ObjectiveTo learn the density and seasonal variation of adult mosquitoes in Pudong New Area of Shanghai, and to explore the influence of meteorological factors on the density of adult mosquitoes. MethodsFrom April to November in 2017‒2021, adult mosquito density in Pudong New Area was monitored every ten days a time by using CO₂ trapping light method. Meteorological data were collected during the same time, and Pearson correlation analysis and multiple linear regression model were used to investigate the correlation between adult mosquito density and meteorological factors. ResultsThe seasonal variation of adult mosquito density showed a single-peak pattern, with the peak of 7.09 mosquitoes·(set·time)^-1 in July. The adult mosquito density was positively correlated with the monthly average temperature, monthly maximum temperature, monthly minimum temperature, and monthly average relative humidity (r=0.813, 0.793, 0.820, 0.617, all P<0.05), but negatively correlated with monthly average air pressure (r=-0.738, P<0.05). The regression equation of the adult mosquito density and monthly minimum temperature in Pudong New Area of Shanghai was Y=0.066 X₃-0.884, with a corrected R² of 0.673, indicating a good model fitting. ConclusionThe overall seasonal variation of adult mosquito density in Pudong New Area showed a single-peak pattern. The density of adult mosquitoes was correlated with the monthly average temperature, monthly maximum temperature, monthly minimum temperature, monthly average relative humidity, and monthly average air pressure, and linearly correlated with monthly minimum temperature.

Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels: individual, equipment, management, and environment in past 12 months. Data balancing was performed using resampling, and LASSO regression was used to select factors of non-fatal occupational injuries. The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable, where variables with estimated coefficients > 0 are risk factors, and those <0 are protective factors. The area under the receiver operating characteristic (ROC)curve (AUC) was used to test the performance of the model, with an AUC value > 0.7 indicating good model performance. Results Among the 2243 frontline workers, males accounted for 77.7% (1742 out of 2243), with the main age range being 40-49 years old, representing 29.5% (661 out of 2243), 82.7% of the workers (1854 out of 2243) were married, and 55.6% (1248 out of 2243) had a junior middle school education level. The average monthly income for 51.0% (1144 out of 2243) of the workers was between 5000 and 6999 Chinese Yuan. The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4% (189/2243) in the past 12 months. Among the 22 factors associated with the occurrence of non-fatal occupational injuries (P<0.05), 10 were individual-level factors, including gender, smoking, alcohol consumption, colleague relationships, average exercise duration, job burnout, work fatigue, musculoskeletal disorders, cardiovascular diseases, and neurological and sensory organ diseases; 3 were equipment-level factors, including equipment operability, hazardous workpieces, and safety hazards; 5 were environmental-level factors, including low temperatures, special operations, noise, workspace size, and dirty and disorderly environment; and 4 were management-level factors, including daily working hours, weekly working days, overtime, and pre-job technical training. The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables. Among them, there were 7 risk factors for non-fatal occupational injuries (coefficient > 0), including safety hazards, musculoskeletal disorders, dangerous workpieces, job burnout, dirty and disorderly environment, smoking, and male gender; and 3 protective factors (coefficient < 0), including pre-job technical training, good colleague relationship, and long working days per week. Conclusion Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interventions for non-fatal occupational injuries by controlling potential safety hazards, providing pre-job technical training, reducing dangerous workpieces, rectifying working environment, and reasonably arranging working hours.

Malignant proliferating liver cancer cells possess the ability to detect and respond to various body signals, thereby facilitating tumor growth, invasion, and metastasis. One crucial mechanism through which hepatocellular carcinoma (HCC) cells interpret these signals is crosstalk. Within liver cancer tissues, cancer cells engage in communication with hepatic stellate cells (HSCs), tumor-associated macrophages (TAMs), and immune cells. This interaction plays a pivotal role in regulating the proliferation, invasion, and metastasis of HCC cells. Crosstalk occurs in multiple ways, each characterized by distinct functions. Its molecular mechanisms primarily involve regulating immune cell functions through the expression of specific receptors, such as CD24 and CD47, modulating cell functions by secreting cytokines like transforming growth factor-β (TGF-β) and platelet-derived growth factor (PDGF), and mediating cell growth and proliferation by activating pathways such as Wnt/β-catenin and Hedgehog. A comprehensive understanding of the mechanisms and interactions within crosstalk is essential for unraveling the pathogenesis of HCC. It also opens up new avenues for the development of innovative therapeutic strategies. This article reviews the relationship between crosstalk and the progression of HCC, offering insights and inspiration for future research.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Hepatic Stellate Cells/physiology* ; Disease Progression ; Signal Transduction/physiology* ; Transforming Growth Factor beta/metabolism* ; Cell Proliferation ; Hedgehog Proteins/metabolism* ; Tumor-Associated Macrophages ; Platelet-Derived Growth Factor/metabolism* ; Cell Communication/physiology*

OBJECTIVE: This study aimed to determine the expression levels and prognostic significance of MYCN in bone marrow of adult patients with newly diagnosed acute myeloid leukemia (AML). METHODS: A total of 62 newly diagnosed patients with non-M3 AML were enrolled as the study group, and 20 healthy donors as the control group. Real-time quantitative reverse transcription-polymerase chain reaction (PCR) was performed to detect the expression level of MYCN, and the relationship between MYCN expression and prognosis of AML patients was analyzed. RESULTS: MYCN was up-regulated in newly diagnosed AML patients compared with normal controls (P < 0.001). Receiver operating characteristic (ROC) curve analysis revealed that MYCN could serve as a diagnostic biomarker for AML. Kaplan-Meier survival analysis showed that the patients with high MYCN expression had a shorter overall survival (OS) time than the patients with low MYCN expression (P =0.016). The expression level of MYCN was lower during the complete ressimion (CR) phase of AML compared to the initial diagnosis, but it returned to the initial diagnostic level or even higher during relapse phase. Multivariate Cox regression analysis showed that high expression of MYCN was an independent risk factor for OS of AML patients (P =0.021). CONCLUSION MYCN is highly expressed and associated with poor prognosis in de novo AML, which might be serve as a novel diagnostic and prognostic biomarker for adult AML.
Humans ; Leukemia, Myeloid, Acute/metabolism* ; Prognosis ; N-Myc Proto-Oncogene Protein ; Adult ; Female ; Male ; Middle Aged

OBJECTIVE: To investigate the predictive value of morphology, immunology, and cytogenetics for isocitrate dehydrogenase 1 and 2 (IDH1/2) gene mutation in newly diagnosed acute myeloid leukemia (AML) patients. METHODS: The clinical data of 186 newly diagnosed AML patients (except M3 subtype) in the First People's Hospital of Changzhou were retrospectively analyzed, and the variables associated with IDH1/2 mutation in patients were screened using LASSO regression to construct a multivariate logistic regression analysis model. The Bootstrap method was used for internal validation of the model and nomograms were used to visualize the model, and receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of the model. RESULTS: A total of 60 AML patients had IDH1/2 mutation at initial diagnosis. LASSO regression screened 9 predictive variables associated with IDH1/2 mutation, including CD7, CD56, CD11b, CD15, CD64, HLA-DR, platelet count≥50×10⁹/L, isolated +8 and normal karyotype. The nomogram and ROC curve were plotted based on the above 9 variables. The area under the ROC curve (AUC) of the training set and the validation set were 0.871 and 0.806, respectively. Internal validation showed that the nomogram had good predictive ability. CONCLUSION The prediction model based on MIC typing constructed in this study has a good predictive ability for the presence of IDH1/2 mutations in newly diagnosed AML patients and has important clinical application value when the gene mutation detection results are unavailable.
Humans ; Isocitrate Dehydrogenase/genetics* ; Leukemia, Myeloid, Acute/genetics* ; Mutation ; Retrospective Studies ; Nomograms ; Female ; Male ; ROC Curve ; Middle Aged

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.

Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5％in all clinical isolates amd 5.7％in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7％(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)％,followed by secretions/pus(16.4±2.3)％and urine(16.0±0.9)％.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9％),and only(7.1±0.8)％of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)％compared to the inpatients in any other departement.Overall,≤ 7.9％of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6％of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7％vs 3.9％).Overall,≤8.1％of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5％of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0％over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.

Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10％of the Proteus and Morganella strains were resistant,while less than 20％of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4％in Proteus isolates,1.9％in Morganella isolates,and 15.6％in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.