In this study, we constructed a GLP-2R-HEK293 cell line and established a method for the determination of the in vitro biological activity of teduglutide based on HTRF, after optimizing experimental conditions and methodological verification. We also carried out relative potency detection of teduglutide pharmaceutical products using this method. The result showed that there was a quantitative-efficient relationship between the teduglutide activity and cAMP contents in GLP-2R-HEK293 cells, which conformed to four-parameter model. Method verification results of five concentrations of teduglutide (64%, 80%, 100%, 125% and 156%) met the requirements of the General Rules of Chinese Pharmacopoeia, 2020 edition, Volume IV (9401). We then analyzed the relative potency of three batches of teduglutide drug substances and three batches of drug products. The linearity, regression and parallelism of the obtained curves all fit the system suitability requirements. The relative potency of six batches of teduglutide was from 83% to 105%. In summary, the biological activity detection method established in this study was accurate, precise, simple and time-saving, which can be used for quality control of teduglutide pharmaceutical products.

ObjectiveTo explore the impact of Gegen Qinliantang（GQT） on the fecal short-chain fatty acids（SCFAs） metabolism in antibiotic-associated diarrhea（AAD） through targeted metabolomics. MethodA total of 240 SD rats were randomly divided into six groups（n=40， half male and half female）， including blank group， model group， bifidobiogen group（0.15 g·kg^-1）， and GQT high-， medium-， and low-dose groups（10.08， 5.04， 2.52 g·kg^-1）， except for the blank group， clindamycin（250 mg·kg^-1） was given to all groups by gavage for modeling every day for 7 d. After successful modeling， each administered group was gavaged with the corresponding dose of the drug， and the blank and model groups were gavaged with an equal volume of normal saline solution， 1 time/d， for 14 d. At 0， 3， 7， 14 d after the drug intervention， eight rats were randomly selected from each group， respectively. Gas chromatography-time-of-flight mass spectrometry（GC-TOF-MS） was used to perform targeted metabolomic analysis of SCFAs in the feces of rats， and partial least squares-discriminant analysis（PLS-DA） was applied to compare the differences in metabolic profiles between groups at different treatment times， and to compare the changes in the contents of SCFAs in rat feces between groups. ResultPLS-DA results showed that the blank group could be clearly distinguishable from the model group， with GQT exhibiting a closer proximity to the blank group after 7 d of treatment. After further analyzing the composition of SCFAs， it was found that the proportion of acetic acid increased and the proportions of butyric acid， valeric acid， hexanoic acid and isovaleric acid decreased in the model group compared with the blank group. After the treatment with GQT， the proportions of butyric acid， isobutyric acid， valeric acid， and isovaleric acid increased， and the proportions of acetic acid， propionic acid and caproic acid decreased. Subsequent differential analysis revealed that GQT could significantly improve the content of butyric acid， and had a certain retrogressive effect on the contents of valeric acid and hexanoic acid. ConclusionThe medium dose group of GQT can improve the contents of SCFAs in AAD feces after 7 days of treatment， which may be related to the improvement of the composition ratio of SCFAs and the contents of butyric acid， valeric acid and caproic acid.

This study constructed a LHCGR-CRE-luc-HEK293 transgenic cell line according to the activation of the cAMP signaling pathway after recombinant human chorionic gonadotropin binding to the receptor. The biological activity of recombinant human chorionic gonadotropin was assayed using a luciferase assay system. The relative potency of the samples was calculated using four-parameter model. And the method conditions were optimized to validate the specificity, relative accuracy, precision and linearity of the method. The results showed that there was a quantitative potency relationship of human chorinonic gonadotropin (hCG) in the method and it was in accordance with the four-parameter curve. After optimization, the conditions were determined as hCG dilution concentration of 2.5 μg·mL^-1, dilution ratio of 1∶4, cell number of 10 000-15 000 cells/well, and induction time of 6 h. The method had good specificity, relative accuracy with relative bias ranging from -8.9% to 3.4%, linear regression equation correlation coefficient of 0.996, intermediate precision geometric coefficient of variation ranging from 3.3% to 15.0%, and linearity range of 50% to 200%. This study successfully established and validated a reporter gene method to detect hCG biological activity, which can be used for hCG biological activity assay and quality control.

During the occurrence and development of various heart diseases,continuous deterioration of myocardial fibrosis leads to remodeling and dysfunction of the cardiac structure.As a newly discovered mechanically sensitive ion channel,Piezo1 has opened up a new field of research on cellular mechanical transduction.Piezo1 combines a fine force transducer with Ca2+ influx and participates in the regulation of cellular mechanical transduction,thereby regulating cellular biological functions.Recent studies have shown that the biomechanical changes induced by myocardial injury regulate the expression of Piezo1 in cardiomyocytes and cause an imbalance in calcium homeostasis,which plays an important role in the positive feedback loop of myocardial fibrosis.This review summarizes the theoretical basis and related studies of Piezo1 in regulating cardiac fibrosis and suggests that the Piezo1 channel may become a new target for the treatment of cardiac fibrosis,thereby providing a new research horizon for the prevention and treatment of cardiac fibrosis.

Objective:To investigate the changing trend of mortality rate and death cause spectrum among household-registered residents aged 60 and above in Beijing from 2007 to 2020.Methods:The mortality data was collected from the Beijing Death Information Registration and Management System. We calculated the mortality rates and constituent ratios by gender, age groups, and death causes and estimated the changing trend of mortality rate and average annual percent change (AAPC) by Joinpoint 4.3.1.Results:The crude mortality rate decreased from 27.62‰ in 2007 to 23.55‰ in 2020 (AAPC=-1.18%, P<0.001), and the standard rate also decreased from 25.39‰ in 2007 to 19.85‰ in 2020 (AAPC=-1.68%, P<0.001) among registered residents aged 60 and above in Beijing. The top 5 causes of death were heart diseases, malignant tumors, cerebrovascular diseases, respiratory diseases, and endocrine and nutritional metabolic diseases, accounting for 87.1% of the total deaths. The mortality rates of heart diseases (AAPC=-1.08%, P=0.024), cerebrovascular diseases (AAPC=-3.79%, P<0.001), malignant tumors (AAPC=-0.31%, P=0.006) and respiratory diseases (AAPC=-5.56%, P=0.007) showed a decreasing trend. The rate of injury and poisoning showed an increasing trend (AAPC=1.54%, P=0.001), while no statistically significant change was found in endocrine and nutritional metabolic diseases mortality rates (AAPC=-1.46%, P=0.054). Conclusions:The mortality rate of registered residents aged 60 years and over in Beijing showed a downward trend from 2007 to 2020. Heart diseases, cerebrovascular diseases, malignant tumors, and respiratory diseases should be treated as the key diseases for prevention and control, and targeted measures should be taken to improve the health level of the elderly population.

Objective To investigate the association between the serum creatinine/cystatin C ratio(SCr/Cys C)as a Sarcopenia index(SI)and the incidence of in-hospital adverse events in patients with acute myocardial infarction(AMI)undergoing emergency percutaneous coronary intervention(PCI).Additionally,we evaluate the predictive efficacy of the SI in predicting major adverse cardiovascular events(MACEs)during hospitalization.Methods A total of 306 patients with AMI who underwent emergency PCI in the 904th Hospital of PLA Joint Logistics Support Force from January 2020 to March 2023 were consecutively included in this retrospective analysis.Patients were divided into two groups based on the occurrence of MACEs during hospitalization:MACEs group(n=43)and non-MACEs group(n=263).Clinical characteristics and pre-PCI laboratory test results were collected.Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for MACEs.The predictive performance of SI was assessed using receiver operating characteristic(ROC)curve analysis.Results The incidence of in-hospital MACEs in AMI patients was 14.1%.The results of the independent samples t-test showed that the SI level in MACEs group was significantly lower than that in non-MACEs group,with a statistically significant difference(P<0.001).The results of the multivariate logistic regression analysis suggested that new-onset atrial fibrillation,Killip class 2-4,SI,and TG were independent risk factors for in-hospital adverse events after emergency PCI.The ROC curve results showed that the predictive value of SI(AUC=0.741,95%CI 0.666-0.816)using the SCr/Cys C ratio was superior to that of single Cys C(AUC=0.658,95%CI 0.570-0.746)for predicting post-PCI MACEs,with a statistically significant difference(P<0.05),and the optimal cutoff value for SI was 78.14.After stratifying SI based on the cutoff value,the results of the independent samples t-test showed that compared to the higher SI group,the lower SI group had a higher occurrence of specific adverse events such as heart failure(P<0.001),malignant arrhythmias(P=0.009),and strokes(P=0.003),with statistically significant differences.Conclusions The results highlight SI as an independent risk factor for MACEs during hospitalization after emergency PCI in AMI patients.Furthermore,SI has proven to be an effective prognostic index for patient outcomes.

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.