Salvianolate lyophilized injection (SLI), a freeze-dried powder injection derived from aqueous extract of S. miltiorrhiza, is therapeutically used to treat the syndrome of blood stasis and collateral blockage during the recovery period after stroke. To date, it has remained a significant challenge to comprehensively characterize the compounds of SLI, particularly the minor components with potential bioactivities, in one sample injection analysis. Using an integrative four scan modes approach coupled with ultra-high performance liquid chromatography-triple quadrupole-linear ion trap mass spectrometry (UHPLC-QTRAP-MS/MS), we propose a novel, sensitive, and simple strategy for systematic and rapid profiling of the chemical components of SLI. First, an in-house database of constituents from the water-soluble extract of Danshen was created. Second, the fragmentation behaviors of the representative components in SLI were obtained using the untargeted scan mode enhanced MS (EMS)-information dependent acquisition (IDA)-enhanced product ion (EPI). The specific fragments acquired were then utilized to conduct precursor ion (Prec) and neutral loss (NL)-IDA-EPI scans. Following that, a sensitive predictive multiple reaction monitoring (pMRM)-IDA-EPI scan method with 454 transitions was developed based on the prominent fragment ions and plausible predictions. A total of 171 compounds were tentatively identified from SLI. Among them, 27 minor components have not been previously reported. This strategy allows most isomeric compounds at trace levels to be readily distinguished and annotated. Finally, 15 batches of 13 representative components in SLI selected by the qualitative results were accurately quantified. Salvianolic acid A (Sal A), Sal B, Sal D, lithospermic acid (LA), and rosmarinic acid (RA) were proved to be the predominant constituents. Sal B had the highest amount (195.08-350.46 μg·mg), followed by LA, Sal A, Sal D, and RA. Moreover, these 15 batches of samples showed good uniformity, and no abnormal batches existed. These results suggest that this novel strategy can accelerate the identification of undiscovered chemical components and serve as an alternative method for in-depth profiling of compounds in other traditional Chinese medicines (TCMs).
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http://dx.doi.org/10.1016/j.jpba.2022.114769 | DOI Listing |
World J Gastroenterol
January 2025
College of Medicine, Federal University of Alagoas, Maceio 57072-970, Alagoas, Brazil.
Although the liver has a remarkable regenerative capacity, sepsis-associated liver injury (SLI) is a complication often seen in intensive care units. Due to its role in immune and inflammatory regulation, the liver is particularly vulnerable during severe infections. Understanding the global prevalence, causes, and management of SLI is essential to improve outcomes and reduce healthcare costs.
View Article and Find Full Text PDFJ Ethnopharmacol
November 2024
Department of General Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, 300122, PR China; Tianjin Key Laboratory of General Surgery in Construction, Tianjin Union Medical Center Tianjin, 300122, PR China. Electronic address:
Ethnopharmacological Relevance: As a traditional Chinese medicine, Salvia miltiorrhiza Bunge has been widely used to treat ischemic and inflammation-related diseases for more than 2000 years. S. miltiorrhiza Bunge has hepatoprotective effects, but the underlying mechanism is not fully understood.
View Article and Find Full Text PDFAcc Chem Res
November 2024
Department of Chemistry, Texas A&M University, College Station, Texas 77843, United States.
ConspectusMetal-organic frameworks (MOFs) represent a sophisticated blend of inorganic and organic components, promoting the development of coordination chemistry greatly and offering a versatile platform for tailored functionalities. By combining various metal nodes, organic linkers, and functional guests, MOFs provide numerous pathways for their design, synthesis, and customization. Among these, sequential linker installation (SLI) stands out as a novel and crucial strategy, enabling the precise integration of desired properties and functions at the atomic scale.
View Article and Find Full Text PDFImplement Sci Commun
September 2024
British Population Health Sciences Institute, University of Bristol, Bristol, UK.
Comput Biol Med
May 2024
School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield, Australia; Centre for Health Research, University of Southern Queensland, Australia. Electronic address:
Background: Timely detection of neurodevelopmental and neurological conditions is crucial for early intervention. Specific Language Impairment (SLI) in children and Parkinson's disease (PD) manifests in speech disturbances that may be exploited for diagnostic screening using recorded speech signals. We were motivated to develop an accurate yet computationally lightweight model for speech-based detection of SLI and PD, employing novel feature engineering techniques to mimic the adaptable dynamic weight assignment network capability of deep learning architectures.
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