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| 1 | Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing,China显示文摘Previous studies have showed clinical characteristics of patients with the 2019 novel coronavirus disease(COVID-19)and the evidence of person-to-person transmission.Limited data are available for asymptomatic infections.This study aims to present the clinical characteristics of 24 cases with asymptomatic infection screened from close contacts and to show the transmission potential of asymptomatic COVID-19 virus carriers.Epidemiological investigations were conducted among all close contacts of COVID-19 patients(or suspected patients)in Nanjing,Jiangsu Province,China,from Jan 28 to Feb 9,2020,both in clinic and in community.Asymptomatic carriers were laboratory-confirmed positive for the COVID-19 virus by testing the nucleic acid of the pharyngeal swab samples.Their clinical records,laboratory assessments,and chest CT scans were reviewed.As a result,none of the 24 asymptomatic cases presented any obvious symptoms while nucleic acid screening.Five cases(20.8%)developed symptoms(fever,cough,fatigue,etc.)during hospitalization.Twelve(50.0%)cases showed typical CT images of ground-glass chest and 5(20.8%)presented stripe shadowing in the lungs.The remaining 7(29.2%)cases showed normal CT image and had no symptoms during hospitalization.These 7 cases were younger(median age:14.0 years;P=0.012)than the rest.None of the 24 cases developed severe COVID-19 pneumonia or died.The median communicable period,defined as the interval from the first day of positive nucleic acid tests to the first day of continuous negative tests,was 9.5 days(up to 21 days among the 24 asymptomatic cases).Through epidemiological investigation,we observed a typical asymptomatic transmission to the cohabiting family members,which even caused severe COVID-19 pneumonia.Overall,the asymptomatic carriers identified from close contacts were prone to be mildly ill during hospitalization.However,the communicable period could be up to three weeks and the communicated patients could develop severe illness.These results highlighted the importance of close contact tracing and longitudinally surveillance via virus nucleic acid tests.Further isolation recommendation and continuous nucleic acid tests may also be recommended to the patients discharged. | Zhiliang Hu Ci Song Chuanjun Xu Guangfu Jin Yaling Chen Xin Xu Hongxia Ma Wei Chen Yuan Lin Yishan Zheng Jianming Wang Zhibin Hu Yongxiang Yi Hongbing Shen | 2020 | Science China(Life Sciences)2020，63，5： | 77 |
| 2 | Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies显示文摘Background:Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperpla-sia,the positive rate for malignancy identification during biopsy is low,thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt.Here,we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning.Methods:An endoscopic images-based nasopharyngeal malignancy detection model(eNPM-DM)consisting of a fully convolutional network based on the inception architecture was developed and fine-tuned using separate training and validation sets for both classification and segmentation.Briefly,a total of 28,966 qualified images were collected.Among these images,27,536 biopsy-proven images from 7951 individuals obtained from January 1st,2008,to December 31st,2016,were split into the training,validation and test sets at a ratio of 7:1:2 using simple randomiza-tion.Additionally,1430 images obtained from January 1st,2017,to March 31st,2017,were used as a prospective test set to compare the performance of the established model against oncologist evaluation.The dice similarity coef-ficient(DSC)was used to evaluate the efficiency of eNPM-DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images,by comparing automatic segmentation with manual segmenta-tion performed by the experts.Results:All images were histopathologically confirmed,and included 5713(19.7%)normal control,19,107(66.0%)nasopharyngeal carcinoma(NPC),335(1.2%)NPC and 3811(13.2%)benign diseases.The eNPM-DM attained an overall accuracy of 88.7%(95%confidence interval(CI)87.8%-89.5%)in detecting malignancies in the test set.In the prospective comparison phase,eNPM-DM outperformed the experts:the overall accuracy was 88.0%(95%CI 86.1%-89.6%)vs.80.5%(95%CI 77.0%-84.0%).The eNPM-DM required less time(40 s vs.110.0±5.8 min)and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background,with an average DSC of 0.78±0.24 and 0.75±0.26 in the test and prospective test sets,respectively.Conclusions:The eNPM-DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant,and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images. | Chaofeng Li Bingzhong Jing Liangru Ke Bin Li Weixiong Xia Caisheng He Chaonan Qian Chong Zhao Haiqiang Mai Mingyuan Chen Kajia Cao Haoyuan Mo Ling Guo Qiuyan Chen Linquan Tang Wenze Qiu Yahui Yu Hu Liang Xinjun Huang Guoying Liu Wangzhong Li Lin Wang Rui Sun Xiong Zou Shanshan Guo Peiyu Huang Donghua Luo Fang Qiu Yishan Wu Yijun Hua Kuiyuan Liu Shuhui Lv Jingjing Miao Yanqun Xiang Ying Sun Xiang Guo Xing Lv | 2018 | Cancer Communications2018，38，1： | 9 |
| 3 | Anaerobic treatment of wastewater containing methanol in up-flow anaerobic sludge bed (UASB) reactor显示文摘The direct conversion of methanol into methane is the main process in anaerobic treatment of methanol containing wastewater.However,acetic acid can also be produced from methanol theoretically,which may probably result in an abrupt pH drop and deteriorate the anaerobic process.Therefore,it is interesting to know what would really happen in an anaerobic reactor treating methanol wastewater.In this study,an up-flow anaerobic sludge bed(UASB)reactor treating methanol wastewater was operated.The chemical oxygen demand(COD),acetic acid and pH of the effluent were monitored at different loadings and influent alkalinity.The results showed that the anaerobic reactor could be operated steadily at as low as 119 mg/L of influent alkalinity and high organic loading rate with no obvious pH drops.Volatile fatty acids accumulation was not observed even at strong shock loadings.The microorganisms in the sludge at the end of the test became homogeneous in morphology,which were mainly spherical or spheroidal in shape. | Yishan LIN Yanling HE Zhuo MENG Shucheng YANG | 2008 | Frontiers of Environmental Science & Engineering2008，2，2： | 2 |
| 4 | Single cell analysis reveals inhibition of angiogenesis attenuates the progression of heterotopic ossification in Mkx^(−/−)mice显示文摘Tendon heterotopic ossification(HO)is characterized by bone formation inside tendon tissue,which severely debilitates people in their daily life.Current therapies fail to promote functional tissue repair largely due to our limited understanding of HO pathogenesis.Here,we investigate the pathological mechanism and propose a potential treatment method for HO.Immunofluorescence assays showed that the Mohawk(MKX)expression level was decreased in human tendon HO tissue,coinciding with spontaneous HO and the upregulated expression of osteochondrogenic and angiogenic genes in the tendons of Mkx^(−/−)mice.Single-cell RNA sequencing analyses of wild-type and Mkx^(−/−)tendons identified three cell types and revealed the excessive activation of osteochondrogenic genes during the tenogenesis of Mkx^(−/−)tendon cells.Single-cell analysis revealed that the gene expression program of angiogenesis,which is strongly associated with bone formation,was activated in all cell types during HO.Moreover,inhibition of angiogenesis by the small-molecule inhibitor BIBF1120 attenuated bone formation and angiogenesis in the Achilles tendons of both Mkx mutant mice and a rat traumatic model of HO.These findings provide new insights into the cellular mechanisms of tendon HO and highlight the inhibition of angiogenesis with BIBF1120 as a potential treatment strategy for HO. | Junxin Lin Yuwei Yang Wenyan Zhou Chao Dai Xiao Chen Yuanhao Xie Shan Han Huanhuan Liu Yejun Hu Chenqi Tang Varitsara Bunpetch Dandan Zhang Yishan Chen Xiaohui Zou Di Chen Wanlu Liu Hongwei Ouyang | 2022 | Bone Research2022，10，4： | 1 |
| 5 | Balancing green and grain trade显示文摘 | CHEN Yiping WANG Kaibo LIN Yishan | 2015 | Nature Geoscience2015，8，10： | 1 |
| 6 | A high-resolution route map reveals distinct stages of chondrocyte dedifferentiation for cartilage regeneration显示文摘Articular cartilage damage is a universal health problem.Despite recent progress,chondrocyte dedifferentiation has severely compromised the clinical outcomes of cell-based cartilage regeneration.Loss-of-function changes are frequently observed in chondrocyte expansion and other pathological conditions,but the characteristics and intermediate molecular mechanisms remain unclear.In this study,we demonstrate a time-lapse atlas of chondrocyte dedifferentiation to provide molecular details and informative biomarkers associated with clinical chondrocyte evaluation.We performed various assays,such as single-cell RNA sequencing(scRNA-seq),live-cell metabolic assays,and assays for transposase-accessible chromatin with high-throughput sequencing(ATAC-seq),to develop a biphasic dedifferentiation model consisting of early and late dedifferentiation stages.Early-stage chondrocytes exhibited a glycolytic phenotype with increased expression of genes involved in metabolism and antioxidation,whereas late-stage chondrocytes exhibited ultrastructural changes involving mitochondrial damage and stress-associated chromatin remodeling.Using the chemical inhibitor BTB06584,we revealed that early and late dedifferentiated chondrocytes possessed distinct recovery potentials from functional phenotype loss.Notably,this two-stage transition was also validated in human chondrocytes.An image-based approach was established for clinical use to efficiently predict chondrocyte plasticity using stage-specific biomarkers.Overall,this study lays a foundation to improve the quality of chondrocytes in clinical use and provides deep insights into chondrocyte dedifferentiation. | Yishan Chen Yeke Yu Ya Wen Juan Chen Junxin Lin Zixuan Sheng Wenyan Zhou Heng Sun Chengrui An Jiansong Chen Weiliang Wu Chong Teng Wei Wei Hongwei Ouyang | 2022 | Bone Research2022，10，3： | 1 |
| 7 | A HYBRID ELECTRONIC NOSES’SYSTEM BASED ON MOS-SAW DETECTION UNITS INTENDED FOR LUNG CANCER DIAGNOSIS显示文摘In this paper,a hybrid electronic noses’system(HENS)based on MOS-SAW detection units intended for lung cancer diagnosis is proposed.The MOS gas sensors are used to detect the VOC molecules with low molecular weight(LMW),and the SAW sensors are adopted for the detection of VOC with high molecular weight(HMW).Thus,the novel combination of these two kinds of gas sensors provides higher sensitivities to more of VOC species in breath than that of using only a single kind of sensor.The signals from MOS-SAW detection units are then recognized by a multi-model diagnosis method.Applying four algorithms,six models were established for diagnosis and tested by leave-one-out cross-validation method.The model by artificial neural network(ANN)was selected as the best model to analyze breath samples.89 clinical samples were tested with MOS-SAW ANN diagnostic model,which takes the features derived from both the MOS and SAW sensors.It shows the highest sensitivity of 93.62%,and the highest selectivity of 83.37%.The study shows that,promisingly,our HENS is effective during screening of lung cancer patients,especially among the people of high risk. | DI WANG KAI YU YISHAN WANG YANJIE HU CONG ZHAO LIN WANG KEJING YING PING WANG | 2012 | Journal of Innovative Optical Health Sciences2012，5，1： | 0 |
| 8 | 基于内镜图像深度学习的鼻咽恶性肿瘤检测模型的建立与验证显示文摘背景与目的由于鼻咽部解剖位置隐匿且腺体增生频发,活检时恶性肿瘤的阳性率较低,从而导致初诊时鼻咽恶性肿瘤确诊延时或漏诊。本文旨在建立一种人工智能工具——基于深度学习的内镜检查,来检测鼻咽恶性肿瘤。方法建立了一种基于内镜图像的鼻咽恶性肿瘤检测模型(endoscopic imagesbased nasopharyngeal malignancies detection model,eNPM-DM),该模型由基于空间结构的全卷积网络构成,采用单独训练集和验证集对分类和分割进行微调。总共收集了28,966张合格图像。其中,自2008年1月1日至2016年12月31日,从7951例个体中获得了27,536张经活检证实的图像,按照7∶1∶2的比例随机分为训练、验证和测试集。此外,将2017年1月1日到2017年3月31日获得的1430张图像纳入预测集,用以对建立模型的性能与肿瘤专家的评价进行比较。以鼻咽镜图像为背景,对自动分割和专家手工分割进行比较,采用dice相似系数(dice similarity coefficient,DSC)评价eNPM-DM从鼻咽部内镜图像的背景中自动分割出恶性肿瘤区域的效率。结果所有图像经过病理组织学验证,包括正常对照5713(19.7%)例、鼻咽癌(nasopharyngeal carcinoma,NPC)19,107(66.0%)例、其他恶性肿瘤335(1.2%)例和3811(13.2%)例良性病变。在测试集中,eNPM-DM检测恶性肿瘤的总准确率达88.7%[95%置信区间(confidence interval,CI):87.8%–89.5%]。在预测比较阶段,eNPM-DM表现优于专家:总准确率分别为88.0%(95%CI:86.1%–89.6%)和80.5%(95%CI:77.0%–84.0%)。eNPM-DM耗时更短(40 s vs. 110.0±5.8 min),且从背景中自动分割出鼻咽恶性肿瘤区域方面表现优秀,测试集和预测集中的平均DSC分别为0.78±0.24和0.75±0.26。结论 eNPM-DM在鼻咽肿块良性/恶性诊断分类方面优于肿瘤学家评估,并且实现了从鼻咽内镜图像背景中对恶性区域自动分割。 | Chaofeng Li Bingzhong Jing Liangru Ke Bin Li Weixiong Xia Caisheng He Chaonan Qian Chong Zhao Haiqiang Mai Mingyuan Chen Kajia Cao Haoyuan Mo Ling Guo Qiuyan Chen Linquan Tang Wenze Qiu Yahui Yu Hu Liang Xinjun Huang Guoying Liu Wangzhong Li Lin Wang Rui Sun Xiong Zou Shanshan Guo Peiyu Huang Donghua Luo Fang Qiu Yishan Wu Yijun Hua Kuiyuan Liu Shuhui Lv Jingjing Miao Yanqun Xiang Ying Sun Xiang Guo Xing Lv | 2019 | 癌症2019，38，7： | 0 |
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