Objective:To explore the mechanisms of oxaliplatin resistance mediated by TET2 methylation in the treatment of acute lymphoblastic leukemia (ALL) using bioinformatics methods.Methods:The data on drug-resistant and sensitive cell lines related to oxaliplatin treatment for ALL were download using the Genomics of Drug Sensitivity in Cancer (GDSC) database (updated in December 2023); the drug-resistant cell lines were screened based on half maximal inhibitory concentration ( IC50) > 10 μmol/L, and the difference in IC50 between drug-resistant and sensitive cell lines were analyzed using Mann-Whitney U test. The cancer driver mutation genes in drug-resistant cell lines were retrieved using the Cancer Cell Line Encyclopedia (CCLE) database (updated in December 2023). Using the protein-protein interaction (PPI) network functional enrichment analysis (STRING) database (updated in June 2024), PPI network analysis was performed on cancer driver mutation genes with biological functions. A confidence threshold of ≥ 0.7 (high confidence) and an average network node degree above 4 (high average) were selected to screen for cancer driver mutation genes with significant biological functions. Using the microRNA Data Integration Portal (mirDIP) database (updated in June 2024), the coexpression data of microRNA (miRNA) and mutant target genes were queried, miRNA-target gene pairs were screened according to the highest score threshold of 1% miRNA and interaction score > 0.9, and the regulatory effect of miRNA on mutant genes was analyzed. DNA methylation data were download from the Methylation in Human Cancer (MethHC) database (updated in June 2024) and the methylSig R software package was used to analyze the differentially methylated regions (DMR) of DNA methylation between drug-resistant and sensitive cell lines; genes with P < 0.05 and absolute difference > 0.2 were selected, and they were divided into high methylation gene group and low methylation gene group. Spearman correlation analysis and Spearman rank test were performed for the degree of methylation and gene expression, and the key genes with P < 0.01 were screened to reveal the relationship between methylation degree and gene expression. Results:As a result of searching the GDSC database, there were a total of 9 drug-resistant cell lines and 17 sensitive cell lines related to oxaliplatin treatment for ALL; after Z-score normalization of IC50 data between drug-resistant and sensitive cell lines, the average rank of drug-resistant cell lines was 21, and the average rank of sensitive cell lines was 8.5, with a statistically significant difference ( Z = -4.08, P < 0.01). Eight cancer driver mutation genes with significant biological functions that lead to drug resistance of the cell lines were screened using the CCLE database and STRING database. According to the mirDIP database, there were a total of 12 pairs of miRNA-target gene pairs with miRNA-target gene interaction scores >0.9. miRNA had strong regulatory effects on the expressions of NRAS and MAP2K1 target genes. In the MethHC database, the β values (numerical value of increased methylation level) of DMR for genes such as TP53, RXRG and SGIP in drug-resistant cell lines were 0.151, 0.165 and 0.149, respectively, compared to those in sensitive cell lines, the differences were statistically significant (all P < 0.01). The degree of methylation of SGIP gene was negatively correlated with the relative expression level of SGIP mRNA ( r = -0.71, P < 0.01), and SGIP gene underwent high methylation at promoter site 143886940. The cg08321569 locus in the TET2 gene domain of drug-resistant cell lines exhibited persistent high methylation, with a methylation level of β = 0.89. This locus was located 1.2 kb downstream of the transcription start point of exon 4, and the degree of TET2 methylation was negatively correlated with the relative expression level of TET2b mRNA ( r = -0.81, P < 0.01). Conclusions:TET2 methylation may be an important factor for oxaliplatin resistance in the treatment of ALL.

Objective:To explore the mechanisms of oxaliplatin resistance mediated by TET2 methylation in the treatment of acute lymphoblastic leukemia (ALL) using bioinformatics methods.Methods:The data on drug-resistant and sensitive cell lines related to oxaliplatin treatment for ALL were download using the Genomics of Drug Sensitivity in Cancer (GDSC) database (updated in December 2023); the drug-resistant cell lines were screened based on half maximal inhibitory concentration ( IC50) > 10 μmol/L, and the difference in IC50 between drug-resistant and sensitive cell lines were analyzed using Mann-Whitney U test. The cancer driver mutation genes in drug-resistant cell lines were retrieved using the Cancer Cell Line Encyclopedia (CCLE) database (updated in December 2023). Using the protein-protein interaction (PPI) network functional enrichment analysis (STRING) database (updated in June 2024), PPI network analysis was performed on cancer driver mutation genes with biological functions. A confidence threshold of ≥ 0.7 (high confidence) and an average network node degree above 4 (high average) were selected to screen for cancer driver mutation genes with significant biological functions. Using the microRNA Data Integration Portal (mirDIP) database (updated in June 2024), the coexpression data of microRNA (miRNA) and mutant target genes were queried, miRNA-target gene pairs were screened according to the highest score threshold of 1% miRNA and interaction score > 0.9, and the regulatory effect of miRNA on mutant genes was analyzed. DNA methylation data were download from the Methylation in Human Cancer (MethHC) database (updated in June 2024) and the methylSig R software package was used to analyze the differentially methylated regions (DMR) of DNA methylation between drug-resistant and sensitive cell lines; genes with P < 0.05 and absolute difference > 0.2 were selected, and they were divided into high methylation gene group and low methylation gene group. Spearman correlation analysis and Spearman rank test were performed for the degree of methylation and gene expression, and the key genes with P < 0.01 were screened to reveal the relationship between methylation degree and gene expression. Results:As a result of searching the GDSC database, there were a total of 9 drug-resistant cell lines and 17 sensitive cell lines related to oxaliplatin treatment for ALL; after Z-score normalization of IC50 data between drug-resistant and sensitive cell lines, the average rank of drug-resistant cell lines was 21, and the average rank of sensitive cell lines was 8.5, with a statistically significant difference ( Z = -4.08, P < 0.01). Eight cancer driver mutation genes with significant biological functions that lead to drug resistance of the cell lines were screened using the CCLE database and STRING database. According to the mirDIP database, there were a total of 12 pairs of miRNA-target gene pairs with miRNA-target gene interaction scores >0.9. miRNA had strong regulatory effects on the expressions of NRAS and MAP2K1 target genes. In the MethHC database, the β values (numerical value of increased methylation level) of DMR for genes such as TP53, RXRG and SGIP in drug-resistant cell lines were 0.151, 0.165 and 0.149, respectively, compared to those in sensitive cell lines, the differences were statistically significant (all P < 0.01). The degree of methylation of SGIP gene was negatively correlated with the relative expression level of SGIP mRNA ( r = -0.71, P < 0.01), and SGIP gene underwent high methylation at promoter site 143886940. The cg08321569 locus in the TET2 gene domain of drug-resistant cell lines exhibited persistent high methylation, with a methylation level of β = 0.89. This locus was located 1.2 kb downstream of the transcription start point of exon 4, and the degree of TET2 methylation was negatively correlated with the relative expression level of TET2b mRNA ( r = -0.81, P < 0.01). Conclusions:TET2 methylation may be an important factor for oxaliplatin resistance in the treatment of ALL.

Objective:To explore the research hotspots and effective promotion paths of post market surveillance and supervise of medical consumables with non-active medical devices.Methods:Data mining methods were used to collect related journal literatures and documents from the websites of China regulatory institutions and the China National Knowledge Infrastructure(CNKI),order sub item data of medical device adverse event reports,extract the MeSH element words of literatures and documents,perform bibliometric analysis and visual display.Results:The number of medical devices adverse event reports in China has been increasing year by year,reaching 694 866 in 2022,in the four statistical years from 2019 to 2022,the number of reports on non-active medical devices and IVD reagents also showed a parallel increasing trend,accounting for about 65.00% of the total number of adverse event reports on medical devices in the year.The bibliometric analysis of journal literature shows that research in this field has received varying degrees of participation from regulatory institutions,universities,medical institutions,and enterprises.Regulatory institutions have contributed 46 articles,accounting for 56.79% of the total number of articles,followed by 28 articles from universities.The co-occurrence analysis shows that hot topic is focused in 5 clusters:quality management,risk management,international experiences discussion and adverse event surveillance and re-evaluation and real-world research.China regulatory institutions attach great importance to post market surveillance and supervise,and have issued more than 20 relevant documents since 2006,focusing on specific topics and gradually deepening around safety and effectiveness.Conclusion:The post market surveillance and supervise of medical devices,especially medical consumables based on non-active medical devices,need to be promoted synchronously in three dimensions:regulatory institutions,medical institutions,and enterprises.Universities,research institutes,and industry organizations should work in coordinating to strengthen the collection,identification,and active surveillance of risk signals based on adverse event surveillance,safety evaluation based on risk management,and conducting real-world research,research and develop risk control and corrective and preventive measures.

Head and neck malignant tumor is one of the most heterogeneous diseases.The multi-disciplinary team(MDT)is an essen-tial component for personal precise diagnosis,treatment and integrated care management of oncologic diseases including head and neck malignant tumor.MDT clinical practice is also an important teaching mode for head and neck malignant tumors,but it is limited by time and space in actual teaching.An internet visualization platform was constructed based on the Internet,hospital HIS/PACS/LIS/EMR system,medical visualization screen,oral endoscope,remote consultation platform and other accessible audio and video terminals,and has been applied in MDT clinical teaching of head and neck malignant tumors,allowing medical students to participate in MDT through a networked visualization platform.Medical students will achieve deep learning for the most heterogeneous malignant tumor.MDT sup-ported by the internet visualization platform provides a new pathway for clinical medical education.

Objective To comprehensively analyze the epidemiological characteristics and resistance mechanisms of New Delhi metallo-β-lactamase(NDM)-positive multidrug-resistant bacteria in China.Methods Relevant literatures on NDM-positive multidrug-resistant bacteria discovered in China were searched in the CNKI and PubMed databases(publications from January 1,2017 to December 31,2023).The epidemiological analysis was conducted on the types of NDM-positive bacterial strains,their regional distribution,infection sources,resistance profiles,and transfer mechanisms.Results A total of 118 eligible articles were collected,reporting 1627 NDM-positive bacterial strains.The number of reports increased annually from 2011 to 2019,but began to decline annually from 2020 onwards.NDM-1 and NDM-5 were the most commonly reported variants.The highest number of reports came from Eastern China,followed by Central China and North China.The primary pathogens were Klebsiella pneumoniae,Escherichia coli,and Enterobacter cloacae.The age distribution of patients with NDM-positive infections showed distinct patterns,with neonates and children accounting for 27.25％and patients over 50 years old accounting for 49.57％.The majority of positive bacterial infections came from sputum(38.28％),urine(28.94％),and blood(23.28％).The main departments reporting NDM-positive bacteria were the ICU(39.93％)and pediatrics(20.14％).These resistant bacteria exhibited resistance to more than 50.00％of antibiotics,with lower resistance to colistin and tigecycline(below 30.00％).The predominant plasmid type carrying the blaNDMwas IncX3,and the insertion sequences upstream and downstream of the blaNDM showed diversity.Conclusion NDM-positive multidrug-resistant bacteria are widely prevalent across regions in China,exhibiting multidrug-resistance.This poses significant challenges to clinical antibiotic selection and necessitates the development of effective countermeasures.

OBJECTIVE To study the improvement effects and mechanism of rhein on immunoglobulin A nephropathy （IgAN） model rat based on signal transducer and activator of transcription 3 （STAT3） signaling pathway. METHODS Rats were randomly divided into normal control group， IgAN model group and rhein treatment group， with 10 rats in each group. IgAN model group and rhein treatment group were given combination of bovine serum albumin+lipopolysaccharide+carbon tetrachloride to induce IgAN model. Since the 7th week， rhein treatment group rats were intragastrically given relevant medicine， and normal control group and model group rats were given equal amount of normal saline intragastrically， for consecutive 4 weeks. After the last administration， the count of urine sediment erythrocyte， 24 h-urine total protein （UTP）， the levels of immunoglobulin A （IgA） in serum and secretory immunoglobulin A （sIgA） in intestinal mucosa were detected. The pathological changes of Peyer’s patch in renal cortex and intestinal mucosa and IgA deposition in renal cortex were observed. The expressions of interleukin-17 （IL-17）， IL- 6 and transforming growth factor β （TGF-β） in Peyer’s patch of intestinal mucosa in rats were detected. The expressions of STAT3 and related orphan receptor γt （RORγt） mRNA in Peyer’s patch were detected. The expressions of p-STAT3 and RORγt proteins in Peyer’s patch were detected. RESULTS Compared with normal control group， the count of urine sediment erythrocyte， 24 h-UTP， the levels of IgA in serum and sIgA in intestinal mucosa were increased significantly in IgAN model group （P＜0.01）； enlarged renal corpuscles， dilated renal sacs， obvious intratubular mesangial hyperplasia and fibrosis were observed in renal cortex； the volume and germinal center of Peyer’s patch in intestinal mucosa increased； IgA deposition of renal cortex zxyylxk20220103） was obvious； the expressions of IL-17， IL-6 and TGF-β in Peyer’s patch， mRNA expressions of STAT3 and RORγt， protein expressions of p-STAT3 and RORγt were increased significantly （P＜0.01）. Compared with IgAN model group，above indexes were decreased significantly in rhein treatment group （P＜0.01）， pathological damage of renal cortex was improved， the volume of Peyer’s patch and germinal center of intestinal mucosa were reduced， and IgA deposition in renal cortex was weakened. CONCLUSIONS Rhein can improve IgAN model rats， the mechanism of which may be associated with inhibiting STAT3 signaling pathway and regulating immune function of Peyer’s patch in intestinal mucosa.

OBJECTIVE: To establish a new emergency dynamic score (EDS) method based on modified early warning score (MEWS) combined with clinical symptoms, rapidly available examination results and bedside examination data in the emergency department, and to observe its applicability and feasibility in the clinical application of emergency department. METHODS: A total of 500 patients admitted to the department of emergency of Xing'an County People's Hospital from July 2021 to April 2022 were selected as research objects. After admission, EDS and MEWS scores were performed first, and then acute physiology and chronic health evaluation II (APACHE II) was performed retrospectively, and the prognosis of patients was followed up. The difference of short-term mortality in patients with different score segments of EDS, MEWS and APACHE II were compared. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the prognostic value of various scoring methods in critically ill patients. RESULTS: The mortality of patients in different score groups of each scoring method increased with the increase of the score value [The mortality of 0-1, 2-3, 4-5, 6-7 and ≥ 8 of MEWS were 1.9% (3/159), 2.9% (6/208), 12.4% (11/89), 29.0% (9/31) and 61.5% (8/13), respectively. The mortality of EDS stage 1 weighted MEWS score 0-3, 4-6, 7-9, 10-12 and ≥ 13 were 0 (0/49), 3.2% (8/247), 6.6% (10/152), 31.9% (15/47) and 80.0% (4/5), respectively. The mortality of EDS stage 2 clinical symptom score 0-4, 5-9, 10-14, 15-19, ≥ 20 were 0 (0/13), 0.4% (1/235), 3.6% (6/165), 26.2% (17/65), 59.1% (13/22), respectively. The mortality of EDS stage 3 rapid test data score 0-6, 7-12, 13-18, 19-24 and ≥ 25 were 0 (0/16), 0.6% (1/159), 4.6% (6/131), 13.7% (7/51) and 65.0% (13/20), respectively. The mortality of patients with APACHE II score 0-6, 7-12, 13-18, 19-24 and ≥ 25 were 1.9% (1/53), 0.4% (1/277), 4.6% (5/108), 34.2% (13/38) and 70.8% (17/24), respectively, all P < 0.01]. When the MEWS score was more than 4, the specificity was 87.0%, the sensitivity was 67.6%, and the maximum Youden index was 0.546, which was the best cut-off point. When the weighted MEWS score of EDS in the first stage was greater than 7, the specificity of predicting the prognosis of patients was 76.2%, the sensitivity was 70.3%, and the maximum Youden index was 0.465, which was the best cut-off point. When clinical symptom score of EDS in the second stage was more than 14, the specificity and sensitivity of predicting the prognosis of patients were 87.7% and 81.1%, respectively, and the maximum Youden index was 0.688, which was the best cut-off point. When the third stage rapid test of EDS reached 15 points, the specificity of predicting the prognosis of patients was 70.9%, and the sensitivity was 96.3%, and the maximum Youden index was 0.672, which was the best cut-off point. When APACHE II score was higher than 16, the specificity was 87.9%, the sensitivity was 86.5%, and the maximum Youden index was 0.743, which was the best cut-off point. ROC curve analysis showed that: EDS score in the stage 1, 2 and 3, MEWS score and APACHE II score can predict the short-term mortality risk of critically ill patients. The area under the ROC curve (AUC) and 95% confidence interval (95%CI) were 0.815 (0.726-0.905), 0.913 (0.867-0.959), 0.911 (0.860-0.962), 0.844 (0.755-0.933) and 0.910 (0.833-0.987), all P < 0.01. In terms of the differential ability to predict the risk of death in the short-term, the AUC in the second and third stages of EDS were highly close to APACHE II score (0.913, 0.911 vs. 0.910), and significantly higher than MEWS score (0.913, 0.911 vs. 0.844, both P < 0.05). CONCLUSIONS EDS method can dynamically evaluate emergency patients in stages, and has the characteristics of fast, simple, easy to obtain test and inspection data, which can facilitate emergency doctors to evaluate emergency patients objectively and quickly. It has strong ability to predict the prognosis of emergency patients, and is worth popularizing in emergency departments of primary hospitals.
Humans ; Research Design ; Critical Illness ; Retrospective Studies ; Hospitals ; Emergency Service, Hospital

ObjectiveTo investigate the role of endoplasmic reticulum stress genes in the prognosis of pancreatic cancer， and to establish a prognostic prediction model based on the prognostic markers for pancreatic cancer. MethodsTranscriptome sequencing data were downloaded from TCGA and GTEx databases， and MsigDB website was used to obtain endoplasmic reticulum stress genes. A univariate Cox regression analysis was performed to obtain the genes associated with the prognosis of pancreatic cancer， and a consensus clustering analysis was used to construct the molecular typing of pancreatic cancer， while the differentially expressed genes between the two subgroups were obtained. A Lasso regression analysis was used to obtain the core genes associated with the prognosis of pancreatic cancer， which were used to construct a prognostic prediction model for pancreatic cancer. Related datasets were obtained from the GEO database to validate the predictive performance of the model. The CIBERSORT analysis was used to investigate the correlation between risk score and immune infiltration. Quantitative real-time PCR was used to measure the expression of genes in pancreatic cancer tissue and cell lines. The independent-samples t test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between groups. Survival was compared using Log-rank test. The predictive value of the model was evaluated by evaluating the area under the ROC curve. ResultsThe endoplasmic reticulum stress genes CEBPB， MARCKS， PMAIP1， and UBXN10 were independent risk factors for the prognosis of pancreatic cancer， and based on the expression characteristics of these genes， the TCGA pancreatic cancer cohort was divided into two subgroups， i.e.， cluster A and cluster B， while the cluster A patients had a significantly shorter overall survival time than the cluster B patients （P<0.01）. The Lasso regression analysis obtained 5 core genes from the differentially expressed genes affecting the prognosis of pancreatic cancer， and the risk scoring system was established as risk score=0.156×CDA+0.135×AHNAK2+0.020×RHOV+0.095×LY6D+0.054×SPRR1B. The ROC curve analysis showed that this model had good overall predictive performance， with the area under the ROC curve of 0.731 at 1 year， 0.712 at 3 years， and 0.686 at 5 years， and the low-risk group based on this model had a significantly longer overall survival time than the high-risk group （χ²=11.733， P=0.001）. The model showed good predictive performance in the external dataset GSE57495. Quantitative real-time PCR results showed that the expression levels of CDA， AHNAK2， RHOV， LY6D， and SPRR1B in 40 pancreatic cancer tissue samples were significantly upregulated compared with those in normal adjacent tissue samples （t=2.529， 2.458， 3.314， 3.583， and 5.082， all P<0.05）. ConclusionThe expression characteristics of CDA， AHNAK2， RHOV， LY6D， and SPRR1B can be used to predict the prognosis of pancreatic cancer， and the high expression levels of these genes are associated with the poor prognosis of pancreatic cancer patients.

Anti-seizure medications (ASMs) are the main therapy for epilepsy.There are many kinds of ASMs with complex mechanism of action, so it is difficult for pharmacists to examine prescriptions.This paper put forward some suggestions on the indications, dosage forms/routes of administration, appropriateness of usage and dosage, combined medication and drug interaction, long-term prescription review, individual differences in pathophysiology of children, and drug selection when complicated with common epilepsy, for the reference of doctors and pharmacists.

The transcription factor nuclear factor of kappa-light-chain-enhancer of activated B cells (NF-κB) is expressed in brown adipocytes, but its role remains largely unknown in the cells. This issue was addressed in current study by examining NF-κB in brown adipocytes in vitro and in vivo. NF-κB activity was increased by differentiation of brown adipocytes through elevation of p65 (RelA) expression. The transcriptional activity of NF-κB was induced by the cold stimulation with an elevation in S276 phosphorylation of p65 protein. Inactivation of NF-κB in brown adipocytes made the knockout mice [uncoupling protein 1 (Ucp1)-CreER-p65^f/f, U-p65-KO] intolerant to the cold environment. The brown adipocytes exhibited an increase in apoptosis, a decrease in cristae density and uncoupling activity in the interscapular brown adipose tissue (iBAT) of p65-KO mice. The alterations became severer after cold exposure of the KO mice. The brown adipocytes of mice with NF-κB activation (p65 overexpression, p65-OE) exhibited a set of opposite alterations with a reduction in apoptosis, an increase in cristae density and uncoupling activity. In mechanism, NF-κB inhibited expression of the adenine nucleotide translocase 2 (ANT2) in the control of apoptosis. Data suggest that NF-κB activity is increased in brown adipocytes by differentiation and cold stimulation to protect the cells from apoptosis through down-regulation of ANT2 expression.