Objective To propose a novel method based on three-dimensional depthwise separable convolution network(3D DSN)for the separation of PET images with dual tracers of 18F-FDG and 18F-FAPI.Methods A total of 120 pairs of 18F-FDG and 18F-FAPI PET images of the same patient scanned separately at different time points were collected,and the dual-tracer PET image was generated through simulation.After the image registration of PET images of two tracers for ensuring spatial position matching,the registered PET images were forward-projected to generate sinogram data,and the sinogram data of two tracers were accumulated to obtain mixed sinogram data.Subsequently,the dual-tracer PET image was reconstructed using maximum likelihood expectation maximization and input into a 3D DSN based network for image separation,thereby obtaining PET images of two single tracers.Results Compared with 3D CNN method,the proposed method increased the structure similarity index measure(SSIM)of the separated 18F-FDG images to the real 18F-FDG images by 0.87%,increased the peak signal-to-noise ratio(PSNR)by 11.8%,and reduced the normalized root mean square error(NRMSE)by 52%.The SSIM of the separated 18F-FAPI images to the real 18F-FAPI images increased by 1.1%,PSNR increased by 17.0%,and NRMSE decreased by 51%.Conclusion The proposed method can be effectively applied to simultaneous PET imaging with dual PET tracers,reducing the number of scans and costs in time and money,and providing clinical doctors more accurate and abundant diagnostic information.

Objective To propose a novel method based on three-dimensional depthwise separable convolution network(3D DSN)for the separation of PET images with dual tracers of 18F-FDG and 18F-FAPI.Methods A total of 120 pairs of 18F-FDG and 18F-FAPI PET images of the same patient scanned separately at different time points were collected,and the dual-tracer PET image was generated through simulation.After the image registration of PET images of two tracers for ensuring spatial position matching,the registered PET images were forward-projected to generate sinogram data,and the sinogram data of two tracers were accumulated to obtain mixed sinogram data.Subsequently,the dual-tracer PET image was reconstructed using maximum likelihood expectation maximization and input into a 3D DSN based network for image separation,thereby obtaining PET images of two single tracers.Results Compared with 3D CNN method,the proposed method increased the structure similarity index measure(SSIM)of the separated 18F-FDG images to the real 18F-FDG images by 0.87%,increased the peak signal-to-noise ratio(PSNR)by 11.8%,and reduced the normalized root mean square error(NRMSE)by 52%.The SSIM of the separated 18F-FAPI images to the real 18F-FAPI images increased by 1.1%,PSNR increased by 17.0%,and NRMSE decreased by 51%.Conclusion The proposed method can be effectively applied to simultaneous PET imaging with dual PET tracers,reducing the number of scans and costs in time and money,and providing clinical doctors more accurate and abundant diagnostic information.

Objective: To investigate the prevalence of major chronic diseases among residents in Xiamen City, Fujian Province, so as to provide insights into enhancing the prevention and control of chronic diseases. Methods: The residents aged 18 years and older and lived for 6 months and more were selected from 6 districts in Xiamen City from 2021 to 2022 using the stratified random sampling method. Demographic information, disease history, blood pressure, fasting blood glucose and blood cholesterol were collected through questionnaire surveys, physical examination and laboratory tests. The prevalence rates of hypertension, diabetes and hypercholesterolemia were calculated and standardized using the 2020 National Population Census data, and were analyzed by age and gender. Results: Totally 22 289 residents were investigated, including 10 444 males (46.86%) and 11 845 females (53.14%). The prevalence rates of hypertension, diabetes and hypercholesterolemia were 15.35%, 4.30% and 10.45%, and the standardized prevalence rates were 16.25%, 4.81% and 10.21%, respectively. The standardized prevalence rates of hypertension, diabetes and hypercholesterolemia in males were 19.20%, 5.71% and 9.97%, respectively, and were higher than those in females, which were 13.62%, 4.03% and 10.29%, respectively (all P<0.05). The crude prevalence rates of hypertension and diabetes in males aged 18 to 59 years were higher than those in females, the crude prevalence rate of hypercholesterolemia in males aged 18 to 49 years was higher than that in females, and the crude prevalence rate of hypercholesterolemia aged 50 years and over in males was lower than that in females (all P<0.05). Conclusion From 2017 to 2022, the prevalence rates of hypertension, diabetes, and hypercholesterolemia in males were higher than those in females in Xiamen City, while the prevalence rate of hypercholesterolemia in females was higher than that in males after the age of 50 years.

Objective The prediction of RR intervals in hypertensive patients can help clinicians to analyze and warn patients'heart condition.Methods Using 8 patients'data as samples,the RR intervals of patients were predicted by long short-term memory network(LSTM)and gradient lift tree(XGBoost),and the prediction results of the two models were combined by the inverse variance method to overcome the disadvantage of single model prediction.Results Compared with the single model,the proposed combined model had a different degree of improvement in the prediction of RR intervals in 8 patients.Conclusion LSTM-XGBoost model provides a method for predicting RR intervals in hypertensive patients,which has potential clinical feasibility.

Various types of software needed in radiomics studies come with the problems such as data incompatibility and hyperparameter tuning.Therefore,an artificial intelligence-based software is developed for radiomics studies,providing doctors and researchers a solution with image preprocessing,feature extraction,feature selection,modeling analysis and data visualization.The usability of the software is demonstrated using a public data set.Eight sets of feature selectors and classifiers are established for classification predication on test data set and key performance indicator output.Through hyperparameter tuning,the model is further optimized.Researchers will focus more on the research itself rather than unnecessary development efforts,and radiomics studies will become more convenient and efficient with the software addressed.

Various types of software needed in radiomics studies come with the problems such as data incompatibility and hyperparameter tuning.Therefore,an artificial intelligence-based software is developed for radiomics studies,providing doctors and researchers a solution with image preprocessing,feature extraction,feature selection,modeling analysis and data visualization.The usability of the software is demonstrated using a public data set.Eight sets of feature selectors and classifiers are established for classification predication on test data set and key performance indicator output.Through hyperparameter tuning,the model is further optimized.Researchers will focus more on the research itself rather than unnecessary development efforts,and radiomics studies will become more convenient and efficient with the software addressed.

Objective:To investigate the acceptance and attitude toward a novel fecal immunochemical test (FIT) in colorectal cancer screening among populations in China.Methods:From May 2018 to May 2019, 2 474 people aged 50-74 years were recruited from five provinces of China (Zhejiang, Anhui, Jiangsu, Hunan and Yunnan). The general demographic characteristics, acceptance of the new FIT technology and operational difficulties through the whole screening process were obtained through questionnaire survey. Multivariate logistic regression model was used to analyze the factors related to difficulties encountered in sampling stool, reading and uploading results.Results:The subjects were (60.0±6.4) years old, and female, high school of above educated, unemployed/retired/other, married and with medical insurance status of “new rural cooperative medical care (NRCMC)” accounted for 61.7% (1 526), 29.0%(718), 34.3% (849), 92.7% (2 293) and 31.3%(775), respectively. The population's acceptance of the FIT technology was 94.8%. In the process of FIT screening, the percentage of occurred difficulties in sampling stool, reading and uploading results were 33.1% (819), 46.4% (1 147) and 62.9% (1 557), respectively. The main difficulties were the uncertainty about whether the sampling operation was standard (28.0%), the inability to accurately judge the result displayed (32.5%) and the need for help without using a smartphone (44.2%). The results of multivariate logistic regression model analysis showed that people aged 65-74 years old and with medical insurance status of “NRCMC” were more likely to encounter difficulties in sampling, and those who were unemployed/retired/other and living with 3 or more family members were less likely to encounter difficulties in sampling. Those aged 65-74 years old, farmers or migrant workers, and those with “NRCMC” were more likely to encounter difficulties in readingresults, and those with 3 or more family members were less likely to encounter difficulties in reading result. Those with “NRCMC” were more likely to encounter difficulties in uploading results, and those with education level of high school or above, living with more than 3 family members were less likely to encounter difficulties in uploading results.Conclusion:The acceptance of the new FIT technology is relatively high among the subjects. Age, education level, occupation, number of family members living together and medical insurance status might be related to difficulties encountered in sampling stool, reading and uploading results, and it can be further strengthened in terms of the technology and characteristics of sub-populations.

Objective:To investigate the acceptance and attitude toward a novel fecal immunochemical test (FIT) in colorectal cancer screening among populations in China.Methods:From May 2018 to May 2019, 2 474 people aged 50-74 years were recruited from five provinces of China (Zhejiang, Anhui, Jiangsu, Hunan and Yunnan). The general demographic characteristics, acceptance of the new FIT technology and operational difficulties through the whole screening process were obtained through questionnaire survey. Multivariate logistic regression model was used to analyze the factors related to difficulties encountered in sampling stool, reading and uploading results.Results:The subjects were (60.0±6.4) years old, and female, high school of above educated, unemployed/retired/other, married and with medical insurance status of “new rural cooperative medical care (NRCMC)” accounted for 61.7% (1 526), 29.0%(718), 34.3% (849), 92.7% (2 293) and 31.3%(775), respectively. The population's acceptance of the FIT technology was 94.8%. In the process of FIT screening, the percentage of occurred difficulties in sampling stool, reading and uploading results were 33.1% (819), 46.4% (1 147) and 62.9% (1 557), respectively. The main difficulties were the uncertainty about whether the sampling operation was standard (28.0%), the inability to accurately judge the result displayed (32.5%) and the need for help without using a smartphone (44.2%). The results of multivariate logistic regression model analysis showed that people aged 65-74 years old and with medical insurance status of “NRCMC” were more likely to encounter difficulties in sampling, and those who were unemployed/retired/other and living with 3 or more family members were less likely to encounter difficulties in sampling. Those aged 65-74 years old, farmers or migrant workers, and those with “NRCMC” were more likely to encounter difficulties in readingresults, and those with 3 or more family members were less likely to encounter difficulties in reading result. Those with “NRCMC” were more likely to encounter difficulties in uploading results, and those with education level of high school or above, living with more than 3 family members were less likely to encounter difficulties in uploading results.Conclusion:The acceptance of the new FIT technology is relatively high among the subjects. Age, education level, occupation, number of family members living together and medical insurance status might be related to difficulties encountered in sampling stool, reading and uploading results, and it can be further strengthened in terms of the technology and characteristics of sub-populations.

As the breakthrough in gene editing, represented by CRISPR/Cas9, gene manipulations now are more maneuverable, economically feasible and time saving. It is possible for China to catch an overtaking in researching and industrializing of downside sections (especially the application of plant gene editing), also the incubation of professional companies in gene editing fields. For this consideration, it is necessary and urgent to find the key demands and potential application for gene editing in China. Questionnaire and statistic analysis were carried out to find the key demands and the most potential application fields of the development for gene editing. Firstly, an ordered multi-classification Logistic regression model was established following with dependent variable analysis. Eight out of 24 questionnaires questions in 4 categories were regarded as independent variables with significance test. Then, regression model based on ordered multi-classification logistic method was established to analyze the specific impact of different options on the development of gene editing. The results showed that most researchers in the field of gene editing take the view that development of potential competitive advantages lies in the field of plant science. The results also showed that major gene editing experts believe more attention should be paid on how to carry out technology industrialization while focusing on basic technology development, as well as the development of potential competitive advantages of gene editing technology in plant field. To promote the development of gene editing in China, not only the participation of scientific research institution was needed, but also the synergy of various forces both universities and governments. It is urgent both properly guiding public opinion on gene editing and establishing a national safety standard system. At the same time, the key point of technology risk avoidance should be put on biological weapons and bioterrorism, gene editing related infectious disease, and the potential risk of species genetic change on the ecological environment, etc.
CRISPR-Cas Systems/genetics* ; China ; Clustered Regularly Interspaced Short Palindromic Repeats ; Gene Editing ; Plants/genetics*

The aim of this study is to investigate the effect of fibreoptic endoscopic of sallowing （FEES） in the assessment of pharyngeal dysphagia in post-irradiated patients with nasopharyngeal carcinoma. Fifty-three NPC patients with post-irradiated underwent FEES and video fluoroscopy（VF）.The results were analyzed using the Bolus Residue Scale and Rosenbek's penetration aspiration scale. The agreement in the detection of penetration and aspiration between FEES and VF of liquid（κ=0.56, 95% 0.38-0.73） and porridge（κ=0.64, 95% 0.43-0.81） was "fair". The detection rates of penetration on FEES with liquid and porridge were 60% and 51%, the detection rates of aspiration on VF with liquid and porridge were 70% and 53%. There were no statistical differences. The agreement in the detection of pharyngeal residue between FEES and VF of liquid （κ=0.38, 95%0.12-0.62） and porridge （κ=0.66, 95% 0.44-0.86） was "fair". The detection rates of pharyngeal residue on FEES and VF with porridge were 43% and 45%, the difference was not statistically significant. The detection rates of pharyngeal residue on FEES and VF with liquid were 44% and 24%, and the difference was statistically significant. FEES is an effective and valuable tool for evaluating pharyngeal dysphagia in post-irradiated patients with nasopharyngeal carcinoma.