Chinchilla has been successfully used as an animal model in the study of auditory system, microorgan-ism and parasitic infection, because of its unique biological features, and it can be further developed for the research of se-nile diseases, metabolic diseases, etc.This paper will introduce the related biological characteristics of chinchilla, and briefly reviewed the progress of its application in medical research.

Objective To explore the method of Oncomelania hupensis snail surveillance in transmission?interrupted re?gions of schistosomiasis,so as to provide a new pattern for the surveillance of snail status in the transmission?interrupted areas. Methods In Dongtai County,north of Jiangsu Province where the transmission of schistosomiasis was interrupted,the surveil?lance of snail status was performed by means of the village?level general survey,village?level sampling survey,snail survey in key settings of township and county,and snail reporting by residents. In addition,quality?control snail sites were set up for quali?ty control. The effectiveness and cost of the four methods of snail surveillance was compared. Results A total of 163 079 set?tings and 22 785.62 hm2 were surveyed in Dongtai County from 2008 to 2013,and 89 residual snail breeding sites were found, with a snail area of 1.48 hm2. The patterns of village?level general survey,village?level sampling survey,and snail survey in key settings of township and county were employed for investigation of 94 550,45 033 and 23 496 settings,consisting of 57.98%, 27.61%and 14.41%of total settings,and 2,0 and 6 settings were found with snails,with 0.021/thousand,0,and 0.255/thou?sand detection rates of settings with snail breading sites,respectively. The pattern of snail survey in key settings of township and county was more effective than that of village?level survey to detect snail breeding sites(χ2 =19.158,P=0). The recovery rate of quality?control snail breeding sites was 52.56%,38.27%and 73.62%for the three patterns of snail survey,respectively,and the pattern of snail survey in key settings of township and county showed a higher quality for snail survey than that of village?lev?el survey(χ2 =111.597 and 85.991,both P=0). During the period from 2008 to 2013,289 person?times reported 279 sus?pected snail habitats and 1 501 living snails,and no Oncomelania snails were found. During the 6?year period,there were 1617.5,964.7 and 527.7 thousand RMB invested for village?level general survey,village?level sampling survey,and snail sur?vey in key settings of township and county,and the cost of snail survey per hm2 was 129.88,133.6 and 162.57 RMB/hm2,re?spectively. The cost of village?level general survey and snail survey in key settings of township and county to detect a snail?breed?ing site was 808 800 and 88 000 RMB,respectively(t=12.850,P=0.000),and the cost of snail survey in key settings of town?ship and county was 10.88%of that of village?level general survey. Conclusion The snail survey in key settings of township and county is a highly effective and high?quality method for snail surveillance,which may serve as a prior way for the surveil?lance of snail status in the transmission?interrupted areas of schistosomiasis.

ObjectiveIn view of the problems of large errors and poor accuracy in pulmonary function testing in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), a predictive classification model of pulmonary function in patients with AECOPD was proposed by comparing the prediction performance of different machine learning models to find the optimal model. MethodsFrom January, 2018 to February, 2020, 90 patients with different degrees of COPD from the Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University were collected. Six machine learning model algorithms (K-nearest neighbor, logistic regression, support vector machine, naive Bayes, decision tree and random forest) were used to establish AECOPD predictive classification models. Their area under the curve of receiver operating characteristic (AUC-ROC) and accuracy were compared. Ten-fold cross-validation method was used to validate the data set. ResultsThe model based on random forest worked best in predicting and classifying AECOPD patients, with an accuracy rate of 0.844 and an AUC-ROC of 0.916. ConclusionRandom forest-based predictive model is a powerful tool for identifying patients with AECOPD, providing decision support when it is difficult to give a definitive diagnosis.

【Objective】 To detect the anti-SARS-CoV-2 antibody levels in blood donors in Guangzhou, so as to provide laboratory data support for the collection and clinical use of convalescent plasma. 【Methods】 Anti-SARS-CoV-2 antibodies were measured by ELISA in qualified donors. Among them, 326 donors who gave blood in February 2023 were tested for IgG antibodies, 444 donors were tested for neutralizing antibodies. In July 2023, 398 donors were tested for IgG and IgM. 【Results】 399 of 724 blood samples diluted with normal saline (1∶160) were IgG reactive, with a reactive rate of 55.11%. Chi-square test showed that there was a significant difference in the reactive rate of IgG among samples collected at different times (25.46% in February vs 79.40% in July, χ²=210.74, P<0.01, 95%CI: 7.97, 15.98), but there was no significant difference in the reactive rate between different genders and different age groups. IgM was detected in 5 of 398 blood samples, with a reactive rate of 1.26%. The IgG test results of these five blood donors were all reactive, whereas the nucleic acid test results were negative. Neutralizing antibody was detected in 440 of 444 blood samples, with a reactive rate of 99.10%, and 71.59% of the reactive donors had a neutralizing antibody level of 10 μg/mL or more. 【Conclusion】 Blood donors in Guangzhou have a high level of SARS-CoV-2 antibody, which is sufficient to provide convalescent plasma for clinical treatment.