Aim To detect the expression of nerve growth factor （NGF） and vascular endothelial growth factor （VEGF） in salivary adenoid cystic carcinoma （SACC） tissues, as well as to determine the correlation between growth...Aim To detect the expression of nerve growth factor （NGF） and vascular endothelial growth factor （VEGF） in salivary adenoid cystic carcinoma （SACC） tissues, as well as to determine the correlation between growth factor expression and prognosis in SACC. Methodology Medical records of 63 patients surgically treated for SACC between January 1988 and October 2005 were reviewed. Immunohistochemistry was performed to examine the expression of NGF and VEGF in tumor tissues. Kaplan-Meier analysis and Cox＇s proportional hazard regression model were applied to assess predictors of survival. Results NGF and VEGF were overexpressed in SACC tissues, compared with those in normal salivary tissues （P〈0.05）, and the staining intensity of these two factors was stronger in groups of solid subtype, advanced TNM stage, perineural invasion and recurrence. Patients with high- expression of NGF and VEGF, solid subtype, advanced stage, perineural invasion, recurrence and extended resection alone had worse survival rates （P〈0.05）. Conclusion NGF and VEGF are expressed increasingly in the tissues of SACC cases with invasion and metastasis. NGF expression and VEGF expression are independent prognosis factors for survival.展开更多
The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available.The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting en...The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available.The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting endoscopic screening and diagnosis of gastric lesions.Simultaneously,with the development of convolutional neural network,artificial intelligence(AI)has made unprecedented breakthroughs in medical imaging,including the ongoing trials of computer-aided detection of colorectal polyps and gastrointestinal bleeding.In the past demi-decade,applications of AI systems in gastric cancer have also emerged.With AI’s efficient computational power and learning capacities,endoscopists can improve their diagnostic accuracies and avoid the missing or mischaracterization of gastric neoplastic changes.So far,several AI systems that incorporated both traditional and novel endoscopy technologies have been developed for various purposes,with most systems achieving an accuracy of more than 80%.However,their feasibility,effectiveness,and safety in clinical practice remain to be seen as there have been no clinical trials yet.Nonetheless,AI-assisted endoscopies shed light on more accurate and sensitive ways for early detection,treatment guidance and prognosis prediction of gastric lesions.This review summarizes the current status of various AI applications in gastric cancer and pinpoints directions for future research and clinical practice implementation from a clinical perspective.展开更多
To the Editor: Since avian influenza A(H7N9) was first identified in Shanghai, China, in March 2013, there have been a total of five epidemics. These have amounted to 1564 laboratory-confirmed cases up to September 20...To the Editor: Since avian influenza A(H7N9) was first identified in Shanghai, China, in March 2013, there have been a total of five epidemics. These have amounted to 1564 laboratory-confirmed cases up to September 2017, with a fatality rate of about 40%.[1] In the fifth wave, 4.09% of cases (31/758) were infected with the highly pathogenic avian influenza (HPAI) A(H7N9). This indicated that the pathotype of the A(H7N9) had switched from low pathogenic avian influenza (LPAI) to HPAI.展开更多
This paper proposes a new approach for variable selection in partially linear errors-in-variables （EV） models for longitudinal data by penalizing appropriate estimating functions. We apply the SCAD penalty to simult...This paper proposes a new approach for variable selection in partially linear errors-in-variables （EV） models for longitudinal data by penalizing appropriate estimating functions. We apply the SCAD penalty to simultaneously select significant variables and estimate unknown parameters. The rate of convergence and the asymptotic normality of the resulting estimators are established. Furthermore, with proper choice of regularization parameters, we show that the proposed estimators perform as well as the oracle procedure. A new algorithm is proposed for solving penalized estimating equation. The asymptotic results are augmented by a simulation study.展开更多
基金supported by National Natural Science Foundation of China (30060082)Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry ([2003] 593)+3 种基金Key Research Project Foundation of Guangxi Health Bureau (200006)Guangxi Science Foundation for Returned Overseas Scholars (0836013)Educational Scientific Research Foundation of Chinese Society of Higher Education (06AIL077 0110)Innovation Project of Guangxi Graduate Education (2009105981003M174)
文摘Aim To detect the expression of nerve growth factor （NGF） and vascular endothelial growth factor （VEGF） in salivary adenoid cystic carcinoma （SACC） tissues, as well as to determine the correlation between growth factor expression and prognosis in SACC. Methodology Medical records of 63 patients surgically treated for SACC between January 1988 and October 2005 were reviewed. Immunohistochemistry was performed to examine the expression of NGF and VEGF in tumor tissues. Kaplan-Meier analysis and Cox＇s proportional hazard regression model were applied to assess predictors of survival. Results NGF and VEGF were overexpressed in SACC tissues, compared with those in normal salivary tissues （P〈0.05）, and the staining intensity of these two factors was stronger in groups of solid subtype, advanced TNM stage, perineural invasion and recurrence. Patients with high- expression of NGF and VEGF, solid subtype, advanced stage, perineural invasion, recurrence and extended resection alone had worse survival rates （P〈0.05）. Conclusion NGF and VEGF are expressed increasingly in the tissues of SACC cases with invasion and metastasis. NGF expression and VEGF expression are independent prognosis factors for survival.
文摘The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available.The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting endoscopic screening and diagnosis of gastric lesions.Simultaneously,with the development of convolutional neural network,artificial intelligence(AI)has made unprecedented breakthroughs in medical imaging,including the ongoing trials of computer-aided detection of colorectal polyps and gastrointestinal bleeding.In the past demi-decade,applications of AI systems in gastric cancer have also emerged.With AI’s efficient computational power and learning capacities,endoscopists can improve their diagnostic accuracies and avoid the missing or mischaracterization of gastric neoplastic changes.So far,several AI systems that incorporated both traditional and novel endoscopy technologies have been developed for various purposes,with most systems achieving an accuracy of more than 80%.However,their feasibility,effectiveness,and safety in clinical practice remain to be seen as there have been no clinical trials yet.Nonetheless,AI-assisted endoscopies shed light on more accurate and sensitive ways for early detection,treatment guidance and prognosis prediction of gastric lesions.This review summarizes the current status of various AI applications in gastric cancer and pinpoints directions for future research and clinical practice implementation from a clinical perspective.
文摘To the Editor: Since avian influenza A(H7N9) was first identified in Shanghai, China, in March 2013, there have been a total of five epidemics. These have amounted to 1564 laboratory-confirmed cases up to September 2017, with a fatality rate of about 40%.[1] In the fifth wave, 4.09% of cases (31/758) were infected with the highly pathogenic avian influenza (HPAI) A(H7N9). This indicated that the pathotype of the A(H7N9) had switched from low pathogenic avian influenza (LPAI) to HPAI.
基金Supported by the National Natural Science Foundation of China (Nos.11126332 and 11101452)the National Social Science Foundation of China (No.11CTJ004)+1 种基金the Natural Science Foundation Project of CQ CSTC(No.cstc2011jjA00014)the Research Foundation of Chongqing Municipal Education Commission (No.KJ110720)
文摘This paper proposes a new approach for variable selection in partially linear errors-in-variables （EV） models for longitudinal data by penalizing appropriate estimating functions. We apply the SCAD penalty to simultaneously select significant variables and estimate unknown parameters. The rate of convergence and the asymptotic normality of the resulting estimators are established. Furthermore, with proper choice of regularization parameters, we show that the proposed estimators perform as well as the oracle procedure. A new algorithm is proposed for solving penalized estimating equation. The asymptotic results are augmented by a simulation study.
