Noise power spectrum (NPS) in computed tomography: Enabling local NPS measurement without stationarity and ergodicity assumptions.

BACKGROUND: Conventional methods for estimating the noise power spectrum (NPS) often necessitate multiple computed tomography (CT) data acquisitions and are required to satisfy stringent stationarity and ergodicity conditions, which prove challenging in CT imaging systems. PURPOSE: The aim was to revisit the conventional NPS estimation method, leading to a new framework that estimates local NPS without relying on stationarity or ergodicity, thus facilitating experimental NPS estimations. METHODS: The scientific foundation of the conventional CT NPS measurement method, based on the Wiener-Khintchine theorem, was reexamined, emphasizing the critical conditions of stationarity and ergodicity. This work proposes an alternative framework, characterized by its independence from stationarity and ergodicity, and its ability to facilitate local NPS estimations. A spatial average of local NPS over a Region of Interest (ROI) yields the conventional NPS for that ROI. The connections and differences between the proposed alternative method and the conventional method are discussed. Experimental studies were conducted to validate the new method. RESULTS: (1) The NPS estimated using the conventional method was demonstrated to correspond to the spatial average of pointwise NPS from the proposed NPS estimation framework. (2) The NPS estimated over an ROI with the conventional method was shown to be the sum of the NPS estimated from the proposed method and a contribution from measurement uncertainty. (3) Local NPS estimations from the proposed method in this work elucidate the impact of surrounding image content on local NPS variations. CONCLUSION: The NPS estimation method proposed in this work allows for the estimation of local NPS without relying on stationarity and ergodicity conditions, offering local NPS estimations with significantly improved precision.

Experimental measurement of local noise power spectrum (NPS) in photon counting detector-CT (PCD-CT) using a single data acquisition.

BACKGROUND: Accurate noise power spectra (NPS) measurement in clinical X-ray CT exams is challenging due to the need for repeated scans, which expose patients to high radiation risks. A reliable method for single CT acquisition NPS estimation is thus highly desirable. PURPOSE: To develop a method for estimating local NPS from a single photon counting detector-CT (PCD-CT) acquisition. METHODS: A novel nearly statistical bias-free estimator was constructed from the raw counts data of PCD-CT scan to estimate the variance of sinogram projection data. An analytical algorithm is employed to reconstruct point-wise covariance cov ( x i , x j ) $\text{cov}({\bf x}_i,{\bf x}_j)$ between any two image pixel/voxel locations x i ${\bf x}_i$ and x j ${\bf x_j}$ . A Fourier transform is applied to obtain the desired point-wise NPS for any chosen location x i ${\bf x}_i$ . The method was validated using experimental data acquired from a benchtop PCD-CT system with various physical phantoms, and the results were compared with the conventional local NPS measurement method using repeated scans and statistical ensemble averaging. RESULTS: The experimental results demonstrate that (1) the proposed method can achieve pointwise/local NPS measurement for a region of interest (ROI) located at any chosen position, accurately characterizing the NPS with spatial structures resulting from image content heterogeneity; (2) the local NPS measured using the proposed method show a higher precision in the measured NPS compared to the conventional measurement method; (3) spatial averaging of the local NPS yields the conventional NPS for a given local ROI. CONCLUSION: A new method was developed to enable local NPS from a single PCD-CT acquisition.

Approaches, advantages, and challenges to photon counting detector and multi-energy CT.

Photon counting detector CT (PCD-CT) is the newest major development in CT technology and has been commercially available since 2021. It offers major technological advantages over current standard-of-care energy integrating detector CT (EID-CT) including improved spatial resolution, improved iodine contrast to noise ratio, multi-energy imaging, and reduced noise. This article serves as a foundational basis to the technical approaches and concepts of PCD-CT technology with primary emphasis on detector technology in direct comparison to EID-CT. The article also addresses current technological challenges to PCD-CT with particular attention to cross talk and its causes (e.g., Compton scattering, fluorescence, charge sharing, K-escape) as well as pile-up.

Danggui Shaoyao San protects cyclophosphamide-induced premature ovarian failure by inhibiting apoptosis and oxidative stress through the regulation of the SIRT1/p53 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: It has been reported that apoptosis and oxidative stress are related to cyclophosphamide (CYC)-induced premature ovarian failure (POF). Therefore, anti-apoptotic and anti-oxidative stress treatments exhibit therapeutic efficacy in CYC-induced POF. Danggui Shaoyao San (DSS), which has been extensively used to treat gynecologic diseases, is found to inhibit apoptosis and reduce oxidative stress. However, the roles of DSS in regulating apoptosis and oxidative stress during CYC-induced POF, and its associated mechanisms are still unknown. AIM OF THE STUDY: This work aimed to investigate the roles and mechanisms of DSS in inhibiting apoptosis and oxidative stress in CYC-induced POF. MATERIALS AND METHODS: CYC (75 mg/kg) was intraperitoneally injected in mice to construct the POF mouse model for in vivo study. Thereafter, alterations of body weight, ovary morphology and estrous cycle were monitored to assess the ovarian protective properties of DSS. Serum LH and E2 levels were analyzed by enzyme-linked immunosorbent assay (ELISA). Hematoxylin-eosin (HE) staining was employed for examining ovarian pathological morphology and quantifying follicles in various stages. Meanwhile, TUNEL staining and apoptosis-related proteins were adopted for evaluating apoptosis. Oxidative stress was measured by the levels of ROS, MDA, and 4-HNE. Western blot (WB) assay was performed to detect proteins related to the SIRT1/p53 pathway. KGN cells were used for in vitro experiment. TBHP stimulation was carried out for establishing the oxidative stress-induced apoptosis cell model. Furthermore, MTT assay was employed for evaluating the protection of DSS from TBHP-induced oxidative stress. The anti-apoptotic ability of DSS was evaluated by hoechst/PI staining, JC-1 staining, and apoptosis-related proteins. Additionally, the anti-oxidative stress ability of DSS was measured by detecting the levels of ROS, MDA, and 4-HNE. Proteins related to SIRT1/p53 signaling pathway were also measured using WB and immunofluorescence (IF) staining. Besides, SIRT1 expression was suppressed by EX527 to further investigate the role of SIRT1 in the effects of DSS against apoptosis and oxidative stress. RESULTS: In the in vivo experiment, DSS dose-dependently exerted its anti-apoptotic, anti-oxidative stress, and ovarian protective effects. In addition, apoptosis, apoptosis-related protein and oxidative stress levels were inhibited by DSS treatment. DSS treatment up-regulated SIRT1 and down-regulated p53 expression. From in vitro experiment, it was found that DSS treatment protected KGN cells from TBHP-induced oxidative stress injury. Besides, DSS administration suppressed the apoptosis ratio, apoptosis-related protein levels, mitochondrial membrane potential damage, and oxidative stress. SIRT1 suppression by EX527 abolished the anti-apoptotic, anti-oxidative stress, and ovarian protective effects, as discovered from in vivo and in vitro experiments. CONCLUSIONS: DSS exerts the anti-apoptotic, anti-oxidative stress, and ovarian protective effects in POF mice, and suppresses the apoptosis and oxidative stress of KGN cells through activating SIRT1 and suppressing p53 pathway.

Deep-Interior: A new pathway to interior tomographic image reconstruction via a weighted backprojection and deep learning.

BACKGROUND: In recent years, deep learning strategies have been combined with either the filtered backprojection or iterative methods or the direct projection-to-image by deep learning only to reconstruct images. Some of these methods can be applied to address the interior reconstruction problems for centered regions of interest (ROIs) with fixed sizes. Developing a method to enable interior tomography with arbitrarily located ROIs with nearly arbitrary ROI sizes inside a scanning field of view (FOV) remains an open question. PURPOSE: To develop a new pathway to enable interior tomographic reconstruction for arbitrarily located ROIs with arbitrary sizes using a single trained deep neural network model. METHODS: The method consists of two steps. First, an analytical weighted backprojection reconstruction algorithm was developed to perform domain transform from divergent fan-beam projection data to an intermediate image feature space, B ( x ⃗ ) $B(\vec{x})$ , for an arbitrary size ROI at an arbitrary location inside the FOV. Second, a supervised learning technique was developed to train a deep neural network architecture to perform deconvolution to obtain the true image f ( x ⃗ ) $f(\vec{x})$ from the new feature space B ( x ⃗ ) $B(\vec{x})$ . This two-step method is referred to as Deep-Interior for convenience. Both numerical simulations and experimental studies were performed to validate the proposed Deep-Interior method. RESULTS: The results showed that ROIs as small as a diameter of 5 cm could be accurately reconstructed (similarity index 0.985 ± 0.018 on internal testing data and 0.940 ± 0.025 on external testing data) at arbitrary locations within an imaging object covering a wide variety of anatomical structures of different body parts. Besides, ROIs of arbitrary size can be reconstructed by stitching small ROIs without additional training. CONCLUSION: The developed Deep-Interior framework can enable interior tomographic reconstruction from divergent fan-beam projections for short-scan and super-short-scan acquisitions for small ROIs (with a diameter larger than 5 cm) at an arbitrary location inside the scanning FOV with high quantitative reconstruction accuracy.

20(S)-ginsenoside Rg3 exerts anti-fibrotic effect after myocardial infarction by alleviation of fibroblasts proliferation and collagen deposition through TGFBR1 signaling pathways.

Background: Myocardial fibrosis post-myocardial infarction (MI) can induce maladaptive cardiac remodeling as well as heart failure. Although 20(S)-ginsenoside Rg3 (Rg3) has been applied to cardiovascular diseases, its efficacy and specific molecular mechanism in myocardial fibrosis are largely unknown. Herein, we aimed to explore whether TGFBR1 signaling was involved in Rg3's anti-fibrotic effect post-MI. Methods: Left anterior descending (LAD) coronary artery ligation-induced MI mice and TGF-ß1-stimulated primary cardiac fibroblasts (CFs) were adopted. Echocardiography, hematoxlin-eosin and Masson staining, Western-blot and immunohistochemistry, CCK8 and Edu were used to study the effects of Rg3 on myocardial fibrosis and TGFBR1 signaling. The combination mechanism of Rg3 and TGFBR1 was explored by surface plasmon resonance imaging (SPRi). Moreover, myocardial Tgfbr1-deficient mice and TGFBR1 adenovirus were adopted to confirm the pharmacological mechanism of Rg3. Results: In vivo experiments, Rg3 ameliorated myocardial fibrosis and hypertrophy and enhanced cardiac function. Rg3-TGFBR1 had the 1.78 × 10-7 M equilibrium dissociation constant based on SPRi analysis, and Rg3 inhibited the activation of TGFBR1/Smads signaling dose-dependently. Cardiac-specific Tgfbr1 knockdown abolished Rg3's protection against myocardial fibrosis post-MI. In addition, Rg3 down-regulated the TGF-ß1-mediated CFs growth together with collagen production in vitro through TGFBR1 signaling. Moreover, TGFBR1 adenovirus partially blocked the inhibitory effect of Rg3. Conclusion: Rg3 improves myocardial fibrosis and cardiac function through suppressing CFs proliferation along with collagen deposition by inactivation of TGFBR1 pathway.

Ethyl ferulate suppresses post-myocardial infarction myocardial fibrosis by inhibiting transforming growth factor receptor 1.

BACKGROUND: With an increasing number of myocardial infarction (MI) patients, myocardial fibrosis is becoming a widespread health concern. It's becoming more and more urgent to conduct additional research and investigations into efficient treatments. Ethyl ferulate (EF) is a naturally occurring substance with cardioprotective properties. However, the extent of its impact and the underlying mechanism of its treatment for myocardial fibrosis after MI remain unknown. PURPOSE: The goal of this study was to look into how EF affected the signaling of the TGF-receptor 1 (TGFBR1) in myocardial fibrosis after MI. METHODS: Echocardiography, hematoxylin-eosin (HE) and Masson trichrome staining were employed to assess the impact of EF on heart structure and function in MI-affected mice in vivo. Cell proliferation assay (MTS), 5-Ethynyl-2'-deoxyuridine (EdU), and western blot techniques were employed to examine the influence of EF on native cardiac fibroblast (CFs) proliferation and collagen deposition. Molecular simulation and surface plasmon resonance imaging (SPRi) were utilized to explore TGFBR1 and EF interaction. Cardiac-specific Tgfbr1 knockout mice (Tgfbr1ΔMCK) were utilized to testify to the impact of EF. RESULTS: In vivo experiments revealed that EF alleviated myocardial fibrosis, improved cardiac dysfunction after MI and downregulated the TGFBR1 signaling in a dose-dependent manner. Moreover, in vitro experiments revealed that EF significantly inhibited CFs proliferation, collagen deposition and TGFBR1 signaling followed by TGF-ß1 stimulation. More specifically, molecular simulation, molecular dynamics, and SPRi collectively showed that EF directly targeted TGFBR1. Lastly, knocking down of Tgfbr1 partially reversed the inhibitory activity of EF on myocardial fibrosis in MI mice. CONCLUSION: EF attenuated myocardial fibrosis post-MI by directly suppressing TGFBR1 and its downstream signaling pathway.

Ferrostatin-1 suppresses cardiomyocyte ferroptosis after myocardial infarction by activating Nrf2 signaling.

OBJECTIVES: Ferroptosis, a new regulated cell death pathway, plays a crucial part in the development of cardiovascular disease. However, the precise underlying mechanism remains unclear. Therefore, this study aimed to elucidate this. METHODS: Herein, an erastin-induced H9C2 cell ferroptosis in vitro model and a myocardial infarction murine model, which was created by ligating the left anterior descending coronary artery, were established. Ferroptosis-related indicators, myocardial injury-related indicators, and Nrf2 signaling-related proteins expression were analyzed to explore the potential mechanism underlying cardiomyocyte ferroptosis-mediated cardiovascular disease development. RESULTS: We demonstrated that Nrf2 downregulation in myocardial tissue, accompanied by ferroptotic events and changes in xCT and GPX4 expressions, induced cardiomyocyte ferroptosis and myocardial injury after myocardial infarction. These events, including ferroptosis and changes in Nrf2, xCT, and GPX4 expressions, were improved by ferrostatin-1 in vivo and in vitro. Besides, Nrf2 deficiency or inhibition aggravated myocardial infarction-induced cardiomyocyte ferroptosis by decreasing xCT and GPX4 expressions in vivo and in vitro. Moreover, ferrostatin-1 directly targeted Nrf2, as evidenced by surface plasmon resonance analysis. CONCLUSIONS: These results indicated that myocardial infarction is accompanied by cardiomyocyte ferroptosis and that Nrf2 signaling plays a crucial part in regulating cardiomyocyte ferroptosis after myocardial infarction.

Training certified detectives to track down the intrinsic shortcuts in COVID-19 chest x-ray data sets.

Deep learning faces a significant challenge wherein the trained models often underperform when used with external test data sets. This issue has been attributed to spurious correlations between irrelevant features in the input data and corresponding labels. This study uses the classification of COVID-19 from chest x-ray radiographs as an example to demonstrate that the image contrast and sharpness, which are characteristics of a chest radiograph dependent on data acquisition systems and imaging parameters, can be intrinsic shortcuts that impair the model's generalizability. The study proposes training certified shortcut detective models that meet a set of qualification criteria which can then identify these intrinsic shortcuts in a curated data set.

Correcting statistical CT number biases without access to raw detector counts: Applications to high spatial resolution photon counting CT imaging.

BACKGROUND: Due to the nonlinear nature of the logarithmic operation and the stochastic nature of photon counts (N), sinogram data of photon counting detector CT (PCD-CT) are intrinsically biased, which leads to statistical CT number biases. When raw counts are available, nearly unbiased statistical estimators for projection data were developed recently to address the CT number bias issue. However, for most clinical PCD-CT systems, users' access to raw detector counts is limited. Therefore, it remains a challenge for end users to address the CT number bias issue in clinical applications. PURPOSE: To develop methods to correct statistical biases in PCD-CT without requiring access to raw PCD counts. METHODS: (1) The sample variance of air-only post-log sinograms was used to estimate air-only detector counts, N ¯ 0 $\bar{N}_0$ . (2) If the post-log sinogram data, y, is available, then N of each detector pixel was estimated using N = N ¯ 0 e - y $N = \bar{N}_0 \, \mathrm{e}^{-y}$ . Once N was estimated, a closed-form analytical bias correction was applied to the sinogram. (3) If a patient's post-log sinogram data are not archived, a forward projection of the bias-contaminated CT image was used to perform a first-order bias correction. Both the proposed sinogram domain- and image domain-based bias correction methods were validated using experimental PCD-CT data. RESULTS: Experimental results demonstrated that both sinogram domain- and image domain-based bias correction methods enabled reduced-dose PCD-CT images to match the CT numbers of reference-standard images within [-5, 5] HU. In contrast, uncorrected reduced-dose PCD-CT images demonstrated biases ranging from -25 to 55 HU, depending on the material. No increase in image noise or spatial resolution degradation was observed using the proposed methods. CONCLUSIONS: CT number bias issues can be effectively addressed using the proposed sinogram or image domain method in PCD-CT, allowing PCD-CT acquired at different radiation dose levels to have consistent CT numbers desired for quantitative imaging.

Training certified detectives to track down the intrinsic shortcuts in COVID-19 chest x-ray data sets.

Deep learning faces a significant challenge wherein the trained models often underperform when used with external test data sets. This issue has been attributed to spurious correlations between irrelevant features in the input data and corresponding labels. This study uses the classification of COVID-19 from chest x-ray radiographs as an example to demonstrate that the image contrast and sharpness, which are characteristics of a chest radiograph dependent on data acquisition systems and imaging parameters, can be intrinsic shortcuts that impair the model's generalizability. The study proposes training certified shortcut detective models that meet a set of qualification criteria which can then identify these intrinsic shortcuts in a curated data set.

Unbiased zero-count correction method in low-dose high-resolution photon counting detector CT.

Objective.To address the zero-count problem in low-dose, high-spatial-resolution photon counting detector CT (PCD-CT) without introducing statistical biases or degrading spatial resolution.Approach.The classical approach to generate the sinogram projection data for estimating the line integrals of the linear attenuation coefficients of the image object is to take a log transform of detector counts, which requires zero counts to be replaced by positive numbers. Both the log transform and the zero-count replacement introduce biases. After analyzing the statistical properties of the zero-count replaced pre-log and post-log data, a formula for the statistical sinogram bias was derived, based on which a new sinogram estimator was empirically constructed to cancel the statistical biases. Dose- and object-independent free parameters in the proposed estimator were learned from simulated data, and then the estimator was applied to experimental low-dose PCD-CT data of physical phantoms for validation and generalizability testing. Both bias and noise performances of the proposed method were evaluated and compared with those of previous zero-count correction methods, including zero-weighting, zero-replacement, and adaptive filtration-based methods. The impact of these correction methods on spatial resolution was also quantified using line-pair patterns.Main Results.For all objects and reduced-dose levels, the proposed method reduces the statistical CT number biases to be within ± 10 HU, which is significantly lower than the biases given by the classical zero-count correction methods. The Bland-Altman analysis demonstrated that the proposed correction led to negligible sinogram biases at all attenuation levels, whereas the other correction methods did not. Additionally, the proposed method was found to have no discernible impact on image noise and spatial resolution.Significance.The proposed zero-count correction scheme allows the CT numbers of low-dose, high-spatial-resolution PCD-CT images to match those of standard-dose and standard-resolution PCD-CT images.

A quality-checked and physics-constrained deep learning method to estimate material basis images from single-kV contrast-enhanced chest CT scans.

BACKGROUND: Single-kV CT imaging is one of the primary imaging methods in radiology practices. However, it does not provide material basis images for some subtle lesion characterization tasks in clinical diagnosis. PURPOSE: To develop a quality-checked and physics-constrained deep learning (DL) method to estimate material basis images from single-kV CT data without resorting to dual-energy CT acquisition schemes. METHODS: Single-kV CT images are decomposed into two material basis images using a deep neural network. The role of this network is to generate a feature space with 64 template features with the same matrix dimensions of the input single-kV CT image. These 64 template image features are then combined to generate the desired material basis images with different sets of combination coefficients, one for each material basis image. Dual-energy CT image acquisitions with two separate kVs were curated to generate paired training data between a single-kV CT image and the corresponding two material basis images. To ensure the obtained two material basis images are consistent with the encoded spectral information in the actual projection data, two physics constraints, that is, (1) effective energy of each measured projection datum that characterizes the beam hardening in data acquisitions and (2) physical factors of scanners such as detector and tube characteristics, are incorporated into the end-to-end training. The entire architecture is referred to as Deep-En-Chroma in this paper. In the application stage, the generated material basis images are sent to a deep quality check (Deep-QC) network to assess the quality of estimated images and to report the pixel-wise estimation errors for users. The models were developed using 5592 training and validation pairs generated from 48 clinical cases. Additional 1526 CT images from another 13 patients were used to evaluate the quantitative accuracy of water and iodine basis images estimated by Deep-En-Chroma. RESULTS: For the iodine basis images estimated by Deep-En-Chroma, the mean difference with respect to dual-energy CT is -0.25 mg/mL, and the agreement limits are [-0.75 mg/mL, +0.24 mg/mL]. For the water basis images estimated by Deep-En-Chroma, the mean difference with respect to dual-energy CT is 0.0 g/mL, and the agreement limits are [-0.01 g/mL, 0.01 g/mL]. Across the test cohort, the median [25th, 75th percentiles] root mean square errors between the Deep-En-Chroma and dual-energy material images are 14 [12, 16] mg/mL for the water images and 0.73 [0.64, 0.80] mg/mL for the iodine images. When significant errors are present in the estimated material basis images, Deep-QC can capture these errors and provide pixel-wise error maps to inform users whether the DL results are trustworthy. CONCLUSIONS: The Deep-En-Chroma network provides a new pathway to estimating the clinically relevant material basis images from single-kV CT data and the Deep-QC module to inform end-users of the accuracy of the DL material basis images in practice.

Wenqingyin suppresses ferroptosis in the pathogenesis of sepsis-induced liver injury by activating the Nrf2-mediated signaling pathway.

BACKGROUND: Wenqingyin (WQY) is a classic traditional Chinese medicine formula used to treat various inflammatory diseases. However, its protective activity against ferroptosis in the pathogenesis of sepsis-induced liver injury and underlying mechanisms remain unclear. PURPOSE: This study aimed to determine the therapeutic efficacy and potential mechanism of action of WQY in sepsis-induced liver injury both in vivo and in vitro. METHODS: In vivo: Lipopolysaccharide was intraperitoneally injected into nuclear factor erythroid 2-related factor 2 (Nrf2) knockout (Nrf2-/-) and wild-type mice to construct a septic liver injury mouse model. Experimental mice were intraperitoneally injected with ferroptosis-1 and intragastrically administered WQY. In vitro: LO2 hepatocytes were stimulated with erastin to activate ferroptosis and later treated with varying concentrations of WQY and an Nrf2 inhibitor (ML385). Pathological damage was evaluated following hematoxylin and eosin staining. Lipid peroxidation levels were assessed using malondialdehyde, superoxide dismutase, and glutathione, as well as reactive oxygen species fluorescent probes. JC-1 staining was performed to evaluate the mitochondrial membrane potential damage. Quantitative reverse transcription polymerase chain reaction and western blot assay were performed to detect the related gene and protein levels. The levels of inflammatory factors were measured using Enzyme-Linked Immunosorbent Assay kits. RESULTS: In vivo, sepsis-induced liver injury activated ferroptosis in mouse liver tissue. Fer-1 and WQY attenuated septic liver injury, which was associated with increased Nrf2 expression. Deletion of the Nrf2 gene led to aggravation of septic liver injury. The effect of WQY on the attenuation of septic liver injury was partially abolished by the knockdown of Nrf2. In vitro, erastin-induced ferroptosis resulted in decreased hepatocyte viability, lipid peroxidation, and mitochondrial membrane potential damage. WQY protected hepatocytes from erastin-induced ferroptosis by activating Nrf2. The attenuation effect of ferroptosis in hepatocytes by WQY was partially abolished by the inhibition of Nrf2. CONCLUSION: Ferroptosis has a critical role in the development of sepsis-mediated liver injury. Inhibition of ferroptosis is a possible novel treatment strategy for alleviating septic liver injury. WQY attenuates sepsis-mediated liver injury by suppressing ferroptosis in hepatocytes, which is related to its ability to activate Nrf2.

Elevated fatty acid ß-oxidation by leptin contributes to the proinflammatory characteristics of fibroblast-like synoviocytes from RA patients via LKB1-AMPK pathway.

Fibroblast-like synoviocytes (FLS) maintain chronic inflammation leading to joint destruction in rheumatoid arthritis (RA). Fatty acid ß-oxidation (FAO) regulates cell function. Here, we aimed to investigate the effect of FAO enhanced by leptin on the characteristics of RA-FLS and elucidate the potential metabolic mechanism. Key enzymes involved in lipid metabolism were detected with qPCR in HSF, MH7A cell line and isolated RA-FLS treated with RA or healthy control (HC) serum. In some experiments, FAO inhibitor, etomoxir (ETO) or anti-leptin antibody were added into serum-treated RA-FLS. In other experiments, RA-FLS were stimulated with leptin together with ETO or AMP-activated protein kinase (AMPK) inhibitor compound C (CC) or silencing liver kinase B1 (LKB1). Cell proliferation, proinflammatory factor production, pro-angiogenesis, chemoattractive potential, FAO-related key enzymes, AMPK and LKB1 in FLS were analyzed. FAO-related key enzymes were evaluated in serum-treated RA-FLS with or without anti-leptin antibody. Related functions of leptin-stimulated RA-FLS were examined in the presence or absence of ETO. AMP-activated protein kinase (AMPK) and liver kinase B1 (LKB1) in leptin-stimulated RA-FLS were tested with western blot. Activation of AMPK in leptin-stimulated RA-FLS was detected after silencing LKB1. We found that MH7A cell line and RA serum-treated FLS exhibited upregulated FAO, and ETO could inhibit the proinflammatory phenotypes of RA-FLS. The addition of anti-leptin antibody suppressed the elevation of FAO mediated by RA serum. More importantly, leptin promoted the proinflammatory characteristics of RA-FLS, which was reversed by ETO. Leptin activated AMPK by upregulating LKB1. CC impaired leptin-induced CPT-1A expression in RA-FLS. Our study uncovers that elevated FAO mediated by leptin drives abnormal function of RA-FLS and suggests leptin or FAO inhibition may serve as a promising therapeutic strategy for RA.

Calycosin protects against oxidative stress-induced cardiomyocyte apoptosis by activating aldehyde dehydrogenase 2.

Myocardial infarction (MI) is the leading cause of death worldwide, and oxidative stress is part of the process that causes MI. Calycosin, a naturally occurring substance with cardioprotective properties, is one of the major active constituents in Radix Astragali. In this study, effect of Calycosin was investigated in vivo and in vitro to determine whether it could alleviate oxidative stress and oxidative stress-induced cardiac apoptosis in neonatal cardiomyocytes (NCMs) via activation of aldehyde dehydrogenase 2 (ALDH2). Calycosin protected against oxidative stress and oxidative stress-induced apoptosis in NCMs. Molecular docking revealed that the ALDH2-Calycosin complex had a binding energy of -9.885 kcal/mol. In addition, molecular docking simulations demonstrated that the ALDH2-Calycosin complex was stable. Using BLI assays, we confirmed that Calycosin could interact with ALDH2 (KD  = 1.9 × 10-4 M). Furthermore, an ALDH2 kinase activity test revealed that Calycosin increased ALDH2 activity, exhibiting an EC50 of 91.79 µM. Pre-incubation with ALDH2 inhibitor (CVT-10216 or disulfiram) reduced the cardio-protective properties Calycosin. In mice with MI, Calycosin therapy substantially reduced myocardial apoptosis, oxidative stress, and activated ALDH2. Collectively, our findings clearly suggest that Calycosin reduces oxidative stress and oxidative stress-induced apoptosis via the regulation of ALDH2 signaling, which supports potential therapeutic use in MI.

Calycosin reduces myocardial fibrosis and improves cardiac function in post-myocardial infarction mice by suppressing TGFBR1 signaling pathways.

BACKGROUND: Excessive myocardial fibrosis is the pathological basis of heart failure following myocardial infarction (MI). Although calycosin improves cardiac function, its effect on cardiac fibrosis and cardiac function after MI in mice and its precise mechanism remain unclear. PURPOSE: Here, we firstly investigated the effects of calycosin on cardiac fibrosis and ventricular function in mice after MI and the role of transforming growth factor-beta receptor 1 (TGFBR1) signaling in the amelioration of cardiac fibrosis and ventricular function. METHODS: In vivo effects of calycosin on cardiac structure and function in mice with MI induced by left anterior descending coronary artery ligation were determined by hematoxylin and eosin staining, Masson trichrome staining, and echocardiography. The molecular mechanism of the interaction between TGFBR1 and calycosin was investigated using molecular docking, molecular dynamics (MD) simulation, surface plasmon resonance imaging (SPRi), immunohistochemistry, and western blotting (WB). Subsequently, cardiac-specific Tgfbr1 knockout mice were used to verify the effects of calycosin. The effect of calycosin on primary cardiac fibroblasts (CFs) proliferation and collagen deposition was detected using cell counting (CCK-8), EdU assay, and WB in vitro. CFs infected with an adenovirus that encodes TGFBR1 were used to verify the effects of calycosin. RESULTS: In vivo, calycosin attenuated myocardial fibrosis and cardiac dysfunction following MI in a dose-dependent pattern. Calycosin-TGFBR1 complex was found to have a binding energy of -9.04 kcal/mol based on molecular docking. In addition, calycosin bound steadily in the cavity of TGFBR1 during the MD simulation. Based on SPRi results, the solution equilibrium dissociation constant for calycosin and TGFBR1 was 5.11 × 10-5 M. Calycosin inhibited the expression of TGFBR1, Smad2/3, collagen I, and collagen III. The deletion of TGFBR1 partially counteracted these effects. In vitro, calycosin suppressed CFs proliferation and collagen deposition after TGF-ß1 stimulation by suppressing the TGFBR1 signaling pathway. The suppressive effects of calycosin were partially rescued by overexpression of TGFBR1. CONCLUSION: Calycosin attenuates myocardial fibrosis and cardiac dysfunction following MI in mice in vivo via suppressing the TGFBR1 signaling pathway. Calycosin suppresses CFs proliferation and collagen deposition induced by TGF-ß1 via inhibition of the TGFBR1 signaling pathway in vitro.

Corrigendum to "Ginsenoside Ro, an oleanolic saponin of Panax ginseng, exerts anti-inflammatory effect by direct inhibiting toll like receptor 4 signaling pathway" [J Ginseng Res 46 (2022) 156-166].

[This corrects the article DOI: 10.1016/j.jgr.2021.05.011.].

Anti-Inflammatory Effects of Ginsenoside Rb3 in LPS-Induced Macrophages Through Direct Inhibition of TLR4 Signaling Pathway.

Panax ginseng has therapeutic effects on various inflammation-related diseases. Ginsenoside Rb3 (GRb3), a natural compound with anti-inflammatory and immunomodulatory properties, is one of the main active panaxadiol extracted from Panax ginseng. We explored whether GRb3 inhibited LPS-mediated inflammation through TLR4/NF-κB/MAPK signaling in macrophages. GRb3 attenuated NO and PGE2 production by attenuating iNOS and COX2 expression. GRb3 also suppressed pro-inflammatory cytokines levels, including IL-1ß, IL-6, and TNF-α. Moreover, GRb3 administration significantly suppressed NF-κB (p65) nuclear translocation and the phosphorylation levels of p65, IκBα, JNK, p38, and ERK dose-dependently. Molecular docking demonstrated that GRb3 could dock onto the hydrophobic binding site of TLR4/MD2 complex, with a binding energy of -8.79 kcal/mol. Molecular dynamics (MD) displayed stable TLR4-MD2-GRb3 modeling. GRb3 dose-dependently inhibited LPS binding to cell membranes and blocked TLR4 expression. Surface plasmon resonance imaging (SPRi) revealed that GRb3 had an excellent binding affinity to TLR4/MD2 complex. Notably, resatorvid (TAK242), a selective TLR4 inhibitor, did not increase the repressive influence of GRb3 in RAW264.7 macrophages. Moreover, TLR4 overexpression partially reversed the repressive roles of GRb3 on the NF-κB/MAPK pathway and inflammatory mediators. Collectively, our study strongly indicated that GRb3 attenuated LPS-mediated inflammation through direct inhibition of TLR4 signaling. A novel insight into the underlying mechanism of anti-inflammatory effects of GRb3 in macrophages was confirmed.

Ginsenoside Ro, an oleanolic saponin of Panax ginseng, exerts anti-inflammatory effect by direct inhibiting toll like receptor 4 signaling pathway.

BACKGROUND: Panax ginseng Meyer (P. ginseng), a herb distributed in Korea, China and Japan, exerts benefits on diverse inflammatory conditions. However, the underlying mechanism and active ingredients remains largely unclear. Herein, we aimed to explore the active ingredients of P. ginseng against inflammation and elucidate underlying mechanisms. METHODS: Inflammation model was constructed by lipopolysaccharide (LPS) in C57BL/6 mice and RAW264.7 macrophages. Molecular docking, molecular dynamics, surface plasmon resonance imaging (SPRi) and immunofluorescence were utilized to predict active component. RESULTS: P. ginseng significantly inhibited LPS-induced lung injury and the expression of pro-inflammatory factors, including TNF-α, IL-6 and IL-1ß. Additionally, P. ginseng blocked fluorescence-labeled LPS (LPS488) binding to the membranes of RAW264.7 macrophages, the phosphorylation of nuclear factor-κB (NF-κB) and mitogen-activated protein kinases (MAPKs). Furthermore, molecular docking demonstrated that ginsenoside Ro (GRo) docked into the LPS binding site of toll like receptor 4 (TLR4)/myeloid differentiation factor 2 (MD2) complex. Molecular dynamic simulations showed that the MD2-GRo binding conformation was stable. SPRi demonstrated an excellent interaction between TLR4/MD2 complex and GRo (KD value of 1.16 × 10-9 M). GRo significantly inhibited LPS488 binding to cell membranes. Further studies showed that GRo markedly suppressed LPS-triggered lung injury, the transcription and secretion levels of TNF-α, IL-6 and IL-1ß. Moreover, the phosphorylation of NF-κB and MAPKs as well as the p65 subunit nuclear translocation were inhibited by GRo dose-dependently. CONCLUSION: Our results suggest that GRo exerts anti-inflammation actions by direct inhibition of TLR4 signaling pathway.