ObjectiveTo investigate the intervention effects and mechanisms of the flavonoid hyperoside （Hyp） on lipopolysaccharide （LPS）-induced inflammation in the zebrafish model. MethodsZebrafish larvae were either microinjected with 0.5 g·L^-1 LPS or immersed in 1 g·L^-1 LPS for the modeling of inflammation. The larvae were then treated with Hyp at 25， 50， and 100 mg·L^-1 through immersion for four consecutive days. The inflammatory phenotypes were assessed by analyzing the mortality rate， malformation rate， body length， and yolk sac area ratio. Behavioral tests were conducted to evaluate the inflammatory stress responses， and macrophage migration was observed by fluorescence microscopy. Additionally， the mRNA levels of inflammation-related genes， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， chemokine C-C motif ligand 2 （CCL2）， chemokine C-X3-C motif receptor 1 （CX3CR1）， chemokine C-C motif receptor 2 （CCR2）， and genes associated with the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-kappa B （NF-κB） signaling pathway， were measured by Real-time quantitative polymerase chain reaction（Real-time PCR）. ResultsCompared with the pure water injection group， the model group exhibited increased mortality， malformation rates and yolk sac area ratio （P0.01）， reduced body length （P0.01）， increased total swimming distance and high-speed swimming duration （P0.01）， and up-regulated mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.01）. Hyp at low， medium and high doses， as well as aspirin， reduced the mortality and malformation rates （P0.05，P0.01）， increased the body length （P0.05，P0.01）， decreased the yolk sac area ratio （P0.01）， reduced the high-speed swimming duration （P0.01）， and down-regulated the mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.05，P0.01） compared with the model group. ConclusionHyp may modulate the TLR4/MyD88/NF-κB pathway to ameliorate inflammatory phenotypes and alleviate stress conditions in zebrafish， thereby exerting the anti-inflammatory effect.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Human infection with Orf virus is a rare zoonotic disease in clinical practice,mainly caused by human contact with infected sheep or its pollutants.It is commonly seen in shepherds and slaughterhouse workers.The le-sion mainly involves the skin.Since it is rare in clinic and difficult to diagnose and treat,it is easy to be misdiag-nosed and underdiagnosed.This paper reports a case of human infection with Orf virus,with locally dense skin le-sions.The clinical diagnosis and treatment processes of this case are analyzed,and relevant literatures are reviewed retrospectively,so as to improve clinical understanding on this disease.

To analyze the epidemiological characteristics of COVID-19 in Fujian Province from the 49th week of 2022 to the 5th week of 2023,after further optimization of China's COVID-19 prevention and control measures on December 7,2022(the 49th week of 2022),this study used multi-dimensional surveillance data to dynamically assess population infection levels and their changing trends.The aim of the study was to provide a scientific basis for early warning of epidemic risk,medical resource allocation,and evalu-ation of socio-economic impact.A multi-source data surveillance system was constructed,encompassing surveillance of fever clinics at medical institutions(weekly collection of visits,positive nucleic acid and antigen test results,inpatients,and severe cases in sec-ondary or above hospitals),population nucleic acid test monitoring(weekly person-times and positivity rates of single-tube tests from the provincial system),sentinel hospital monitoring(weekly proportion of influenza-like illness visits at 18 sentinel hospitals and re-lated viral testing data),and monitoring of novel coronavirus variants(weekly systematic collection of genomic sequences of local and imported cases).Line charts were plotted weekly,and time series analysis,molecular epidemiological methods,and an improved SEIAR model were used to simulate epidemic spread.During the study period,the COVID-19 epidemic in Fujian Province exhibited three distinct stages.In the infection peak stage(52nd week of 2022),the provincial fever clinic visits reached 606 893 person-times,and a 49.2%positivity rate in population single-tube nucleic acid tests and 63.8%positivity rate in sentinel hospital monitoring were observed.In the medical load peak stage(2nd week of 2023),274 460 inpatients and 28 487 severe cases were recorded.In the epidemic decline stage(4th to 5th weeks of 2023),fever clinic visits decreased by 96.3%with respect to the peak,the single-tube nucleic acid test positivity rate decreased to 6.3%,and the sentinel hospital COVID-19 nucleic acid test positivity rate was 6.4%.All 508 sequenced local cases were Omicron variants,predominantly BA.5.2 and its sub-lineages(67.4%).Among 56 imported se-quenced cases,BA.5.2 and its sub-lineages accounted for 50.0%,and 16.1%comprised nine variants of interest including XBB and BQ.The model predicted the infection peak in the 52nd week of 2022,whereas the hospitalization peak lagged by approximately 10.6 days.Multi-source data monitoring revealed a three-stage development of the COVID-19 epidemic in Fujian.The BA.5.2 strain was dominant during the epidemic.The combination of multi-source monitoring data and modeling provides important references for epi-demic prevention and control,and highlights the need to improve the monitoring system in follow-up.

To analyze the epidemiological characteristics of COVID-19 in Fujian Province from the 49th week of 2022 to the 5th week of 2023,after further optimization of China's COVID-19 prevention and control measures on December 7,2022(the 49th week of 2022),this study used multi-dimensional surveillance data to dynamically assess population infection levels and their changing trends.The aim of the study was to provide a scientific basis for early warning of epidemic risk,medical resource allocation,and evalu-ation of socio-economic impact.A multi-source data surveillance system was constructed,encompassing surveillance of fever clinics at medical institutions(weekly collection of visits,positive nucleic acid and antigen test results,inpatients,and severe cases in sec-ondary or above hospitals),population nucleic acid test monitoring(weekly person-times and positivity rates of single-tube tests from the provincial system),sentinel hospital monitoring(weekly proportion of influenza-like illness visits at 18 sentinel hospitals and re-lated viral testing data),and monitoring of novel coronavirus variants(weekly systematic collection of genomic sequences of local and imported cases).Line charts were plotted weekly,and time series analysis,molecular epidemiological methods,and an improved SEIAR model were used to simulate epidemic spread.During the study period,the COVID-19 epidemic in Fujian Province exhibited three distinct stages.In the infection peak stage(52nd week of 2022),the provincial fever clinic visits reached 606 893 person-times,and a 49.2%positivity rate in population single-tube nucleic acid tests and 63.8%positivity rate in sentinel hospital monitoring were observed.In the medical load peak stage(2nd week of 2023),274 460 inpatients and 28 487 severe cases were recorded.In the epidemic decline stage(4th to 5th weeks of 2023),fever clinic visits decreased by 96.3%with respect to the peak,the single-tube nucleic acid test positivity rate decreased to 6.3%,and the sentinel hospital COVID-19 nucleic acid test positivity rate was 6.4%.All 508 sequenced local cases were Omicron variants,predominantly BA.5.2 and its sub-lineages(67.4%).Among 56 imported se-quenced cases,BA.5.2 and its sub-lineages accounted for 50.0%,and 16.1%comprised nine variants of interest including XBB and BQ.The model predicted the infection peak in the 52nd week of 2022,whereas the hospitalization peak lagged by approximately 10.6 days.Multi-source data monitoring revealed a three-stage development of the COVID-19 epidemic in Fujian.The BA.5.2 strain was dominant during the epidemic.The combination of multi-source monitoring data and modeling provides important references for epi-demic prevention and control,and highlights the need to improve the monitoring system in follow-up.

Human infection with Orf virus is a rare zoonotic disease in clinical practice,mainly caused by human contact with infected sheep or its pollutants.It is commonly seen in shepherds and slaughterhouse workers.The le-sion mainly involves the skin.Since it is rare in clinic and difficult to diagnose and treat,it is easy to be misdiag-nosed and underdiagnosed.This paper reports a case of human infection with Orf virus,with locally dense skin le-sions.The clinical diagnosis and treatment processes of this case are analyzed,and relevant literatures are reviewed retrospectively,so as to improve clinical understanding on this disease.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective To explore the correlation of MPV,NLR,PT,APTT and FIB with early pro-gression of ACI in patients with BAD.Methods A total of 303 ACI patients with BAD admitted in our department of neurology from October 2021 to September 2023 were consecutively recrui-ted,and according to their progression within 7 d of onset,they were divided into progression group(89 cases)and un-progression group(214 cases).The general clinical data,blood routine re-lated indicators(MPV,NLR)and coagulation related indicators(PT,APTT,FIB)were compared between the two groups.Multivariate logistic regression analysis was applied to identify the rela-tionship of above indicators with early progression of ACI in BAD patients.ROC curve was plot-ted to analyze the predictive value of the indictors for disease progression in these patients.Results The progression group had significantly advanced age,larger proportions of diabetes,hyperlipi-demia and stroke history,and increased levels of uric acid,LDL-C,homocysteine,MPV,platelet distribution width,NLR,D-dimer and FIB,and shorter TT,PT and APTT when compared with the un-progressed group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that MPV,NLR,PT,APTT,and FIB were all independent influencing factors for early disease pro-gression of ACI in patients with BAD(P＜0.05,P＜0.01).ROC curve indicated that the AUC value of combined MPV,NLR,PT,APTT and FIB in detecting early disease progression was 0.859(95％CI:0.813-0.905).Conclusion Blood routine(MPV,NLR)and coagulation related indicators(PT,APTT,FIB)are closely associated with the early disease progression of ACI in BAD patients,and these indicators are of high value in predicting the early disease progression.

Objective:To investigate the clinical and gene variant characteristics of PCDH19 gene related epilepsy, and improve the ability of clinicians in early disease identification. Methods:The clinical data of 3 PCDH19 gene related epilepsy patients admitted to Children′s Hospital Affiliated to Zhengzhou University from October 2018 to August 2023 diagnosed by gene detection were reviewed and analyzed. Results:All the patients are female, and the onset age of seizure ranged in their infancy. Seizures in clusters and fever sensitivity were observed in all patients, and were very hard to control by single-drug treatment. Proband 1 was seizure-free after 2 kinds of anti-epileptic drug treatment, but with mild degree of intellectual disability. Proband 2 had refractory epilepsy with severe degree of intellectual disability. Proband 3 was seizure-free after 2 kinds of anti-epileptic drug treatment and without intellectual disability. In the first family, the proband carried heterozygous c.369C>G variant in the PCDH19 gene which was identified as de novo after parental validation. In the second family, the proband carried c.1652T>A variant inherited from her mother. In the third family, the proband carried c.278G>A variant inherited from her father. The 3 mutations had not been reported in the Human Gene Mutation Database. Conclusions:PCDH19 gene related epilepsy is one special kind of X-linked inherited epilepsy syndrome characterized by seizures in clusters and sensitivity to fever. And gene detection can help with early diagnosis and make rational clinical strategies in time. The variants c.369C>G, c.1652T>A and c.278G>A have enriched the gene variant spectrum of PCDH19.

Objective To investigate the efficacy of electromagnetic guidance and bedside ultrasound in the placement of nasointestinal feeding tubes in neurocritical care patients,providing a reference for nurses to accurately and efficiently place tubes at the bedside. Methods A tatal of 85 patients were selected as the study subjects,who required nasoenteric tube placement and treated in the department of neurocritical care unit of the First Affiliated Hospital of Zhengzhou University from January 2023 to June 2023. Patients were randomly divided into an experimental group (43 cases) and a control group (42 cases) using a random number table. The experimental group used electromagnetic guidance-assisted nasointestinal tube placement,while the control group utilized bedside ultrasound technology. The differences in the success rate of one-time tube placement,placement time,and complications between the two groups were compared. Results The success rate of one-time tube placement in the experimental group was higher than that in the control group[97.67％ (42/43) vs. 95.24％ (40/42)],but the difference was not statistically significant (P>0.05). The placement time in the experimental group was significantly reduced compared to the control group (minutes:16.23±3.06 vs. 25.07±3.26,P<0.05),and the number of positioning attempts was significantly fewer[attempts:1 (1,3) vs. 3 (3,4),P<0.05]. Scores for theoretical knowledge,operational practice,placement preparation,catheter position visualization,and catheter position interpretation in the experimental group were significantly lower than those in the control group[theoretical knowledge score:2.67±0.52 vs. 4.67±0.52,operational practice score:2.50±0.55 vs. 5.00±0.00,placement preparation score:2.33 (2.00,3.00) vs. 3.00 (2.00,4.00),catheter position visualization score:1.83±0.41 vs. 4.83±0.41,catheter position interpretation score:1.83±0.41 vs. 3.83±0.41,all P<0.05]. The technical difficulty score was significantly lower in the experimental group than in the control group (11.17±0.75 vs. 21.33±0.82,P<0.05). The incidence of nasal bleeding complications in the experimental group was significantly lower than that in the control group[6.98％ (3/43) vs. 23.81％ (10/42),P<0.05]. No other placement complications occurred in either group. Conclusions The success rates of one-time tube placement using electromagnetic navigation and bedside ultrasound for bedside placement of nasointestinal feeding tubes were comparable,but electromagnetic guidance offered higher efficiency and safety. It is suggested that bedside ultrasound be used for gastrointestinal evaluation before electromagnetic guidance-assisted tube placement to assist nurses in implementing personalized pre-placement preparations,thereby further increasing the success rate of tube placement.