OBJECTIVES: To investigate the regulatory role of nucleotide-bound oligomerized domain-like receptor containing pyrin-domain protein 6 (NLRP6) in liver lipid metabolism and non-alcoholic fatty liver disease (NAFLD). METHODS: Mouse models with high-fat diet (HFD) feeding for 16 weeks (n=6) or with methionine choline-deficient diet (MCD) feeding for 8 weeks (n=6) were examined for the development of NAFLD using HE and oil red O staining, and hepatic expressions of NLRP6 were detected with RT-qPCR, Western blotting, and immunohistochemical staining. Cultured human hepatocytes (LO2 cells) with adenovirus-mediated NLRP6 overexpression or knock-down were treated with palmitic acid (PA) in the presence or absence of compound C (an AMPK inhibitor), and the changes in cellular lipid metabolism were examined by measuring triglyceride, ATP and β-hydroxybutyrate levels and using oil red staining, RT-qPCR, and Western blotting. RESULTS: HFD and MCD feeding both resulted in the development of NAFLD in mice, which showed significantly decreased NLRP6 expression in the liver. In PA-treated LO2 cells, NLRP6 overexpression significantly decreased cellular TG content and lipid deposition, while NLRP6 knockdown caused the opposite effects. NLRP6 overexpression in PA-treated LO2 cells also increased mRNA and protein expressions of PGC1A and CPT1A, levels of ATP and β-hydroxybutyrate, and the phosphorylation level of AMPK pathway; the oxidative decomposition of lipids induced by Ad-NLRP6 was inhibited by the use of AMPK inhibitors. CONCLUSIONS NLRP6 overexpression promotes lipid oxidation and decomposition through AMPK/CPT1A/PGC1A to alleviate lipid deposition in hepatocytes.
Non-alcoholic Fatty Liver Disease/metabolism* ; Animals ; Hepatocytes/metabolism* ; Lipid Metabolism ; Mice ; Humans ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha ; AMP-Activated Protein Kinases/metabolism* ; Carnitine O-Palmitoyltransferase/metabolism* ; Diet, High-Fat ; Male ; Mice, Inbred C57BL ; Signal Transduction

Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.

This study aims to investigate the medication rules of patented traditional Chinese medi-cine(TCM)compound formulas and molecular mechanisms of core drugs for treating sepsis using data mining and network pharmacology approaches.In the present study,we first searched the PubMed database,Web of Science database,and the China National Knowledge Infrastructure(CNKI)since the establishment of the library to April 30,2024 for the relevant literature on the treatment of sepsis by traditional Chinese medicine.The prescriptions were then statistically ana-lyzed for drug frequency and association analysis to obtain the core drugs.Then we screened the ef-fective active ingredients of the core drugs by TCMSP and other database platforms,obtained sep-sis-related genes in GeneCards and other databases,and statistically intersected targets,and predic-ted the mechanism of action of the core TCMs by subjecting the intersected targets to PPI analy-sis,GO function and KEGG pathway enrichment analysis.Finally,the relationship between key tar-gets and herbal components was examined in reverse by molecular docking method.The results showed that 64 compound formulas were obtained,with a total of 150 Chinese medicines,which were mostly sweet in taste,cold in nature,and belonged to the spleen,stomach and intestinal me-ridians.According to the association rules,the core drugs were identified as"mirabilite-peach ker-nel-rheum officinale".There were 79 intersecting targets between the core drugs and sepsis,with core targets such as IL-1β,EGFR and SRC.MAPK,TNF,IL-17 and other signaling pathways are involved to mediate inflammatory responses,apoptosis and other biological processes to exert ther-apeutic effects on sepsis.The molecular docking results indicated that the docking activity of the key targets with the main components of the drug,and sennoside E_qt has the lowest binding ener-gy and the best docking activity with SRC.In conclusion,this study showed that the prescription of Chinese medicine for sepsis is mostly based on tonifying the spleen and clearing heat.The mecha-nism of action of the core drug"mirabilite-peach kernel-rheum officinale"in the treatment of sep-sis is multilevel and multifaceted,which provides a certain theoretical basis for the treatment of sepsis by traditional Chinese medicine.

Type 2 diabetes mellitus(T2DM)is a metabolic disease characterized by insulin resistance,and is one of the most common chronic non-communicable diseases worldwide.In the field of traditional Chinese medicine(TCM),yang deficiency causing diabetes is one of the important pathogenetic mechanisms of T2DM and contributes to the core pathological basis of insulin resistance.Guided by the theory of yang deficiency causing diabetes,this paper reviewed the relevant domestic literature issued in recent years,sorted out western medical pathogenesis and treatment for insulin resistance in T2DM,TCM theory of yang deficiency causing diabetes and its clinical application,and the clinical efficacy of TCM for the treatment of insulin resistance,and then explored the applicability of theory of yang deficiency causing diabetes for TCM treatment of insulin resistance in T2DM.It is concluded that TCM treatment for insulin resistance in T2DM based on the theory of yang deficiency causing diabetes has significant efficacy and advantages,for it realizes the integration of advantages of TCM and western medicine and achieves the synergistic actions through keeping the scientific nature and standardization of western medicine and by maintaining the advantages of holism and individualization of TCM treatment.TCM treatment for insulin resistance is effective on improving insulin signal transduction,insulin secretion function and other related metabolic abnormalities indicators through multiple pathways and targets,thus to improve the health status of the body.TCM treatment for insulin resistance exerts good safety and tolerance,and can reduce the incidence of adverse reactions caused by western medicine.However,the research on TCM treatment for insulin resistance still has the insufficiencies such as low quality of clinical trials,unclear therapeutic mechanism,and lack of innovation and pioneering.Further relevant research needs to be carried out in-depth,so as to provide a scientific basis for TCM to play a greater role in preventing and treating metabolic diseases.

This study aims to investigate the medication rules of patented traditional Chinese medi-cine(TCM)compound formulas and molecular mechanisms of core drugs for treating sepsis using data mining and network pharmacology approaches.In the present study,we first searched the PubMed database,Web of Science database,and the China National Knowledge Infrastructure(CNKI)since the establishment of the library to April 30,2024 for the relevant literature on the treatment of sepsis by traditional Chinese medicine.The prescriptions were then statistically ana-lyzed for drug frequency and association analysis to obtain the core drugs.Then we screened the ef-fective active ingredients of the core drugs by TCMSP and other database platforms,obtained sep-sis-related genes in GeneCards and other databases,and statistically intersected targets,and predic-ted the mechanism of action of the core TCMs by subjecting the intersected targets to PPI analy-sis,GO function and KEGG pathway enrichment analysis.Finally,the relationship between key tar-gets and herbal components was examined in reverse by molecular docking method.The results showed that 64 compound formulas were obtained,with a total of 150 Chinese medicines,which were mostly sweet in taste,cold in nature,and belonged to the spleen,stomach and intestinal me-ridians.According to the association rules,the core drugs were identified as"mirabilite-peach ker-nel-rheum officinale".There were 79 intersecting targets between the core drugs and sepsis,with core targets such as IL-1β,EGFR and SRC.MAPK,TNF,IL-17 and other signaling pathways are involved to mediate inflammatory responses,apoptosis and other biological processes to exert ther-apeutic effects on sepsis.The molecular docking results indicated that the docking activity of the key targets with the main components of the drug,and sennoside E_qt has the lowest binding ener-gy and the best docking activity with SRC.In conclusion,this study showed that the prescription of Chinese medicine for sepsis is mostly based on tonifying the spleen and clearing heat.The mecha-nism of action of the core drug"mirabilite-peach kernel-rheum officinale"in the treatment of sep-sis is multilevel and multifaceted,which provides a certain theoretical basis for the treatment of sepsis by traditional Chinese medicine.

Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.

Objective To prepare Zishen pills as gel plaster according to the prescription,and investigate its transdermal absorption characteristics in vitro.Methods Based on preliminary experiments,the matrix prescription of the gel plaster was optimized by single-factor tests and the Box-Behnken design.Evaluation indicators included initial viscosity,viscosity retention and sensory scores.The modified Franz diffusion cell was used to investigate the effect of penetration enhancers on the transdermal characteristics of gel plaster in vitro,with the permeability of neomangiferin,phellodendrine hydrochloride,mangiferin and berberine hydrochloride as evaluation indicators.Results The prescription dosage of the preferred matrix for the Zishen gel plaster was sodium polyacrylate NP700 2.55 g,glycerin 11.04 g,polyvinylpyrrolidone K90 1.13 g,tartaric acid 0.1 g,glycyrrhizin 0.1 g,kaolin 0.3 g,and distilled water 15 g.Among different types and concentrations of permeation enhancers,5%aminoketone showed the best permeation performance.The permeation rates for neomangiferin,phellodendrine hydrochloride,mangiferin,and berberine hydrochloride were 1.5338,1.7809,2.3247 and 20.0899 μg·(cm2)-1·h-1,and the penetration rates were 2.4319,1.9408,1.9604 and 1.4701,respectively.The percutaneous absorption curve of the drug conformed to the zero-order kinetic equation.Conclusion The preparation process of the obtained gel plaste is stable and feasible,with good adhesive properties,sustained drug release,and favorable in vitro percutaneous permeability,indicating potential clinical application value.

Cardiopulmonary exercise testing(CPET)refers to a method of measuring various indicators of the human body under gradually increasing exercise loads to objectively evaluate cardiopulmonary reserve function and exercise endurance.Currently,CPET detection systems primarily measure subjects'ECG,respiratory flow,oxygen(O2),and carbon dioxide(CO2)parameters.This paper introduces a non-invasive multi-parameter exercise cardiopulmonary function evaluation system that incorporates impedance cardiography monitoring.The system integrates impedance cardiography monitoring with conventional CPET detection parameters and detects changes in the hemodynamic parameters of the body during exercise,aiding in the evaluation of exercise capacity.Additionally,the system features a portable design with Wi-Fi wireless transmission,which enhances its applicability.

OBJECTIVE To investigate the inhibitory effects of Ginkgo biloba extract （GBE） on renal inflammation in diabetic nephropathy （DN） model mice， and its potential mechanism. METHODS KK/Ay mice were fed with high fat and high sugar to induce DN model. They were divided into model group， positive control group [metformin 200 mg/（kg·d）]， GBE low-dose and high-dose groups [100， 200 mg/（kg·d）]， with 6 mice in each group. Six C57BL/6J mice were fed with a regular diet as the control group. Administration groups were given relevant liquid intragastrically， control group and model group were given constant volume of normal saline intragastrically， once a day， for 8 consecutive weeks. The body weight， fasting blood glucose， 24-hour food intake， 24-hour urine output， monocyte chemoattractant protein-1 （MCP-1）， interleukin-12 （IL-12）， IL-10， advanced glycation end products （AGEs）， blood urea nitrogen （BUN） and serum creatinine （Scr） of mice were measured， and the ratio of bilateral kidneys to body weight was also calculated. The pathological injury and fibrotic changes of the renal cortex were observed， and the expressions of macrophage polarization marker proteins [type M1： inducible nitric oxide synthase （iNOS）； type M2： arginase-1 （Arg-1）] and AGEs-the receptor of advanced glycation end products （RAGE）/Ras homolog gene pharm_chenjing@163.com family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） signaling pathway-related proteins were determined in renal cortex. RESULTS Compared with the model group， the symptoms such as renal cortical hyperplasia， vacuoles， infiltration of inflammatory cells， and renal cortical fibrosis had been improved in GBE low-dose and high-dose groups； body weight， serum level of IL-10， the expression of Arg-1 in the renal cortex were significantly higher than model group （P＜ 0.01）； fasting blood glucose， 24-hour food intake， 24-hour urine output， serum levels of MCP-1， IL-12， BUN， Scr and AGEs， the ratio of bilateral kidneys to body weight， renal injury score， the proportion of renal interstitial fibrosis， the protein expressions of iNOS， RAGE， RhoA and ROCK1 （except for GBE low-dose group） in renal cortex were significantly lower than model group （P＜0.01）. CONCLUSIONS GBE could improve kidney damage and alleviate inflammatory response in DN model mice， the mechanism of which may be related to inhibiting the AGEs-RAGE/RhoA/ROCK signaling pathway and regulating macrophage polarization.

Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1 250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAXGv).The videos were divided into development set(245 A4C,155 PLAX,225 PSAXGV),semi-automated training set(98 A4C,62 PLAX,90 PSAXGV)and test set(147 A4C,93 PLAX,135 PSAXGV)at the ratio of 5:2:3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33％,97.26％,97.26％and 97.26％to 99.73％,99.65％,99.77％and 99.71％,respectively,while the overall accuracy for assessing A4C,PLAX and PSAXGV TTE as standard views in test set improved from 89.12％,83.87％and 90.37％to 93.20％,90.32％and 93.33％,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.