Objective To explore the effectiveness of the cumulative sum (CUSUM) and the exponentially weighted moving average (EWMA) for early warning of influenza epidemic using two datasets of reported influenza cases and influenza-like illness (ILI) cases. Methods Using the reported cases of influenza and ILI in Daxing District, Beijing, from week 23 of 2018 to week 22 of 2024 as data sets, the CUSUM and EWMA models were established, respectively. The positive rate of influenza etiology was used as the ^“gold standard^”, and the Youden index was used as the evaluation index to compare the early warning effect of the two models under different data sets and different parameters. Results In CUSUM, the optimal Youden indices of the reported influenza cases set and the ILI cases set were 0.751 and 0.635, respectively. In EWMA, the optimal Youden indices of the reported influenza cases set and the ILI cases set were 0.544 and 0.464, respectively. The optimal EWMA and CUSUM models could both issue early warning signals in advance of the ^“gold standard^”. Conclusion In the influenza epidemic early warning in Daxing District, Beijing, the CUSUM model established with the reported cases of influenza can achieve good early warning effects, but the model parameters need to be dynamically adjusted according to the local epidemic characteristics.

OBJECTIVE To analyze the peak wideband acoustic immittance(WAI)values reflecting the tympanic membrane absorption characteristics during the measurement process in patients with congenital middle ear malformation.METHODS We selected 36 patients diagnosed with congenital middle ear malformation by CT as subjects and evaluated their tympanic membrane absorption characteristics by measuring their acoustic impedance peak pressure.Then,we divided these data into two groups based on the pathological malformation obseved during the surgical process,namely the auditory ossicular chain soft connection group and the auditory ossicular chain fixation group.Calculate the absorption rate values of the tympanic membrane at each frequency corresponding to the peak pressure value of the tympanogram,and the relative area of absorption rate.By conducting independent t-tests,we compared two groups-normal children and patients who had undergone ossicular chain fixation surgery-to analyze the absorption area and peak absorption rate of their tympanic peak pressure values.RESULTS Under peak pressure,there were significant differences(P<0.001)in the full frequency range tympanic membrane absorption rate and peak absorption rate between the group with fixed ossicular chain and the normal group.However,there was no difference in the full frequency range tympanic membrane absorption rate and peak absorption rate between the group with soft ossicular chain and the normal group.Under peak pressure,the absorption area of the ossicular chain fixation group was significantly lower than that of the normal group in the low frequency range of 226-1 000 Hz(P<0.001),while the absorption area of the ossicular chain soft connection group was significantly higher than that of the normal group in the low frequency range of 226-1 000 Hz(P<0.001).CONCLUSION When conducting broadband acoustic impedance test,there is a significant difference in the relative area of tympanic membrane absorption rate of acoustic impedance peak pressure between the auditory ossicular chain soft connection group and the auditory ossicular chain fixation group across 226-1 000 Hz.It has application value as a clinical rapid screening and diagnostic tool for middle ear malformations.

[摘 要] 目的：探究牛蒡子苷元（ARC）通过调控Notch/Hes-1信号通路对口腔鳞状细胞癌（OSCC）HSC-3细胞增殖、凋亡和侵袭的影响及其机制。方法：使用不同质量浓度的ARC处理人HSC-3细胞，CCK-8法检测ARC对细胞增殖活力的影响，以选择适宜的药物浓度。将HSC-3细胞分为对照组、ARC-L组（10 mg/L ARC）、ARC-M组（20 mg/L ARC）、ARC-H组（40 mg/L ARC）和ARC-H+Jagged1/FC组（40 mg/L ARC+1.2 μg/mL Jagged1/FC）。采用EdU法检测细胞增殖能力，划痕愈合实验、Transwell实验和流式细胞术分别检测细胞的迁移、侵袭能力及细胞周期和细胞凋亡率，WB法检测增殖（c-Myc、cyclin D1）、凋亡（BAX、Bcl-2、survivin）、EMT（E-cadherin、vimentin、Snail）及Notch/Hes-1通路（Notch 1、Hes-1、NICD）相关蛋白的表达水平。结果：与0 mg/L相比，10~80 mg/L的ARC均能显著降低HSC-3细胞增殖活力（均P<0.05）。与对照组相比，ARC-L组、ARC-M组和ARC-H组HSC-3细胞EdU阳性率、划痕愈合率、侵袭细胞数、S期和G2/M期细胞占比及c-Myc、cyclin D1、Bcl-2、survivin、vimentin、Snail、Notch 1、Hes-1和NICD蛋白表达均显著降低（均P<0.05），细胞凋亡率、G0/G1期细胞占比及BAX、E-cadherin的蛋白表达均显著升高（均P<0.05），且呈浓度梯度依赖性。同时使用Notch激动剂Jagged1/FC，则可部分逆转ARC对HSC-3细胞增殖、迁移、侵袭、凋亡及相关蛋白表达的作用（均P<0.05）。结论：ARC可能通过抑制Notch/Hes-1信号通路抑制OSCC细胞HSC-3增殖和侵袭并促进细胞凋亡。

Objective To investigate the sleep disorders and its effects on the changes in quality of life in patients with liver cancer from the hospital admission to 6 months after surgery and to analyse the correlation between the sleep disorder and quality of life.Methods A total of 214 patients who underwent surgery for liver cancer for the first time were included in the study.Demographic questionnaire,Pittsburgh sleep quality index(PSQI),and functional assessment of cancer therapy-hepatobiliary(FACT-Hep)were used for the investigation at admission and at 1,3 and 6 months after surgery.Multiple linear regression was employed to analyse the correlation between the sleep disorders at the admission and its effect on quality of life up to 6 months after surgery.Results Toally 214 patients finished the study at admission and 209 finished the study 1 month after surgery,and 208 finished the stuoly 3 months after surgery,and 205 patients finished the study 6 months after surgery.The scores of both of PSQI at admission and the quality of life at 6 months after surgery varied across the tested time points with a statistically significant difference(both P<0.001).The overall level of sleep disorder in the patients showed a characteristic pattern with initially increasing and then decreasing,and the quality of life presented a characteristic tendency of starting from high to low and then gradually increasing.It showed that the sleep disorder at admission was attributive to the poorer quality of life at 6 months after surgery.The hierarchical regression analysis showed that among the patients at BCLC Stage A,sleep disorder at admission was the influencing factor of the quality of life at 6 months after surgery.Conclusions The sleep disorder and quality of life in the patients who had surgical operations for hepatocellular carcinoma both changed dynamically from admission to the 6 months after surgery.The quality of life was poor in the patients with sleep disorder at admission.Therefore,medical staff should enhance the sleep management at admission,conduct dynamic assessment of the sleep disorder and quality of life of the patients,and then develop continuity nursing measures to improve the quality of life after surgery.

The nasal swab samples of swine influenza(SI)suspected pigs were collected and tested for H3 subtype swine influenza virus(SIV)positive by RT-qPCR.The positive samples were inoc-ulated into SPF chicken embryos for virus isolation.The full genome sequencing and sequence anal-ysis of the isolated H3N2 subtype SIV were conducted,and its pathogenicity was studied.The re-sults showed that a strain of SIV was successfully isolated and identified as H3N2 subtype by RT-PCR,named A/Swine/Yunnan/KM/06/2023(H3N2).The BLSAT results showed that the eight segments of SIV H3N2 KM had the highest homology with eight different strains of swine influ-enza or human influenza viruses,reaching 95.41％-97.49％.The HA and NA segments were de-rived from H3N2 subtype SIV,the NP segment was derived from H1N1 subtype human influenza virus,the M segment was derived from H1N2 subtype SIV,and all other segments were derived from H1N1 subtype SIV.The key receptor sites(190D,223V,226I,228S)of HA protein remained unchanged.The pathogenicity experiment results showed that infected piglets exhibited symptoms such as fever,sneezing,runny nose,the virus could be detoxified to the outside through the nasal cavity,and the lungs had different degrees of lesion.Immunohistochemistry(IHC)showed that the virus could replicate in the lungs.In conclusion,a strain of H3N2 subtype SIV was successfully iso-lated,and the genetic evolution,molecular characteristics and pathogenicity of the virus were stud-ied.It revealed that H3N2 subtype SIV is constantly evolving and had pathogenicity to piglets,pro-viding a reference for monitoring and preventing SIV epidemics in China,and provided a candidate strain for SI vaccine development.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Ablation of ventricular arrhythmia originating from the epicardial and intramural sites tends to be challenging in clinical practice.As the reflux system of cardiac blood flow,tributaries of the coronary venous system widely covers the surface and the myocardium tissue of the heart,which could serve as alternative access route for auxiliary mapping and ablation.This review updated the research progress on the novel ablation methods via the coronary venous system.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Lactic acid bacteria(LAB)were isolated and cultivated from the intestinal contents of rabbits by MRS-CaCO3 solid medium.Identification was achieved through morphological observa-tion,Gram staining,physiological and biochemical characterisation,16S rDNA sequence analysis,and ERIC-PCR analysis.Strains displaying typical Lactobacilli characteristics were exanimated for their biological characteristics,resistance properties,adherence capacity in vitro,colonization abili-ty in vivo,and safety profile.In this study,a total of four strains of Lactobacillus reuteri were iso-lated from rabbits,all of which exhibited typical biological characteristics of LAB.These strains demonstrated inhibitory effects on common pathogenic bacteria in the gastrointestinal tract,with the primary inhibitory substance being bacteriocin.Furthermore,they showed sensitivity to chlor-amphenicol,rifampicin,and erythromycin,and displayed a degree of tolerance to gastrointestinal conditions and high temperature.These stains were capable of successful colonization in rabbits with a higher degree of safety.This study lays a foundation for the development of LAB prepara-tions for the prevention and treatment of rabbit intestinal diseases.

Objective:To investigate the value of immune inflammatory index in predic-ting the therapeutic efficacy of neoadjuvant chemoradiotherapy for esophageal squamous cell carci-noma (ESCC).Methods:The retrospective case-control study was conducted. The clinicopatholo-gical data of 163 patients with ESCC who were admitted to Zhongshan Hospital of Fudan University from December 2015 to December 2020 were collected. There were 135 males and 28 females, aged (62±8)years. All 163 patients underwent neoadjuvant chemoradiotherapy and radical resection for ESCC. Observation indicators: (1) relationship between immune inflammatory index and clinical characteristic in patients; (2) relationship between immune inflammatory index and efficacy of neoadjuvant chemoradiotherapy in patients; (3) influencing factor analysis for pathologic complete response and good response of tumor regression grade after neoadjuvant chemoradiotherapy; (4) efficiency of immune inflammatory index in predicting efficacy of neoadjuvant chemoradiotherapy. Measurement data with normal distribution were represented as Mean± SD. Count data were described as absolute numbers, and comparison between groups was conducted using chi-square test. Comparison of ordinal data was conducted using the rank sum test. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value. Univariate and multi-variate analyses were conducted using the Logistic regression model. The area under the curve (AUC) of ROC curve was used to evaluate the efficiency of predictive model. Results:(1) Relationship between immune inflammatory index and clinical characteristic in patients. ① Optimal cut-off value of systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR), platelet-lympho-cyte ratio (PLR). Results of ROC curve analysis showed that the AUC of SII, NLR, PLR in predicting efficacy of neoadjuvant chemoradiotherapy for patients with ESCC was 0.70(95% confidence interval as 0.61?0.77), 0.78(95% confidence interval as 0.69?0.84), 0.79(95% confidence interval as 0.70?0.85), respectively, with the maximum value of Youden index and the optimal cut-off value as 0.25, 0.32, 0.52 and 446×10 9/L, 2.09, 138. ② Relationship between SII, NLR, PLR and clinical charac-teristic in patients. According to the optimal cut-off value of SII, NLR, PLR, all 163 patients were divided into cases with SII <446×10 9/L as 99, cases with SII ≥446×10 9/L as 64, cases with NLR <2.09 as 107, cases with NLR ≥2.09 as 56, cases with PLR<138 as 88, cases with PLR ≥138 as 75, respectively. There was a significant difference in clinical N staging of tumor in patients with SII <446×10 9/L and SII ≥446×10 9/L ( P<0.05). There were significant differences in clinical N staging and clinical TNM staging of tumor in patients with NLR<2.09 and NLR≥2.09 ( P<0.05). (2) Relationship between immune inflammatory index and efficacy of neoadjuvant chemoradiotherapy in patients. Of 163 patients undergoing neoadjuvant chemoradiotherapy, there were 54 cases with pathologic complete response and 109 cases without pathologic complete response, 94 cases with good response of tumor regression grade and 69 cases with poor response of tumor regression grade. Of the 54 patients with pathologic complete response, cases with SII <446×10 9/L and SII ≥446×10 9/L, cases with NLR <2.09 and NLR ≥2.09, cases with PLR <138 and PLR ≥138 before neoadjuvant chemoradiotherapy were 42 and 12, 47 and 7, 48 and 6, respectively. The above indicators were 57 and 52, 60 and 49, 40 and 69 in the 109 cases without pathologic complete response. There were significant differences in the above indicators between patients with pathologic complete response and without pathologic complete response ( χ2=9.83, 16.39, 39.60, P<0.05). Of the 94 cases with good response of tumor regression grade, cases with SII <446×10 9/L and SII ≥446×10 9/L, cases with NLR <2.09 and NLR ≥2.09, cases with PLR <138 and PLR ≥138 before neoadjuvant chemoradiotherapy were 59 and 35, 78 and 16, 56 and 38, respectively. The above indicators were 40 and 29, 29 and 40, 32 and 37 in the 69 cases with poor response of tumor regression grade. There was no significant difference in the SII and PLR ( χ2=0.38, 2.79, P>0.05) and there was a significant difference in the NLR ( χ2=29.59, P<0.05) between patients with good response of tumor regression grade and poor response of tumor regre-ssion grade. (3) Influencing factor analysis for pathologic complete response and good response of tumor regression grade after neoadjuvant chemoradiotherapy. Results of multivariate analysis showed that PLR <138 before neoadjuvant chemoradiotherapy was an independent protective factor for pathologic complete response in ESCC patients undergoing neoadjuvant chemoradiotherapy ( odds ratio=1.98, 95% confidence interval as 1.56?2.51, P<0.05) and NLR <2.09 before neoadjuvant chemo-radiotherapy was an independent protective factor for good response of tumor regression grade ( odds ratio=2.50, 95% confidence interval as 1.40?4.46, P<0.05). (4) Efficiency of immune inflam-matory index in predicting efficacy of neoadjuvant chemoradio-therapy. The AUC of PLR <138 before neoadjuvant chemoradiotherapy in predicting pathologic complete response of ESCC patients undergoing neoadjuvant chemoradiotherapy was 0.79(95% confidence interval as 0.64?0.87, P<0.05), with the sensitivity, specificity and Youden index as 0.89, 0.63 and 0.52, respectively. The AUC of NLR <2.09 before neoadjuvant chemoradiotherapy in predic-ting good response of tumor regression grade of ESCC patients undergoing neoadjuvant chemoradio-therapy was 0.76 (95% confidence interval as 0.64?0.81, P<0.05), with the sensitivity, specificity and Youden index as 0.83, 0.58 and 0.41, respectively. Conclusion:The PLR<138 and NLR <2.09 before neoadjuvant chemoradiotherapy are independent protective factors for the pathologic complete response and good response of tumor regression grade, respectively, of ESCC patients undergoing neoadjuvant chemoradiotherapy, and both of them can predict the curative effect of neoadjuvant chemoradiotherapy well.