Objective To observe the targeted function of a mesothelin antibody modified nanoprobe in human pancreatic cancer BxPC3 cell.Methods The Fe3O4@SiO2 nanoprobe was prepared by St(o)ber method,and then quantum dots (CdTe) and mesothelin antibody was crosslinked to obtain the properties of targeting and fluorescent.Fluorescent nano Fe3O4@SiO2 probes and BxPC3 cells were incubated in vitro for 30 min.Its targeting performance was tested by the CCD imaging system and magnetic separation technology.HepG-2 and K562 cells with low expression of mesothelin were selected as reference cells.Results This preparation method of nanoprobe could produce a uniform and narrow distribution particle with particle size mainly ranging from 120 to 140 nm.The cell adsorption experiments showed that the adsorption efficiency of BxPC3,HepG-2 and K562 by nanoprobe without crosslinking antibody were less than 20％,as a non-specific adsorption; and the adsorption efficiency of BxPC3,HepG-2 and K562 by crosslinking mesothelin antibody nanoprobe were (53.9 ± 1.8) ％,(8.0 ± 2.1) ％ and (8.9 ± 2.3) ％ respectively,and the adsorption capacity with BxPC3 was significantly increased.Conclusions The nanoprobe modified by mesothelin antibody can effectively recognize BxPC3 cells which highly expressing mesothelin.

Posttransplant lymphoproliferative disease (PTLD) is a fatal complication after lung transplantation, which is intimately associated with age, immunosuppression level and Epstein-Barr virus (EBV) infection, etc. Reducing immunosuppression level, rituximab therapy and T cell immunotherapy are common treatments for PTLD. With the rapid development of lung transplantation in China, PTLD after lung transplantation has attracted widespread attention. This article reviews the risk factors, pathological types, clinical manifestations, diagnosis, treatment, prognosis and prevention of PTLD after lung transplantation, aiming to provide reference for early monitoring and management of the incidence and progression of PTLD.

Objective To investigate the application of somatosensory evoked potential stim-ulator in cancerous pain nursing assessment of cancer patients.Methods Selected 102 cancerous pain patients from 2013 June to 2014 March in our hospital oncology,Respectively by using visual analogue scale (VAS)and somatosensory evoked potential stimulator to assess Cancerous pain,and given other routine nursing care.The results of two assessment tools and their correlation were ob-served.Results The average pain degree evaluated by somatosensory evoked potential stimulator was 1.55±0.83,the average VAS was 1.67±0.71,By correlation analysis,there was a signifi-cant positive correlation between the two (r =0.823,P <0.001).Conclusions Somatosensory e-voked potential stimulator has good correlation with VAS in cancerous pain assessment,can be used in the clinical assessment of cancer pain degree and the judgment of efficacy of treatment.

Objective To investigate the application of somatosensory evoked potential stim-ulator in cancerous pain nursing assessment of cancer patients.Methods Selected 102 cancerous pain patients from 2013 June to 2014 March in our hospital oncology,Respectively by using visual analogue scale (VAS)and somatosensory evoked potential stimulator to assess Cancerous pain,and given other routine nursing care.The results of two assessment tools and their correlation were ob-served.Results The average pain degree evaluated by somatosensory evoked potential stimulator was 1.55±0.83,the average VAS was 1.67±0.71,By correlation analysis,there was a signifi-cant positive correlation between the two (r =0.823,P <0.001).Conclusions Somatosensory e-voked potential stimulator has good correlation with VAS in cancerous pain assessment,can be used in the clinical assessment of cancer pain degree and the judgment of efficacy of treatment.

How Th2 immunity develops in vivo remains obscure. Basophils have been considered key innate cells producing IL-4, a cytokine essential for Th2 immunity. Increasing evidence suggests that basophils are dispensable for the initiation of Th2 immunity. In this study, we revisited the role of basophils in Th2 immune responses induced by various types of adjuvants. Mice deficient in IL-3 or IL-3 receptor, in which basophil lymph node recruitment is completely abolished, fully developed wild type level Th2 CD4 T cell responses in response to parasite antigen or papain immunization. Similar finding was also observed in mice where basophils are inducibly ablated. Interestingly, IL-4-derived from non-T cells appeared to be critical for the generation of IL-4-producing CD4 T cells. Other Th2 promoting factors including IL-25 and thymic stromal lymphopoietin (TSLP) were dispensable. Therefore, our results suggest that IL-3- and basophil-independent in vivo Th2 immunity develops with the help of non-T cell-derived IL-4, offering an additional mechanism by which Th2 type immune responses arise in vivo.
Animals ; Basophils ; Immunization ; Interleukin-3 ; Interleukin-4* ; Lymph Nodes ; Mice ; Papain ; Parasites ; Receptors, Interleukin-3 ; T-Lymphocytes

Objective:According to the regulatory requirement in China, double filing system including institutional filing and project filing is mandated for conducting stem cell clinical research at medical institutions. Thus, the organization and implementation of stem cell clinical research is different from traditional drug clinical trials. Based on the analysis of the main roles and responsibilities of stem cell clinical research, this article explores countermeasures to promote the legal and regulatory development of stem cell clinical research.Methods:This study sorts out and analyzes the changes in the main roles and responsibilities of stem cell clinical research in the context of double filing system, and conducts analysis on the main-role construction of stem cell clinical research.Results:Combining the institutional practical experience of conducting and managing stem cell clinical research, three key issues are proposed to promote stem cell clinical research, which including the construction of quality inspection platform, optimizing institutional setting and talent training.Conclusions:It is recommended to strengthen the construction of the main roles and responsibilities of stem cell clinical research, which has important practical significance for promoting stem cell clinical research and accelerating the clinical translation and application of stem cells.

Objective: To find out the characteristics and regularity trend of influenza activity according to the analyses of influenza surveillance data in Yangzhou from 2012 to 2017, and to provide scientific supports for predicting and controlling the pandemic outbreak of influenza effectively. Methods: The influenza samples were collected from Northern Jiangsu People′s Hospital, Yangzhou First People's Hospital and Gaoyou People’s Hospital, using fluorescent RT-PCR method to detect influenza virus nucleic acid and classifying influenza virus subtypes. Finally, the surveillance data from January, 2012 to December, 2017 of influenza like illness (ILI) cases of Yangzhou were analyzed. Results: Totally 18 083 throat swabs of ILI specimens were collected from 2012—2017 in Yangzhou, 1 983 samples were positive (10.97%), the difference in positive rates of adjacent years was statistically significant (χ²=167.93, P<0.001). In Yangzhou city, influenza virus kept activative in whole year. The influenza epidemic season was winter-spring and summer, accounting for 83.61% of all positive cases, with type A influenza prevalent throughout all year and type B influenza mainly prevalent in spring and winter, each subtype showed alternating prevalence. The influenza virus infection occurred in every age group. The highest positive rate was 16.33% in the age group of 10-19 years and the lowest was 8.52% in the age group of 20-29 years among all detected age groups. Conclusions From 2012 to 2017, the epidemic of influenza in Yangzhou was obviously seasonal and all the subtypes of influenza were in prevalent status alternately. The high-risk groups of Influenza were infants and teenagers who under the age of 19 years. So a long-term influenza surveillance is much needed for the early warning and forecasting the spread of influenza.

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.