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CT whole lung radiomic nomogram:a potential biomarker for lung function evaluation and identification of COPD

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Military Medical Research 2025年第1期12卷 36-47页

作者： Tao-Hu Zhou Xiu-Xiu Zhou Jiong Ni yan-qing Ma Fang-Yi Xu bing Fan Yu Guan Xin-Ang Jiang Xiao-qing Lin Jie Li Yi Xia Xiang Wang Yun Wang Wen-Jun Huang Wen-ting Tu Peng Dong zhao-Bin Li Shi-Yuan liu Li Fan Department of Radiology the Second Affiliated Hospital of Naval Medical UniversityShanghai 200003China School of Medical Imaging Shandong Second Medical UniversityWeifang 261053ShandongChina Department of Radiology School of MedicineTongji HospitalTongji UniversityShanghai 200065China Department of Radiology Zhejiang Province People’s HospitalAffiliated People’s Hospital of Hangzhou Medical CollegeHangzhou 310014China Department of Radiology Sir Run Run Shaw HospitalZhejiang 310018China Jiangxi Provincial People’s Hospital the First Affiliated Hospital of Nanchang Medical CollegeNanchang 330006China College of Health Sciences and Engineering University of Shanghai for Science and TechnologyShanghai 200093China Department of Radiology the Second People’s Hospital of DeyangDeyang 618000SichuanChina Department of Radiation Oncology Shanghai Jiao Tong University Affiliated Sixth People’s HospitalShanghai 200233China

Background:Computed tomography(CT)plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease(COPD).This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD ***:This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD *** radiomic features of the whole lung volume were *** absolute shrinkage and selection operator(LASSO)logistic regression was applied for feature selection and radiomic signature construction.A radiomic nomogram was established by combining the radiomic score and clinical *** operating characteristic(ROC)curve analysis and decision curve analysis(DCA)were used to evaluate the predictive performance of the radiomic nomogram in the training,internal validation,and independent external validation ***:Eighteen radiomic features were collected from the whole lung volume to construct a radiomic *** area under the curve(AUC)of the radiomic model in the training,internal,and independent external validation cohorts were 0.888[95%confidence interval(CI)0.869–0.906],0.874(95%CI 0.844–0.904),and 0.846(95%CI 0.822–0.870),*** were higher than the clinical model(AUC were 0.732,0.714,and 0.777,respectively,P<0.001).DCA demonstrated that the nomogram constructed by combining radiomic score,age,sex,height,and smoking status was superior to the clinical factor ***:The intuitive nomogram constructed by CT-based whole-lung radiomic has shown good performance and high accuracy in identifying COPD in this multicenter study.

关键词： Chronic obstructive pulmonary disease(COPD) Computed tomography(CT) Radiomic

Encoding syntactic representations with a neural network for sentiment collocation extraction

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Science China(Information Sciences) 2017年第11期60卷 7-18页

作者： yanyan zhao bing qin ting liu Department of Media Technology and Art Harbin Institute of Technology Department of Computer Science and Technology Harbin Institute of Technology

Sentiment collocation refers to the collocation of a target word and a polarity word. Sentiment collocation extraction aims to extract the targets and their modifying polarity words by analyzing the relationships between them. This can be regarded as a basic sentiment analysis task and is relevant in many practical applications. Previous studies relied mainly on the syntactic path, which is used to connect the target word and the polarity word. To deeply exploit the semantic information of the syntactic path, we propose two types of syntactic representation, namely, relation embedding and subtree embedding, to capture the latent semantic features. Relation embedding is used to represent the latent semantics between targets and their corresponding polarity words, and subtree embedding is used to explore the rich syntactic information for each word on the path. To combine the two types of syntactic representations, a neural network is constructed. We use a recursive neural network(RNN) to model the subtree embeddings, and then the subtree embedding and the word embedding are combined as the enhanced word representation for each word in the syntactic path. Finally,a convolutional neural network(CNN) is adopted to integrate the two types of syntactic representations to extract the sentiment collocations from reviews. Our experiments were conducted on six types of reviews, which included product domains(such as cameras and phones) and service domains(such as hotels and restaurants).The experimental results show that our proposed method can accurately capture the latent semantic features hidden behind the syntactic paths that neither the common feature-based methods nor the syntactic-path-based method can handle, and, further, that it significantly outperforms numerous baselines and previous methods.

关键词： sentiment collocation extraction sentiment analysis syntactic representation neural network re cursive neural network(RNN) convolutional neural network(CNN)

A syntactic path-based hybrid neural network for negation scope detection

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Frontiers of Computer Science 2020年第1期14卷 84-94页

作者： Lydia LAZIB bing qin yanyan zhao Weinan ZHANG ting liu Research Center for Social Computing and Information Retrieval Harbin Institute of TechnologyHarbin 150001China

The automatic detection of negation is a crucial task in a wide-range of natural language processing(NLP)applications,including medical data mining,relation extraction,question answering,and sentiment *** this paper,we present a syntactic path-based hybrid neural network architecture,a novel approach to identify the scope of negation in a *** hybrid architecture has the particularity to capture salient information to determine whether a token is in the scope or not,without relying on any human *** approach combines a bidirectional long shortterm memory(Bi-LSTM)network and a convolutional neural network(CNN).The CNN model captures relevant syntactic features between the token and the cue within the shortest syntactic path in both constituency and dependency parse *** Bi-LSTM learns the context representation along the sentence in both forward and backward *** evaluate our model on the Bioscope corpus,and get 90.82%F-score(78.31%PCS)on the abstract sub-corpus,outperforming features-dependent approaches.

关键词： natural language processing negation scope detection convolutional neural network recurrent neural network syntactic path

Generating Chinese named entity data from parallel corpora

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Frontiers of Computer Science 2014年第4期8卷 629-641页

作者： Ruiji FU bing qin ting liu School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

Annotating named entity recognition （NER） training corpora is a costly but necessary process for supervised NER approaches. This paper presents a general framework to generate large-scale NER training data from parallel corpora. In our method, we first employ a high performance NER system on one side of a bilingual corpus. Then, we project the named entity （NE） labels to the other side according to the word level alignments. Finally, we propose several strategies to select high-quality auto-labeled NER training data. We apply our approach to Chinese NER using an English-Chinese parallel corpus. Experimental results show that our approach can collect high-quality labeled data and can help improve Chinese NER.

关键词： named entity recognition Chinese named entity training data generating parallel corpora

Recent advances in deep learning based sentiment analysis

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Science China(Technological Sciences) 2020年第10期63卷 1947-1970页

作者： YUAN JianHua WU yang LU Xin zhao yanyan qin bing liu ting Research Center for Social Computing and Information Retrieval Harbin Institute of TechnologyHarbin 150001China Pengcheng Lab Shenzhen 518066China

Sentiment analysis is one of the most popular research areas in natural language *** is extremely useful in many applications,such as social media monitoring and *** application of deep learning based methods has dramatically changed the research strategies and improved the performance of many traditional sentiment analysis tasks,such as sentiment classification and aspect based sentiment ***,it also pushed the boundary of various sentiment analysis task,including sentiment classification of different text granularities and in different application scenarios,implicit sentiment analysis,multimodal sentiment analysis and generation of sentiment-bearing *** this paper,we give a brief introduction to the recent advance of the deep learning-based methods in these sentiment analysis tasks,including summarizing the approaches and analyzing the *** survey can be well suited for the researchers studying in this field as well as the researchers entering the field.

关键词： coarse-grained fine-grained implicit multi-modal generation

Negation scope detection with a conditional random field model

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High Technology Letters 2017年第2期23卷 191-197页

作者： Lydia Lazib zhao yanyan qin bing liu ting Research Center for Social Computing and Information Retrieval Harbin Institute of Technology Harbin 150001 P. R. China

Identifying negation cues and their scope in a text is an important subtask of information extraction that can benefit other natural language processing tasks,including but not limited to medical data mining,relation extraction,question answering and sentiment *** tasks of negation cue and negation scope detection can be treated as sequence labelling *** this paper,a system is presented having two components:negation cue detection and negation scope *** the first phase,a conditional random field(CRF) model is trained to detect the negation cues using a lexicon of negation words and some lexical and contextual ***,another CRF model is trained to detect the scope of each negation cue identified in the first phase,using basic lexical and contextual *** two models are trained and tested using the dataset distributed within the* Sem Shared Task 2012 on resolving the scope and focus of *** results show that the system outperformed all the systems submitted to this shared task.

关键词： negation detection negation cue detection negation scope detection natural language processing

氮素水平对北方优良食味粳米品质及精碾磨粉颗粒特性的影响

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作物学报 2025年第2期51卷 503-515页

作者：闫秉春万雪钟敏刘宇奇赵艳泽姜红芳刘雅刘惠玲马沁春高继平张文忠沈阳农业大学水稻研究所/北方粳稻育种栽培技术国家地方联合工程实验室/农业农村部东北水稻生物学与遗传育种重点实验室辽宁沈阳110866

为探究氮素对粳米食味品质、营养品质和精碾磨粉特性的影响,以不同食味粳稻品种沈农9816、秋田小町、北粳3号和盐粳476为试验材料,设置0 kg hm^(-2) (N0)、50 kg hm^(-2) (N1)、100 kg hm^(-2) (N2)和200 kg hm^(-2) (N3)4个氮素水平,... 详细信息

为探究氮素对粳米食味品质、营养品质和精碾磨粉特性的影响,以不同食味粳稻品种沈农9816、秋田小町、北粳3号和盐粳476为试验材料,设置0 kg hm^(-2) (N0)、50 kg hm^(-2) (N1)、100 kg hm^(-2) (N2)和200 kg hm^(-2) (N3)4个氮素水平,研究了氮素水平对不同食味稻米品质与精碾磨粉颗粒形态特征的影响及其相互关系。结果表明:(1)稻米食味值表现为秋田小町>盐粳476>北粳3号>沈农9816,在不同氮素水平下表现一致。(2)随着氮素水平的提高,除秋田小町外,不同粳稻品种的食味品质(蒸煮食味值、外观、黏度、胶稠度)、支链淀粉A链、B1链含量均显著降低,硬度、直链淀粉含量和蛋白组分含量显著提高;峰值黏度、热浆黏度、最终黏度呈降低趋势,崩解值、消减值、糊化温度受氮素影响较小;精碾磨粉表面由光滑变为粗糙,颗粒粒径变大、数量增多呈堆积状,并伴随裂痕和空隙现象发生。(3)相关分析表明,氮素水平与与蒸煮食味品质(黏度、外观和食味值)、RVA特征值谱(峰值黏度、热浆黏度、最终黏度)均呈极显著负相关,但与硬度及精碾磨粉表面颗粒粒径呈极显著正相关;精碾磨粉表面颗粒粒径与蒸煮食味品质(食味值、外观)、RVA特征值谱(黏度、峰值黏度、热浆黏度及最终黏度)呈极显著负相关,但与硬度呈显著正相关。综合来看,食味值高的品种对氮素响应较弱,且精碾磨粉表面特性稳定,进而保证了其食味品质的稳定性。

关键词：食味品质淀粉含量蛋白组分精碾磨粉颗粒粒径氮素

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Discovery of MicroRNAs Associated with the S Type Cytoplasmic Male Sterility in Maize

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Journal of Integrative Agriculture 2013年第2期12卷 229-238页

作者： YU Jiang-hua zhao yan-xin qin Ya-ting YUE bing ZHENG Yong-lian XIAO Hai-lin National Key Laboratory of Crop Genetic Improvement/Huazhong Agricultural University

MicroRNAs （miRNAs） are endogenous small RNAs that play important regulatory roles in the growth and development processes of plants and animals. In this study, we examined the expression profiles of pollen miRNAs from a maize S type cytoplasmic male sterile line and its fertility restored line. In total, 100 known miRNAs belonging to 20 families and 81 novel miRNAs belonging to 44 families were identified. Two and seven known miRNAs had significant expression difference between the two lines at the level of P-value〈0.01 and 0.01〈P-value〈0.05, respectively. Four miRNAs showing 〉1.5 fold expression difference were verified by stem-loop RT-qPCR. Gene Ontology analysis of miRNA target genes revealed that these genes mainly participated in the transcriptional regulation processes.

关键词： CMS-S microRNAs real-time PCR Solexa sequencing target gene maize

Effects of urea enhanced with different weathered coal-derived humic acid components on maize yield and fate of fertilizer nitrogen

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Journal of Integrative Agriculture 2019年第3期18卷 656-666页

作者： ZHANG Shui-qin YUAN Liang LI Wei LIN Zhi-an LI yan-ting HU Shu-wen zhao bing-qiang Key Laboratory of Plant Nutrition and Fertilizer Ministry of Agriculture/Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural Sciences College of Resources and Environmental Sciences China Agricultural University

Humic acid(HA) is a readily available and low-cost material that is used to enhance crop production and reduce nitrogen(N) loss. However, there is little consensus on the efficacy of different HA components. In the current study, a soil column experiment was conducted using the ^(15)N tracer technique in Dezhou City, Shandong Province, China, to compare the effects of urea with and without the addition of weathered coal-derived HA components on maize yield and the fate of fertilizerderived N(fertilizer N). The HA components were incorporated into urea by blending different HA components into molten urea to obtain the three different types of HA-enhanced urea(HAU). At harvest, the aboveground dry biomass of plants grown with HAU was enhanced by 11.50–21.33% when compared to that of plants grown with U. More significantly, the grain yields under the HAU treatments were 5.58–18.67% higher than the yield under the urea treatment. These higher yields were due to an increase in the number of kernels per plant rather than the weight of individual kernels. The uptake of fertilizer N under the HAU treatments was also higher than that under the urea treatment by 11.49–29.46%, while the unaccounted N loss decreased by 12.37–30.05%. More fertilizer-derived N was retained in the 0–30 cm soil layer under the HAU treatments than that under the urea treatment, while less N was retained in the 30–90 cm soil layer. The total residual amount of fertilizer N in the soil column, however, did not differ significantly between the treatments. Of the three HAU treatments investigated, the one with an HA fraction derived from extraction with pH values ranging from 6 to 7, resulted in the best improvement in all assessment targets. This is likely due to the abundance of the COO/C–N=O group in this HA component.

关键词： humic acid enhanced urea maize aboveground dry biomass fertilizer N uptake fertilizer N residue