AIM: To investigate the changes in serum levels of trefoil factor 1(Tff1)and bone morphogenetic protein 4(BMP4)in patients with diabetic retinopathy, and to evaluate their diagnostic value for diabetic retinopathy.METHODS: From January 2022 to January 2024, 186 patients with type 2 diabetes were selected as the study group and divided into a retinopathy subgroup(52 cases)and a non-retinopathy subgroup(134 cases)based on the presence of retinopathy. Another 186 healthy volunteers who underwent physical examinations during the same period were chosen as the control group. Serum Tff1 and BMP4 levels were measured using the enzyme-linked immunosorbent assay(ELISA). Pearson analysis was used to assess the correlation between serum Tff1, BMP4 levels, and clinical data. Multivariate Logistic regression analysis was performed to identify factors influencing the development of retinopathy in type 2 diabetic patients. Receiver operating characteristic(ROC)curve analysis was conducted to evaluate the diagnostic value of serum Tff1 and BMP4 levels for retinopathy in type 2 diabetic patients.RESULTS: Compared to the control group, serum Tff1 levels were lower and BMP4 levels were higher in both retinopathy and non-retinopathy subgroups(all P<0.05). Specifically, serum Tff1 levels were lower and BMP4 levels were higher in the retinopathy subgroup than in the non-retinopathy subgroup(all P<0.05). Pearson analysis revealed that Tff1 levels in type 2 diabetes patients were negatively correlated with disease duration, glycated hemoglobin levels, and triglyceride levels, while BMP4 levels were positively correlated(all P<0.05). Multivariate Logistic regression analysis identified type 2 diabetes duration, glycated hemoglobin, triglycerides, Tff1, and BMP4 as influencing factors for retinopathy development in type 2 diabetes patients(all P<0.05). ROC curve analysis showed that the combined diagnosis of serum Tff1 and BMP4 had an area under the curve(AUC)of 0.901, which was significantly higher than that of Tff1 alone(Z=2.069, P=0.039)and BMP4 alone(Z=2.072, P=0.038).CONCLUSION: Serum Tff1 levels are decreased and BMP4 levels are increased in patients with diabetic retinopathy, and the combined detection of these two markers offers high diagnostic value for diabetic retinopathy.

Objective To analyze the factors related to early allograft dysfunction(EAD)after liver transplantation and to construct a predictive model.Methods A total of 375 patients who underwent liver transplantation in our hospital from December 2008 to December 2021 were collected,including 90 patients with EAD and 266 patients without EAD.Thirty items of baseline data for the 2 groups were compared and analyzed.Aftergrouping in a ratio of 7∶3,univariate and multivariate logistic regression analyses were used in the training set to evaluate the factors related to EAD and construct a nomogram.Receiver operating characteristic(ROC)curve,decision curve analysis(DCA),sensitivity,specificity,positive predictive value,negative predictive value,Kappa value and other indicators were used to evaluate the model performance.Results The incidence of EAD after liver transplantation was 24%.Multivariate logistic regression analysis showed that preoperative tumor recurrence history(OR=3.15,95%CI:1.28～7.77,P=0.013)and operation time(OR=1.22,95%CI:1.04～1.42,P=0.015)were related to the occurrence of EAD after surgery.After predicting the outcome according to the cut-off point of 0.519 identified by the Youden index,the model performance in the both training set and validation set was acceptable.DCA suggested the model has good clinical applicability.Conclusion The risk factors for EAD after liver transplantation are preoperative tumor recurrence history and operation time,and the established model has predictive effect on prognosis.

Objective:To investigate the diagnostic value of an intelligent assisted grading algorithm for nuclear cataract using anterior segment optical coherence tomography (AS-OCT) images.Methods:A diagnostic test study was conducted.AS-OCT image data were collected from 939 cases of 1 608 eyes of nuclear cataract patients at the Shanghai Tenth People's Hospital of Tongji University from November 2020 to September 2021.The data were obtained from the electronic case system and met the requirements for clinical reading clarity.Among them, there were 398 cases of 664 male eyes and 541 cases of 944 female eyes.The ages of the patients ranged from 18 to 94 years, with a mean age of (65.7±18.6) years.The AS-OCT images were labelled manually from one to six levels according to the Lens Opacities Classification System Ⅲ (LOCS Ⅲ grading system) by three experienced clinicians.This study proposed a global-local cataract grading algorithm based on multi-level ranking, which contains five basic binary classification global local network (GL-Net).Each GL-Net aggregates multi-scale information, including the cataract nucleus region and original image, for nuclear cataract grading.Based on ablation test and model comparison test, the model's performance was evaluated using accuracy, precision, sensitivity, F1 and Kappa, and all results were cross-validated by five-fold.This study adhered to the Declaration of Helsinjki and was approrved by Shanghai Tenth People's Hospital of Tongji University (No.21K216).Results:The model achieved the results with an accuracy of 87.81%, precision of 88.88%, sensitivity of 88.33%, F1 of 88.51%, and Kappa of 85.22% on the cataract dataset.The ablation experiments demonstrated that ResNet18 combining local and global features for multi-level ranking classification improved the accuracy, recall, specificity, F1, and Kappa metrics.Compared with ResNet34, VGG16, Ranking-CNN, MRF-Net models, the performance index of this model were improved.Conclusions:The deep learning-based AS-OCT nuclear cataract image multi-level ranking classification algorithm demonstrates high accuracy in grading cataracts.This algorithm may help ophthalmologists in improving the diagnostic accuracy and efficiency of nuclear cataract.

Objective:To investigate the mechanisms underlying the effect of levocarnitine on myocardial cell fibrosis, proliferation, apoptosis and migration.Methods:Between June and December 2022, an overexpression vector for tissue inhibitor-1 of metalloproteinase(TIMP-1)and siRNA TIMP-1 were used to transfect rat H9c2 cardiomyocytes(from the cell bank of the Chinese Academy of Sciences), and transfection efficiency was measured using fluorescence reverse transcription quantitative PCR(RT-qPCR). After treating H9c2 cells with angiotensin Ⅱ(AngⅡ), the expression of the MMP3 and TIMP-1 genes in the cells was detected by RT-qPCR.A CCK8 kit was used to assess the effect of levocarnitine intervention on the proliferation of myofibroblasts after overexpression or knockdown of TIMP-1.The effects of levocarnitine on apoptosis and migration of myofibroblasts were detected by flow cytometry and Transwell assays.Results:The RT-qPCR results showed that the expression level of the MMP3 gene(1.38±0.05)in cardiomyocytes treated with AngⅡ for 24 hours exhibited an upward trend( P<0.01), while the expression level of the TIMP-1 gene(0.71±0.03)showed a downward trend( P<0.01). In addition, H9c2 cells with TIMP-1 overexpression(905.98±24.17)and knockdown(0.18±0.01)%, respectively, were successfully constructed.Based on CCK-8 detection results, knockdown of TIMP-1(86.56±7.98)% was able to promote the proliferation of H9c2 cells induced by levocarnitine( P<0.01). Apoptosis experiments showed that inhibition of TIMP-1 expression(23.22±2.69)significantly reduced the apoptosis level of H9c2 cells induced by levocarnitine( P<0.01). Migration experiments showed that inhibition of TIMP-1 expression(217.67±23.44)significantly promoted the migration ability of H9c2 cells induced by levocarnitine( P<0.01). Conclusions:After intervention to reduce TIMP-1 expression, levocarnitine can promote proliferation, inhibit apoptosis and promote migration of myofibroblasts and may therefore ameliorate myocardial fibrosis.

Objective:To observe any effect of cooling on the amplitude of vibration-induced sensory nerve action potentials (SNAPs) in human digits.Methods:The middle fingers of 15 healthy adults were either cooled to about 22℃ using an ice pack or kept at about 32℃. A vibrator was applied to the joint connecting the middle finger and the palm vibrating with an amplitude of 2mm at a frequency of 60Hz. The amplitudes of middle finger SNAPs before, during and right after the vibration were recorded.Results:The SNAP amplitude at a given temperature was lower during vibration than before it, but it immediately returned to the pre-vibration level after the vibration ceased. The middle finger SNAP amplitudes at 22℃ were significantly higher than those at 32℃ throughout. The decrease in amplitude at 32℃ (61.7±15.1%) was significantly greater than that at 22℃ (24.1±7.0%).Conclusions:Cooling significantly reduces the effect of vibration on the amplitude of digital SNAPs. That suggests a way to protect the sensory nerves in hand-arm vibration syndrome.

Objective: To investigate the changes of microorganisms and metabolites in joint effusion of patients with Rheumatoid arthritis(RA), Osteoarthritis(OA) and Urarthritis(UA). To provide new ideas for the study of the effect of microbiota on the pathogenesis of arthritis. Methods: Joint effusion samples were collected from 20 patients with RA, 20 patients with OA, and 20 patients with UA. 16S rRNA gene sequencing and untargeted ultra-high performance Liquid chromatography-mass spectrometry(LC-MS) were used to explore the differences in microorganisms and metabolites among the three groups. Pearson correlation analysis was used to detect the correlation between effusion microbiota and metabolites. Results: There were differences in microbial diversity and microbiota composition among the three groups. Combined with VIP>1 from OPLS-DA andP<0.05 from two-tailed Students t-test, 45 differential metabolites(Between RA and OA groups), 38 differential metabolites(Between UA and OA groups) and 16 differential metabolites(Between RA and UA groups), were identified. GO analysis and KEGG pathway analysis showed that the differential metabolic pathways among the three groups were mainly concentrated in citric acid cycle(TCA cycle), nucleotide metabolism, amino acid metabolism and glycolysis pathway. Correlation analysis of joint effusion microbiota and metabolites suggested that bacteria enriched in the three groups of joint effusion, such asPrevotella,Clostridium ruminosus,Prevotellaceae＿UCG-001, were related to many key metabolites such as lysozyme, uric acid, glucose, and L-glutamine. Conclusion This study shows that there are a variety of bacterial flora in joint cavity effusion of RA, OA, and UA patients, and the differential metabolites produced by them are involved in the pathogenesis of the three types of arthritis by affecting a variety of metabolic pathways.

Background Previous research on chlorinated paraffins (CPs) in fine particulate matter (PM_2.5) has predominantly focused on short- and medium-chain chlorinated paraffins (SCCPs and MCCPs), and few studies could simultaneously determine short-, medium-, and long-chain chlorinated paraffins (LCCPs). Simultaneous extraction and determination of SCCPs, MCCPs, and LCCPs in PM_2.5 could provide technical support for their environmental monitoring and human health risk assessment. Objective To establish a method based on QUEChERS pretreatment method in conjunction with ultra-performance liquid chromatography-quadrupole/orbitrap high resolution mass spectrometry for simultaneously determining the levels of SCCPs, MCCPs, and LCCPs in PM_2.5. Methods The extraction solvents, extraction salts, and extraction steps of a QuEChERS method were optimized. The extraction efficiencies of the target substances were compared under 4 extraction solvents [acetonitrile, dichloromethane, and n-hexane solvents in sequence; acetonitrile: dichloromethane: n-hexane = 1: 1: 2 (v/v/v) mixed solvent; 1% acetic acid-acetonitrile: dichloromethane: n-hexane = 1: 1: 1 (v/v/v) mixed solvent; acetonitrile: dichloromethane: n-hexane = 1: 1: 1 (v/v/v) mixed solvent], 2 dehydrated salts (anhydrous MgSO₄+NaCl and anhydrous Na₂SO₄+NaCl), 2 purification salts (C18 and PSA), and 4 vortex time (5, 7.5, 10, and 12.5 min) conditions. Then internal standard was utilized to estimate linear range and detection limit of the refined QuEChERS approach. Results The linearities of SCCPs, MCCPs, and LCCPs were good in the range of 10~1000 ng·mL⁻¹ with the correlation coefficients all greater than 0.96. The method detection limits (MDLs) ranged from 0.01 to 0.29 ng·m⁻³. The spiked recoveries of SCCPs, MCCPs, and LCCPs at the low, medium, and high concentrations were 77.38%-81.64%, 93.11%-99.78%, and 87.41%-101.39%, respectively, and the relative standard deviations (RSDs) were 2.90%-12.84%. This method was used to determine the CPs levels in 11 PM_2.5 samples from Shijiazhuang. The positive rates of ∑SCCPs, ∑MCCPs, and ∑LCCPs were all 100%, the concentration ranges were 0.24-2.18 ng·m⁻³ (mean 0.84 ng·m⁻³), 0.17-1.67 ng·m⁻³ (mean 0.70 ng·m⁻³), and 0.01-0.16 ng·m⁻³ (mean 0.04 ng·m⁻³), respectively, and the percentages to ΣCPs were 52.95%, 44.39%, and 2.66%, respectively. Conclusion The method established in this study is simple, time-saving, solvent saving, and can simultaneously detect SCCPs, MCCPs, and LCCPs in PM_2.5, which is suitable for the determination of PM_2.5 samples in large quantities, and can also provide a reference for the detection methods of other halogenated organic compounds in PM_2.5.

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.