Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

As the number of patients with compromised immune function increases and fungal resistance develops, so does the risk of contracting deadly fungi in humans. Both fungi and humans are eukaryotes, so identifying unique targets for antifungal drug development is difficult. In addition, the existing antifungal drugs are limited by toxicity, drug interaction and drug resistance in practical application, which leads to the increasing incidence and fatal rate of fungal infections. Therefore, it is urgent to develop new antifungal drugs. The semi-synthetic technology using microbial fermentation products from natural sources as lead compounds has become the most used method in structural modification of antifungal drugs due to its advantages of few reaction steps and easy operation. This paper will introduce the current status of natural antifungal drugs in clinical use, as well as the latest progress in the research and development of new semi-synthetic antifungal drugs, and summarize their mechanism of action, structural modifications, advantages and disadvantages, so as to provide reference for the subsequent development of new antifungal drugs.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

ObjectiveGQDs has become a superstar among zero-dimensional carbon-based materials. As one of the most abundant and important biological elements, its unique optical properties, high dispersion and biocompatibility have attracted extensive attention from scientists. This paper aims to investigate the effect of GQDs on cell viability, apoptosis and inflammatory factor expression in RAW264.7 macrophages and evaluate cell imaging capability of GQDs in vitro, which could provide theoretical basis for the safe application of GQDs in biomedical field. MethodsGraphene oxide was prepared by modified Hummer’s method. H₂O₂ and W₁₈O₄₉ interacted with each other under hydrothermal conditions to produce hydroxyl radicals, which can cut graphene oxide into GQDs using a top-down approach. The microstructure of GQDs was analyzed in detail by X-ray powder diffraction, X-ray photoelectron spectroscopy, transmission electron microscopy, atomic force microscopy, scanning electron microscopy and Fourier infrared transform. The biocompatibility of GQDs on macrophage was evaluated by CCK-8 and dead/alive staining. Flow cytometry results showed the apoptosis of RAW264.7 macrophages induced by GQDs. mRNA expression of inflammatory factors was evaluated byRT-qPCR. Cell imaging was exhibited by laser scanning confocal. ResultsHydroxyl radicals are produced by H₂O₂ and W₁₈O₄₉ under hydrothermal conditions, which contribute to cut graphene oxide into 3-5 nm GQDs in one step. The quantum yield of this method is 43%. Fluorescence lifetime of these blue GQDs is 1.67 ns. The Zigzag-type site and defect state of the triplet carbene radical lead to the excitation wavelength dependence of GQDs, and the optimal excitation and emission wavelengths are 330 nm and 400 nm, respectively. The boundary effect and amphiphilicity of quantum dots make GQDs possess abundant functional groups, vacancy defects and high dispersion, which results in GQDs exhibits good water solubility. RAW264.7 macrophages are incubated with different concentration in DEME medium for 24 h, 48 h and 72 h to evaluate cell. The survival rate of RAW264.7 cells is significantly dependent on the concentration and time of GQDs. CCK-8 and dead/alive staining show that GQDs have high biocompatibility. The effect of 200 mg/L GQDs on apoptosis of RAW264.7 cells is revealed by the scatter plot of bivariate flow cytometry. Under the stimulation of LPS+INF‑γ, the expression of TNF-α was increased in RAW264.7 cells, which co-acted with other cytokines to participate in the immune response of RAW264.7 cells in vitro, and mediated the production of IL-1β inflammatory factor in RAW264.7 cells, thereby inducing apoptosis of RAW264.7 cells. The results of RT-qPCR showed that GQDs can inhibit the growth of RAW264.7 cells in vitro, and stimulate them to increase TNF-α expression in RAW264.7 cells, which make cell membrane rupture and produce IL-1β inflammatory factors to induce cell apoptosis. The high biocompatibility of GQDs is attributed to the rich oxygen-containing functional groups (―COOH, ―OH, and CO) on the surface of GQDs, which makes its surface negatively charged and easy to be swallowed into the cell interior when interacting with the cell membrane with low affinity. Transmission electron microscopy (TEM) observed that the GQDs were swallowed into the cells. Furthermore, laser confocal results displayed that blue GQDs has certain ability of cell imaging in vitro. ConclusionThe water solubility, low toxicity, fluorescence properties and the induction effect of inflammatory factors of GQDs provide broad prospects for their application in the field of immunotherapy and cell imaging in the future.

Objective:To analyze the correlation among human retinol binding protein 4(RBP4),miR-1-3p,re-combinant human vitamin D binding protein(VDBP)and severity of ST-segment elevation myocardial infarction(STEMI)based on SYNTAX score and their diagnostic value for it.Methods:A total of 162 STEMI patients admit-ted to our hospital for treatment from January 2020 to June 2021 were selected as STEMI group,and another 67 healthy subjects who received physical examination in our hospital simultaneously were selected as healthy control group.According to SYNTAX score,STEMI group was further divided into low risk group(n=68,＜22 points),medium risk group(n=53,23 points≤SYNTAX score≤32 points)and high risk group(n=41,＞33 points).Lev-els of RBP4,VDBP and miR-1-3p expression were compared among above groups.Diagnostic value of single and combined detection of above indexes for severity of STEMI were analyzed.Correlation between SYNTAX score and above indexes were analyzed in STEMI patients.Results:Compared with healthy control group,there were signifi-cant rise in levels of RBP4[(47.18±5.24)μg/L vs.(81.40±6.11)μg/L]and VDBP[(2.36±0.75)μg/ml vs.(3.55±1.04)μg/ml],and significant reduction in miR-1-3p expression[(1.18±0.13)vs.(0.72±0.07)]in STEMI group,P＜0.001 all.Compared with low risk group,there were significant rise in levels of RBP4[(69.97±2.98)μg/L vs.(85.23±3.76)μg/L vs.(95.41±3.16)μg/L]and VDBP[(3.19±0.50)μg/ml vs.(3.55±0.52)μg/ml vs.(4.16±0.64)μg/ml],and significant reduction in miR-1-3p expression[(0.80±0.05)vs.(0.70±0.04)vs.(0.61±0.03)]in medium risk group and high risk group,and levels of RBP4 and VDBP in high risk group were significantly higher than those of medium risk group,miR-1-3p expression in high risk group was significantly lower than that of medium risk group(P＜0.001 all).ROC analysis indicated that area under the curve(AUC)of combined detection of above indexes was 0.892,which was significantly higher than each single detection(Z=4.787,3.078,2.495,P＜0.05 or＜0.01).Spearman correlation analysis indicated that STEMI severity was significant positively correlated with levels of RBP4 and VDBP(r=0.849,0.776,P＜0.001 both),and significant inversely correla-ted with miR-1-3p expression(r=-0.790,P＜0.001).Conclusion:Levels of RBP4 and VDBP,and miR-1-3p ex-pression can reflect severity of STEMI patients.Triple combined detection possesses high diagnostic efficacy for disease se-verity,which can be used as clinical important indexes for assessing patient's condition.

Objective To design an automatic monitor for patient urine output based on volume measurement with high accuracy,stability and convenience.Methods The patient urine output automatic monitor was designed by means of divide and conquer,which was composed of a micro-controller control module,an urine segmentation module,a liquid level detection module,an electromagnetic valve drive module,a data display module,a transmission module,a storage module and a power management module.The micro-controller control module consisted of a STM32F103C8T6 SCM and its peripheral circuits,which manipulated the working process of all the peripheral modules and urine volume calculation;the urine segmentation module consisted of two solenoid valves,two level detection electrodes and a liquid collection tube,which functioned to divide the urine into several portions with fixed volumes;the liquid level detecttion module was made up of two resistors and a capacitor,which was to determine the urine filling status in the liquid collection tube;a DRV8870 full-bridge driver chip was involved in the electromagnetic valve.Results The monitor developed realized accurate and automatic urine output monito-ring,with the influences of the changing factors eliminated such as urine density and urine bag's position.Conclusion The monitor developed gains advantages in convenience,accuracy,stability and reliability,and is thus worthy promoting pra-ctically to facilitate physicians to determine patient conditions and adjust treatment plans accordingly.[Chinese Medical Equipment Journal,2024,45(6):33-37]

Objective To construct the demand model of four types of medical resources including beds in hospi-tal,beds in intensive care unit(ICU),ventilators and medical human resources during the major infectious disease epidemic events,simulate and analyze the treatment of infectious diseases when different medical resources are in short supply.Methods Based on the susceptible-exposed-infectious-recovered(SEIR)model,considering the infec-tivity of infected persons,the susceptibility of the population and the immunity of convalescents,the characteristics of asymptomatic COVID-19 patients and different clinical types,the"COVID-19 infection-hospitalization model"was constructed.By collecting and setting the parameters of disease transmission,clinical course and medical re-source shortage scenarios,an analysis model of allocation and supply of urban medical resources during infectious di-sease epidemic events was initially formed based on Anylogic platform,the supply and demand of medical resources during infectious disease events in different scenarios were analyzed.Results In the non-intervention scenario,the peak time of bed demand was on the 107th day,and the peak value was 160.92 beds per thousand people;the peak time of ventilator demand was on the 122nd day,and the peak value was 5.61 units per thousand people;the peak time of ICU bed demand was on the 117th day,and the peak value was 12.78 beds per thousand people;the peak time of the demand for medical human resources was on the 109th day,and the peak value was 151.12 persons per thousand persons.The simulation results suggested that there were some differences in the impact of different medi-cal resources on the outcome of medical treatment.Conclusion This study constructs an analytical tool for the allo-cation and supply of urban medical resources under the epidemic events of infectious diseases,and the results of mul-tiple simulation experiments suggest that bed resources and medical human resources play more important roles in the outcome of medical treatment.

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.