PURPOSE: Mesangial cell extracellular matrix (ECM) synthesis plays an important role in various renal diseases. Mycophenolic acid (MPA), which is an inhibitor of inosine monophosphate dehydrogenase (IMPDH), inhibits mesangial cell proliferation and ECM synthesis. However, the exact mechanism of MPA has not been clearly elucidated in mesangial cells. To examine the relative importance of IMPDH on the inhibitory action of MPA, we compared the effects of MPA or IMPDH2 siRNA on platelet-derived growth factor (PDGF)-induced fibronectin secretion and cellular reactive oxygen species (ROS) in mouse mesangial cells (MMC). METHODS: MMC were stimulated with PDGF 10 ng/ml with or without MPA 0.1~10micrometer, IMPDH2 siRNA 10~50 nM, or N-acetylcystein (NAC). IMPDH2 siRNA was transiently transfected by lipofectamine for 24 hours. MPA 0.1~10micrometer, ribavirin 10~100micrometer, and NAC 5 mM were administered 1 hour before the stimulation. Cell viability was measured by methylthiazoletetrazolium (MTT) assay, fibronectin secretion by Western blot analysis, and dichlorofluorescein (DCF)-sensitive cellular ROS by flow cytometry. RESULTS: PDGF 10 ng/ml effectively increased fibronectin secretion and cellular ROS in MMC. MPA and NAC at concentration without affecting basal level of fibronectin and cellular ROS ameliorated PDGF-induced fibronectin secretion and cellular ROS. However, IMPDH2 siRNA only partially reduced PDGF- induced fibronectin secretion and cellular ROS in MMC. CONCLUSION: These results suggest that MPA may inhibit PDGF-induced fibronectin secretion partly through IMPDH2 or cellular ROS in MMC, and there may be other mechanisms on the inhibitory action of MPA in mesenchymal cells.
Animals ; Blotting, Western ; Cell Survival ; Extracellular Matrix ; Fibronectins* ; Flow Cytometry ; Inosine Monophosphate* ; Inosine* ; Mesangial Cells* ; Mice* ; Mycophenolic Acid ; Oxidoreductases* ; Platelet-Derived Growth Factor ; Reactive Oxygen Species* ; Ribavirin ; RNA, Small Interfering

PURPOSE: Vascular smooth muscle cell (VSMC) proliferation plays an important role in the development and progression of chronic allograft vasculopathy. Mycophenolic acid (MPA) inhibits various mesenchymal cell proliferation, and reactive oxygen species (ROS) are involved in the anti-pro-liferative effect of MPA. In this study, we investigated the effects of MPA on oleic acid (OA)-induced VSMC proliferation and also the role of ROS in these processes. METHODS: Primary cultured rat VSMCs from Sprague-Dawley were stimulated with OA 100micrometer. MPA 0.1~10micrometer and N-acetylcystein (NAC) 5 mM were administered 1 hour before adding the OA. Cell proliferation was measured by Methylthiazoletetrazolium (MTT) assay, proliferating cell nuclear antigen (PCNA) expression by Western blot analysis, and dichlorofluorescein (DCF)-sensitive cellular ROS by flow cytometry. RESULTS: OA at 100micrometer significantly increased MTT level by 1.6-fold as well as PCNA expression at 48 hours in rat VSMCs. OA also induced DCF-sensitive cellular ROS by 1.6-fold at 5 minutes and the increment of cellular ROS remained for up to 1 hour. MPA at above 1micrometer inhibited OA- induced VSMC proliferation and cellular ROS in a dose-ependent manner. NAC 5 mM also inhibited OA-induced rat VSMC activation. CONCLUSION: These results suggest that MPA inhibits OA-induced VSMC proliferation partially through the inhibition of cellular ROS.
Allografts ; Animals ; Blotting, Western ; Cell Proliferation* ; Flow Cytometry ; Muscle, Smooth, Vascular* ; Mycophenolic Acid* ; Oleic Acid ; Proliferating Cell Nuclear Antigen ; Rats* ; Rats, Sprague-Dawley ; Reactive Oxygen Species

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.