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"SONG, KANG"
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Multi-omics analysis reveals metabolic regulation of phosphatidylcholine, triglycerides, phosphatidylethanolamine, and cardiolipin metabolism in mouse liver with metabolic dysfunction-associated steatotic liver disease
The dysregulation of phosphatidylcholine (PC), triglycerides (TG), phosphatidylethanolamine (PE), and cardiolipin (CL) metabolism is believed to contribute to the development of MASLD. However, little is known about the mechanisms underlying the onset of this condition. To establish a mouse model of MASLD, C57BL/6J mice were fed a high-fat diet (HFD). Lipidomics was applied to identify differences in liver lipids. RNA-sequencing and bioinformatics analyses were conducted to investigate changes in the expression of genes and pathways associated with these metabolic processes. 49 lipid classes and 3221 lipid species were identified using positive- and negative-ion pattern identification. A total of 678 differentially expressed genes were identified, of which 364 were upregulated and 314 were downregulated in the MASLD group. KEGG enrichment pathway analysis highlighted the downregulation of four genes such as Gpat4 , Gpcpd1 , Chkb , and Etnppl. These findings contribute to our understanding of the metabolic changes associated with MASLD.
Journal Article
Comprehensive metabolomics and transcriptomics analysis reveals protein and amino acid metabolic characteristics in liver tissue under chronic hypoxia
At high altitudes, oxygen deprivation can cause pathophysiological changes. Liver tissue function is known to impact whole-body energy metabolism; however, how these functions are affected by chronic hypoxia remains unclear. We aimed to elucidate changing characteristics underlying the effect of chronic hypoxia on protein and amino acid metabolism in mouse livers. Mice were maintained in a hypobaric chamber simulating high altitude for 4 weeks. Livers were collected for metabolomic analysis via ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry. For transcriptomics analysis, we conducted RNA sequencing of hepatic tissues followed by Gene Ontology and KEGG pathway enrichment analyses. Chronic hypoxic exposure caused metabolic disorders of amino acids and their derivatives in liver tissue. We identified a number of metabolites with significantly altered profiles (including amino acids, peptides, and analogues), of which serine, phenylalanine, leucine, proline, aspartic acid, L-glutamate, creatine, 5-aminovaleric acid, L-hydroxyarginin, and g-guanidinobutyrate showed great potential as biomarkers of chronic hypoxia. A total of 2124 genes with significantly different expression levels were identified in hypoxic liver tissue, of which 1244 were upregulated and 880 were downregulated. We found pathways for protein digestion and absorption, arginine and proline metabolism, and mineral absorption related to amino acid metabolism were affected by hypoxia. Our findings surrounding the regulation of key metabolites and differentially expressed genes provide new insights into changes in protein and amino acid metabolism in the liver that result from chronic hypoxia.
Journal Article
Elucidating ascorbate and aldarate metabolism pathway characteristics via integration of untargeted metabolomics and transcriptomics of the kidney of high-fat diet-fed obese mice
Obesity is a major independent risk factor for chronic kidney disease and can activate renal oxidative stress injury. Ascorbate and aldarate metabolism is an important carbohydrate metabolic pathway that protects cells from oxidative damage. However the effect of oxidative stress on this pathway is still unclear. Therefore, the primary objective of this study was to investigate the ascorbate and aldarate metabolism pathway in the kidneys of high-fat diet-fed obese mice and determine the effects of oxidative stress. Male C57BL/6J mice were fed on a high-fat diet for 12 weeks to induce obesity. Subsequently, non-targeted metabolomics profiling was used to identify metabolites in the kidney tissues of the obese mice, followed by RNA sequencing using transcriptomic methods. The integrated analysis of metabolomics and transcriptomics revealed the alterations in the ascorbate and aldarate metabolic pathway in the kidneys of these high-fat diet-fed obese mice. The high-fat diet-induced obesity resulted in notable changes, including thinning of the glomerular basement membrane, alterations in podocyte morphology, and an increase in oxidative stress. Metabolomics analysis revealed 649 metabolites in the positive-ion mode, and 470 metabolites in the negative-ion mode. Additionally, 659 differentially expressed genes (DEGs) were identified in the obese mice, of which 34 were upregulated and 625 downregulated. Integrated metabolomics and transcriptomics analyses revealed two DEGs and 13 differential metabolites in the ascorbate and aldarate metabolic pathway. The expression levels of
ugt1a9
and
ugt2b1
were downregulated, and the ascorbate level in kidney tissue of obese mice was reduced. Thus, renal oxidative stress injury induced by high-fat diet affects metabolic regulation of ascorbate and aldarate metabolism in obese mice. Ascorbate emerged as a potential marker for predicting kidney damage due to high-fat diet-induced obesity.
Journal Article
Comprehensive lipidomic analysis reveals regulation of glyceride metabolism in rat visceral adipose tissue by high-altitude chronic hypoxia
Adipose tissue plays a central role in energy substrate homeostasis and is a key regulator of lipid flow throughout these processes. As hypoxia affects lipid metabolism in adipose tissue, we aimed to investigate the effects of high-altitude chronic hypoxia on lipid metabolism in the adipose tissue of rats using a lipidomic analysis approach. Visceral adipose tissues from rats housed in a high-altitude hypoxia environment representing 4,300 m with 14.07% oxygen (hypoxia group) and from rats housed in a low-altitude normoxia environment representing 41 m with 20.95% oxygen (normoxia group) for 8 weeks were analyzed using an ultra-performance liquid chromatography-Orbitrap mass spectrometry system. After 8 weeks, the body weight and visceral adipose tissue weight of the hypoxia group were significantly decreased compared to those of the normoxia group (p < 0.05). The area and diameter of visceral adipose cells in the hypoxia group were significantly smaller than those of visceral adipose cells in the normoxia group (p < 0.05). The results of lipidomic analysis showed a total of 21 lipid classes and 819 lipid species. The total lipid concentration of the hypoxia group was lower than that in the normoxia group (p < 0.05). Concentrations of diacylglycerols and triacylglycerols in the hypoxia group were significantly lower than those in the normoxia group (p < 0.05). Using univariate and multivariate analyses, we identified 74 lipids that were significantly altered between the normoxia and hypoxia groups. These results demonstrate that high-altitude chronic hypoxia changes the metabolism of visceral adipose glycerides, which may potentially modulate other metabolic processes.
Journal Article
The circular RNA circDLG1 promotes gastric cancer progression and anti-PD-1 resistance through the regulation of CXCL12 by sponging miR-141-3p
Background
Dysregulation of circular RNAs (circRNAs) plays an important role in the development of gastric cancer; thus, revealing the biological and molecular mechanisms of abnormally expressed circRNAs is critical for identifying novel therapeutic targets in gastric cancer.
Methods
A circRNA microarray was performed to identify differentially expressed circRNAs between primary and distant metastatic tissues and between gastric cancer tissues sensitive or resistant to anti-programmed cell death 1 (PD-1) therapy. The expression of circRNA discs large homolog 1 (DLG1) was determined in a larger cohort of primary and distant metastatic gastric cancer tissues. The role of circDLG1 in gastric cancer progression was evaluated both in vivo and in vitro, and the effect of circDLG1 on the antitumor activity of anti-PD-1 was evaluated in vivo. The interaction between circDLG1 and miR-141-3p was assessed by RNA immunoprecipitation and luciferase assays.
Results
circDLG1 was significantly upregulated in distant metastatic lesions and gastric cancer tissues resistant to anti-PD-1 therapy and was associated with an aggressive tumor phenotype and adverse prognosis in gastric cancer patients treated with anti-PD-1 therapy. Ectopic circDLG1 expression promoted the proliferation, migration, invasion, and immune evasion of gastric cancer cells. Mechanistically, circDLG1 interacted with miR-141-3p and acted as a miRNA sponge to increase the expression of CXCL12, which promoted gastric cancer progression and resistance to anti-PD-1-based therapy.
Conclusions
Overall, our findings demonstrate how circDLG1 promotes gastric cancer cell proliferation, migration, invasion and immune evasion and provide a new perspective on the role of circRNAs during gastric cancer progression.
Journal Article
Adaptive self-healing electronic epineurium for chronic bidirectional neural interfaces
Realizing a clinical-grade electronic medicine for peripheral nerve disorders is challenging owing to the lack of rational material design that mimics the dynamic mechanical nature of peripheral nerves. Electronic medicine should be soft and stretchable, to feasibly allow autonomous mechanical nerve adaptation. Herein, we report a new type of neural interface platform, an adaptive self-healing electronic epineurium (A-SEE), which can form compressive stress-free and strain-insensitive electronics-nerve interfaces and enable facile biofluid-resistant self-locking owing to dynamic stress relaxation and water-proof self-bonding properties of intrinsically stretchable and self-healable insulating/conducting materials, respectively. Specifically, the A-SEE does not need to be sutured or glued when implanted, thereby significantly reducing complexity and the operation time of microneurosurgery. In addition, the autonomous mechanical adaptability of the A-SEE to peripheral nerves can significantly reduce the mechanical mismatch at electronics-nerve interfaces, which minimizes nerve compression-induced immune responses and device failure. Though a small amount of Ag leaked from the A-SEE is observed in vivo (17.03 ppm after 32 weeks of implantation), we successfully achieved a bidirectional neural signal recording and stimulation in a rat sciatic nerve model for 14 weeks. In view of our materials strategy and in vivo feasibility, the mechanically adaptive self-healing neural interface would be considered a new implantable platform for a wide range application of electronic medicine for neurological disorders in the human nervous system.
Electronic implantable devices should be soft and stretchable, such that nerves can adapt mechanically and autonomously. Here, the authors present an adaptive self-healing electronic epineurium which can form compressive stress-free and strain-insensitive electronics-nerve interfaces.
Journal Article
Non-Intrusive Load Identification Based on Retrainable Siamese Network
Non-intrusive load monitoring (NILM) can identify each electrical load and its operating state in a household by using the voltage and current data measured at a single point on the bus, thereby behaving as a key technology for smart grid construction and effective energy consumption. The existing NILM methods mainly focus on the identification of pre-trained loads, which can achieve high identification accuracy and satisfying outcomes. However, unknown load identification is rarely involved among those methods and the scalability of NILM is still a crucial problem at the current stage. In light of this, we have proposed a non-intrusive load identification method based on a Siamese network, which can be retrained after the detection of an unknown load to increase the identification accuracy for unknown loads. The proposed Siamese network comprises a fixed convolutional neural network (CNN) and two retrainable back propagation (BP) networks. When an unknown load is detected, the low-dimensional features of its voltage–current (V-I) trajectory are extracted by using the fixed CNN model, and the BP networks are retrained online. The finetuning of BP network parameters through retraining can improve the representation ability of the network model; thus, a high accuracy of unknown load identification can be achieved by updating the Siamese network in real time. The public WHITED and PLAID datasets are used for the validation of the proposed method. Finally, the practicality and scalability of the method are demonstrated using a real-house environment test to prove the ability of online retraining on an embedded Linux system with STM32MP1 as the core.
Journal Article