM, with the binding enhancement achieved through the preformation of a binding pocket and a reduced dissociation rate. The tight binding of Q4 and Q4-ds-A with EPI allows us to develop a novel magnetic bead-based affinity purification system to effectively extract EPI from Rhizoma coptidis (Huang Lian) extracts.

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Pipeline

Pipeline Snapshot as of 05 Feb 2025

The statistics for drugs in the Pipeline is the current organization and its subsidiaries are counted as organizations,Early Phase 1 is incorporated into Phase 1, Phase 1/2 is incorporated into phase 2, and phase 2/3 is incorporated into phase 3

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