Objective To investigate the distribution of carbapenem-resistant genes and their drug susceptibility in vitro on carbapen-em-resistant Enterobacter cloacae(CRECC)in Taizhou area,and provide evidence for effective anti-infective treatment in clinical prac-tice.Methods Forty-seven strains of CRECC isolated from Enze Hospital,Taizhou Enze Medical Center(Group)and Luqiao Reha-bilitation Hospital during January 2015 and November 2022 were retrospectively analyzed.The enzyme types and resistance genes of carbapenemase were detected by the NG-Test Carba 5 and Carba-R Xpert,respectively,and the susceptibility of CERCC to common drugs was tested in vitro.Results Among 47 strains of CRECC,27 were detected to produce carbapenemase,including 24 producing New Delhi metallo-β-lactamase(NDM)type,1 producing both Klebsiella pneumoniae carbapenemase(KPC)and NDM types,and 2 producing imipenemase(IMP)type.One strain belonged to NDM genotype but no NDM enzyme type was detected.The CRECC strains had the highest sensitivity to polymyxin B(95.7%),followed by tigecycline(93.6%),fosfomycin(61.7%),and ceftazidime/avibac-tam(40.4%).In addition,the CRECC strains producing carbapenemase were more sensitive to polymyxin B,fosfomycin and aztreo-nam than those without producing carbapenemase.Conclusion The CRECC strains in Taizhou area are mainly NDM type,which has high sensitivity to polycolistin B,tigecycline and fosfomycin.NG-Test Carba 5 can not cover some strains that do not produce carbapen-emase or carry mutations in carbapenemase.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.

Prostate cancer is the most prevalent malignant tumor among men, ranking first in incidence and second in mortality globally. Novel hormone therapies (NHT) targeting the androgen receptor (AR) pathway have become the standard of care for metastatic prostate cancer. This review offers a comprehensive overview of NHT, including abiraterone, enzalutamide, apalutamide, darolutamide, and rezvilutamide, which have demonstrated efficacy in delaying disease progression and improving patient survival and quality of life. Nevertheless, resistance to NHT remains a critical challenge. The mechanisms underlying resistance are complex, involving AR gene amplification, mutations, splice variants, increased intratumoral androgens, and AR-independent pathways such as the glucocorticoid receptor, neuroendocrine differentiation, DNA repair defects, autophagy, immune evasion, and activation of alternative signaling pathways. This review discusses these resistance mechanisms and examines strategies to counteract them, including sequential treatment with novel AR-targeted drugs, chemotherapy, poly ADP-ribose polymerase inhibitors, radionuclide therapy, bipolar androgen therapy, and approaches targeting specific resistance pathways. Future research should prioritize elucidating the molecular basis of NHT resistance, optimizing existing therapeutic strategies, and developing more effective combination regimens. Additionally, advanced sequencing technologies and resistance research models should be leveraged to identify novel therapeutic targets and improve drug delivery efficiencies. These advancements hold the potential to overcome NHT resistance and significantly enhance the management and prognosis of patients with advanced prostate cancer.

Objective:To establish a prediction model for larger for gestational age(LGA)infants in pregnant women with gestational diabetes mellitus(GDM)in order to improve pregnancy outcomes.Methods:A retro-spective analysis was performed on the clinical data of 338 pregnant women with GDM who underwent routine prenatal examinations and were hospitalized for delivery in the First Affiliated Hospital of Nanjing Medical Universi-ty from January 1,2018 to December 31,2023.Pregnant women with complete HbAlc data during pregnancy were divided into a training set of 241 cases and a validation set of 97 cases.Lasso and Logistic regression analysis and variable screening combined with previous clinical experience were used to construct a nomogram model,and its degree of differentiation and calibration were evaluated.Result:①By Lasso regression analysis,age,family histo-ry of type 2 diabetes,body mass index(BMI),gestational weight gain(GWG),fasting blood glucose(FBG),postprandial 1-hour blood glucose(1h PBG),HbAlc,free triiodothyronine(FT3),free thyroxine(FT4)and insulin treatment were important predictors of LGA.②Multivariate Logistic regression analysis showed that GWG and HbAlc were independent risk factors for LGA in pregnant women with GDM(OR＞1,P＜0.05).③Combined with Lasso and Logistic regression analysis,previous literature reports and clinical experience,BMI,GWG,FBG,1h PBG,HbAlc and FT3 were selected as independent variables,and LGA as dependent variable.A nomogram pre-diction model was constructed in the training set,and the C-index of 0.71.ROC curve analysis showed that the AUC values of the training set and the validation set were 0.709 and 0.700,respectively,and the discriminative a-bility of the model was acceptable.The calibration curve of the model was close to the ideal curve,and the clinical decision curve suggested that the model showed a positive net benefit at the threshold of 10％to 50％.Conclu-sion:The predictive model has certain value in predicting the occurrence of LGA in pregnant women with GDM,and provides help for early diagnosis,treatment and clinical intervention of GDM and its complications,in order to improve perinatal and long-term adverse outcomes.

Objective To investigate the distribution of carbapenem-resistant genes and their drug susceptibility in vitro on carbapen-em-resistant Enterobacter cloacae(CRECC)in Taizhou area,and provide evidence for effective anti-infective treatment in clinical prac-tice.Methods Forty-seven strains of CRECC isolated from Enze Hospital,Taizhou Enze Medical Center(Group)and Luqiao Reha-bilitation Hospital during January 2015 and November 2022 were retrospectively analyzed.The enzyme types and resistance genes of carbapenemase were detected by the NG-Test Carba 5 and Carba-R Xpert,respectively,and the susceptibility of CERCC to common drugs was tested in vitro.Results Among 47 strains of CRECC,27 were detected to produce carbapenemase,including 24 producing New Delhi metallo-β-lactamase(NDM)type,1 producing both Klebsiella pneumoniae carbapenemase(KPC)and NDM types,and 2 producing imipenemase(IMP)type.One strain belonged to NDM genotype but no NDM enzyme type was detected.The CRECC strains had the highest sensitivity to polymyxin B(95.7%),followed by tigecycline(93.6%),fosfomycin(61.7%),and ceftazidime/avibac-tam(40.4%).In addition,the CRECC strains producing carbapenemase were more sensitive to polymyxin B,fosfomycin and aztreo-nam than those without producing carbapenemase.Conclusion The CRECC strains in Taizhou area are mainly NDM type,which has high sensitivity to polycolistin B,tigecycline and fosfomycin.NG-Test Carba 5 can not cover some strains that do not produce carbapen-emase or carry mutations in carbapenemase.

Objective:To establish a prediction model for larger for gestational age(LGA)infants in pregnant women with gestational diabetes mellitus(GDM)in order to improve pregnancy outcomes.Methods:A retro-spective analysis was performed on the clinical data of 338 pregnant women with GDM who underwent routine prenatal examinations and were hospitalized for delivery in the First Affiliated Hospital of Nanjing Medical Universi-ty from January 1,2018 to December 31,2023.Pregnant women with complete HbAlc data during pregnancy were divided into a training set of 241 cases and a validation set of 97 cases.Lasso and Logistic regression analysis and variable screening combined with previous clinical experience were used to construct a nomogram model,and its degree of differentiation and calibration were evaluated.Result:①By Lasso regression analysis,age,family histo-ry of type 2 diabetes,body mass index(BMI),gestational weight gain(GWG),fasting blood glucose(FBG),postprandial 1-hour blood glucose(1h PBG),HbAlc,free triiodothyronine(FT3),free thyroxine(FT4)and insulin treatment were important predictors of LGA.②Multivariate Logistic regression analysis showed that GWG and HbAlc were independent risk factors for LGA in pregnant women with GDM(OR＞1,P＜0.05).③Combined with Lasso and Logistic regression analysis,previous literature reports and clinical experience,BMI,GWG,FBG,1h PBG,HbAlc and FT3 were selected as independent variables,and LGA as dependent variable.A nomogram pre-diction model was constructed in the training set,and the C-index of 0.71.ROC curve analysis showed that the AUC values of the training set and the validation set were 0.709 and 0.700,respectively,and the discriminative a-bility of the model was acceptable.The calibration curve of the model was close to the ideal curve,and the clinical decision curve suggested that the model showed a positive net benefit at the threshold of 10％to 50％.Conclu-sion:The predictive model has certain value in predicting the occurrence of LGA in pregnant women with GDM,and provides help for early diagnosis,treatment and clinical intervention of GDM and its complications,in order to improve perinatal and long-term adverse outcomes.

Objective:To comprehensively evaluate the performance of the iterative cone beam CT (iCBCT) imaging mode of Varian linear accelerators and to explore its specific advantages in clinical application.Methods:The kV cone beam CT (CBCT) imaging systems of Halcyon 2.0, Edge, and VitalBeam linear accelerators from Tianjin Medical University Cancer Institute & Hospital were selected, among which Halcyon 2.0 and Edge were equipped with the iCBCT imaging mode. The Penta-Guide phantom was used to evaluate the registration accuracy of iCBCT imaging modes. The accuracy of treatment couch position was measured by a ruler. The image quality of the iCBCT and conventional CBCT modes of various imaging devices were analyzed using the CatPhan604 phantom. The imaging beam-on time and reconstruction time were measured to assess image acquisition efficiency. The uniformity, spatial resolution, contrast, contrast-to-noise ratio (CNR), image acquisition time and reconstruction time between two imaging modes were statistically analyzed by t-test. Results:The maximum deviations of image registration measurement results of the iCBCT mode for Halcyon 2.0 and Edge accelerators compared to the standard values were 0.7 mm and 0.6 mm, respectively. The treatment couch position error of all devices was less than 1 mm. The iCBCT images under head scanning protocol primarily improved the uniformity and CNR. Compared to conventional CBCT images, Halcyon iCBCT increased the uniformity and CNR by 2.50% ( P<0.001) and 78.85% ( P<0.001), respectively, while Edge increased them by 2.18% ( P<0.001) and 86.42% ( P<0.001), both superior to VitalBeam CBCT images. Under pelvis scanning protocols, iCBCT images primarily improved the CNR compared to conventional CBCT images. Halcyon and Edge iCBCT increased the CNR by 113.57% ( P<0.001) and 133.87% ( P<0.001), respectively, both superior to VitalBeam CBCT images. In terms of image acquisition efficiency, the average reconstruction times for Halcyon and Edge iCBCT images increased by 7.28 s and 15.53 s, respectively, and the total image acquisition time of Halcyon accelerator was the shortest. Conclusions:While ensuring the registration accuracy, iCBCT imaging mode can significantly improve the CNR of images and improve the uniformity of images under head scanning protocol. The Halcyon imaging system can enhance image acquisition efficiency.

Objective To investigate and analyze the impact of three personalized surgical design schemes for SPT trans PRK on postoperative visual quality and higher-order aberrations in individuals with myopic astigma-tism,aiming to provide a foundation for more rational selection of personalized design schemes.Methods The 96 cases(96 eyes)with myopic astigmatism were divided into three groups based on three personalized design schemes and a conventional mode.Specifically,24 eyes were assigned to the personalized group 1,which focused on coma elimination;another 24 eyes belonged to personalized group 2,where the aim was to minimize spherical aberration elimination;and the remaining 24 eyes were further categorized into personalized group 3 based on a model that aimed at minimizing spherical aberration.Additionally,there were also 24 eyes in the control group treated using the conventional mode.The study compared and analyzed various parameters including best corrected visual acuity,spherical aberration,coma,total higher-order aberration of the anterior corneal surface,as well as differences in corneal ablation thickness between personalized and conventional schemes within the surgical design software.Results(1)The postoperative visual acuity of the personalized group was significantly superior to that of the control group(P＜0.05);(2)Among the personalized groups,Group 2 exhibited a reduced amount of cor-neal tissue ablation compared to other groups(P＜0.01);(3)Group 2 demonstrated lower values than the other groups after surgery(P＜0.05).(4)Coma:The control group showed a significantly higher level of coma com-pared to preoperative measurements(P＜0.01).No significant differences were observed between Groups 1,2,and 3 after surgery(P＞0.05).(5)Total higher-order aberrations:All groups experienced a significant increase in total higher-order aberrations following surgery(P＜0.01).Group 2 exhibited lower values than the other groups postoperatively(P＜0.05).Conclusion For myopic astigmatism,SPT trans PRK incorporates the personalized surgical scheme with a focus on minimizing spherical aberration elimination mode,resulting in enhanced optimiza-tion of postoperative high-order aberration and improved visual quality,while preserving corneal tissue.

Objective To investigate and analyze the impact of three personalized surgical design schemes for SPT trans PRK on postoperative visual quality and higher-order aberrations in individuals with myopic astigma-tism,aiming to provide a foundation for more rational selection of personalized design schemes.Methods The 96 cases(96 eyes)with myopic astigmatism were divided into three groups based on three personalized design schemes and a conventional mode.Specifically,24 eyes were assigned to the personalized group 1,which focused on coma elimination;another 24 eyes belonged to personalized group 2,where the aim was to minimize spherical aberration elimination;and the remaining 24 eyes were further categorized into personalized group 3 based on a model that aimed at minimizing spherical aberration.Additionally,there were also 24 eyes in the control group treated using the conventional mode.The study compared and analyzed various parameters including best corrected visual acuity,spherical aberration,coma,total higher-order aberration of the anterior corneal surface,as well as differences in corneal ablation thickness between personalized and conventional schemes within the surgical design software.Results(1)The postoperative visual acuity of the personalized group was significantly superior to that of the control group(P＜0.05);(2)Among the personalized groups,Group 2 exhibited a reduced amount of cor-neal tissue ablation compared to other groups(P＜0.01);(3)Group 2 demonstrated lower values than the other groups after surgery(P＜0.05).(4)Coma:The control group showed a significantly higher level of coma com-pared to preoperative measurements(P＜0.01).No significant differences were observed between Groups 1,2,and 3 after surgery(P＞0.05).(5)Total higher-order aberrations:All groups experienced a significant increase in total higher-order aberrations following surgery(P＜0.01).Group 2 exhibited lower values than the other groups postoperatively(P＜0.05).Conclusion For myopic astigmatism,SPT trans PRK incorporates the personalized surgical scheme with a focus on minimizing spherical aberration elimination mode,resulting in enhanced optimiza-tion of postoperative high-order aberration and improved visual quality,while preserving corneal tissue.

Objective:To explore the safety of azivudine tablets in the treatment of moderate coronavirus disease 2019 (COVID-19).Methods:Clinical data of adult COVID-19 patients who were hospitalized and treated with azivudine tablets at Xinglin Branch, the First Affiliated Hospital of Xiamen University from August 18 to September 18, 2022 were collected. The incidence, clinical manifestations, severity, and outcome of adverse reactions during treatment were analyzed descriptively and statistically.Results:A total of 117 patients were entered in the analysis, including 68 males (58.1%) and 49 females (41.9%); the age ranged from 18 to 76 years, with a median age of 44 years. The course of COVID-19 before taking azivudine tablets ranged from 2 to 25 days, with an average time of 13 days. Azivudine tablets were applicated for 2-14 days with an average time of 8 days. Among 117 patients, 10 patients (8.5%) had adverse reactions during taking azivudine tablets, including 5 patients with gastrointestinal reactions (2 had nausea, 2 had diarrhea, and 1 had abdominal distension), 2 patients with liver dysfunction and 2 patients with dizziness, 1 patient with elevated serum triglyceride level, and 1 with fatigue. Of them, one patient had 2 times of adverse reactions, which manifested as dizziness and abdominal distension. All patients recovered after discontinuation of azivudine tablets and/or symptomatic treatments. The severity of adverse reactions was grade 1 in 7 patients and grade 2 in 3 patients, and no grade 3 and above serious adverse reactions occurred. All adverse reactions observed in the study had been recorded in the drug label, and no new adverse reactions were found.Conclusions:Azivudine tablets is safe and well tolerated in the treatment of moderate COVID-19. The common adverse reactions were gastrointestinal reactions, abnormal liver function, and dizziness.