ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

Objective:To establish a stable rat model of sequelae of pelvic inflammatory disease(SPID)with clinical characteristics,and to provide a reliable experimental model for the study of the pharmcological effect and mechanism of SPID.Methods:Twenty-four 7-week-old SD rats were divided into sham operation group,model-A(108 cfu/mL mixed bacterial solution,0.2 mL),model-B(109 cfu/mL mixed bacterial solution 0.2 mL),and model-C(108 cfu/mL E.coli 0.2 mL).The weight of the rat's uterine was weighed and the uterine index was calculated.The automatic hematology analyzer was used to detect the blood routine;hematoxylin-eosin staining(HE)and masson staining were used to detect uterine pathlogical changes in rats.Enzyme-linked immunosorbent assay(ELISA)was used to detect interleukin-1β(IL-1β),interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in rat uterine tissue homogenates.Western blot was used to detect the expression of proteins related to NF-κB signaling pathway.Results:Compared with the sham operation group,the uterine index of model-A,model-B,and model-C were significantly increased(P＜0.05,P＜0.01).The levels of WBC and NE in the model-A increased significantly(P＜0.01).The level of LY in model-B decreased significantly(P＜0.01).The levels of IL-1β,TNF-α in model-A,model-B,and model-C were significantly increased(P＜0.01).The levels of IL-6 in model-A and model-B were significantly increased(P＜0.05,P＜0.01).The collagen volume fraction of model-A and model-B were significantly increased(P＜0.01).Mechanism study indicates that the expression levels of p-IKKβ/IKKβ,p-IκBα/IκBα and p-p65/p65 in model-A were significantly increased(P＜0.01),and the expression levels of IκBα/β-actin were significantly decreased(P＜0.01).The expression level of p-IKKβ/IKKβ in model-B was significantly increased(P＜0.01).Conclusions:A stable rat model of SPID that conforms to clinical characteristics can be successfully constructed by combining 0.2 mL of mixed bacterial solution with a concentration of 108 cfu/mL and mechanical injury.This modeling method intervened in the expression of the NF-κB inflammatory signaling pathway.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Objective To investigate application value of three-dimensional light sheet microscopy imaging for evaluating intraplaque neovascularization in arterial plaques and the efficacy of intervention,and to assess the effect of melatonin(MLT)on neovascularization by these means.Methods Thirty-six ApoE-/-model mice were randomly divided into three groups(n=12):vehicle group,MLT group,and MLT+GW9662 intervention group(MLT+GW).The mice were treated with vehicle,MLT alone,or MLT combined with peroxisome proliferator activated receptor-γ(PPARγ)inhibitor GW9662,respectively.The carotid arteries of the models were three-dimensionally imaged using a light sheet microscopy,and the length,volume and other indicators of neovascularization were quantitatively analyzed using Imaris software.Subsequently,CD31 immunohistochemical staining was performed for verification.Results The light sheet microscopy preliminarily achieved the three-dimensional visualization of intraplaque neovascularization,and its structure was observed to be three-dimensionally reticular and scattered.The results of Imaris quantitative analysis showed that,compared with vehicle group,the total intraplaque neovas cularization length in the MLT group was shortened[(15.79±12.90)mm vs.(33.42±11.16)mm,P<0.05],the total volume was reduced[(1.34±1.47)×10-3 mm3 vs.(13.44±7.35)×10-3 mm3,P<0.05],and the volume ratio was decreased(0.44%±0.47%vs.3.76%±1.74%,P<0.05).The above indicators in MLT+GW group were significantly increased compared with those in MLT group[total length:(35.31±4.69)mm,total volume:(8.87±3.46)×10-3 mm3,volume ratio:2.89%±0.38%;P<0.05].The CD31 immunohistochemical staining also supported the above findings(P<0.05).Conclusions Based on the light sheet microscopy imaging technology,the three-dimensional visualization and quantitative analysis of intraplaque neovascularization were preliminarily realized.It was found that MLT could reduce the overall burden of intraplaque neovascularization,and PPARγ might be involved in its regulatory process.

Prostate-specific membrane antigen(PSMA)positron emission tomography(PET)is currently a precise diagnostic imaging technology for prostate cancer(PCa).Artificial intelligence(AI)technologies,particularly machine learning and deep learning algorithms,when combined with PSMA PET,showed extensive potential applications in various aspects of PCa management.These include the diagnosis and differential diagnosis of primary tumors,staging,recurrence detection,and treatment planning for PCa.At present,a few AI models have received clinical approval.This paper reviews the application progress of AI combined with PSMA PET in the diagnosis and treatment of PCa,explores the current limitations of AI technologies in clinical practice,and aim to provide references to future diagnosis and treatment studies for PCa.

Objective To analyze the prognosis of patients with sepsis-related liver injury(SRLI)and establish a prediction model for the occurrence of SRLI after ICU admission in sepsis patients u-sing eight machine learning methods.Methods Patients who met the sepsis diagnostic criteria and had no underlying liver or biliary diseases were included from the MIMIC-Ⅳ database,and were clas-sified into SRLI and non-SRLI groups based on liver enzymes ≥ 5 times the upper limit of normal(ULN)or bilirubin ≥2.Omg/dL.Chi-square test,multivariate Logistic regression analysis,and pro-pensity score matching were used to analyze the mortality risk between the two groups.Eight machine learning algorithms[Logistic regression,classification and regression tree(CART),random forest(RF),support vector machine(SVM),K-nearest neighbors(K-NN),naive Bayes method(NBM),extreme gradient boosting(XGBoost),and gradient boosting decision tree(GBDT)]were employed to construct and validate the SRLI prediction model.Results The chi-square test(P＜0.001),multivariate Logistic regression analysis(P＜0.05),and log-rank test after propensity score matching(P＜0.05)all indicated that SRLI increased the mortality risk of patients.Among the SRLI prediction models,RF algorithm had the highest area under the curve(AUC),with its value of 0.866,followed by GBDT(AUC=0.862),Logistic regression(AUC=0.859),SVM(AUC=0.837),NBM(AUC=0.830),CART(AUC=0.771),XGBoost(AUC=0.764),and K-NN(AUC=0.722).Conclusion SRLI increases the mortality risk of patients.The prediction model construc-ted using the RF algorithm has high diagnostic value.

Objective : To establish a method for measuring major organic acids in the tricarboxylic acid cycle using a high-performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS) system, and to investigate the changes in six tricarboxylic acid cycle organic acids(fumaric acid, malic acid, succinic acid, α-ketoglutaric acid, cis-aconitic acid, and citric acid) in the serum, liver, and placenta of mice exposed to di(2-ethylhexyl) phthalate(DEHP) during pregnancy. Methods : The serum, liver and placental samples from pregnant mice were processed and eluted through a Waters ACQUITY UPLC BEH Amide Column(130 Å, 1.7 μm, 2.1 mm × 150 mm) using a gradient elution program. Mobile phase A comprised an aqueous solution of 10 mmol/L ammonium acetate and 5 μmol/L methanephosphonic acid, while mobile phase B consisted of a 90% acetonitrile aqueous solution containing 10 mmol/L ammonium acetate and 5 μmol/L methanephosphonic acid, with a flow rate maintained at 0.35 ml/min. The mass spectrometry detection system utilized an electrospray ionization technique with negative ion mode for multiple reaction monitoring. Results : The correlation coefficients of the standard curves for the six tricarboxylic acid cycle organic acid metabolites were all above 0.996 within the quantitative range. The method's accuracy ranged from 97.14% to 108.26%, with inter-day and intra-day precision relative standard deviation between 1.35% and 6.73%. The matrix effect was between 93.29% and 107.47%, and the extraction recovery rate ranged from 94.82% to 112.57%. Analysis of six tricarboxylic acid cycle organic acids in the liver, serum, and placenta of DEHP-exposed mice during pregnancy showed significant reductions in fumaric acid, malic acid, α-ketoglutaric acid, cis-aconitic acid, and citric acid compared to the control group(P<0.05). Conclusion The HPLC-MS/MS method established in this study for detecting six tricarboxylic acid cycle organic acids in the serum, liver, and placenta of DEHP-exposed pregnant mice is stable, highly sensitive and selective. Prenatal DEHP exposure induced alterations in the levels of tricarboxylic acid(TCA) cycle organic acid metabolites in the liver, serum, and placenta of mice, suggesting that DEHP exposure during pregnancy may interfere with mitochondrial TCA cycle processes. These findings indicate potential value in the diagnosis and treatment of diseases associated with prenatal DEHP exposure.

Iodine speciations in aquatic environments are affected by dissolved oxygen,redox potential,microbial activity,organic matter decomposition,light reaction,etc.Accurate quantification of iodine speciation can not only help to understand the geochemical cycle of iodine,but also help to trace and study environmental processes.Based on the combination of ion chromatography(IC)and inductively coupled plasma mass spectrometry(ICP-MS),a rapid and sensitive method was established for determining the speciations of iodine in environmental water samples including seawater,river water,lake water,rainwater,groundwater,etc.The results presented here showed that IO3?and I?in seawater were quickly separated and measured within 120 s when using guard column AG22 and 8 mmol/L(NH4)2CO3 as the mobile phase.While for lake water,river water and precipitation samples with high soluble organically bond iodine(SOI),an AS22 separation column(250 mm×4 mm)connected with a guard column and using 50 mmol/L(NH4)2CO3 as mobile phase could effectively separate unknown SOI from IO3? to achieve accurate quantification of IO3?.For accurate correction of iodine measurement signal fluctuations,133Cs was directly added to the(NH4)2CO3 mobile phase as an internal standard.The SOI content was calculated by the total iodine concentrations minus the sum of IO3?and I?.The precision of the established iodine speciation analytical method was better than 3.5%,and the standard addition experiment showed that the analytical method was accurate.When the injection volume was 25 μL,the detection limits were 0.011?0.025 μg/L for IO3? and 0.023?0.031 μg/L for I?,respectively.The method was successfully used to analyze IO3?,SOI and I? in environmental water samples,such as seawater,river water,rainwater and groundwater.

The cycling of iodine in the atmosphere and ocean plays a critical role in climate and environmental change.Ice cores and tree rings,as ideal climate archives,can provide essential data for paleoclimate reconstruction through accurate iodine analysis.However,iodine concentrations in ice core samples are as low as 0.01 μg/L,and as low as 0.01 μg/g in tree rings.Most currently reported analytical methods face challenges in accurately quantifying such low levels.In this study,a highly sensitive analytical method for trace iodine in environmental samples was developed based on inductively coupled plasma mass spectrometry(ICP-MS),incorporating a collision/reaction cell under the optimized collision/reaction gas conditions.Collision/reaction cell mode was employed to evaluate potential interferences in determination of trace iodine by ICP-MS.The results indicated that peak tailing from adjacent mass-to-charge ratios and polyatomic ion interferences could be considered negligible.However,residual iodine in ultrapure water constituted the major source of background,highlighting the need for strict control of sample pretreatment and procedural blanks in trace-level iodine analysis.By utilizing collision focusing effect of helium,the measurement sensitivity of iodine was enhanced to 3.5×105 cps(counts per second)/(μg/L),and the detection limit was reduced to 0.002 μg/L.The developed method exhibited a deviation of less than 2.3%in measurement of low-concentration standard solutions,indicating good accuracy.For actual samples and blanks,the precision of repeated measurements within 2 h was better than 1.6%,demonstrating excellent repeatability.No significant memory effect was observed during the measurements.The established method was successfully applied to determination of trace iodine in ice cores,tree rings,and other environmental samples,providing a robust technical foundation for investigating the role of iodine in climate and environmental change.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.