ObjectiveTo investigate the epigenetic mechanism of Diwu Yanggan Capsule in improving liver regeneration microenvironment in a rat model of liver cancer by regulating DNA methylation， and to provide a basis for scientific clinical medication. MethodsA total of 48 specific pathogen-free Sprague-Dawley rats were divided into normal group， model group， and Diwu Yanggan Capsule group using a random number table， with 16 rats in each group. The Solt-Farber two-step method was used to establish a rat model of liver cancer. The rats in the Diwu Yanggan Capsule group were given Diwu Yanggan Capsule at a dose of 750 mg/kg/d by gavage， and those in the normal group and the model group were given an equal volume of normal saline by gavage. Liver tissue samples were collected from each group of rats after 16 weeks of continuous intervention； DNA methylation chips were used to analyze the change in DNA methylation in liver tissue， and gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were used for data analysis. In addition， the MeDIP-PCR technique was used to detect the changes in candidate differentially methylated genes such as YWHAB， ADCK2， ERLIN2， SEMA3B， and TPH2 in the liver tissue of rats， and Western blot and RT-qPCR were used to verify the expression of key methylated genes. The independent-samples t test was used for comparison of continuous data between two groups， and a one-way analysis of variance was used for comparison between multiple groups， while the least significant difference t-test was used for further comparison between two groups. ResultsThe DNA methylation chip analysis showed that compared with the normal group， the model group had significant methylation changes in the promoter region of 2 422 genes in liver tissue of rats. The GO functional enrichment analysis and the KEGG pathway enrichment analysis showed that these differentially methylated genes were significantly enriched in metabolic pathways such as steroid hormone biosynthesis and drug metabolism-cytochrome P450. Compared with the model group， the Diwu Yanggan Capsule group had significant reversal of promoter methylation in 1 650 genes， and the KEGG enrichment analysis showed that these genes were mainly involved in the pathways closely associated with cell proliferation， apoptosis， and microenvironment regulation， such as the calcium ion signaling pathway， the cAMP signaling pathway， and the extracellular factor signaling pathway. Compared with the model group， the Diwu Yanggan Capsule group had a significant increase in the promoter methylation level of the ADCK2 gene （P<0.05） and significant reductions in the promoter methylation levels of the ERLIN2 and TPH2 genes （all P<0.05）. Compared with the model group， the Diwu Yanggan Capsule group had significant reductions in the mRNA expression levels and the protein expression levels of the ADCK2 （all P<0.05）. ConclusionAbnormal DNA methylation in liver tissue participates in the development and progression of liver cancer. The effect of Diwu Yanggan Capsule on DNA methylation level is an important epigenetic mechanism for its effect in the prevention and treatment of liver cancer.

Objective:To explore the composition of gut microbiome, the characteristics of virulence factor genes and their relationship with liver metabolic inflammation in overweight or obese children.Methods:A case-control design was conducted. From the children who visited the West China Second University Hospital of Sichuan University for medical or physical examinations between August 2021 and April 2022, a total of 23 obese children (obesity group), 8 overweight children (overweight group), and 22 healthy children (control group) were recruited. The body mass index of children was calculated after anthropometric measurements; metabolic inflammation indexes such as the levels of fasting blood glucose and hepatic function and renal function etc. were detected. The composition and abundance of gut microbiota in the feces of the children were detected by metagenomic sequencing technology and the Shannon index and Simpson index were calculated to assess the α diversity of virulence factor genes. The Wilcoxon rank-sum test was used for pairwise comparison between groups. The Spearman′s rank correlation test was used for correlation analysis, and the Benjamini-Hochberg method was used to correct the P-value of multiple tests. Results:The obese group included 23 children aged 8.5 (6.3, 11.8) years, of whom 9 (39%) were male. The overweight group consisted of 8 children aged 9.2 (5.5, 12.3) years, of whom 4 were male. The control group comprised 22 children aged 5.3 (5.1, 5.4) years, of whom 10 (45%) were male. The obese group exhibited higher levels of alanine aminotransferase (ALT), gamma-glutamyl transferase (γ-GT), globulin, and uric acid compared to those of the control group (all P<0.05), with ALT also higher than that of the overweight group ( P<0.05). The levels of fasting blood glucose, γ-GT, globulin, and uric acid in the overweight group were all higher than those in the control group (all P<0.05). The abundance of Coprococcus A (0.76 (0.00, 3.11) vs. 0.00 (0.00, 0.00), false discovery rate ( FDR)<0.05) and Parasutterella (0.89 (0.08, 1.79) vs. 0.00 (0.00, 0.08), FDR<0.05) in the gut of children in the obese group were both higher than those of the control group. The number of virulence factor genes in the obese group was higher than those of the control group (941 (886, 977) vs. 890 (807, 920), P<0.05). The Simpson index and Shannon index of gut microbial virulence factor genes in the obese group were both higher than those of the control group (0.993 (0.992, 0.993) vs. 0.991(0.990, 0.991), (5.50 (5.46, 5.56) vs. 5.37 (5.30, 5.43), both P<0.01). The abundance of gut microbiota virulence factors genes all showed positive correlations with fasting blood glucose, ALT, γ-GT, and uric acid levels in children (all r>0.3, all FDR<0.05). The abundance of 17 gut microbial virulence factor genes were all positively associated with γ-GT levels (all r>0.3, all FDR<0.05). The virulence factor genes (LpxH, LpxB, LpxK) of lipopolysaccharide were all positively correlated with plasma γ-GT and globulin levels (all r>0.3, all FDR<0.05). Conclusions:Overweight or obese children exhibited elevated liver metabolic-inflammatory markers compared to their normal-weight counterparts. Notably, obese children demonstrated gut microbiota dysbiosis accompanied by enrichment of virulence factor genes, which may promote liver metabolic inflammation through pathways such as lipopolysaccharide biosynthesis.

BACKGROUND:In recent years,numerous studies have shown that autophagy and mitophagy play an important role in the regulation of bone metabolism.Under non-physiological conditions,mitophagy breaks the balance of bone metabolism and triggers metabolism disorders,which affect osteoblasts,osteoclasts,osteocytes,chondrocytes,bone marrow mesenchymal stem cells,etc. OBJECTIVE:To summarize the mechanism of mitophagy in regulating bone metabolic diseases and its application in clinical treatment. METHODS:PubMed,Web of Science,CNKI,WanFang and VIP databases were searched by computer using the keywords of"mitophagy,bone metabolism,osteoblasts,osteoclasts,osteocytes,chondrocytes,bone marrow mesenchymal stem cells"in English and Chinese.The search time was from 2008 to 2023.According to the inclusion criteria,90 articles were finally included for review and analysis. RESULTS AND CONCLUSION:Mitophagy promotes the generation of osteoblasts through SIRT1,PINK1/Parkin,FOXO3 and PI3K signaling pathways,while inhibiting osteoclast function through PINK1/Parkin and SIRT1 signaling pathways.Mitophagy leads to bone loss by increasing calcium phosphate particles and tissue protein kinase K in bone tissue.Mitophagy improves the function of chondrocytes through PINK1/Parkin,PI3K/AKT/mTOR and AMPK signaling pathways.Modulation of mitophagy shows great potential in the treatment of bone diseases,but there are still some issues to be further explored,such as different stages of drug-activated mitophagy,and the regulatory mechanisms of different signaling pathways.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Objective:To gain insight into the multidimensional needs of adults with moderate-to-severe psoriasis at different stages of disease progression diagnostic and treatment dynamics based on patient journey maps, providing a basis for developing precise intervention strategies and optimizing care throughout the journey.Methods:From September to October 2024, 14 adult patients with moderate-to-severe psoriasis admitted to the Department of Dermatology of the First Hospital of Shanxi Medical University were selected by purposive sampling method for semi-structured interviews. Content analysis was used to analyze the data, drawing on theory of "timing it right" to depict a patient journey map that was reviewed and improved by the research team and patients.Results:Patient journey map was developed and condensed into four themes of experiences and challenges from pre-diagnosis to adaptation, complex emotional experiences, experiential pain points at each stage of the diagnosis and treatment, and opportunity points to improve the experience and quality of the diagnosis and treatment.Conclusions:At different stages of disease progression, the diagnosis and treatment needs of adults with moderate-to-severe psoriasis are characterized by dynamic evolution and multidimensional integration. The journey map can accurately identify patients' differentiated experiences and needs, and can provide a reference for healthcare professionals and policy makers to optimize patients' diagnostic and treatment experiences and focus on patients' health management.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Objective:To gain insight into the multidimensional needs of adults with moderate-to-severe psoriasis at different stages of disease progression diagnostic and treatment dynamics based on patient journey maps, providing a basis for developing precise intervention strategies and optimizing care throughout the journey.Methods:From September to October 2024, 14 adult patients with moderate-to-severe psoriasis admitted to the Department of Dermatology of the First Hospital of Shanxi Medical University were selected by purposive sampling method for semi-structured interviews. Content analysis was used to analyze the data, drawing on theory of "timing it right" to depict a patient journey map that was reviewed and improved by the research team and patients.Results:Patient journey map was developed and condensed into four themes of experiences and challenges from pre-diagnosis to adaptation, complex emotional experiences, experiential pain points at each stage of the diagnosis and treatment, and opportunity points to improve the experience and quality of the diagnosis and treatment.Conclusions:At different stages of disease progression, the diagnosis and treatment needs of adults with moderate-to-severe psoriasis are characterized by dynamic evolution and multidimensional integration. The journey map can accurately identify patients' differentiated experiences and needs, and can provide a reference for healthcare professionals and policy makers to optimize patients' diagnostic and treatment experiences and focus on patients' health management.

Objective:To explore the composition of gut microbiome, the characteristics of virulence factor genes and their relationship with liver metabolic inflammation in overweight or obese children.Methods:A case-control design was conducted. From the children who visited the West China Second University Hospital of Sichuan University for medical or physical examinations between August 2021 and April 2022, a total of 23 obese children (obesity group), 8 overweight children (overweight group), and 22 healthy children (control group) were recruited. The body mass index of children was calculated after anthropometric measurements; metabolic inflammation indexes such as the levels of fasting blood glucose and hepatic function and renal function etc. were detected. The composition and abundance of gut microbiota in the feces of the children were detected by metagenomic sequencing technology and the Shannon index and Simpson index were calculated to assess the α diversity of virulence factor genes. The Wilcoxon rank-sum test was used for pairwise comparison between groups. The Spearman′s rank correlation test was used for correlation analysis, and the Benjamini-Hochberg method was used to correct the P-value of multiple tests. Results:The obese group included 23 children aged 8.5 (6.3, 11.8) years, of whom 9 (39%) were male. The overweight group consisted of 8 children aged 9.2 (5.5, 12.3) years, of whom 4 were male. The control group comprised 22 children aged 5.3 (5.1, 5.4) years, of whom 10 (45%) were male. The obese group exhibited higher levels of alanine aminotransferase (ALT), gamma-glutamyl transferase (γ-GT), globulin, and uric acid compared to those of the control group (all P<0.05), with ALT also higher than that of the overweight group ( P<0.05). The levels of fasting blood glucose, γ-GT, globulin, and uric acid in the overweight group were all higher than those in the control group (all P<0.05). The abundance of Coprococcus A (0.76 (0.00, 3.11) vs. 0.00 (0.00, 0.00), false discovery rate ( FDR)<0.05) and Parasutterella (0.89 (0.08, 1.79) vs. 0.00 (0.00, 0.08), FDR<0.05) in the gut of children in the obese group were both higher than those of the control group. The number of virulence factor genes in the obese group was higher than those of the control group (941 (886, 977) vs. 890 (807, 920), P<0.05). The Simpson index and Shannon index of gut microbial virulence factor genes in the obese group were both higher than those of the control group (0.993 (0.992, 0.993) vs. 0.991(0.990, 0.991), (5.50 (5.46, 5.56) vs. 5.37 (5.30, 5.43), both P<0.01). The abundance of gut microbiota virulence factors genes all showed positive correlations with fasting blood glucose, ALT, γ-GT, and uric acid levels in children (all r>0.3, all FDR<0.05). The abundance of 17 gut microbial virulence factor genes were all positively associated with γ-GT levels (all r>0.3, all FDR<0.05). The virulence factor genes (LpxH, LpxB, LpxK) of lipopolysaccharide were all positively correlated with plasma γ-GT and globulin levels (all r>0.3, all FDR<0.05). Conclusions:Overweight or obese children exhibited elevated liver metabolic-inflammatory markers compared to their normal-weight counterparts. Notably, obese children demonstrated gut microbiota dysbiosis accompanied by enrichment of virulence factor genes, which may promote liver metabolic inflammation through pathways such as lipopolysaccharide biosynthesis.

Objective:To analyze the status of respiratory pathogen detection and the clinical features in children with Mycoplasma pneumoniae pneumonia (MPP). Methods:A prospective, multicenter study was conducted to collect clinical data, including medical history, laboratory examinations and multiplex PCR tests of children diagnosed with MPP from 4 hospitals in China between November 15 th and December 20 th, 2023. The multiplex PCR results and clinical characteristics of MPP children in different regions were analyzed. The children were divided into severe and mild groups according to the severity of the disease. Patients in the severe group were further divided into Mycoplasma pneumoniae (MP) alone and Multi-pathogen co-detection groups based on whether other pathogens were detected besides MP, to analyze the influence of respiratory pathogen co-detection rate on the severity of the disease. Mann-Whitney rank sum test and Chi-square test were used to compare data between independent groups. Results:A total of 298 children, 136 males and 162 females, were enrolled in this study, including 204 children in the severe group with an onset age of 7.0 (6.0, 8.0) years, and 94 children in the mild group with an onset age of 6.5 (4.0, 7.8) years. The level of C-reactive protein, D-dimer, lactic dehydrogenase (LDH) were significantly higher (10.0 (5.0, 18.0) vs. 5.0 (5.0, 7.5) mg/L, 0.6 (0.4, 1.1) vs. 0.5 (0.3, 0.6) mg/L, 337 (286, 431) vs. 314 (271, 393) U/L, Z=2.02, 2.50, 3.05, all P<0.05), and the length of hospitalization was significantly longer in the severe group compared with those in mild group (6.0 (6.0, 7.0) vs. 5.0 (4.0, 6.0) d, Z=4.37, P<0.05). The time from onset to admission in severe MPP children was significantly shorter than that in mild MPP children (6.0 (5.0, 9.5) vs. 9.0 (7.0, 13.0) d, Z=2.23, P=0.026). All patients completed the multiplex PCR test, with 142 cases (47.7%) MPP children detected with 21 pathogens including adenovirus 25 cases (8.4%), human coronavirus 23 cases (7.7%), rhinovirus 21 cases (7.0%), Streptococcus pneumoniae 21 cases (7.0%), influenza A virus 18 cases (6.0%). The pathogens with the highest detection rates in Tianjin, Shanghai, Wenzhou and Chengdu were Staphylococcus aureus at 10.7% (8/75), adenovirus at 13.0% (10/77), adenovirus at 15.3% (9/59), and both rhinovirus and Haemophilus influenzae at 11.5% (10/87) each. The multi-pathogen co-detection rate in severe MPP children was significantly higher than that in mild MPP group (52.9% (108/204) vs. 36.2% (34/94), χ2=10.62, P=0.005). Among severe MPP children, there are 89 cases in the multi-pathogen co-detection group and 73 cases in the simple MPP group. The levels of LDH, D-dimer and neutrophil counts in the multi-pathogen co-detection group were significantly higher than those in the simple MPP group (348 (284, 422) vs. 307 (270, 358) U/L, 0.8 (0.5, 1.5) vs. 0.6 (0.4, 1.0) mg/L, 4.99 (3.66, 6.89)×10 9vs. 4.06 (2.91, 5.65)×10 9/L, Z=5.17, 4.99, 6.11, all P<0.05). Conclusions:The co-detection rate of respiratory pathogens, LDH and D-dimer in children with severe MPP were higher than those with mild MPP. Among severe MPP children the stress response of children in co-detection group was more serious than that of children with simple MPP.