A systematic comparison was made of the detected metabolite profiles for two plant materials (black beans and soybeans) and a dietary supplement (black cohosh) extracted using sequential (hexane, ethyl acetate, and 50% aqueous methanol) and direct extraction with three solvent systems (80% aqueous methanol, methanol/chloroform/water (2.5:1:1, v/v/v) and water). Extracts were analyzed by LC-MS (without derivatization) and GC-FID (with BSTFA/TMCS derivatizations). For sequential extraction, HPLC-UV and BSTFA/TMCS-derivatized GC-FID detection were more responsive to the polar molecules with a rough distribution of 10%, 10%, and 80% of the total signals in hexane, ethyl acetate, and 50% aqueous methanol, respectively. With HPLC-MS detection, the distribution of signals was more balanced, roughly 40%, 30%, and 30% for the same extracts (hexane, ethyl acetate, and 50% aqueous methanol). For direct extraction, HPLC-UV and BSTFA/TMCS-derivatized 4GC-FID provided signals between 60% and 150% of the total sequential extracted signals. The overlap of signals for the 3 sequential extracts ranged from 1% to 3%. The overlap of the signals for direct extraction with the total for sequential extraction ranged from 15% to 98%. With HPLC-MS detection, signals varied from 30% to 40% of the total signals for sequential extraction. Multivariate analysis showed that the components for the sequential and direct extracts were statistically different. However, each extract, sequential or direct, allowed discrimination between the 3 plant materials.
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http://dx.doi.org/10.1016/j.jchromb.2017.12.005 | DOI Listing |
Clin Res Hepatol Gastroenterol
January 2025
Evidence-Based Medicine Center, School of Basic Medical Science, Lanzhou University, 730000, Lanzhou, China; Centre for Evidence-Based Social Science/Center for Health Technology Assessment, School of Public Health, Lanzhou University, 730000, Lanzhou, China; Gansu Key Laboratory of Evidence-Based Medicine, Lanzhou University, 730000, Lanzhou, China. Electronic address:
Background: Acute liver failure (ALF) poses a significant threat to patient health with high mortality rates. While Non-Bioartificial Artificial Liver Support system (NBALSS) has been utilized as a transitional intervention to liver transplant, its efficacy remains uncertain, It is also used as a last-line treatment for patients who are not candidates for liver transplantation.
Objective: The aim of this study was to perform a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the efficacy of NBALSS in treating acute liver failure (ALF).
J Environ Manage
January 2025
Department of Agricultural Chemistry, National Taiwan University, Taipei, 106319, Taiwan. Electronic address:
Molybdenum (Mo) is an essential micronutrient for plants, yet it also poses potential environmental risks when present in excess. This study investigated the Mo speciation in soils with varying properties and their influences on Mo uptake by wheat (Triticum aestivum L.), a staple crop with significant implications for global food security.
View Article and Find Full Text PDFEnviron Pollut
January 2025
Applied Geochemistry, Department of Civil, Environmental and Natural Resource Engineering, Luleå University of Technology, Luleå, Sweden.
Research regarding the geochemistry of beryllium (Be) in terrestrial environments is hindered by its high toxicity to humans and the low concentrations normally occurring in the environment. Although Be is considered an immobile element, extremely high dissolved concentrations have been detected in groundwater in the legacy Tailings Storage Facility (TSF) of Smaltjärnen, Sweden. Therefore, a detailed study was conducted to determine physiochemical parameters affecting the speciation of Be in the groundwater.
View Article and Find Full Text PDFis a species closely linked to human health. This study investigated the acaricidal efficacy of methanol extracts from 18 traditional Chinese medicinal plants against . The extract from DC.
View Article and Find Full Text PDFSensors (Basel)
January 2025
NUS-ISS, National University of Singapore, Singapore 119615, Singapore.
Recognizing the action of plastic bag taking from CCTV video footage represents a highly specialized and niche challenge within the broader domain of action video classification. To address this challenge, our paper introduces a novel benchmark video dataset specifically curated for the task of identifying the action of grabbing a plastic bag. Additionally, we propose and evaluate three distinct baseline approaches.
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