Aim: To evaluate the antioxidant capacity and quality of traditional Chinese medicines using TLC-bioautography.
Methods: Two chromatograms of each crude drug sample were obtained, after developing, by spraying with 1,1-diphenyl-2-picrylhydrazyl (DPPH) solution in ethanol and classical stained reagents, separately. The images sprayed with DPPH solution were captured under light after the plates were heated at 40 degrees C for 30 min, and scanned using video scan software to get peak areas of active compounds.
Results: Total peak areas of the spots on TLC were calculated to evaluate the antioxidant capacity of the tested crude drugs from different habitats and sources. The results indicated that Radix Linderae cultivated in Tiantai (Zhejiang province), Cortex Magnoliae Officinalis cultivated in Liangshan (Sichuan province), and Fructus Perillae acquired in Shanghai have the highest scavenging properties towards DPPH in their respective TLC-autographic assays. Norisoboldine, magnolol and honokiol, luteolin, apigenin and an unknown compound "U" proved to be the major antioxidant components in the corresponding crude drugs as they contribute the dominating peak areas to the total ones.
Conclusion: TLC-bioautography can not only be used for screening of the components with antioxidant potency but also for the purpose of quality evaluation of traditional Chinese medicines at the same time, and the method proved to be selective, simple and reproducible.
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Purpose: To explore the evaluation value of contrast enhanced ultrasound (CEUS) quantitative parameters in ischemic-type biliary lesions after liver transplantation to assist its early-diagnosis.
Methods: Patients who underwent liver transplantation and intravenous CEUS at Beijing Friendship Hospital, Capital Medical University from June 25, 2020 to December 28, 2022 and were diagnosed with Ischemic-type biliary lesions (ITBLs) by Magnetic Resonance Cholangiopancreatography (MRCP) or Endoscopic Retrograde Cholangiopancreatography (ERCP) or Percutaneous Transhepatic Cholangiography (PTC) were prospectively enrolled. SonoLiver software was used to quantitatively analyze the contrast images, transplanted livers with normal biliary tracts as the control group.
Sensors (Basel)
January 2025
Skin Sensing Research Group, School of Health Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Southampton SO17 1HE, UK.
Measuring interface pressure is currently used in a variety of settings, e.g., automotive or clinical, to evaluate pressure distribution at support surface interfaces.
View Article and Find Full Text PDFJ Orthop Surg Res
January 2025
Department of Orthopedic Surgery, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Middle Road, Shanghai, 200072, People's Republic of China.
Background: Controversy exists regarding the reconstruction of bone defects in Enneking III. This study aimed to use the finite element analysis (FEA) method to clarify (1) the utility of reconstructing the pelvis Enneking III region and (2) the optimal approach for this reconstruction.
Methods: FEA models were generated for three types of Enneking III defects in the pelvis, replacing all the defect areas in region III with a sizable solid box for topology optimization (TO).
J Orthop Surg Res
January 2025
Medical College, Tibet University, Lhasa, Tibet, 850000, China.
Background: Knee osteoarthritis (KOA) is a prevalent degenerative joint disease. The primary pathological manifestations of KOA include articular cartilage degeneration, joint space narrowing, and osteophyte formation, leading to a spectrum of symptoms, including joint pain, stiffness, reduced mobility, diminished muscle strength, and severe disability. We aimed to utilize a meta-analysis to evaluate the efficacy of isokinetic muscle strengthening training (IMST) as a rehabilitation treatment for KOA in lowland areas.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Biological and Chemical Systems - Functional Molecular Systems (IBCS-FMS), Karlsruhe Institute of Technology (KIT), Karlsruhe, 76344, Germany.
Multiple linear regression models were trained to predict the degree of substitution (DS) of cellulose acetate based on raw infrared (IR) spectroscopic data. A repeated k-fold cross validation ensured unbiased assessment of model accuracy. Using the DS obtained from H NMR data as reference, the machine learning model achieved a mean absolute error (MAE) of 0.
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