Objective:This study aims to explore the prevalence of hepatitis E virus (HEV) infection in patients and the screening value of serological indicators for HEV infection patients.Methods:Retrospective analysis was conducted on 97 440 cases of anti-HEV IgM and IgG simultaneously tested in two Beijing hospitals from January 1, 2018 to August 31, 2023. Among them, there were 61 005 males and 36 435 females, with an average age of 51.65±13.05 years old. According to the positivity of anti HEV specific antibodies, they were divided into anti-HEV IgM positive group (3 588 cases), anti-HEV IgG positive group (18 083 cases), and anti-HEV antibody negative group (78 892 cases). Results of HEV RNA, liver function, AFP, PIVKA-Ⅱ and PT were collected, and their basic clinical information were recorded. The prevalence of HEV infection in patients, as well as the relationship between the positivity of anti-HEV specific antibodies and the patient′s age group, HEV RNA, and clinical characteristics were analyzed.Results:Among 97 440 patients who tested anti-HEV IgM and IgG simultaneously, the positivity rate of anti-HEV IgM was 3.68% (3 588/97 440), and was 18.56% for anti-HEV IgG (18 083/97 440). The overall positivity rates of anti-HEV IgM in two Beijing hospitals from 2018 to 2023 were 2.51%, 2.53%, 3.02%, 4.59%, 5.72%, and 4.26% ( χ2=1 401.73, P<0.001), while the positivity rates of anti-HEV IgG were 12.56%, 12.32%, 12.85%, 22.65%, 27.42%, and 26.66% ( χ2=1 058.29, P<0.001). These rates showed a gradual increase until 2023 when a decline was observed. The positivity rates of anti-HEV IgM (2.28%, 3.60%, 4.47%) ( χ2=89.62, P<0.001) and IgG (4.71%, 17.86%, 25.94%) ( χ2=2 017.32, P<0.001) increased with age in patients who aged 1-30, >30-60, and over 60 years old. The age and ALB values of patients in the anti-HEV IgM positive group were lower than the IgG-positive group, while the proportion of males, TBIL, ALT, AFP and PT values were higher than the IgG-positive group, and the differences were statistically significance ( P<0.05). Furthermore, patients in both the anti-HEV IgM and IgG positive groups had higher age, male proportion, TBIL, ALT, AFP, PIVKA-Ⅱ, and PT values than the anti-HEV negative group. Additionally, both groups had lower ALB values than the anti-HEV negative group, all of which were statistically significant ( P<0.05). 2 162 HEV infected patients were grouped based on HEV RNA positivity. The proportion of anti-HEV IgM single positive, IgG single positive, IgM+IgG double positive, and antibody negative patients in the HEV RNA positive group were 5.42% (18/332), 3.62% (12/332), 90.36% (300/332), and 0.60% (2/332), respectively. Among them, the proportion of anti-HEV IgM+IgG double positive patients in the HEV RNA positive group was higher than that in the HEV RNA negative group ( χ2=302.87, P<0.001), while the proportion of anti-HEV IgG single positive ( χ2=174.36, P<0.001) and anti-HEV antibody negative patients ( χ2=59.28, P<0.001) were lower than that in the HEV RNA negative group, both of which were statistically significant ( P<0.001). In addition, the positive rates of HEV RNA in anti-HEV IgM positive, IgG positive, and antibody negative patients were 29.23% (318/1 088), 17.59% (312/1 774), and 0.65% (2/306), respectively. Conclusion:The HEV infection rate among patients declined in 2023. HEV infection is age-related, with older individuals being more susceptible. Abnormal liver function and jaundice were commonly observed during HEV infection. It is crucial to note that the absence of anti-HEV specific antibodies cannot rule out HEV infection; therefore, additional testing for HEV RNA and/or HEV Ag is necessary for accurate diagnosis.

Objective:To explore the correlation between the methylation of sclerostin (SOST) promoter and glucocorticoid-induced osteoporosis (GIOP) in children.Methods:Children with GIOP ( n=66) were selected as the experimental group. At the same time, children treated with glucocorticoid whose bone mass were selected as the control group ( n=72). The general clinical information of all children was compared, and the data collected by CT were detected by lumbar QCT, and the levels of bone metabolism related indexes were detected by biochemical analyzer. The mRNA expression of SOST was detected by fluorescence quantitative PCR, and the protein content of SOST was detected by enzyme-linked Immunosorbent Assay (ELISA). Methylation status of SOST gene promoter was detected by methylation-specific PCR (MSP), and the risk factors affecting GIOP were compared and analyzed, and the diagnostic and therapeutic value of each index for children with GIOP was evaluated. Results:Compared with the control group, the duration of hormone application and the current dose of hormone in the experimental group were higher, and the expression levels of bone metabolism indexes β-collagen carboxy terminal peptide ( β-CTX) ( t=9.87, P<0.01), typeⅠprocollagenamino-terminal peptide (P1NP) ( t=16.09, P<0.001), osteopontin (OPN) ( t=21.32, P<0.001) and N-MID ( t=15.21, P<0.01) were significantly increased, with statistical significance. However, in terms of bone mineral density, the related level of children in the experimental group was low ( t=22.49, P<0.001), and the expression of SOST mRNA ( t=9.48, P<0.01) and protein content ( t=7.70, P<0.01) was significantly decreased, and the children in the experimental group showed methylation status of SOST. Pearson analysis showed that the level of serum SOST protein in the experimental group was negatively correlated with the levels of β-CTX ( r=-0.16, P=0.012), P1NP ( r=-0.35, P=0.021), OPN ( r=-0.25, P=0.043) and N-MID ( r=-0.09, P=0.036). At the same time, the Logistic regression analysis showed that the high expression of P1NP ( SE=0.35, P<0.001), OPN (S E=0.37, P<0.001) and SOST ( SE=0.33, P<0.001) were risk factors for glucocorticoid-induced osteoporosis in children. The receiver operating characteristic (ROC) curve showed that the area under the curve of SOST was 0.874 (95% CI: 0.824-0.934), with higher sensitivity and specificity. Conclusions:There is a correlation between the methylation of SOST promoter and the GIOP of children. Besides, SOST can be used as a potential diagnostic index of GIOP with high value among many factors affecting children’s GIOP. In this case, the medical industry needs to further strengthen the prevention and treatment of children’s GIOP.

Objective To screen ischemia and hypoxiarelated genes(IAHRGs)after spinal cord injury(SCI)and analyze their immune infiltration patterns by bioinformatics methods.Methods The expression profiles of SCI-related GSE5296,GSE47681 and GSE217797 were downloaded from the Gene Expression Omnibus(GEO)database,where GSE5296,GSE47681 samples were used as the test set and GSE217797 samples as the validation set,and the differentially expressed genes(DEGs)between SCI and healthy samples were obtained.IAHRGs were screened in GeneCards and MSigDB databases.The intersection of DEGs and IAHRGs yielded ischemic and hypoxia related differentially expressed genes(IAHRDEGs).Based on the IAHRDEGs,the key genes were jointly screened by LASSO model and SVM analysis.The key genes were subjected to logistic regression analysis and a diagnostic model was constructed.The diagnostic ability of the diagnostic model was analyzed by Nomogram and the column line graph of Logistic predictive values was plotted.The diagnostic value of the diagnostic model and key genes for SCI was evaluated using the receiver operating characteristics(ROC).Immune cell infiltration patterns of the disease were analyzed using the CIBERSORT tool.Results A total of 388 IAHRGs were screened,313 differentially expressed genes were detected between SCI and healthy samples,among which 312 were up-regulated and 1 was down-regulated.A sum of 27 up-regulated IAHRDEGs genes were obtained.Five key genes related to ischemia and hypoxia after SCI(Abca1,Caspl,Lpl,Procr,Tnfrsf1a)were screened by LASSO model and SVM analysis based on IAHRDEGs.Nomogram analysis confirms the effect of logistics diagnosis model.ROC curve analysis showed that Casp1,Lpl and Tnfrsf1a had higher diagnostic efficacy(AUC＞0.9),followed by Abca1 and Procr(AUC:0.7～0.9),and the logistics linear predictors had the best diagnostic effect(AUC=0.964).CIBERSORT analysis showed that five key genes were associated with the infiltration of eight types of immune cells(neutrophil cells,B cells naive,plasma cells,M0 macrophage,T cells CD4 naive,T cells CD4 follicular,Th17 cells,and NK resting).Conclusion The five key genes of Abcal,Caspl,Lpl,Procr,and Tnfrsfla,may be closely related to ischemic-hypoxic pathogenesis after SCI,and can be used as candidate molecular markers for the diagnosis and treatment after SCI.

Artificial neural network(ANN)is a simulation of a biological neural network.It is an adaptive,non-linear,dynamic network system formed by interconnections.The advantages of ANN include easy optimization,simple modeling,and ac-curate results.This review examines the application of ANN in therapeutic drug monitoring for immunosuppressants,antibacteri-als,and anti-epileptic drugs.It discusses the advantages and disadvantages of the current ANN models and highlights future de-velopment directions.The aim is to provide valuable reference information for future researchers.The use of ANN for therapeutic drug monitoring shows great potential and holds promise as an effective method of personalizing patient medication.

Objective:To explore the optimal blood glucose-lowering strategies for patients with diabetic ketoacidosis (DKA) to enhance personalized treatment effects using machine learning techniques based on the United States Critical Care Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ).Methods:Utilizing the MIMIC-Ⅳ database, the case data of 2 096 patients with DKA admitted to the intensive care unit (ICU) at Beth Israel Deaconess Medical Center from 2008 to 2019 were analyzed. Machine learning models were developed, and receiver operator characteristic curve (ROC curve) and precision-recall curve (PR curve) were plotted to evaluate the model's effectiveness in predicting four common adverse outcomes: hypoglycemia, hypokalemia, reductions in Glasgow coma scale (GCS), and extended hospital stays. The risk of adverse outcomes was analyzed in relation to the rate of blood glucose decrease. Univariate and multivariate Logistic regression analyses were conducted to examine the relationship between relevant factors and the risk of hypokalemia. Personalized risk interpretation methods and predictive technologies were applied to individualize the analysis of optimal glucose control ranges for patients.Results:The machine learning models demonstrated excellent performance in predicting adverse outcomes in patients with DKA, with areas under the ROC curve (AUROC) and 95% confidence interval (95% CI) for predicting hypoglycemia, hypokalemia, GCS score reduction, and extended hospital stays being 0.826 (0.803-0.849), 0.850 (0.828-0.870), 0.925 (0.903-0.946), and 0.901 (0.883-0.920), respectively. Analysis of the relationship between the rate of blood glucose reduction and the risk of four adverse outcomes showed that a maximum glucose reduction rate > 6.26 mmol·L -1·h -1 significantly increased the risk of hypoglycemia ( P < 0.001); a rate > 2.72 mmol·L -1·h -1 significantly elevated the risk of hypokalemia ( P < 0.001); a rate > 5.53 mmol·L -1·h -1 significantly reduced the risk of GCS score reduction ( P < 0.001); and a rate > 8.03 mmol·L -1·h -1 significantly shortened the length of hospital stay ( P < 0.001). Multivariate Logistic regression analysis indicated significant correlations between maximum bicarbonate levels, blood urea nitrogen levels, and total insulin doses with the risk of hypokalemia (all P < 0.01). In terms of establishing personalized optimal treatment thresholds, assuming optimal glucose reduction thresholds for hypoglycemia, hypokalemia, GCS score reduction, and extended hospital stay were x1, x2, x3, x4, respectively, the recommended glucose reduction rates to minimize the risks of hypokalemia and hypoglycemia should be ≤min{ x1, x2}, while those to reduce GCS score decline and extended hospital stay should be ≥ max{ x3, x4}. When these ranges overlap, i.e., max{ x3, x4} ≤ min{ x1, x2}, this interval was the recommended optimal glucose reduction range. If there was no overlap between these ranges, i.e., max{ x3, x4} > min{ x1, x2}, the treatment strategy should be dynamically adjusted considering individual differences in the risk of various adverse outcomes. Conclusion:The machine learning models shows good performance in predicting adverse outcomes in patients with DKA, assisting in personalized blood glucose management and holding important clinical application prospects.

Objective:To investigate clinical features and current treatment status of patients with physical urticaria (PU) in China.Methods:A questionnaire survey was carried out in patients diagnosed with PU at the first visit at the Department of Dermatology of 12 tertiary hospitals in China from January to December 2019. Physicians filled out the survey questionnaires, which included demographic characteristics, pruritus intensity, the number of wheals, concomitant symptoms (such as pain in skin rashes, arthralgia, and fever), subtypes of PU, treatment regimens, etc. Differences between groups were analyzed using one-way analysis of variance, Kruskal-Wallis test or chi-square test.Results:Overall, 612 PU outpatients were enrolled, including 268 males and 344 females; they were aged 37.4 ± 16.4 years, their age at the onset was 35.1 ± 16.4 years, and the disease duration ( M [ Q1, Q3]) was 0.50 (0.25, 2.00) years. Of these patients, 500 were diagnosed with symptomatic dermographism (SD), 54 with heat contact urticaria (HCU), 43 with cold contact urticaria (CCU), and 15 with delayed pressure urticaria (DPU). There were no significant differences in the gender distribution, age, age at onset, or disease duration among the 4 subtypes of PU patients (all P > 0.05), but the proportions of patients with arthralgia, with eczema/dermatitis, and with elevated total serum IgE levels significantly differed among the 4 subtypes (all P < 0.05). Concretely, the proportion of patients with arthralgia was significantly higher in the DPU group (4/15, 26.7%) than in the SD group (64/500, 12.8%), HCU group (1/54, 1.9%), and CCU group (5/43, 11.6%) (all P < 0.05) ; the proportion of patients with eczema/dermatitis was significantly lower in the HCU group (2/54, 3.7%) than in the SD group (96/500, 19.2%), CCU group (7/43, 16.3%), and DPU group (3/15, 20.0%) (all P < 0.05) ; the proportion of patients with elevated total serum IgE levels was significantly higher in the SD group (185/500, 37.0%) than in the HCU group (9/54, 16.7%), CCU group (11/43, 25.6%), and DPU group (4/15, 26.7%) (all P < 0.05). Among the PU patients, 307 (50.3%) chose dietary avoidance, and only 95 (15.5%) considered that the dietary avoidance was effective for the treatment of PU. At the initial visit, a single second-generation H1 antihistamine (sgAH) was prescribed in 271 cases (44.3%), two or more sgAHs in combination were prescribed in 258 cases (42.2%), and sgAHs were administered at double doses in 17 cases (2.7%) . Conclusion:The PU patients were predominantly young and middle-aged adults, and PU frequently occurred in females; the clinical characteristics varied among the subtypes of PU.

Purpose: PIK3CA and TP53 are the most prevalently mutated genes in breast cancer (BC).Previous studies have indicated an association between concomitant PIK3CA/TP53 mutations and shorter disease-free survival. As its clinical utility remains largely unknown, we aimed to analyze the prognostic and predictive roles of this co-mutation. Methods: We retrospectively analyzed patients who were diagnosed with BC at Guangdong Provincial People’s Hospital (GDPH) who underwent next-generation sequencing. The correlation of concomitant PIK3CA/TP53 mutations with clinicopathological and mutational characteristics, and neoadjuvant systemic therapy (NST) responses was analyzed. The Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset was used to verify associations between concurrent mutations and survival outcomes. Results: In the GDPH cohort, concomitant PIK3CA/TP53 mutations were associated with more aggressive phenotypes, including human epidermal growth factor receptor 2 positive status, hormone receptor negative status, high Ki-67 expression, high histological grade, advanced TNM stage, and additional genetic alterations. Co-mutations also portended a worse response to NST, especially taxane-containing regimens, when compared with the TP53 mutant alone (odds ratio, 3.767; 95% confidence interval, 1.205–13.087; p = 0.028). A significant association was observed between concomitant PIK3CA/TP53 mutations and poor survival outcomes in the METABRIC cohort. Conclusion Concomitant PIK3CA/TP53 mutations not only suggested unfavorable features and poor prognosis in BC but also conferred less benefit to NST than TP53 mutations alone.

ObjectiveTo explore the effect and underlying mechanism of alcohol extract of Phyllanthi Fructus on silicosis mice induced by silicon dioxide （SiO₂）. MethodThirty-six male Kunming mice of SPF grade were randomly divided into a blank group，a model group，high-， medium， and low-dose Phyllanthi Fructus groups （800， 400， 200 mg·kg^-1），and a tetrandrine group （0.039 mg·kg^-1），with six mice in each group. The silicosis model was induced by static SiO₂ exposure in mice except for those in the blank group. After 28 days of administration by gavage，the lung tissues were collected and the organ coefficient was calculated. Hematoxylin-eosin（HE）staining and Masson staining were used to detect the morphology of lung tissues. The content of hydroxyproline （HYP），superoxide dismutase （SOD），malondialdehyde （MDA）， and catalase （CAT） in serum was detected by enzyme-linked immunosorbent assay （ELISA）. Western blot and Real-time polymerase chain reaction（Real-time PCR） were used to detect the protein and mRNA expression of nuclear factor E₂-related factor 2 （Nrf2），heme oxygenase-1 （HO-1），NAD（P）H：quinone oxidoreductase 1 （NQO1），and Kelch-like ECH-associated protein 1 （Keap1）， respectively. ResultCompared with the blank group，the model group showed seriously damaged morphological structure of lung tissues with inflammatory cell infiltration and fibrous tissue proliferation， reduced serum content of SOD and CAT（P<0.01），increased content of HYP and MDA（P<0.01）， down-regulated protein and mRNA expression of Nrf2，HO-1， and NQO1（P<0.01），and up-regulated protein and mRNA expression of Keap1 （P<0.05，P<0.01）. Compared with the model group，the high- and medium-dose Phyllanthi Fructus groups showed significantly restored morphological structure of lung tissues with reduced collagen deposition， increased serum content of SOD and CAT（P<0.05，P<0.01），decreased content of HYP and MDA（P<0.01）， up-regulated protein and mRNA expression of Nrf2，HO-1， and NQO1 （P<0.05，P<0.01），and down-regulated protein and mRNA expression of Keap1（P<0.05，P<0.01）. ConclusionThe alcohol extract of Phyllanthi Fructus can inhibit pulmonary fibrosis in silicosis mice，and the underlying mechanism may be related to the regulation of the Nrf2/antioxidant response element （ARE） signaling pathway.

ObjectiveTo investigate the effect and mechanism of Dahuang Zhechongwan （DHZCW） on adenine-induced renal fibrosis in rats from the perspective of intestinal flora. MethodThirty-six SD rats were randomly divided into a blank group， a model group， and high-， medium- and low-dose DHZCW groups （0.168， 0.084， 0.042 g·kg^-1）， and a pirfenidone group （200 mg·kg^-1）， with 6 rats in each group. Except for those in the blank group， rats in other groups were treated with adenine suspension （250 mg·kg^-1） by gavage for 28 days for renal fibrosis model induction. Subsequently， they received drug intervention for 4 weeks. Urine samples were collected from rats in metabolic cages， and renal function indicators including blood urea nitrogen （BUN）， urea， creatinine （Crea）， cystatin C （Cys C）， and 24-hour urine protein （24 h TP） were measured. Kidney samples were collected and subjected to hematoxylin-eosin （HE） staining and Masson's trichrome staining to observe the pathological changes in rat renal tissues. Western blot was used to detect the expression levels of key effector proteins α-smooth muscle actin （α-SMA）， type Ⅰ collagen （ColⅠ）， and type Ⅲ collagen （ColⅢ） in the kidneys. High-throughput sequencing of 16S rDNA was used to analyze the species diversity of rat intestinal flora. ResultCompared with the blank group， the model group showed increased BUN， urea， Crea， Cys C， and 24 h TP levels （P<0.01）. Compared with the model group， the high-， medium-， and low-dose DHZCW groups， as well as the pirfenidone group， showed significant reductions in BUN， urea， Crea， Cys C， and 24 h TP levels （P<0.01）， indicating that DHZCW intervention significantly improved renal function. In the model group， renal tissues exhibited significant fibrotic changes， and the protein levels of α-SMA， ColⅠ， and ColⅢ were significantly increased （P<0.01） compared to those in the blank group. Compared with the model group， the high-dose DHZCW group and the pirfenidone group had relatively normal tissue structure， with no significant pathological damage observed. However， fibrotic changes were observed in the medium- and low-dose DHZCW groups， with the changes being more significant in the low-dose group. The protein levels of α-SMA， ColⅠ， and ColⅢ were significantly decreased in the high-， medium-， and low-dose DHZCW groups， as well as the pirfenidone group （P<0.01）， indicating that DHZCW effectively reduced abnormal collagen deposition and inhibited renal fibrosis. From the perspective of intestinal flora， at the phylum level， compared with the blank group， the model group showed a significant increase in the abundance of Firmicutes and a decrease in Bacteroidetes， leading to a significant imbalance in their ratio. At the family level， the model group decreased the abundance of Lachnospiraceae， Prevotellaceae， and Bacteroidota_unclassified， and increased the abundance of Ruminococcaceae， Lactobacillaceae， and Oscillospiraceae. At the genus level， the model group showed significantly reduced abundance of Firmicutes_unclassified， Bacteroidota_unclassified， and Prevotellaceae_UCG-001， etc.， and increased abundance of UCG-005， Clostridia_UCG-014_unclassified， etc. Compared with the model group， DHZCW effectively reduced the abundance of potential pathogenic bacteria and increased the abundance of beneficial bacteria， regulating the intestinal flora. ConclusionDHZCW can effectively improve renal function and inhibit renal fibrosis， and its mechanism of action may be related to the regulation of intestinal flora.

Objective:To investigate the predictive value of enhanced CT-based radiomics for brain metastasis (BM) and selective use of prophylactic cranial irradiation (PCI) in limited-stage small cell lung cancer (LS-SCLC).Methods:Clinical data of 97 patients diagnosed with LS-SCLC confirmed by pathological and imaging examination in Shanxi Provincial Cancer Hospital from January 2012 to December 2018 were retrospectively analyzed. The least absolute shrinkage and selection operator (LASSO) Cox and Spearman correlation tests were used to select the radiomics features significantly associated with the incidence of BM and calculate the radiomics score. The calibration curve, the area under the receiver operating characteristic (ROC) curve (AUC), 5-fold cross-validation, decision curve analysis (DCA), and integrated Brier score (IBS) were employed to evaluate the predictive power and clinical benefits of the radiomics score. Kaplan-Meier method and log-rank test were adopted to draw survival curves and assess differences between two groups.Results:A total of 1272 radiomics features were extracted from enhanced CT. After the LASSO Cox regression and Spearman correlation tests, 8 radiomics features associated with the incidence of BM were used to calculate the radiomics score. The AUCs of radiomics scores to predict 1-year and 2-year BM were 0.845 (95% CI=0.746-0.943) and 0.878 (95% CI=0.774-0.983), respectively. The 5-fold cross validation, calibration curve, DCA and IBS also demonstrated that the radiomics model yielded good predictive performance and net clinical benefit. Patients were divided into the high-risk and low-risk cohorts based on the radiomics score. For patients at high risk, the 1-year and 2-year cumulative incidence rates of BM were 0% and 18.2% in the PCI group, and 61.8% and 75.4% in the non-PCI group, respectively ( P<0.001). In the PCI group, the 1-year and 2-year overall survival rates were 92.9% and 78.6%, and 85.3% and 36.8% in the non-PCI group, respectively ( P=0.023). For patients at low risk, the 1-year and 2-year cumulative incidence rates of BM were 0% and 0% in the PCI group, and 10.0% and 20.2% in the non-PCI group, respectively ( P=0.062). In the PCI group, the 1-year and 2-year overall survival rates were 100% and 77.0%, and 96.7% and 79.3% in the non-PCI group, respectively ( P=0.670). Conclusion:The radiomics model based on enhanced CT images yields excellent performance for predicting BM and individualized PCI.