Objective To establish methods for determining the leaching amount of bisphenol A monomer in metal coatings as one of the guidelines on metal materials and containers for drug packaging in the 2025 edition of the Pharmacopoeia of the People's Republic of China.Methods The formulation process of the method for determining the leaching amount of bisphenol A monomer in metal coatings was explained.Through the verification of the two analysis methods,the scientific and rational aspects of the method were examined,and the determination results of the leaching amount of bisphenol A monomer by high performance liquid chromatography(HPLC)and high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)were compared.Results HPLC was suitable for the detection of general routine samples and can obtain experimental results more efficiently;HPLC-MS/MS has higher sensitivity and selectivity,and is more suitable for the detection of trace bisphenol A in samples with complex substrates.Conclusion Enterprises and scientific research institutions can choose their own determination methods and formulate reasonable limits according to the actual situation of products and the configuration needs of daily testing instruments.

Traumatic supraorbital fissure syndrome (TSOFS) is a symptom complex caused by nerve entrapment in the supraorbital fissure after skull base trauma. If the compressed cranial nerve in the supraorbital fissure is not decompressed surgically, ptosis, diplopia and eye movement disorder may exist for a long time and seriously affect the patients′ quality of life. Since its overall incidence is not high, it is not familiarized with the majority of neurosurgeons and some TSOFS may be complicated with skull base vascular injury. If the supraorbital fissure surgery is performed without treatment of vascular injury, it may cause massive hemorrhage, and disability and even life-threatening in severe cases. At present, there is no consensus or guideline on the diagnosis and treatment of TSOFS that can be referred to both domestically and internationally. To improve the understanding of TSOFS among clinical physicians and establish standardized diagnosis and treatment plans, the Skull Base Trauma Group of the Neurorepair Professional Committee of the Chinese Medical Doctor Association, Neurotrauma Group of the Neurosurgery Branch of the Chinese Medical Association, Neurotrauma Group of the Traumatology Branch of the Chinese Medical Association, and Editorial Committee of Chinese Journal of Trauma organized relevant experts to formulate Chinese expert consensus on the diagnosis and treatment of traumatic supraorbital fissure syndrome ( version 2024) based on evidence of evidence-based medicine and clinical experience of diagnosis and treatment. This consensus puts forward 12 recommendations on the diagnosis, classification, treatment, efficacy evaluation and follow-up of TSOFS, aiming to provide references for neurosurgeons from hospitals of all levels to standardize the diagnosis and treatment of TSOFS.

Objective To collect data on imported malaria cases in Jiangsu Province from 2019 to 2023 after malaria elimination and to analyze the current epidemic situation and prevention and control measures of imported malaria, discussing future prevention and control strategies. Methods Malaria case information for Jiangsu Province from 2019 to 2023 was extracted and downloaded from the China Information System for Disease Control and Prevention (CISDCP) as well as the Jiangsu Provincial malaria epidemic database. Statistical analysis was conducted using Stata 12.0 and SPSS 16.0 software. Results From 2019 to 2023, a total of 534 cases of malaria were directly reported online in Jiangsu Province, with annual cases numbering 244, 90, 32, 36, and 132 respectively, all being laboratory-confirmed imported malaria cases from abroad. During the COVID-19 pandemic from 2020 to 2022, the number of imported malaria cases significantly decreased, with several months reporting zero cases. Among the 534 malaria cases, the vast majority were individuals who had traveled to countries in sub-Saharan Africa and Southeast Asia for work, business, international studies, or tourism. Over the five years, the median, minimum, and maximum days for patients from onset of illness to health-seeking were 1(0,12), 1(0,8), 0(0,6), 0(0,10), and 1(0,18) days, with a statistically significant difference in health-seeking time among patients (Fisher's exact test, P=0.03). Over the past three years of the COVID-19 pandemic, compared to outside centralized isolation stations, malaria cases within centralized isolation stations were diagnosed in a shorter time (Fisher exact test, P=0.007). A total of 24 severe malaria cases were reported, with no deaths, including 23 cases of P. falciparum and 1 case of P. ovale. Conclusions After the elimination of malaria, imported malaria cases in Jiangsu Province have sharply decreased due to the impact of the COVID-19 pandemic. Malaria cases in centralized isolation stations (CIS) for COVID-19 control of Jiangsu Province are more likely to be promptly diagnosed, and the timeliness from onset to health-seeking among malaria patients returning from high-malaria areas improved. As COVID-19 prevention and control policies adjusted, there has been a sharp increase in imported malaria cases in 2023. It's still necessary to strengthen measures for malaria prevention and control and maintain the capacity to prevent malaria re-transmission in Jiangsu Province.

Objective:Establish a method for measuring the surface wettability of metal material coatings.Methods:The wettability of the inner surface of metal can coating was measured by standard static contact angle goniometer and Dyne pen.Results:Dyne pen analysis method is simple and effective,and can know the result quickly.The contact angle goniometer has higher measurement accuracy,and can more accurately obtain the wetta-bility of metal material coating surface.Conclusion:Standard static contact angle goniometer and Dyne pen can be used to determine the wettability of metal coating surface,and improve the reference for the determination of the wettability of metal coating surface.

Objective:Establish a method for measuring the surface wettability of metal material coatings.Methods:The wettability of the inner surface of metal can coating was measured by standard static contact angle goniometer and Dyne pen.Results:Dyne pen analysis method is simple and effective,and can know the result quickly.The contact angle goniometer has higher measurement accuracy,and can more accurately obtain the wetta-bility of metal material coating surface.Conclusion:Standard static contact angle goniometer and Dyne pen can be used to determine the wettability of metal coating surface,and improve the reference for the determination of the wettability of metal coating surface.

Objective To develop an evidence-based,localized practice protocol for the interhospital transfer of critically ill children.Methods Through a comprehensive evidence summary and semi-structured interviews,a preliminary inter-hospital transfer practice protocol for critically ill children was formulated.A panel of 31 experts from 12 hospitals in China participated in 2 rounds of expert correspondence between May and July 2022,facilitating meticulous revision of the protocol entries.Results The response rate for both rounds of questionnaires was 100%,and the expert authority coefficients ranged from 0.926 to 0.931.In the second round of consultation,the coefficient of variation for the importance score of each entry ranged from 0.036 to 0.226,and the Kendall's W was determined to be 0.201(P＜0.001).Additionally,the coefficient of variation for the feasibility score of each entry fell within the range of 0.070 to 0.314,with Kendall's W of 0.124(P＜0.001).Ultimately,the final interhospital transfer protocol for critically ill children comprised 8 level Ⅰ entries,16 level Ⅱ entries,and 75 level Ⅲ entries.Conclusion The interhospital transfer protocol constructed in this study is grounded in scientific evidence and exhibits practical feasibility.It serves as a valuable reference for organizing and implementing interhospital transfers of critically ill children.

Objective To create risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on machine learning algorithms, so as to provide insights into early identification of imported malaria cases in Jiangsu Province. Methods Case investigation, first symptoms and time of initial diagnosis of imported malaria patients in Jiangsu Province in 2019 were captured from Infectious Disease Report Information Management System and Parasitic Disease Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention. The risk predictive models of healthcare-seeking delay among imported malaria patients were created with the back propagation (BP) neural network model, logistic regression model, random forest model and Bayesian model using thirteen factors as independent variables, including occupation, species of malaria parasite, main clinical manifestations, presence of complications, severity of disease, age, duration of residing abroad, frequency of malaria parasite infections abroad, incubation period, level of institution at initial diagnosis, country of origin, number of individuals travelling with patients and way to go abroad, and time of healthcare-seeking delay as a dependent variable. Logistic regression model was visualized using a nomogram, and the nomogram was evaluated using calibration curves. In addition, the efficiency of the four models for prediction of risk of healthcare-seeking delay among imported malaria patients was evaluated using the area under curve (AUC) of receiver operating characteristic curve (ROC). The importance of each characteristic was quantified and attributed by using SHAP to examine the positive and negative effects of the value of each characteristic on the predictive efficiency. Results A total of 244 imported malaria patients were enrolled, including 100 cases (40.98%) with the duration from onset of first symptoms to time of initial diagnosis that exceeded 24 hours. Logistic regression analysis identified a history of malaria parasite infection [odds ratio (OR) = 3.075, 95% confidential interval (CI): (1.597, 5.923)], long incubation period [OR = 1.010, 95% CI: (1.001, 1.018)] and seeking healthcare in provincial or municipal medical facilities [OR = 12.550, 95% CI: (1.158, 135.963)] as risk factors for delay in seeking healthcare among imported malaria cases. BP neural network modeling showed that duration of residing abroad, incubation period and age posed great impacts on delay in healthcare-seek among imported malaria patients. Random forest modeling showed that the top five factors with the greatest impact on healthcare-seeking delay included main clinical manifestations, the way to go abroad, incubation period, duration of residing abroad and age among imported malaria patients, and Bayesian modeling revealed that the top five factors affecting healthcare-seeking delay among imported malaria patients included level of institutions at initial diagnosis, age, country of origin, history of malaria parasite infection and individuals travelling with imported malaria patients. ROC curve analysis showed higher overall performance of the BP neural network model and the logistic regression model for prediction of the risk of healthcare-seeking delay among imported malaria patients (Z = 2.700 to 4.641, all P values < 0.01), with no statistically significant difference in the AUC among four models (Z = 1.209, P > 0.05). The sensitivity (71.00%) and Youden index (43.92%) of the logistic regression model was higher than those of the BP neural network (63.00% and 36.61%, respectively), and the specificity of the BP neural network model (73.61%) was higher than that of the logistic regression model (72.92%). Conclusions Imported malaria cases with long duration of residing abroad, a history of malaria parasite infection, long incubation period, advanced age and seeking healthcare in provincial or municipal medical institutions have a high likelihood of delay in healthcare-seeking in Jiangsu Province. The models created based on the logistic regression and BP neural network show a high efficiency for prediction of the risk of healthcare-seeking among imported malaria patients in Jiangsu Province, which may provide insights into health management of imported malaria patients.