Objective To investigate the differences in clinical and radiographic features between severe influenza A H1N1 and H3N2 in children.Methods The clinical and radiographic data of children diagnosed with severe influenza A H1N1 and H3N2 were analyzed retrospectively.According to the pathogen subtypes,they were divided into H1N1 group(34 cases)and H3N2 group(23 cases).Differences in clinical data,laboratory results,treatment,hospitalization time,outcome,and radiographic features between the two groups were analyzed.The t-test was used for the comparison of normally distributed measurement data between the groups,and Mann-Whitney U test was used for the comparison of non-normally distributed measurement data between the groups.Chi-square test or Fisher's exact probability method was used for the analysis of counting data,depending on the situation.Results There were differences in the season of onset,clinical and radiographic features between the two groups.H1N1 subtype mostly occurred in win-ter,and mainly manifested as respiratory symptoms(wheezing/shortness of breath)and respiratory complications(severe pneumonia).H3N2 subtype was mainly observed in summer,and more likely to involve the central nervous system(CNS),presenting with neuro-logical symptoms(convulsions),abnormal electroencephalogram,and concurrent influenza associated encephalopathy(IAE).Conclusion There are significant differences in epidemiology,clinical and radiographic features between severe influenza A H1N1 and H3N2.H3N2 has a higher probability of concurrent IAE and should be highly vigilant in clinical practice.

Objective:To analyze the MRI features of medulloblastoma (MB) in children, and screen out the key signs that can predict the risk of MB before surgery.Methods:Clinical and radiological data of 62 children with MB confirmed by pathology in Shenzhen Children′s Hospital from December 2012 to December 2021 were retrospectively analyzed. According to the diagnosis and treatment guidelines for children with MB (2021 edition), the patients were divided into standard risk group (43 cases) and high risk group (19 cases). MRI features of MB were observed and recorded, including tumor site, location of tumor center, tumor morphology, signal intensity of T 1WI, T 2WI and diffusion weighted imaging (DWI), enhancement pattern, cystic lesion size, location and number, peritumoral edema and hydrocephalus, and the maximum diameter of tumor was measured. The χ 2 test or Fisher exact probability method was used to compare the differences in age, gender and MRI signs between the two groups. The t test of two independent samples was used to compare the differences in the maximum diameter of tumors between the two groups. The indicators with statistically significant differences were included in binary logistic regression analysis to obtain independent influencing factors associated with the risk groups. The receiver operation characteristic curve was used to evaluate the diagnostic efficacy. Results:There were significant differences in age ( P=0.026), enhancement pattern ( P=0.018), cystic lesion size ( P=0.005), location ( P=0.011) and number ( P=0.003) between standard risk group and high risk group. There were no significant differences in gender, tumor site, location of tumor center, tumor morphology, signal intensity of T 1WI, T 2WI and DWI, peritumoral edema, hydrocephalus and maximum diameter of tumor between the two groups ( P>0.05). Binary logistic regression results showed the age (OR=0.207, 95%CI 0.040-0.983, P=0.042) and the number of cystic lesions (OR=0.215, 95%CI 0.073-0.630, P=0.005) were the protective factors for MB in high risk group, the enhancement pattern Ⅲ (OR=5.226, 95%CI 1.516-52.920, P=0.048) was the dangerous factor for MB in high risk group. The area under the curve of the combined diagnosis of high risk MB was 0.845 (95%CI 0.741-0.949). Conclusions:The age and MRI signs the pattern of tumor enhancement Ⅲ and the number of cystic lesion can be used to predict the risk grouping of MB preoperatively. When the child is younger and MB enhancement pattern is mainly peripheral enhancement without obvious cystic change, it may indicate high risk MB.

Objective:Based on the perspective of supply and demand balance, to analyze the implementation effects of primary-feature medical services measures in medical alliances.Methods:From July to September 2019, two regions with different levels of economic development were chosen, and from each region one leading hospital and two community health service centers/township hospitals were selected from its medical alliance. A total of 213 medical staff and 703 residents were surveyed, to learn their awareness and performance appraisal of these feature services.Frequency and proportion were calculated in a descriptive statistical analysis. The scores of the performance appraisal of both supply and demand sides were tested by independent sample t. Results:In the performance appraisal of such measures, the average scoring by medical staff was 4.39±0.07, and that by residents was 3.85±0.06; the residents were more concerned with service capabilities and contents, while medical staff were more concerned with service content and delivery mode; supply and demand sides were found with consensus in terms of improving the medical service quality of chronic diseases in primary level and service accessibility.Conclusions:The county-level medical alliances should focus on enhancing their capacity of primary medical services, and improving their primary service mode with the help of medical insurance institutions. Meanwhile, it is imperative to optimize the primary medical service policy in view of supply and demand balance.

Ensuring food safety is paramount worldwide.Developing effective detection methods to ensure food safety can be challenging owing to trace hazards,long detection time,and resource-poor sites,in addition to the matrix effects of food.Personal glucose meter(PGM),a classic point-of-care testing device,possesses unique application advantages,demonstrating promise in food safety.Currently,many studies have used PGM-based biosensors and signal amplification technologies to achieve sensitive and specific detection of food hazards.Signal amplification technologies have the potential to greatly improve the analytical performance and integration of PGMs with biosensors,which is crucial for solving the challenges associated with the use of PGMs for food safety analysis.This review introduces the basic detection principle of a PGM-based sensing strategy,which consists of three key factors:target recog-nition,signal transduction,and signal output.Representative studies of existing PGM-based sensing strategies combined with various signal amplification technologies(nanomaterial-loaded multienzyme labeling,nucleic acid reaction,DNAzyme catalysis,responsive nanomaterial encapsulation,and others)in the field of food safety detection are reviewed.Future perspectives and potential opportunities and challenges associated with PGMs in the field of food safety are discussed.Despite the need for complex sample preparation and the lack of standardization in the field,using PGMs in combination with signal amplification technology shows promise as a rapid and cost-effective method for food safety hazard analysis.