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http://dx.doi.org/10.1155/2012/103763 | DOI Listing |
Int J Biol Macromol
January 2025
Department of Pain Management, Qilu Hospital of Shandong University, 107# West Wenhua Road, Jinan, Shandong 250012, China. Electronic address:
This investigation represents a pioneering effort to examine the therapeutic effects of PCB specifically in the context of CFA-induced mice, as well as to elucidate the underlying mechanisms that facilitate such effects. Our study utilized advanced methodologies, namely high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS)-based metabolomics, alongside comprehensive multivariate data analysis, to identify a distinctive metabolic profile associated with acute inflammation. Through our analyses, we discovered that several potential metabolites were significantly implicated in a variety of critical metabolic pathways.
View Article and Find Full Text PDFFood Chem
December 2024
Atomic and Mass Spectrometry - A&MS Research Unit, Department of Chemistry, Ghent University, 9000 Ghent, Belgium. Electronic address:
The disruption of Cu homeostasis is associated with the pathogenesis of many diseases and can result in alterations in Cu isotope fractionation. Changes in the Cu isotope ratio (Cu/Cu) of body fluids and tissues have been observed in liver disorders, cancers, and other diseases, displaying diagnostic/prognostic potential. However, it is not entirely clear whether certain physiological or lifestyle factors may also influence the bodily Cu isotopic composition, potentially obfuscating the signature of the pathology.
View Article and Find Full Text PDFTalanta
January 2025
Graduate School of Pharmaceutical Science, Osaka University, Suita, Osaka, 565-0871, Japan; SANKEN (The Institute of Scientific and Industrial Research), Osaka University, Ibaraki, Osaka, 567-0047, Japan; Transdimensional Life Imaging Division, Institute for Open and Transdisciplinary Research Initiative, Osaka University, Suita, Osaka, 565-0871, Japan; Research Institute for Electronic Science, Hokkaido University, Sapporo, Hokkaido, 001-0020, Japan. Electronic address:
Heavy metal contamination in water bodies has raised global concerns due to its significant threats to both public health and ecosystem. Copper (Cu), one of the most widely used metals, is also an essential trace element in physiological systems. Excessive intake of Cu from water can cause toxicity, potentially resulting in serious health risks.
View Article and Find Full Text PDFBioorg Chem
January 2025
School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023 China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203 China; University of the Chinese Academy of Sciences, Beijing 100049 China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200040 China. Electronic address:
The TRPC5 channel plays an important role in regulating various physiological processes, which is related to various human diseases, especially psychiatric and kidney diseases. Although the TRPC5 channel is one of the essential potential target, no drugs against TRPC5 channels have been granted in the market to date. In this study, based on the structure of hit compound ph1, we further synthesied 49 compounds of novel quinazolinone and heterocyclic fusion pyrimidinone derivatives, and their activities were evaluated by electrophysiological assays.
View Article and Find Full Text PDFNeural Netw
January 2025
Tsinghua University, Beijing, China. Electronic address:
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, most existing ANN-based methods require substantial computing resources, which poses challenges for effective deployment on mobile devices. Spiking neural networks (SNNs), on the other hand, hold immense potential for energy-efficient deep learning owing to their binary and event-driven architecture.
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