A study on the treatment effects of Crataegus pinnatifida polysaccharide on non-alcoholic fatty liver in mice by modulating gut microbiota

The objective of this study was to investigate the protective effect of Crataegus pinnatifida polysaccharide (CPP) on non-alcoholic fatty liver disease (NAFLD) induced by a high-fat diet (HFD) in mice. The findings demonstrated that CPP improved free fatty acid (FFA)-induced lipid accumulation in HepG2 cells and effectively reduced liver steatosis and epididymal fat weight in NAFLD mice, as well as decreased serum levels of TG, TC, AST, ALT, and LDL-C. Furthermore, CPP exhibited inhibitory effects on the expression of fatty acid synthesis genes FASN and ACC while activating the expression of fatty acid oxidation genes CPT1A and PPARα. Additionally, CPP reversed disturbances in intestinal microbiota composition caused by HFD consumption. CPP decreased the firmicutes/Bacteroidetes ratio, increased Akkermansia abundance, and elevated levels of total short-chain fatty acid (SCFA) content specifically butyric acid and acetic acid. Our results concluded that CPP may intervene in the development of NAFLD by regulating of intes-tinal microbiota imbalance and SCFAs production. Our study highlights that CPP has a potential to modulate lipid-related pathways via alterations to gut microbiome composition thereby ex-erting inhibitory effects on obesity and NAFLD development

Danon Disease-Associated LAMP-2 Deficiency Drives Metabolic Signature Indicative of Mitochondrial Aging and Fibrosis in Cardiac Tissue and hiPSC-Derived Cardiomyocytes

Danon disease is a severe X-linked disorder caused by deficiency of the lysosome-associated membrane protein-2 (LAMP-2). Clinical manifestations are phenotypically diverse and consist of hypertrophic and dilated cardiomyopathies, skeletal myopathy, retinopathy, and intellectual dysfunction. Here, we investigated the metabolic landscape of Danon disease by applying a multi-omics approach and combined structural and functional readouts provided by Raman and atomic force microscopy. Using these tools, Danon patient-derived cardiac tissue, primary fibroblasts, and human induced pluripotent stem cells differentiated into cardiomyocytes (hiPSC-CMs) were analyzed. Metabolic profiling indicated LAMP-2 deficiency promoted a switch toward glycolysis accompanied by rerouting of tryptophan metabolism. Cardiomyocytes' energetic balance and NAD+/NADH ratio appeared to be maintained despite mitochondrial aging. In turn, metabolic adaption was accompanied by a senescence-associated signature. Similarly, Danon fibroblasts appeared more stress prone and less biomechanically compliant. Overall, shaping of both morphology and metabolism contributed to the loss of cardiac biomechanical competence that characterizes the clinical progression of Danon disease.</p

CAMTA: A Signal-Responsive Transcription Factor That Promotes Cardiac Growth by Opposing Class II Histone Deacetylases

Cardiac growth is finely regulated by transcriptional circuits. In an effort to discover new regulators of cardiac growth, I performed a eukaryotic expression screen for activators of the atrial natriuretic factor (ANF) gene, a cardiac-specific marker of hypertrophic signaling and embryonic development. I discovered that a family of transcription factors, called CAMTAs, regulate the ANF promoter. CAMTA proteins were first discovered in plants, however, little was known of the mechanism of their action and biological function and virtually nothing was known about mammalian CAMTA proteins, CAMTA1 and CAMTA2. CAMTA1 and CAMTA2 are enriched in embryonic and adult hearts, skeletal muscle at the embryonic stage, and brain. To define the mechanism whereby CAMTA2 activates the ANF promoter, I used a series of promoter deletion mutants to map the cis-regulatory sequences that confer responsiveness to CAMTA2. I found that CAMTA activates the ANF gene, at least in part, by associating with Nkx2-5, a cardiac transcription factor. CAMTA proteins also activate promoters of myogenin and beta myosin heavy chain via direct DNA binding. Therefore, CAMTAs activate target genes through diverse mechanisms. Over-expression of CAMTA2 in vitro and in vivo promotes cardiac growth. Based on the ability of CAMTA2 to induce hypertrophy, I tested whether signaling molecules implicated in cardiac hypertrophy might enhance the activity of CAMTA2. I discovered that the transcriptional activity of CAMTAs is governed by association with class II histone deacetylases (HDACs), which negatively regulate cardiac growth. Mice homozygous for a mutation in the CAMTA2 gene are defective in cardiac growth in response to pressure overload and neurohumoral signaling, whereas mice lacking HDAC5, a class II HDAC are sensitized to the pro-hypertrophic actions of CAMTA. CAMTA proteins are also required for embryonic heart development, as demonstrated by heart defects in mice with low dosage of CAMTA1. These findings reveal a transcriptional regulatory mechanism that modulates cardiac growth and gene expression by linking cardiac growth signals to the cardiac genome

Lysosomal Abnormalities in Cardiovascular Disease

The lysosome, a key organelle for cellular clearance, is associated with a wide variety of pathological conditions in humans. Lysosome function and its related pathways are particularly important for maintaining the health of the cardiovascular system. In this review, we highlighted studies that have improved our understanding of the connection between lysosome function and cardiovascular diseases with an emphasis on a recent breakthrough that characterized a unique autophagosome-lysosome fusion mechanism employed by cardiomyocytes through a lysosomal membrane protein LAMP-2B. This finding may impact the development of future therapeutic applications

Differentiation of Pluripotent Stem Cells for Disease Modeling: Learning from Heart Development

Heart disease is a pressing public health problem and the leading cause of death worldwide. The heart is the first organ to gain function during embryogenesis in mammals. Heart development involves cell determination, expansion, migration, and crosstalk, which are orchestrated by numerous signaling pathways, such as the Wnt, TGF-β, IGF, and Retinoic acid signaling pathways. Human-induced pluripotent stem cell-based platforms are emerging as promising approaches for modeling heart disease in vitro. Understanding the signaling pathways that are essential for cardiac development has shed light on the molecular mechanisms of congenital heart defects and postnatal heart diseases, significantly advancing stem cell-based platforms to model heart diseases. This review summarizes signaling pathways that are crucial for heart development and discusses how these findings improve the strategies for modeling human heart disease in vitro

Establishment of prediction model for risk of postoperative cognitive dysfunction after non-cardiac surgery based on different machine learning algorithms

Objective To establish a risk model for predicting postoperative cognitive dysfunction (POCD) after non-cardiac surgery using preoperative indicators based on machine learning algorithm. Methods A case-control study was designed, and conducted on the POCD patients after non-cardiac surgery in the medical big data platform of our hospital from January 2014 to January 2019. Finally, 92 patients were included in the POCD group. According to surgical type and age matched of the POCD group, another 276 patients who did not develop POCD after surgery and discharged from the hospital during the same time period from the same big data platform were assigned into the non-POCD group at a ratio of 1∶3. At the same time, these 368 patients were randomly divided into modeling group (n=259) and validation group (n=109) at a ratio of 7∶3. After data preprocessing and feature selection of preoperative clinical indicators (general data, relevant scoring scales, surgical-related data and results of preoperative laboratory tests), the risk prediction model of POCD for non-cardiac surgery was established based on 3 machine learning algorithms, that is, logistic regression (LR), support vector machine (SVM) and Decision Tree. The model efficacy was evaluated by sensitivity, specificity, F1 score, and the area under the receiver operating characteristic curve (AUC). Results The SVM algorithm was the best model among the 3 machine learning algorithms to predict the risk of POCD after non-cardiac surgery. The AUC value of the model in the validation group was 0.957 (95%CI: 0.905~1.000), with a sensitivity and specificity of 92.6% and 98.8%, respectively. Conclusion A prediction model of POCD after non-cardiac surgery is successfully established based on machine learning algorithm. This model shows good predictive performance for POCD. [Key words] machine learning , prediction model , postoperative cognitive dysfunction

Hydrochemistry and Dissolved Inorganic Carbon (DIC) Cycling in a Tropical Agricultural River, Mun River Basin, Northeast Thailand

Dissolved inorganic carbon isotope composition (&delta;13CDIC), together with major ion concentrations were measured in the Mun River and its tributaries in March 2018 to constrain the origins and cycling of dissolved inorganic carbon. In the surface water samples, the DIC content ranged from 185 to 5897 &mu;mol/L (average of 1376 &mu;mol/L), and the &delta;13CDIC of surface water ranged from &minus;19.6&permil; to &minus;2.7&permil;. In spite of the high variability in DIC concentrations and partial pressure of carbon dioxide (pCO2), the &delta;13CDIC values of the groundwater were relatively consistent, with a mean value of &minus;16.9 &plusmn; 1.4&permil; (n = 9). Spatial changes occurred in the direction and magnitude of CO2 flux through water-air interface (FCO2). In the dry season, fluxes varied from &minus;6 to 1826 mmol/(m2&middot;d) with an average of 240 mmol/(m2&middot;d). In addition to the dominant control on hydrochemistry and dissolved inorganic carbon isotope composition by the rock weathering, the impacts from anthropogenic activities were also observed in the Mun River, especially higher DIC concentration of waste water from urban activities. These human disturbances may affect the accurate estimate contributions of carbon dioxide from tropical rivers to the atmospheric carbon budgets

Spatial and Temporal Variation of Dissolved Heavy Metals in the Mun River, Northeast Thailand

River water samples between August 2017 (wet season) and March 2018 (dry season) from the Mun River Basin in northeast Thailand were collected and their dissolved heavy metals concentrations (Al, Mn, Fe, Cu, Zn, and Ba) were measured. Compared with international drinking water guidelines, Mn was the dominant pollutant in the dry season. The correlation analysis (CA) suggested that similar sources were shown in each element pair of Al-Fe, Mn-Zn, and Fe-Ba in both seasons. The principal component analysis (PCA) results showed that the dominant source of dissolved heavy metals was sedimentary inputs or colloid destabilization in the wet season, while anthropogenic inputs were the main sources in the dry season, such as agricultural runoff, industrial effluents, and domestic discharge. On the basis of water quality index (WQI), water at most sites in the wet and dry seasons can be categorized as excellent water, except for a few sites with substandard values. The river water posed no significant health risks according to the health risk assessment, but Mn, Fe, and Ba needed to be paid more attention due to the relatively high values. Al, Fe, and Ba were the main dissolved heavy metals flowing into the Mekong River, and Cu contributed to the background value in the Mekong river

Danon Disease-Associated LAMP-2 Deficiency Drives Metabolic Signature Indicative of Mitochondrial Aging and Fibrosis in Cardiac Tissue and hiPSC-Derived Cardiomyocytes

Danon disease is a severe X-linked disorder caused by deficiency of the lysosome-associated membrane protein-2 (LAMP-2). Clinical manifestations are phenotypically diverse and consist of hypertrophic and dilated cardiomyopathies, skeletal myopathy, retinopathy, and intellectual dysfunction. Here, we investigated the metabolic landscape of Danon disease by applying a multi-omics approach and combined structural and functional readouts provided by Raman and atomic force microscopy. Using these tools, Danon patient-derived cardiac tissue, primary fibroblasts, and human induced pluripotent stem cells differentiated into cardiomyocytes (hiPSC-CMs) were analyzed. Metabolic profiling indicated LAMP-2 deficiency promoted a switch toward glycolysis accompanied by rerouting of tryptophan metabolism. Cardiomyocytes\u2019 energetic balance and NAD+/NADH ratio appeared to be maintained despite mitochondrial aging. In turn, metabolic adaption was accompanied by a senescence-associated signature. Similarly, Danon fibroblasts appeared more stress prone and less biomechanically compliant. Overall, shaping of both morphology and metabolism contributed to the loss of cardiac biomechanical competence that characterizes the clinical progression of Danon disease