Identification of Lipotoxicity-Related Biomarkers in Diabetic Nephropathy Based on Bioinformatic Analysis.

Objective: This study is aimed at investigating diagnostic biomarkers associated with lipotoxicity and the molecular mechanisms underlying diabetic nephropathy (DN). Methods: The GSE96804 dataset from the Gene Expression Omnibus (GEO) database was utilized to identify differentially expressed genes (DEGs) in DN patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the DEGs. A protein-protein interaction (PPI) network was established to identify key genes linked to lipotoxicity in DN. Immune infiltration analysis was employed to identify immune cells with differential expression in DN and to assess the correlation between these immune cells and lipotoxicity-related hub genes. The findings were validated using the external dataset GSE104954. ROC analysis was performed to assess the diagnostic performance of the hub genes. The Gene set enrichment analysis (GSEA) enrichment method was utilized to analyze the key genes associated with lipotoxicity as mentioned above. Result: In this study, a total of 544 DEGs were identified. Among them, extracellular matrix (ECM), fatty acid metabolism, AGE-RAGE, and PI3K-Akt signaling pathways were significantly enriched. Combining the PPI network and lipotoxicity-related genes (LRGS), LUM and ALB were identified as lipotoxicity-related diagnostic biomarkers for DN. ROC analysis showed that the AUC values for LUM and ALB were 0.882 and 0.885, respectively. The AUC values for LUM and ALB validated in external datasets were 0.98 and 0.82, respectively. Immune infiltration analysis revealed significant changes in various immune cells during disease progression. Macrophages M2, mast cells activated, and neutrophils were significantly associated with all lipotoxicity-related hub genes. These key genes were enriched in fatty acid metabolism and extracellular matrix-related pathways. Conclusion: The identified lipotoxicity-related hub genes provide a deeper understanding of the development mechanisms of DN, potentially offering new theoretical foundations for the development of diagnostic biomarkers and therapeutic targets related to lipotoxicity in DN.

Role of liver FGF21-KLB signaling in ketogenic diet-induced amelioration of hepatic steatosis.

BACKGROUND: The effectiveness of ketogenic diet (KD) in ameliorating fatty liver has been established, although its mechanism is under investigation. Fibroblast growth factor 21 (FGF21) positively regulates obesity-associated metabolic disorders and is elevated by KD. FGF21 conventionally initiates its intracellular signaling via receptor ß-klotho (KLB). However, the mechanistic role of FGF21-KLB signaling for KD-ameliorated fatty liver remains unknown. This study aimed to delineate the critical role of FGF21 signaling in the ameliorative effects of KD on hepatic steatosis. METHODS: Eight-week-old C57BL/6 J mice were fed a chow diet (CD), a high-fat diet (HFD), or a KD for 16 weeks. Adeno-associated virus-mediated liver-specific KLB knockdown mice and control mice were fed a KD for 16 weeks. Phenotypic assessments were conducted during and after the intervention. We investigated the mechanism underlying KD-alleviated hepatic steatosis using multi-omics and validated the expression of key genes. RESULTS: KD improved hepatic steatosis by upregulating fatty acid oxidation and downregulating lipogenesis. Transcriptional analysis revealed that KD dramatically activated FGF21 pathway, including KLB and fibroblast growth factor receptor 1 (FGFR1). Impairing liver FGF21 signaling via KLB knockdown diminished the beneficial effects of KD on ameliorating fatty liver, insulin resistance, and regulating lipid metabolism. CONCLUSION: KD demonstrates beneficial effects on diet-induced metabolic disorders, particularly on hepatic steatosis. Liver FGF21-KLB signaling plays a critical role in the KD-induced amelioration of hepatic steatosis.

Pioglitazone-Enhanced Brown Fat Whitening Contributes to Weight Gain in Diet-Induced Obese Mice.

INTRODUCTION: Pioglitazone is an insulin sensitizer used for the treatment of type 2 diabetes mellitus (T2DM) by activating peroxisome proliferator-activated receptor gamma. This study aimed to investigate the effects of pioglitazone on white adipose tissue (WAT) and brown adipose tissue (BAT) in diet-induced obese (DIO) mice. METHODS: C57BL/6 mice were treated with pioglitazone (30 mg/kg/day) for 4 weeks after a 16-week high-fat diet (HFD) challenge. Body weight gain, body fat mass, energy intake, and glucose homeostasis were measured during or after the treatment. Histopathology was observed by hematoxylin and eosin, oil red O, immunohistochemistry, and immunofluorescence staining. Expression of thermogenic and mitochondrial biogenesis-related genes was detected by quantitative real-time PCR and western blotting. RESULTS: After 4-week pioglitazone treatment, the fasting blood glucose levels, glucose tolerance, and insulin sensitivity were significantly improved, but the body weight gain and fat mass were increased in DIO mice. Compared with the HFD group, pioglitazone did not significantly affect the weights of liver and WAT in both subcutaneous and epididymal regions. Unexpectedly, the weight of BAT was increased after pioglitazone treatment. Histological staining revealed that pioglitazone ameliorated hepatic steatosis, reduced the adipocyte size in WAT, but increased the adipocyte size in BAT. CONCLUSION: Though pioglitazone can promote lipolysis, thermogenesis, and mitochondrial function in WAT, it leads to impaired thermogenesis, and mitochondrial dysfunction in BAT. In conclusion, pioglitazone could promote the browning of WAT but led to the whitening of BAT; the latter might be a new potential mechanism of pioglitazone-induced weight gain during T2DM treatment.

SGLT2 inhibitor empagliflozin downregulates miRNA-34a-5p and targets GREM2 to inactivate hepatic stellate cells and ameliorate non-alcoholic fatty liver disease-associated fibrosis.

BACKGROUND AND RATIONALE: Activation of hepatic stellate cells (HSCs), the central event of fibrosis, indicates the severe stage of non-alcoholic fatty liver disease (NAFLD). MicroRNAs (miRNAs) participate in this process. Treatment with a sodium-glucose cotransporter 2 inhibitor (SGLT2i) alleviates liver fibrosis in patients with type 2 diabetes and NAFLD; however, the role of SGLT2i in ameliorating liver fibrosis in NAFLD by regulating miRNAs remains unclear. APPROACH AND RESULTS: We monitored the expression of NAFLD-associated miRNAs in the livers of two NAFLD models and observed high expression of miR-34a-5p. miR-34a-5p was highly expressed in mouse primary liver non-parenchymal cells and LX-2 HSCs, and this miRNA was positively correlated with alanine transaminase levels in NAFLD models. Overexpression of miR-34a-5p enhanced LX-2 activation, whereas its inhibition prevented HSCs activation by regulating the TGFß signaling pathway. The SGLT2i empagliflozin significantly downregulated miR-34a-5p, inhibited the TGFß signaling pathway, and ameliorated hepatic fibrosis in NAFLD models. Subsequently, GREM2 was identified as a direct target of miR-34a-5p through database prediction and a dual-luciferase reporter assay. In LX-2 HSCs, the miR-34a-5p mimic and inhibitor directly downregulated and upregulated GREM2, respectively. Overexpressing GREM2 inactivated the TGFß pathway whereas GREM2 knockdown activated it. Additionally, empagliflozin upregulated Grem2 expression in NAFLD models. In methionine- and choline-deficient diet-fed ob/ob mice, a fibrosis model, empagliflozin downregulated miR-34a-5p and upregulated Grem2 to improve liver fibrosis. CONCLUSIONS: Empagliflozin ameliorates NAFLD-associated fibrosis by downregulating miR-34a-5p and targeting GREM2 to inhibit the TGFß pathway in HSCs.

How can the landscape ecological security pattern be quantitatively optimized and effectively evaluated? An integrated analysis with the granularity inverse method and landscape indicators.

The optimization of the landscape ecological security pattern aims to construct a suitable ecological environment and promote the harmonious development between humans and nature. The optimization model of the ecological security pattern for the main urban area of Chongqing was constructed with the granularity inverse method, minimum cumulative resistance model, and spatial network analysis method. We used ecological nodes to optimize the landscape ecological security pattern by organically combining the landscape quantity and spatial structure, and analyzed the effectiveness of the optimized pattern. The results were as follows: (1) The optimal granularity for selecting the ecological source in the study area was 500 m. There were 220 ecological sources with a total area of 188691.03 hm2 and a minimum area of 75.15 hm2. (2) The ecological buffer zone, protection and utilization zone, key development zone, coordinated control zone, and restricted development zone accounted for 57.78%, 20.87%, 12.36%, 6.48%, and 2.50%, respectively, of the total area. (3) The construction of the landscape ecological security pattern contained 70 ecological corridors with a total length of 415.89 km. The longest and shortest ecological corridors had lengths of 20.33 km and 1153.23 m, respectively. There were 17 ecological nodes of corridor-resistance and 27 ecological nodes of corridor-corridor. (4) 41 ecological node service areas were constructed, with a total area of approximately 236.0723 hm2, accounting for 0.04% of the total study area, and the largest and smallest ecological node areas were 6.0744 hm2 and 0.0057 hm2, respectively. (5) The optimized result of the landscape ecological security pattern converted 209.1384 hm2 of nonecological land into ecological land.

Human umbilical cord-derived mesenchymal stem cell-exosomal miR-627-5p ameliorates non-alcoholic fatty liver disease by repressing FTO expression.

Non-alcoholic fatty liver disease (NAFLD) is a spectrum of liver disorders. Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs)-based therapy is currently considered to be an effective treatment for NAFLD. The present study aimed to determine whether hUC-MSCs-exosomes have a hepatoprotective effect on NAFLD. We constructed NAFLD rat model by high-fat high-fructose feeding. Liver cells (L-O2) were treated with palmitic acid (PA) to mimic NAFLD model. NAFLD rats and PA-treated L-O2 cells were treated with hUC-MSCs-exosomes, and then we determined the influence of exosomes on liver damage and glucose and lipid metabolism in vivo and in vitro. We found that hUC-MSCs-exosomes exhibited an up-regulation of miR-627-5p. Exosomal miR-627-5p promoted cell viability and repressed apoptosis of PA-treated L-O2 cells. Exosomal miR-627-5p also enhanced the expression of G6Pc, PEPCK, FAS and SREBP-1c and suppressed PPARα expression in PA-treated L-O2 cells. Moreover, miR-627-5p interacted with fat mass and obesity-associated gene (FTO) and inhibited FTO expression in L-O2 cells. MiR-627-5p-enriched exosomes improved glucose and lipid metabolism in L-O2 cells by targeting FTO. In vivo, exosomal miR-627-5p ameliorated insulin tolerance, liver damage, glucose and lipid metabolism and reduced lipid deposition in NAFLD rats. Exosomal miR-627-5p also reduced body weight, liver weight, and liver index (body weight/liver weight) in NAFLD rats. In conclusion, these data demonstrate that HUC-MSCs-derived exosomal miR-627-5p improves glucose and lipid metabolism and alleviate liver damage by repressing FTO expression, thereby ameliorating NAFLD progression. Thus, hUC-MSCs-exosomes may be a potential treatment for NAFLD.

Exoskeleton Follow-Up Control Based on Parameter Optimization of Predictive Algorithm.

The prediction of sensor data can help the exoskeleton control system to get the human motion intention and target position in advance, so as to reduce the human-machine interaction force. In this paper, an improved method for the prediction algorithm of exoskeleton sensor data is proposed. Through an algorithm simulation test and two-link simulation experiment, the algorithm improves the prediction accuracy by 14.23 ± 0.5%, and the sensor data is smooth. Input the predicted signal into the two-link model, and use the calculated torque method to verify the prediction accuracy data and smoothness. The simulation results showed that the algorithm can predict the joint angle of the human body and can be used for the follow-up control of the swinging legs of the exoskeleton.

Metformin Alleviates Steatohepatitis in Diet-Induced Obese Mice in a SIRT1-Dependent Way.

Metformin is the first-line anti-diabetic drug for type 2 diabetes. It has been found to significantly reduce liver aminotransferase in nonalcoholic fatty liver disease (NAFLD). However, whether metformin improves NAFLD progression remains controversial. Sirtuin 1 (SIRT1), an NAD+-dependent deacetylase, plays a vital role in hepatic steatosis and inflammation. Here, we investigated the effect of metformin on steatohepatitis and the role of SIRT1 in diet-induced obese (DIO) mice. The results showed that metformin significantly reduced body weight and fat mass of DIO mice. In addition, metformin also alleviated adiposity and hepatic steatosis, and greatly upregulated uncoupling protein 1 (UCP1) expression in adipose tissues of DIO mice. Unexpectedly, the effects of metformin on reducing body weight and alleviating hepatic steatosis were not impaired in Sirt1 heterozygous knockout (Sirt1 +/- ) mice. However, SIRT1-deficiency remarkably impaired the effects of metformin on lowering serum transaminases levels, downregulating the mRNA expression of proinflammatory factors, and increasing the protein level of hepatic Cholesterol 25-Hydroxylase (CH25H), a cholesterol hydroxylase in cholesterol catabolism. In summary, we demonstrated that metformin alleviates steatohepatitis in a SIRT1-dependent manner, and modulation of M1 polarization and cholesterol metabolism may be the underlying mechanism.

Computer-Aided Diagnosis of COVID-19 CT Scans Based on Spatiotemporal Information Fusion.

Coronavirus disease (COVID-19) is highly contagious and pathogenic. Currently, the diagnosis of COVID-19 is based on nucleic acid testing, but it has false negatives and hysteresis. The use of lung CT scans can help screen and effectively monitor diagnosed cases. The application of computer-aided diagnosis technology can reduce the burden on doctors, which is conducive to rapid and large-scale diagnostic screening. In this paper, we proposed an automatic detection method for COVID-19 based on spatiotemporal information fusion. Using the segmentation network in the deep learning method to segment the lung area and the lesion area, the spatiotemporal information features of multiple CT scans are extracted to perform auxiliary diagnosis analysis. The performance of this method was verified on the collected dataset. We achieved the classification of COVID-19 CT scans and non-COVID-19 CT scans and analyzed the development of the patients' condition through the CT scans. The average accuracy rate is 96.7%, sensitivity is 95.2%, and F1 score is 95.9%. Each scan takes about 30 seconds for detection.

Study on the gradient change of the landscape pattern in the Three Gorges Reservoir area by coupling the optimal grain size method and multidirectional gradient transect method.

Human disturbance in the landscape lead to dramatic changes in the spatial structure of landscape patterns. This paper takes the Chongqing Three Gorges Reservoir area of China as case study to carry out gradient change analysis of the landscape pattern. Firstly, the coupled inflection point analysis, information loss method, and principal component analysis are used to determine the optimal grain size in a landscape gradient analysis. Secondly, the multidirectional gradient transect method is selected to analyze the law of landscape gradient change and the change of the landscape index. Finally, we analyzed various landscapes at the type level and obtained the distributions of the landscape types. The research highlights the gradient characteristics and landscape structure responses of typical transects of landscape subdivision types. The main results are as follows: (1) The optimal grain size of gradient analysis is 50 m. The patch density, patch shape complexity, and land use abundance of transects from the head to the tail of the reservoir increase. (2) At the landscape level, low mountain areas are more strongly blocked, and landscape connectivity reaches a minimum. At the type level, the landscape shape in the urban-rural interface zone is more complex. (3) Various landscape types are regularly ordered and form the gradient of "urban-agricultural-natural."

Multichannel Saliency Detection Based on Visual Bionics.

Inspired by the visual properties of the human eyes, the depth information of visual attention is integrated into the saliency detection to effectively solve problems such as low accuracy and poor stability under similar or complex background interference. Firstly, the improved SLIC algorithm was used to segment and cluster the RGBD image. Secondly, the depth saliency of the image region was obtained according to the anisotropic center-surround difference method. Then, the global feature saliency of RGB image was calculated according to the colour perception rule of human vision. The obtained multichannel saliency maps were weighted and fused based on information entropy to highlighting the target area and get the final detection results. The proposed method works within a complexity of O(N), and the experimental results show that our algorithm based on visual bionics effectively suppress the interference of similar or complex background and has high accuracy and stability.

Direct amidation of non-activated phenylacetic acid and benzylamine derivatives catalysed by NiCl2.

This paper describes an eco-friendly and efficient direct amidation of benzylamine and phenylacetic acid derivatives in the presence of 10 mol% NiCl2 as catalyst without any drying agent. For the different phenylacetic acid and benzylamine derivatives, the direct catalysed amidation gave moderate-to-excellent yields in toluene. The steric and electronic effects of substituent groups on the phenyl ring of acid were crucial to the yields of the direct amidation. The catalyst NiCl2 can be recycled three times without loss of activity.