Objective To compare and analyze the germicidal efficacy of continuous ultraviolet and pulsed ultravio-let(UV)lasers on pathogenic microorganisms.Methods Spore slides of Escherichia coli and Bacillus atrophaeus were irradiated using a 254 nm ultraviolet mercury lamp and UV laser.The carrier quantitative germicidal test was conducted to determine the disinfection efficacy at different irradiation doses.Results When the irradiation dose of the ultraviolet mercury lamp was 245.52 mJ/cm2,the logarithmic killing values of Escherichia coli and Bacillus atro-phaeus spores were 5.00 and 2.92,respectively,and the mean logarithmic killing doses were 49.10 and 84.08 mJ/cm2,respectively;When the UV laser irradiation doses were 208.39 and 206.80 mJ/cm2,the logarithmic killing values for the two microorganisms were 6.29 and 3.32,respectively,and the mean logarithmic killing doses were 33.13 and 62.29 mJ/cm2,respectively.Conclusion Compared with continuous UV radiation,pulsed UV laser has stron-ger penetration ability,better killing efficacy on pathogenic microorganisms at the same radiation dose,and can con-duct targeted disinfection and sterilization on the surface of objects directionally.

Hemodialysis patients exhibit compromised immune function and require long-term repeated vascular punctures as therapeutic approach,the risk of infection increases.Hospital-associated infection in hemodialysis de-partment(center)happens from time to time,which has already become a concern for the medical community,patients and social media.This paper outlines the task origin of China's"Standard for infection prevention and control in hemodialysis department(center)"(WS/T854-2025),the compilation basis and explanations for its key content,feasibility and implementation recommendations,as well as the clarifications on common issues encoun-tered during its promotion and enforcement.

Objective To observe the clinical and echocardiographic manifestations of Williams syndrome(WS).Methods Two children with WS were retrospectively enrolled,and 21 cases of WS in literature were reviewed,and clinical and echocardiographic manifestations of WS were observed.Results Clinical manifestations of 23 cases including 21 cases of"elf"face,8 cases of intellectual disability,7 cases of developmental delay,7 cases of inguinal hernia,6 cases of hypothyroidism,4 cases of hypercalcemia,3 cases of urinary system abnormalities(1 case of hydrocele,1 case of ureteral dilation and tortuosity,and 1 case of kidney stones),2 cases of behavioral abnormalities,2 cases of feeding difficulties,1 case of congenital hypertrophic pyloric stenosis,1 case of binocular esotropia,1 case of hyperbilirubinemia,and 1 case of corpus callosum dysplasia.Echocardiography showed cardiovascular malformations in all 23 cases,including 20 cases of supravalvular aortic stenosis(SVAS),18 cases of pulmonary artery stenosis(PAS)and 10 cases of other cardiovascular malformations.Conclusion WS presented multiple system abnormalities in clinic,and cardiovascular malformations,especially SVAS and PAS could often be detected with echocardiography.

Objective:To investigate the current application of blood purification in the treatment of acute poisoning within Jiangsu Province and to evaluate the impact of extracorporeal blood purification on the clinical outcomes of critically poisoned patients.Methods:This multicenter, cross-sectional real-world observational study followed patients presenting with poisoning to the emergency departments of nine hospitals in Jiangsu Province between June 2015 and May 2019. Data were collected on demographic characteristics, vital signs within the first hour of emergency presentation, treatment modalities, length of hospital stay, and survival outcomes. Clinical data from patients who underwent extracorporeal blood purification were compared with those who did not, using the Wilcoxon rank-sum test and Chi-square test.Results:A total of 4 178 poisoning cases were included between June 2015 and May 2019. Among them, 21.7% (908/4 178) received blood purification therapy, while 78.3% (3 270/4 178) did not. Hemoperfusion (90.4%) was the most frequently employed method, followed by continuous renal replacement therapy (CRRT) (4.4%). In combined blood purification modalities, 4.8% underwent hemoperfusion combined with CRRT, 0.1% received hemoperfusion with plasma exchange, and another 0.1% underwent hemoperfusion combined with both CRRT and plasma exchange. Among patients who underwent blood purification, pesticide poisoning was the most prevalent (76.3%), with the most common toxic agents being paraquat (23.7%), dichlorvos (8.7%), methamidophos (5.2%), omethoate (4.0%), and glyphosate (3.7%). Compared to the non-blood purification group, patients in the blood purification group were more likely to present within the first hour with a low Glasgow Coma Scale (GCS) score (3-8) (22.6% vs. 9.7%, P <0.05), low mean arterial pressure (8.0% vs. 3.2%, P <0.05), longer hospital stays [5(3,9) days vs. 2(1,4) days, P <0.05] and a higher in-hospital mortality rate (21.1% vs. 5.3%, P <0.05). Follow-up via telephone 28 days after discharge revealed a survival rate of 78.9%, with a mortality rate of 21.1% in the blood purification group. Conclusions:Hemoperfusion is the most commonly utilized blood purification technique for treating poisoning in Jiangsu Province, with pesticides being the primary toxic agents treated. Although the mortality rate is higher in the blood purification group, the intervention may still contribute to improved patient outcomes.

Objective To construct a machine learning algorithm using biomarkers to predict the risk of sepsis-induced respiratory tract infection in order to assist clinicians in making decisions.Methods Based on the diagnostic criteria of the research subjects,and the basic clinical data of the participants were collected.The data set was randomly split into a training set(80％)and a validation set(20％).Use feature filtering algorithms to select the best subset of variables from the training set,and use this subset to construct random forest(RF),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),Logistic regression(LR),ridge regression(Ridge),and support vector machine(SVM)classifiers.Then,evaluate the model's generalization ability using a validation dataset.Evaluate the performance of the model comprehensively through accuracy,precision,recall,and area under the curve.Results A total of 377 patients with sepsis-induced respiratory tract infection(case group)and 564 patients with respiratory tract infection(control group)were included,and 17 variables were found to be suitable for the initial model construction.Using feature screening algorithm,we found that the predictive performance of tree models(RF,XGboost,and AdaBoost)was better than that of linear models(LR,SVM,and Ridge).The AdaBoost model included 14 biomarkers,and its prediction accuracy was better than RF,XGBoost,LR,SVM,Ridge models,its precision,recall,accuracy and area under the curve were 0.90,0.84,91.75％and 0.950,respectively.The Ridge model had the worst prediction performance,with an accuracy of 82.97％,its precision,recall and area under the curve were 0.90,0.72 and 0.835 respectively.Conclusion In this study,six predictive models of sepsis-induced respiratory tract infection were developed,among which AdaBoost model could more accurately predict the risk of sepsis-induced respiratory tract infection and help to assist clinical decision-making.

Objective To observe the clinical and echocardiographic manifestations of Williams syndrome(WS).Methods Two children with WS were retrospectively enrolled,and 21 cases of WS in literature were reviewed,and clinical and echocardiographic manifestations of WS were observed.Results Clinical manifestations of 23 cases including 21 cases of"elf"face,8 cases of intellectual disability,7 cases of developmental delay,7 cases of inguinal hernia,6 cases of hypothyroidism,4 cases of hypercalcemia,3 cases of urinary system abnormalities(1 case of hydrocele,1 case of ureteral dilation and tortuosity,and 1 case of kidney stones),2 cases of behavioral abnormalities,2 cases of feeding difficulties,1 case of congenital hypertrophic pyloric stenosis,1 case of binocular esotropia,1 case of hyperbilirubinemia,and 1 case of corpus callosum dysplasia.Echocardiography showed cardiovascular malformations in all 23 cases,including 20 cases of supravalvular aortic stenosis(SVAS),18 cases of pulmonary artery stenosis(PAS)and 10 cases of other cardiovascular malformations.Conclusion WS presented multiple system abnormalities in clinic,and cardiovascular malformations,especially SVAS and PAS could often be detected with echocardiography.

Hemodialysis patients exhibit compromised immune function and require long-term repeated vascular punctures as therapeutic approach,the risk of infection increases.Hospital-associated infection in hemodialysis de-partment(center)happens from time to time,which has already become a concern for the medical community,patients and social media.This paper outlines the task origin of China's"Standard for infection prevention and control in hemodialysis department(center)"(WS/T854-2025),the compilation basis and explanations for its key content,feasibility and implementation recommendations,as well as the clarifications on common issues encoun-tered during its promotion and enforcement.

Objective To compare and analyze the germicidal efficacy of continuous ultraviolet and pulsed ultravio-let(UV)lasers on pathogenic microorganisms.Methods Spore slides of Escherichia coli and Bacillus atrophaeus were irradiated using a 254 nm ultraviolet mercury lamp and UV laser.The carrier quantitative germicidal test was conducted to determine the disinfection efficacy at different irradiation doses.Results When the irradiation dose of the ultraviolet mercury lamp was 245.52 mJ/cm2,the logarithmic killing values of Escherichia coli and Bacillus atro-phaeus spores were 5.00 and 2.92,respectively,and the mean logarithmic killing doses were 49.10 and 84.08 mJ/cm2,respectively;When the UV laser irradiation doses were 208.39 and 206.80 mJ/cm2,the logarithmic killing values for the two microorganisms were 6.29 and 3.32,respectively,and the mean logarithmic killing doses were 33.13 and 62.29 mJ/cm2,respectively.Conclusion Compared with continuous UV radiation,pulsed UV laser has stron-ger penetration ability,better killing efficacy on pathogenic microorganisms at the same radiation dose,and can con-duct targeted disinfection and sterilization on the surface of objects directionally.

Objective To construct a machine learning algorithm using biomarkers to predict the risk of sepsis-induced respiratory tract infection in order to assist clinicians in making decisions.Methods Based on the diagnostic criteria of the research subjects,and the basic clinical data of the participants were collected.The data set was randomly split into a training set(80％)and a validation set(20％).Use feature filtering algorithms to select the best subset of variables from the training set,and use this subset to construct random forest(RF),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),Logistic regression(LR),ridge regression(Ridge),and support vector machine(SVM)classifiers.Then,evaluate the model's generalization ability using a validation dataset.Evaluate the performance of the model comprehensively through accuracy,precision,recall,and area under the curve.Results A total of 377 patients with sepsis-induced respiratory tract infection(case group)and 564 patients with respiratory tract infection(control group)were included,and 17 variables were found to be suitable for the initial model construction.Using feature screening algorithm,we found that the predictive performance of tree models(RF,XGboost,and AdaBoost)was better than that of linear models(LR,SVM,and Ridge).The AdaBoost model included 14 biomarkers,and its prediction accuracy was better than RF,XGBoost,LR,SVM,Ridge models,its precision,recall,accuracy and area under the curve were 0.90,0.84,91.75％and 0.950,respectively.The Ridge model had the worst prediction performance,with an accuracy of 82.97％,its precision,recall and area under the curve were 0.90,0.72 and 0.835 respectively.Conclusion In this study,six predictive models of sepsis-induced respiratory tract infection were developed,among which AdaBoost model could more accurately predict the risk of sepsis-induced respiratory tract infection and help to assist clinical decision-making.

Objective: To analyze the characteristics of influenza virus detection in an influenza outbreak in schools, so as to provide a strategic basis for the treatment of influenza outbreaks in schools. Methods: A total of 1 702 samples were collected from 52 school influenza outbreaks reported in Linyi City in 2021-2022. The samples were divided into 3 types according to different symptoms during the management of the epidemic [group A:influenzalike illness (ILI) group; group B:mild illness group; group C:close contacts group]. Rt-PCR was used to detect influenza virus nucleic acid in the collected samples. The detection rate of influenza virus in the outbreaks was analyzed by χ2 test. Results: In total, 1 071 samples (62.93%) tested positive for influenza virus nucleic acid. Among them, 610 out of 726 samples (84.02%) were detected in group A, while 331 out of 634 samples (52.21%) were detected in group B. In group C, 130 out of 342 samples (38.01%) tested positive. The differences were statistically significant (χ2=260.71, P<0.01). In group A, males had a detection rate of 80.83% for influenza virus nucleic acid, compared to 91.36% for females. For group B, the rates were 53.31% for males and 50.87% for females. In group C, males had a rate of 30.72%, while females had a rate of 43.92%. Statistical significance for gender differences was observed only in groups A and C (χ2=12.67, 6.25, P<0.05). According to the days of onset, the detection rates of influenza virus nucleic acid among patients with onset 0-6 days were 56.30%, 74.49%, 89.35%, 86.23%, 69.67%, 62.75%, 34.33%, respectively, and the difference was statistically significant (χ2=128.27, P<0.01). Conclusions Mild cases and close contacts are likely key factors contributing to the prolonged emergence of new cases within classrooms during school influenza outbreaks. The progression of influenza symptoms is related to the risk of transmission.