Differentiated HepaRG cells maintain liver-specific functions such as drug-metabolizing enzymes. In this study, the feasibility of HepaRG cells as a human hepatocyte model for in vitro toxicity ...assessment was examined using selected hepatotoxic compounds. First, basal drug-metabolizing enzyme activities (CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, uridine 5′-diphospho-glucuronosyltransferase UGT, and sulfotransferases SULT) were measured in HepaRG, human hepatocytes, and HepG2 cells. Enzyme activities in differentiated HepaRG cells were comparable to those in human hepatocytes and much higher than those in HepG2 cells, except for SULT activity. Second, we examined the cytotoxicity of hepatotoxic compounds, acetaminophen (APAP), aflatoxin B1 (AFB1), cyclophosphamide (CPA), tamoxifen (TAM), and troglitazone (TGZ) in HepaRG cells and human hepatocytes. AFB1- and CPA-induced cytotoxicities against HepaRG cells were comparable to those against human hepatocytes. Furthermore, the cytotoxicities of these compounds were inhibited by 1-aminobenzotriazole (ABT), a broad CYP inhibitor, in both cells and were likely mediated by metabolic activation by CYP. Finally, toxicogenomics analysis of HepG2 and HepaRG cells after exposure to AFB1 and CPA revealed that numerous p53-related genes were upregulated- and the expression of these genes was greater in HepaRG than in HepG2 cells. These results suggest that gene expression profiles of HepaRG cells were affected more considerably by the toxic mechanisms of AFB1 and CPA than the profiles of HepG2 cells were. Therefore, our investigation shows that HepaRG cells could be useful human hepatic cellular models for toxicity studies.
Clarifying dynamic processes of materials is an important research topic in materials science. Time-resolved X-ray diffraction is a powerful technique for probing dynamic processes. To understand the ...dynamics, it is essential to analyze time-series data using appropriate time-evolution models and accurate start times of dynamic processes. However, conventional analyses based on non-linear least-squares fitting have difficulty both evaluating time-evolution models and estimating start times. Here, we establish a Bayesian framework including time-evolution models. We investigate an adsorption process, which is a representative dynamic process, and extract information about the time-evolution model and adsorption start time. The information enables us to estimate adsorption properties such as rate constants more accurately, thus achieving more precise understanding of dynamic adsorption processes. Our framework is highly versatile, can be applied to other dynamic processes such as chemical reactions, and is expected to be utilized in various areas of materials science.
Recently found anomalous Hall, Nernst, magnetooptical Kerr, and spin Hall effects in the antiferromagnets Mn
X (X = Sn, Ge) are attracting much attention for spintronics and energy harvesting. Since ...these materials are antiferromagnets, the origin of these functionalities is expected to be different from that of conventional ferromagnets. Here, we report the observation of ferroic order of magnetic octupole in Mn
Sn by X-ray magnetic circular dichroism, which is only predicted theoretically so far. The observed signals are clearly decoupled with the behaviors of uniform magnetization, indicating that the present X-ray magnetic circular dichroism is not arising from the conventional magnetization. We have found that the appearance of this anomalous signal coincides with the time reversal symmetry broken cluster magnetic octupole order. Our study demonstrates that the exotic material functionalities are closely related to the multipole order, which can produce unconventional cross correlation functionalities.
Abstract Time-resolved X-ray magnetic circular dichroism under the effects of ferromagnetic resonance (FMR), known as X-ray ferromagnetic resonance (XFMR) measurements, enables direct detection of ...precession dynamics of magnetic moment. Here we demonstrated XFMR measurements and Bayesian analyses as a quantitative probe for the precession of spin and orbital magnetic moments under the FMR effect. Magnetization precessions in two different Pt/Ni-Fe thin film samples were directly detected. Furthermore, the ratio of dynamical spin and orbital magnetic moments was evaluated quantitatively by Bayesian analyses for XFMR energy spectra around the Ni $$L_{2,3}$$ L 2 , 3 absorption edges. Our study paves the way for a microscopic investigation of the contribution of the orbital magnetic moment to magnetization dynamics.
Endogenous DNA derived from nuclei or mitochondria is released into the blood circulation as cell-free DNA (cfDNA) following cell damage or death. cfDNA is associated with various pathological ...conditions; however, its clinical significance in antineutrophil cytoplasmic antibody-associated vasculitis (AAV) remains unclear. This study aimed to evaluate the clinical significance of cfDNA in AAV.
We enrolled 35 patients with AAV, including 10 with eosinophilic granulomatosis with polyangiitis (EGPA), 13 with microscopic polyangiitis, and 12 with granulomatosis with polyangiitis. Serum cf-nuclear DNA (cf-nDNA) and cf-mitochondrial DNA (cf-mtDNA) levels were measured by quantitative polymerase chain reaction before and after the initiation of immunosuppressive therapy. Tissue samples from EGPA patients were examined by immunofluorescence and transmission electron microscopy. The structure of eosinophil extracellular traps (EETs) and neutrophil extracellular traps (NETs) and stability against DNase were assessed
. Platelet adhesion of EETs were also assessed.
Serum cf-nDNA and cf-mtDNA levels were significantly higher in AAV than in healthy controls, with the highest levels in EGPA; however, serum DNase activities were comparable among all groups. cf-nDNA and cf-mtDNA decreased after treatment and were associated with disease activity only in EGPA. Blood eosinophil count and plasma D-dimer levels were significantly correlated with cf-nDNA in EGPA and cf-mtDNA. EGPA tissue samples showed lytic eosinophils and EETs in small-vessel thrombi. The structure of EETs showed bolder net-like chromatin threads
and EETs showed greater stability against DNase than NETs. EETs provided a scaffold for platelet adhesion.
cfDNA was increased in EGPA, associated with disease activity. The presence of DNase-resistant EETs in small-vessel thrombi might contribute to higher concentration of cfDNA and the occurrence of immunothrombosis in EGPA.
Analyses of life history and population dynamics are essential for effective population control of wild mammals. We developed a model for the simultaneous estimation of seasonal changes in three ...parameters—population density, habitat preference and trap catchability of target animals—based on camera-trapping data and harvest records. The random encounter and staying time model, with no need for individual recognition, is the core component of the model—by combining this model with the catch-effort model, we estimated density at broad spatial scales and catchability by traps. Here, the wild boar population in central Japan was evaluated as a target population. We found that the estimated population density increased after the birth period and then decreased until the next birth period, mainly due to harvesting. Habitat preference changed seasonally, but forests having abandoned fields nearby were generally preferred throughout the season. These patterns can be explained by patterns of food availability and resting or nesting sites. Catchability by traps also changed seasonally, with relatively high values in the winter, which probably reflected changes in the attractiveness of the trap bait due to activity changes in response to food scarcity. Based on these results, we proposed an effective trapping strategy for wild boars, and discussed the applicability of our model to more general conservation and management issues.
Recent advances in cryo-electron microscopy (cryo-EM) have enabled protein structure determination at atomic resolutions. Cryo-EM specimens are prepared by rapidly freezing a protein solution on a ...metal grid coated with a holey carbon film; this results in the formation of an ice film on each hole. The thickness of the ice film is a critical factor for high-resolution structure determination; ice that is too thick degrades the contrast of the protein image while ice that is too thin excludes the protein from the hole or denatures the protein. Therefore, trained researchers need to manually select “good” regions with appropriate ice thicknesses for imaging. To reduce the time spent on such tasks, we developed a deep learning program consisting of a “detector” and a “classifier” to identify good regions from low-magnification EM images. In our method, the holes in a low-magnification EM image are detected via a detector, and the ice image on each hole is classified as either good or bad via a classifier. The detector detected more than 95% of the holes regardless of the type of samples. The classifier was trained for different types of samples because the appropriate ice thickness varies between sample types. The accuracies of the classifiers were 93.8% for a soluble protein sample (β-galactosidase) and 95.3% for a membrane protein sample (bovine heart cytochrome
c
oxidase). In addition, we found that a training data set containing ~ 2100 hole images from 300 low-magnification EM images was sufficient to obtain good accuracy, such as higher than 90%. We expect that the throughput of the cryo-EM data collection step will be greatly improved by using our method.
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