Emodin is an important anthraquinone compound with good anti-inflammatory activity in Chinese traditional medicine rhubarb. Detailed spatial distribution information in bio-tissues plays an important role in revealing the pharmacodynamics, toxicology and chemical mechanism of emodin. Herein, the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-TOF-MSI) analytical method was established to obtain information on the spatial and temporal changes of emodin in multiple mouse tissue sections (heart, liver, spleen, lung, kidney, and brain) after intraperitoneal injection of emodin in mice. The measurements were accomplished in the negative ion mode in the range of m/z 250-285 Da with a spatial resolution on 40 µm. It was found that emodin was predominantly distributed in the arteriolar vascular region of the heart, the capsule region of the spleen, and the cortex of the kidney. Moreover, the MALDI-TOF-MSI result implied that emodin might be distributed in the brain. These more detailed spatial distribution information provides the significant reference for investigating the action mechanism of emodin, which cannot be obtained from conventional LC-MS analysis. The distribution trend of emodin in the results of MALDI-TOF-MSI analysis agreed with the ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) results well, demonstrating the complementarity and reliability of the established MALDI-TOF-MSI method. Our work provided a label-free molecular imaging method to investigate the precise spatial distribution of emodin in various organs, which prove great potential in studying the effective substances and mechanism of rhubarb.
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http://dx.doi.org/10.1007/s44211-024-00644-1 | DOI Listing |
Phys Rev Lett
December 2024
University of Oregon, Department of Physics and Materials Science Institute, Eugene, Oregon 97403, USA.
We consider many-particle diffusion in one spatial dimension modeled as "random walks in a random environment." A shared short-range space-time random environment determines the jump distributions that drive the motion of the particles. We determine universal power laws for the environment's contribution to the variance of the extreme first passage time and extreme location.
View Article and Find Full Text PDFPhys Rev Lett
December 2024
Université de Mons, Laboratoire Interfaces & Fluides Complexes, 20 Place du Parc, B-7000 Mons, Belgium.
The phase separation that occurs in two-temperature mixtures, which are driven out of equilibrium at the local scale, has been thoroughly characterized, but much less is known about the depletion interactions that drive it. Using numerical simulations in dimension 2, we show that the depletion interactions extend beyond two particle diameters in dilute systems, as expected at equilibrium, and decay algebraically with an exponent -4. Solving for the N-particle distribution function in the stationary state, perturbatively in the interaction potential, we show that algebraic correlations with an exponent -2d arise from triplets of particles at different temperatures in spatial dimension d.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia 22904, United States.
Industrialized swine facilities adversely affect the health and well-being of Eastern North Carolina residents in the U.S. and are an issue of environmental racism.
View Article and Find Full Text PDFData Brief
February 2025
Institute for Geography, Leipzig University, Johannisallee 19a, Leipzig, 04103, Germany.
This data set includes the spatial model of the thickness and distribution of fine-grained floodplain deposits in the Leipzig floodplain area. The data set originates from borehole records provided by the Saxon State Office for Environment, Agriculture, and Geology [1]. The data processing involved the categorization of the stratigraphic descriptions of the borehole logs.
View Article and Find Full Text PDFThe spatial arrangement of cells plays a pivotal role in shaping tissue functions in various biological systems and diseased microenvironments. However, it is still under-investigated of the topological coordinating rules among different cell types as tissue spatial patterns. Here, we introduce the Triangulation cellular community motif Neural Network (TrimNN), a bottom-up approach to estimate the prevalence of sizeable conservative cell organization patterns as Cellular Community (CC) motifs in spatial transcriptomics and proteomics.
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