5,577 results on '"Fang, Lu"'
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102. Toxic effects of triclosan on hepatic and intestinal lipid accumulation in zebrafish via regulation of m6A-RNA methylation
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Li, Jinyun, Fang, Lu, Xi, Miaocui, Ni, Anyu, Qian, Qiuhui, Wang, Zejun, Wang, Huili, and Yan, Jin
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- 2024
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103. Flexible electrochemical sensor for simultaneous determination of levodopa and uric acid based on carbon nanotube fibers
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Fang, Lu, Zhang, Yi, Liu, Ye, Shou, Jialong, Liu, Hongying, and Li, Lihua
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- 2024
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104. A^2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation
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Hu, Miao, Li, Yali, Fang, Lu, and Wang, Shengjin
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Learning pyramidal feature representations is crucial for recognizing object instances at different scales. Feature Pyramid Network (FPN) is the classic architecture to build a feature pyramid with high-level semantics throughout. However, intrinsic defects in feature extraction and fusion inhibit FPN from further aggregating more discriminative features. In this work, we propose Attention Aggregation based Feature Pyramid Network (A^2-FPN), to improve multi-scale feature learning through attention-guided feature aggregation. In feature extraction, it extracts discriminative features by collecting-distributing multi-level global context features, and mitigates the semantic information loss due to drastically reduced channels. In feature fusion, it aggregates complementary information from adjacent features to generate location-wise reassembly kernels for content-aware sampling, and employs channel-wise reweighting to enhance the semantic consistency before element-wise addition. A^2-FPN shows consistent gains on different instance segmentation frameworks. By replacing FPN with A^2-FPN in Mask R-CNN, our model boosts the performance by 2.1% and 1.6% mask AP when using ResNet-50 and ResNet-101 as backbone, respectively. Moreover, A^2-FPN achieves an improvement of 2.0% and 1.4% mask AP when integrated into the strong baselines such as Cascade Mask R-CNN and Hybrid Task Cascade., Comment: CVPR2021
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- 2021
105. RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions from Monocular RGBD Stream
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Su, Zhuo, Xu, Lan, Zhong, Dawei, Li, Zhong, Deng, Fan, Quan, Shuxue, and Fang, Lu
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Computer Science - Computer Vision and Pattern Recognition - Abstract
High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applications. However, recent advances still fail to provide reliable performance reconstruction, suffering from challenging interaction patterns and severe occlusions, especially for the monocular setting. To fill this gap, in this paper, we propose RobustFusion, a robust volumetric performance reconstruction system for human-object interaction scenarios using only a single RGBD sensor, which combines various data-driven visual and interaction cues to handle the complex interaction patterns and severe occlusions. We propose a semantic-aware scene decoupling scheme to model the occlusions explicitly, with a segmentation refinement and robust object tracking to prevent disentanglement uncertainty and maintain temporal consistency. We further introduce a robust performance capture scheme with the aid of various data-driven cues, which not only enables re-initialization ability, but also models the complex human-object interaction patterns in a data-driven manner. To this end, we introduce a spatial relation prior to prevent implausible intersections, as well as data-driven interaction cues to maintain natural motions, especially for those regions under severe human-object occlusions. We also adopt an adaptive fusion scheme for temporally coherent human-object reconstruction with occlusion analysis and human parsing cue. Extensive experiments demonstrate the effectiveness of our approach to achieve high-quality 4D human performance reconstruction under complex human-object interactions whilst still maintaining the lightweight monocular setting., Comment: 16 pages, 18 figures. Under review by IEEE TPAMI
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- 2021
106. Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network
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Wu, Gaochang, Liu, Yebin, Fang, Lu, and Chai, Tianyou
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Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
The light field (LF) reconstruction is mainly confronted with two challenges, large disparity and the non-Lambertian effect. Typical approaches either address the large disparity challenge using depth estimation followed by view synthesis or eschew explicit depth information to enable non-Lambertian rendering, but rarely solve both challenges in a unified framework. In this paper, we revisit the classic LF rendering framework to address both challenges by incorporating it with advanced deep learning techniques. First, we analytically show that the essential issue behind the large disparity and non-Lambertian challenges is the aliasing problem. Classic LF rendering approaches typically mitigate the aliasing with a reconstruction filter in the Fourier domain, which is, however, intractable to implement within a deep learning pipeline. Instead, we introduce an alternative framework to perform anti-aliasing reconstruction in the image domain and analytically show comparable efficacy on the aliasing issue. To explore the full potential, we then embed the anti-aliasing framework into a deep neural network through the design of an integrated architecture and trainable parameters. The network is trained through end-to-end optimization using a peculiar training set, including regular LFs and unstructured LFs. The proposed deep learning pipeline shows a substantial superiority in solving both the large disparity and the non-Lambertian challenges compared with other state-of-the-art approaches. In addition to the view interpolation for an LF, we also show that the proposed pipeline also benefits light field view extrapolation., Comment: 15 pages, 12 figures. Accepted by IEEE TPAMI
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- 2021
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107. Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection
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Wang, Zhenyu, Li, Yali, Guo, Ye, Fang, Lu, and Wang, Shengjin
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Computer Science - Computer Vision and Pattern Recognition - Abstract
In this paper, we delve into semi-supervised object detection where unlabeled images are leveraged to break through the upper bound of fully-supervised object detection models. Previous semi-supervised methods based on pseudo labels are severely degenerated by noise and prone to overfit to noisy labels, thus are deficient in learning different unlabeled knowledge well. To address this issue, we propose a data-uncertainty guided multi-phase learning method for semi-supervised object detection. We comprehensively consider divergent types of unlabeled images according to their difficulty levels, utilize them in different phases and ensemble models from different phases together to generate ultimate results. Image uncertainty guided easy data selection and region uncertainty guided RoI Re-weighting are involved in multi-phase learning and enable the detector to concentrate on more certain knowledge. Through extensive experiments on PASCAL VOC and MS COCO, we demonstrate that our method behaves extraordinarily compared to baseline approaches and outperforms them by a large margin, more than 3% on VOC and 2% on COCO., Comment: Accepted by CVPR 2021
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- 2021
108. Light Field Reconstruction Using Convolutional Network on EPI and Extended Applications
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Wu, Gaochang, Liu, Yebin, Fang, Lu, Dai, Qionghai, and Chai, Tianyou
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
In this paper, a novel convolutional neural network (CNN)-based framework is developed for light field reconstruction from a sparse set of views. We indicate that the reconstruction can be efficiently modeled as angular restoration on an epipolar plane image (EPI). The main problem in direct reconstruction on the EPI involves an information asymmetry between the spatial and angular dimensions, where the detailed portion in the angular dimensions is damaged by undersampling. Directly upsampling or super-resolving the light field in the angular dimensions causes ghosting effects. To suppress these ghosting effects, we contribute a novel "blur-restoration-deblur" framework. First, the "blur" step is applied to extract the low-frequency components of the light field in the spatial dimensions by convolving each EPI slice with a selected blur kernel. Then, the "restoration" step is implemented by a CNN, which is trained to restore the angular details of the EPI. Finally, we use a non-blind "deblur" operation to recover the spatial high frequencies suppressed by the EPI blur. We evaluate our approach on several datasets, including synthetic scenes, real-world scenes and challenging microscope light field data. We demonstrate the high performance and robustness of the proposed framework compared with state-of-the-art algorithms. We further show extended applications, including depth enhancement and interpolation for unstructured input. More importantly, a novel rendering approach is presented by combining the proposed framework and depth information to handle large disparities., Comment: Published in IEEE TPAMI, 2019
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- 2021
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109. LEAD: LiDAR Extender for Autonomous Driving
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Zhang, Jianing, Li, Wei, Gou, Honggang, Fang, Lu, and Yang, Ruigang
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Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
3D perception using sensors under vehicle industrial standard is the rigid demand in autonomous driving. MEMS LiDAR emerges with irresistible trend due to its lower cost, more robust, and meeting the mass-production standards. However, it suffers small field of view (FoV), slowing down the step of its population. In this paper, we propose LEAD, i.e., LiDAR Extender for Autonomous Driving, to extend the MEMS LiDAR by coupled image w.r.t both FoV and range. We propose a multi-stage propagation strategy based on depth distributions and uncertainty map, which shows effective propagation ability. Moreover, our depth outpainting/propagation network follows a teacher-student training fashion, which transfers depth estimation ability to depth completion network without any scale error passed. To validate the LiDAR extension quality, we utilize a high-precise laser scanner to generate a ground-truth dataset. Quantitative and qualitative evaluations show that our scheme outperforms SOTAs with a large margin. We believe the proposed LEAD along with the dataset would benefit the community w.r.t depth researches.
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- 2021
110. LSTM with Short-Term Bias Compensation to Determine Trading Strategy under Black Swan Events of Taiwan ETF50 Stock
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Ray-I Chang, Chia-Hui Wang, Lien-Chen Wei, and Ya-Fang Lu
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genetic algorithms ,fuzzy systems ,LSTM ,calibration procedure ,ETF50 ,trading strategy ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
This paper uses Long Short-Term Memory (LSTM) networks to predict the stock prices of the Yuanta Taiwan Top 50 ETF (ETF50). To improve the accuracy of the model’s predictions, a calibration procedure called “Short-Term Bias Compensation” (STBC) is proposed to adjust the predicted stock prices. In STBC, the daily prediction error is calculated to estimate the short-term bias (STB) in prediction. Then, the predicted price of its next day will be corrected if this STB has exceeded a certain threshold. In this paper, we apply Genetic Algorithms (GAs) to optimize the parameters used in STBC for providing more confidence in its estimation. Based on these predicted stock prices, we propose a Genetic Fuzzy System (GFS) to determine the trading strategy, with trading points for buying and selling stocks. In GFS, various technical indicators are used to establish the fuzzy rules of the trading strategy, and GAs are used to evolve the best parameters for these fuzzy rules. Our experiments cover over 17 years of data (from 2003 to 2020) for ETF50 to consider black swan events such as the 2020 COVID-19 pandemic, the 2018 US–China trade war, and the 2011 US debt crisis. The first 90% of the data is used as training data, and the last 10% is used as testing data. We use 12 technical indicators of these data as the input of LSTM. The predicted values of LSTM are corrected using STBC and compared to the uncorrected prices. We use Mean Square Error (MSE) to evaluate the prediction accuracy. The results show that STBC can nearly reduce 90% of the prediction error (where MSE drops from 11.5758 to 1.2687). By using GFS with STBC to determine trading points, we achieve a return rate of 32.0%.
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- 2024
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111. Cluster Nodes Integrity Attestation and Monitoring Scheme for Confidential Computing Platform.
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Ketong Shang, Fang Lu, Ke Huang, Yu Qin, Wei Li, and Wei Feng
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- 2023
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112. MetroScope: An Advanced System for Real-Time Detection and Analysis of Metro-Related Threats and Events via Twitter.
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Jianfeng He, Syuan-Ying Wu, Abdulaziz Alhamadani, Chih-Fang Chen, Wen-Fang Lu, Chang-Tien Lu, David Solnick, and Yanlin Li
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- 2023
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113. Neurotoxic effects of 2-ethylhexyl diphenyl phosphate exposure on zebrafish larvae: Insight into inflammation-driven changes in early motor behavior
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Ni, Anyu, Fang, Lu, Xi, Miaocui, Li, Jinyun, Qian, Qiuhui, Wang, Zejun, Wang, Xuedong, Wang, Huili, and Yan, Jin
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- 2024
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114. Deciphering the molecular mediators of triclosan-induced lipid accumulation: Intervention via short-chain fatty acids and miR-101a
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Yan, Jin, Li, Jinyun, Wang, Yang, Song, Jie, Ni, Anyu, Fang, Lu, Xi, Miaocui, Qian, Qiuhui, Wang, Zejun, and Wang, Huili
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- 2024
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115. Real-time fluorescence imaging with indocyanine green during laparoscopic duodenum-preserving pancreatic head resection
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Huang, Jian, Hu, Wei, Liu, Jinghang, Tang, Xinguo, Fan, Yuting, Ran, Longjian, Li, Bowen, Zhang, Jia, Xiong, Hu, Li, Wen, Liang, Bo, Fang, Lu, and Fu, Xiaowei
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- 2024
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116. Heat-shock protein 90 alleviates oxidative stress and reduces apoptosis in liver of Seriola aureovittata (yellowtail kingfish) under high-temperature stress
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Wang, Lin, Jiang, Yan, Fang, Lu, Guan, Changtao, and Xu, Yongjiang
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- 2024
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117. Platform Information Provision and Consumer Search: A Field Experiment
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Fang, Lu, primary, Chen, Yanyou, additional, Farronato, Chiara, additional, Yuan, Zhe, additional, and Wang, Yitong, additional
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- 2024
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118. Rapid detection of neurons in widefield calcium imaging datasets after training with synthetic data
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Zhang, Yuanlong, Zhang, Guoxun, Han, Xiaofei, Wu, Jiamin, Li, Ziwei, Li, Xinyang, Xiao, Guihua, Xie, Hao, Fang, Lu, and Dai, Qionghai
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- 2023
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119. FBXO22 Accelerates Pancreatic Cancer Growth by Deactivation of the Hippo Pathway via Destabilizing LATS2
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Ma, Jingsheng, Wu, Yajun, Cheng, Shibao, Yang, Wentao, Zhong, Lin, Li, Qigen, and Fang, Lu
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- 2023
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120. Progress on the role of exosomal miRNAs in organ fibrosis
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FANG Lu, LIU Ruiqi, LIANG Peng, CEN Ying
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exosome ,exosomal mirnas ,fibrotic disease ,Medicine - Abstract
Exosomes are tiny vesicles that are actively secreted by a variety of cells, which regulate various physiological and pathological processes of the body by carrying proteins, lipids, miRNAs and other biological molecules. Exocrine microRNAs(miRNAs) stably exist in the body fluid circulation and participate in many pathological processes of organs. In organ fibrosis disease, the content of the exosomal miRNAs shows significant differential expression profile as compared with normal tissues, and promotes or inhibits organ fibrosis by regulating different signal pathways. It is considered to be the latest biological indicator for diagnosing organ fibrosis and judging its degree of fibrosis, and a new therapeutic target for fibrosis disease.
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- 2023
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121. Triglyceride glucose index as a predictor of mortality in middle-aged and elderly patients with type 2 diabetes in the US
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Mengjie Zhao, Mengli Xiao, Qin Tan, and Fang Lu
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Medicine ,Science - Abstract
Abstract Despite a wealth of research linking the triglyceride glucose index (TyG index) to metabolic diseases. However, little evidence links the TyG index to all-cause or CVD mortality in middle-aged and elderly individuals with type 2 diabetes (T2D). This study analyzed data from 2998 patients with T2D who participated in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. The TyG index and mortality in middle-aged and elderly T2D patients were investigated using Cox regression models. The nonlinear association between the TyG index and mortality can be understood with the help of a restricted cubic spline (RCS). During a median follow-up period of 82 months, 883 fatalities were observed from all causes and 265 from CVD. The TyG index was found to have a U-shaped relationship with all-cause and CVD mortality in T2D, with cutoffs of 8.95 and 9, respectively, according to the RCS. After controlling for other factors, an increase of 1 unit in the TyG index was related to an increase of 33% in all-cause mortality and 50% in CVD mortality when TyG was ≥ 8.95 and 9. When TyG
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- 2023
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122. Diagnostic performance of radiomics model for preoperative risk categorization in thymic epithelial tumors: a systematic review and meta-analysis
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Xue-Fang Lu and Tie-Yuan Zhu
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Thymic epithelial tumor ,Risk categorization ,Radiomics ,Meta-analysis ,Medical technology ,R855-855.5 - Abstract
Abstract Background Incidental thymus region masses during thoracic examinations are not uncommon. The clinician’s decision-making for treatment largely depends on imaging findings. Due to the lack of specific indicators, it may be of great value to explore the role of radiomics in risk categorization of the thymic epithelial tumors (TETs). Methods Four databases (PubMed, Web of Science, EMBASE and the Cochrane Library) were screened to identify eligible articles reporting radiomics models of diagnostic performance for risk categorization in TETs patients. The quality assessment of diagnostic accuracy studies 2 (QUADAS-2) and radiomics quality score (RQS) were used for methodological quality assessment. The pooled area under the receiver operating characteristic curve (AUC), sensitivity and specificity with their 95% confidence intervals were calculated. Results A total of 2134 patients in 13 studies were included in this meta-analysis. The pooled AUC of 11 studies reporting high/low-risk histologic subtypes was 0.855 (95% CI, 0.817–0.893), while the pooled AUC of 4 studies differentiating stage classification was 0.826 (95% CI, 0.817–0.893). Meta-regression revealed no source of significant heterogeneity. Subgroup analysis demonstrated that the best diagnostic imaging was contrast enhanced computer tomography (CECT) with largest pooled AUC (0.873, 95% CI 0.832–0.914). Publication bias was found to be no significance by Deeks’ funnel plot. Conclusions This present study shows promise for preoperative selection of high-risk TETs patients based on radiomics signatures with current available evidence. However, methodological quality in further studies still needs to be improved for feasibility confirmation and clinical application of radiomics-based models in predicting risk categorization of the thymic epithelial tumors.
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- 2023
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123. Antihypertensive, antioxidant, and renal protective impact of integrated GJD with captopril in spontaneously hypertensive rats
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Shadi A. D. Mohammed, Hanxing Liu, Salem Baldi, Yu Wang, Pingping Chen, Fang Lu, and Shumin Liu
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Medicine ,Science - Abstract
Abstract Hypertension is the most prevalent chronic disease World-wide, and the leading preventable risk factor for cardiovascular disease (CVD). Few patients accomplish the objective of decreasing blood pressure and avoiding hypertensive target organ damage after treatments with antihypertensive agents which opens the door for other treatments, such as herbal-and antihypertensive combination therapy. Captopril (CAP), as a-pril which inhibits angiotensin converting enzyme has long been used in the management of hypertension and CVD. Gedan Jiangya Decoction (GJD) is known for antihypertensive effects in prior studies. The research is aimed to determine whether GJD in combination with captopril has antihypertensive, kidney protective, antioxidant, and vasoactive effects in spontaneously hypertensive rats (SHR). Regular measurements of systolic and diastolic blood pressure (SBP and DBP), and body weight were monitored weekly. H&E staining was utilized to examine histopathology. The combined effects were studied using ELISA, immunohistochemistry, and qRT-PCR. Significant reductions in SBP, DBP, aortic wall thickness, and improvement in renal tissue were observed following GJD + CAP treatment, with increased serum levels of NO, SOD, GSH-Px, and CAT and decreases in Ang II, ET-1, and MDA. Similarly, GJD + CAP treatment of SHR's significantly decreased ET-1 and AGTR1 mRNA and protein expression while increasing eNOS mRNA and protein expression in thoracic aorta and kidney tissue. In conclusion, the present investigation found that GJD + CAP treatment decreases SHR blood pressure, improves aorta remodeling and renal protection, and that this effect could be attributable, in part, due to antioxidant and vascular tone improvement.
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- 2023
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124. Linking renal hypoxia and oxidative stress in chronic kidney disease: Based on clinical subjects and animal models
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Yizeng Xu, Fang Lu, Meng Wang, Lingchen Wang, Chaoyang Ye, Shuohui Yang, and Chen Wang
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Renal hypoxia ,oxidative stress ,chronic kidney disease ,blood oxygenation level-dependent magnetic resonance imaging ,Biology (General) ,QH301-705.5 - Abstract
This study aims to explore the relationships between renal function, hypoxia, and oxidative stress in chronic kidney disease (CKD). Seventy-six non-dialysis patients with CKD stages 1-5 and eight healthy subjects were included in the clinical research. They were divided into three groups: healthy subjects, CKD stages 1-3, and CKD stages 4-5. In the animal study, 16 rat models of CKD were established through 5/6 renal ablation/infarction (A/I) surgery, and 8 normal rats were split into 3 groups: Sham, CKD, and losartan groups. Blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) was used to measure cortical and medullary T2* values (COT2* and MET2*) in all subjects and rats to evaluate renal oxygenation. Biochemical indicators were used to assess renal function and antioxidant capacity. Furthermore, the effects of losartan on renal fibrosis, hypoxia, and oxidative stress were examined using immunoblotting, colorimetric, and fluorometric assays. The results demonstrated significant positive associations between COT2* and MET2* with estimated glomerular filtration rate (eGFR). Patients with CKD stages 4-5 showed significantly lower serum superoxide dismutase (SOD) levels, which also had positive correlations with eGFR, COT2*, and MET2*. Furthermore, losartan treatment resulted in improved renal function and fibrosis, leading to increased levels of COT2*, MET2*, and SOD levels in 5/6 A/I rats. This was accompanied by reduced levels of hypoxia-inducible factor-1 alpha (HIF-1α) and malondialdehyde. Furthermore, losartan restored the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1), and suppressed the expression of Kelch-like ECH-associated protein 1 (Keap1) in 5/6 A/I kidneys. The study indicates that decline in renal oxygenation and antioxidant capacity is associated with the severity of renal failure in CKD. Losartan can potentially alleviate renal hypoxia and oxidative stress in the treatment of CKD via Keap1-Nrf2/HO-1 pathway.
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- 2024
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125. Retinal detachment with multiple macrocysts in Stickler syndrome: case report and review of the literature
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Guina Liu, Ming Hu, Chengcheng Cai, Xiaoshuang Jiang, and Fang Lu
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Stickler syndrome ,rhegmatogenous retinal detachment ,multiple macrocysts ,COL2A1 ,case report ,Medicine (General) ,R5-920 - Abstract
BackgroundStickler syndrome is a hereditary connective tissue disorder associated with ocular, orofacial, musculoskeletal, and auditory impairments. Its main clinical characteristics include retinal detachment, hearing loss, and midface underdevelopment. In clinical practice, macrocyst is rarely reported in retinal detachment cases with Stickler syndrome.Case presentationWe report the case of a 7-year-old child who developed a rhegmatogenous retinal detachment (RRD) in the right eye, accompanied by multiple peripheral macrocysts. The detachment was successfully surgically repaired with vitrectomy, retinal laser photocoagulation, cryotherapy and silicone oil tamponade. During the operation, a mini-retinectomy in the outer layer of each macrocyst was made for vesicular drainage and retinal reattachment. Genetic testing identified a pathogenic point mutation variant (c.1693C>T; p.Arg565Cys) in exon 26 of the COL2A1 gene. Six-months after the operation, the retina remained attached with improvement of best corrected visual acuity to 20/200.ConclusionPatients with Stickler syndrome may develop RRD of different severity. Macrocyst is rarely reported in previous literature of Stickler syndrome. In this case report, we share our experience in treating with multiple macrocysts in RRD and emphasize the importance of periodic follow-up for patients with Stickler syndrome.
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- 2024
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126. Integrated network pharmacology and phosphoproteomic analyses of Baichanting in Parkinson's disease model mice
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Xin Gao, Jiaqi Fu, DongHua Yu, Fang Lu, and Shumin Liu
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Parkinson's disease ,Baichanting compound ,Apoptosis ,Phosphorylation ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
The incidence rate of Parkinson's disease (PD) is increasing yearly. Neuronal apoptosis caused by abnormal protein phosphorylation is closely related to the pathogenesis of Parkinson's disease. At present, few PD-specific apoptosis pathways have been revealed. To investigate the effect of Baichanting (BCT) on apoptosis from the perspective of protein phosphorylation, α-syn transgenic mice were selected to observe the behavioral changes of the mice, and the apoptosis of substantia nigra cells were detected by the HE method and TUNEL method. Network pharmacology combined with phosphorylation proteomics was used to find relevant targets for BCT treatment of PD and was further verified by PRM and western blotting. BCT improved the morphology of neurons in the substantia nigra and reduced neuronal apoptosis. The main enriched pathways in the network pharmacology results were apoptosis, the p53 signaling pathway and autophagy. Western blot results showed that BCT significantly regulated the protein expression levels of BAX, Caspase-3, LC3B, P53 and mTOR and upregulated autophagy to alleviate apoptosis. Using phosphorylated proteomics and PRM validation, we found that Pak5, Grin2b, Scn1a, BcaN, L1cam and Braf are closely correlated with the targets of the web-based pharmacological screen and may be involved in p53/mTOR-mediated autophagy and apoptosis pathways. BCT can inhibit the activation of the p53/mTOR signaling pathway, thereby enhancing the autophagy function of cells, and reducing the apoptosis of neurons which is the main mechanism of its neuroprotective effect.
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- 2024
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127. Integration of 16S rRNA sequencing and metabolomics to investigate the modulatory effect of ginsenoside Rb1 on atherosclerosis
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Yuqin Liang, Jiaqi Fu, Yunhe Shi, Xin Jiang, Fang Lu, and Shumin Liu
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Atherosclerosis ,Ginsenoside Rb1 ,Inflammation ,Gut microbiota ,Short-chain fatty acid ,Metabolomics ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Background: /aims: Atherosclerosis (AS) is the common pathological basis of a variety of cardiovascular diseases (CVD), and has become the main cause of human death worldwide, and the incidence is increasing and younger trend. Ginsenoside Rb1 (Rb1), an important monomer component of the traditional Chinese herb ginseng, known for its ability to improve blood lipid disorders and anti-inflammatory. In addition, Rb1 was proved to be an effective treatment for AS. However, the effect of Rb1 on AS remains to be elucidated. The aim of this study was to investigate the mechanisms of Rb1 in ameliorating AS induced by high-fat diet (HFD). Materials and methods: In this study, we developed an experimental AS model in Sprague-Dawley rats by feeding HFD with intraperitoneal injection of vitamin D3. The potential therapeutic mechanism of Rb1 in AS rats was investigated by detecting the expression of inflammatory factors, microbiome 16S rRNA gene sequencing, short-chain fatty acids (SCFAs) targeted metabolomics and untargeted metabolomics. Results: Rb1 could effectively alleviate the symptoms of AS and suppress the overexpression of inflammation-related factors. Meanwhile, Rb1 altered gut microbial composition and concentration of SCFAs characterized by Bacteroidetes, Actinobacteria, Lactobacillus, Prevotella, Oscillospira enrichment and Desulfovibrio depletion, accompanied by increased production of acetic acid and propionic acid. Moreover, untargeted metabolomics showed that Rb1 considerably improved faecal metabolite profiles, particularly arachidonic acid metabolism and primary bile acid biosynthesis. Conclusion: Rb1 ameliorated the HFD-induced AS, and the mechanism is related to improving intestinal metabolic homeostasis and inhibiting systemic inflammation by regulating gut microbiota.
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- 2024
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128. Epidemiological and clinical characteristics of open globe injuries in Southwest China
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Qin Chen, Licong Liang, Yuzhuo Shi, and Fang Lu
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open globe injuries ,injuries types ,intraocular foreign body ,Southwest China ,ethnic minorities ,Medicine (General) ,R5-920 - Abstract
BackgroundOpen globe injuries (OGIs) are one of the leading causes of monocular vision loss, and the clinical characteristics of OGIs are region specific. The features and patterns of OGIs in Southwest China are poorly known and not well studied. Our study aimed to review the epidemiological and clinical characteristics of patients hospitalized for OGIs in Southwest China.MethodsA retrospective study of OGI patients admitted to the West China Hospital from January 1st, 2015, to December 31st, 2019, was performed. Demographic characteristics and injury details were recorded. The Birmingham Eye Trauma Terminology system and the ocular trauma score (OTS) were used.ResultsA total of 3,014 patients were included. The male-to-female ratio was 5.2:1, and the mean age was 35.6 ± 19.1 years. 15.2% of patients were from the ethnic groups. The highest-risk occupation was the farmer (30.3%), followed by the worker (28.5%). OGIs occurred more frequently in people with middle (37.0%) and primary school (33.1%) education levels. Types of injuries included 46.8% penetration, 21.2% rupture, 2.9% perforation, and 29.1% intraocular foreign body (IOFB). The injuries types differed between age and occupation groups (p
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- 2024
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129. Integrating fecal metabolomics and intestinal microbiota to study the mechanism of cannabidiol in the treatment of idiopathic pulmonary fibrosis
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Mengdi Sun, Feiyu Zhang, Fang Lu, Donghua Yu, Yu Wang, Pingping Chen, and Shumin Liu
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cannabidiol ,pulmonary fibrosis ,metabolomics ,intestinal microbiota ,mechanism ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Introduction: Idiopathic pulmonary fibrosis is a chronic interstitial lung disease characterized by excessive deposition of extracellular matrix. Cannabidiol, a natural component extracted from plant cannabis, has been shown to have therapeutic effects on lung diseases, but its exact mechanism of action is unknown, hindering its therapeutic effectiveness.Methods: To establish a pulmonary fibrosis model, combined with UPLC-Q-TOF/MS metabolomics and 16S rDNA sequencing, to explore cannabidiol’s mechanism in treating pulmonary fibrosis. The rats were randomly divided into the control group, pulmonary fibrosis model group, prednisone treatment group, and cannabidiol low, medium, and high dose groups. The expression levels of HYP, SOD, and MDA in lung tissue and the expression levels of TNF-α, IL-1β, and IL-6 in serum were detected. Intestinal microbiota was detected using UPLC-QTOF/MS analysis of metabolomic properties and 16S rDNA sequencing.Results: Pathological studies and biochemical indexes showed that cannabidiol treatment could significantly alleviate IPF symptoms, significantly reduce the levels of TNF-α, IL-1β, IL-6, MDA, and HYP, and increase the expression level of SOD (p < 0.05). CBD-H can regulate Lachnospiraceae_NK4A136_group, Pseudomonas, Clostridia_UCG-014, Collinsella, Prevotella, [Eubacterium]_coprostanoligenes_group, Fusobacterium, Ruminococcus, and Streptococcus, it can restore intestinal microbiota function and reverse fecal metabolism trend. It also plays the role of fibrosis through the metabolism of linoleic acid, glycerol, linolenic acid, and sphingolipid.Discussion: Cannabidiol reverses intestinal microbiota imbalance and attenuates pulmonary fibrosis in rats through anti-inflammatory, antioxidant, and anti-fibrotic effects. This study lays the foundation for future research on the pathological mechanisms of IPF and the development of new drug candidates.
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- 2024
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130. The effects of NDM-5 on Escherichia coli and the screening of interacting proteins
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Lin Li, Yiming Gao, Longbo Wang, Fang Lu, Qianyu Ji, Yanfang Zhang, Shuo Yang, Ping Cheng, Feifei Sun, and Shaoqi Qu
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Escherichia coli ,NDM-5 ,transcriptomics ,GST pull-down ,mass spectrometry ,Microbiology ,QR1-502 - Abstract
Carbapenem-resistant Escherichia coli (E. coli) strains are widely distributed and spreading rapidly, creating significant challenges for clinical therapeutics. NDM-5, a novel mutant of New Delhi Metallo-β-Lactamase-1 (NDM-1), exhibits high hydrolase activity toward carbapenems. Since the genetic backgrounds of clinically isolated carbapenem-resistant E. coli are heterogeneous, it is difficult to accurately evaluate the impact of blaNDM–5 on antibiotic resistance. Herein, E. coli BL21 was transformed with a plasmid harboring blaNDM–5, and the resultant strain was named BL21 (pET-28a-blaNDM–5). Consistent with the findings of previous studies, the introduction of exogenous blaNDM–5 resulted in markedly greater resistance of E. coli to multiple β-lactam antibiotics. Compared with BL21 (pET-28a), BL21 (pET-28a-blaNDM–5) exhibited reduced motility but a significant increase in biofilm formation capacity. Furthermore, transcriptome sequencing was conducted to compare the transcriptional differences between BL21 (pET-28a) and BL21 (pET-28a-blaNDM–5). A total of 461 differentially expressed genes were identified, including those related to antibiotic resistance, such as genes associated with the active efflux system (yddA, mcbR and emrY), pili (csgC, csgF and fimD), biofilm formation (csgD, csgB and ecpR) and antioxidant processes (nuoG). Finally, the pGS21a plasmid harboring blaNDM–5 was transformed into E. coli Rosetta2, after which the expression of the NDM-5 protein was induced using isopropyl-β-D-thiogalactoside (IPTG). Using glutathione-S-transferase (GST) pull-down assays, total proteins from E. coli were scanned to screen out 82 proteins that potentially interacted with NDM-5. Our findings provide new insight into the identified proteins to identify potential antibiotic targets and design novel inhibitors of carbapenem-resistant bacteria.
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- 2024
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131. Case report: Malignant transformation of ovarian endometrioma during long term use of dienogest in a young lady
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Yi-Ting Chang, Ting-Fang Lu, Lou Sun, Yu-Hsiang Shih, Shih-Tien Hsu, Chin-Ku Liu, Sheau-Feng Hwang, and Chien-Hsing Lu
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dienogest ,endometrioma ,endometriosis ,ovarian cancer ,clear cell carcinoma ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Endometriosis is a benign disease, which is also regarded as a precursor to ovarian malignancy. Dienogest is a progestin treatment for endometriosis with efficacy and tolerability. A 35-year-old Taiwanese lady with ovarian endometrioma had taken dienogest for the last 5 years. During sonographic follow-up, surgery was suggested owing to suspicious of malignant transformation of ovarian endometrioma. While she hesitated and turned to receive two cycles of oocyte retrieval because of nulliparity. Meanwhile, more papillary growth in the ovarian endometrioma with intratumor flow was found during follow-up. Laparoscopic enucleation was performed later, and pathology revealed clear cell carcinoma with peritoneal involvement, at least FIGO stage IIB. She then underwent debulking surgery to grossly no residual tumor and received adjuvant chemotherapy with no tumor recurrence in post-operative 17-months follow-up. Considering fertility preservation, conservative treatment of ovarian endometrioma is typically indicated for those women who have not yet completed childbearing. However, malignant transformation may still occur despite long-term progestin treatment. Therefore, careful image follow-up is still indispensable.
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- 2024
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132. Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit
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Zhou, Tiankuang, Lin, Xing, Wu, Jiamin, Chen, Yitong, Xie, Hao, Li, Yipeng, Fan, Jintao, Wu, Huaqiang, Fang, Lu, and Dai, Qionghai
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Machine Learning ,Computer Science - Neural and Evolutionary Computing ,Physics - Optics - Abstract
Application-specific optical processors have been considered disruptive technologies for modern computing that can fundamentally accelerate the development of artificial intelligence (AI) by offering substantially improved computing performance. Recent advancements in optical neural network architectures for neural information processing have been applied to perform various machine learning tasks. However, the existing architectures have limited complexity and performance; and each of them requires its own dedicated design that cannot be reconfigured to switch between different neural network models for different applications after deployment. Here, we propose an optoelectronic reconfigurable computing paradigm by constructing a diffractive processing unit (DPU) that can efficiently support different neural networks and achieve a high model complexity with millions of neurons. It allocates almost all of its computational operations optically and achieves extremely high speed of data modulation and large-scale network parameter updating by dynamically programming optical modulators and photodetectors. We demonstrated the reconfiguration of the DPU to implement various diffractive feedforward and recurrent neural networks and developed a novel adaptive training approach to circumvent the system imperfections. We applied the trained networks for high-speed classifying of handwritten digit images and human action videos over benchmark datasets, and the experimental results revealed a comparable classification accuracy to the electronic computing approaches. Furthermore, our prototype system built with off-the-shelf optoelectronic components surpasses the performance of state-of-the-art graphics processing units (GPUs) by several times on computing speed and more than an order of magnitude on system energy efficiency.
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- 2020
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133. Spatial-Angular Attention Network for Light Field Reconstruction
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Wu, Gaochang, Wang, Yingqian, Liu, Yebin, Fang, Lu, and Chai, Tianyou
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Typical learning-based light field reconstruction methods demand in constructing a large receptive field by deepening the network to capture correspondences between input views. In this paper, we propose a spatial-angular attention network to perceive correspondences in the light field non-locally, and reconstruction high angular resolution light field in an end-to-end manner. Motivated by the non-local attention mechanism, a spatial-angular attention module specifically for the high-dimensional light field data is introduced to compute the responses from all the positions in the epipolar plane for each pixel in the light field, and generate an attention map that captures correspondences along the angular dimension. We then propose a multi-scale reconstruction structure to efficiently implement the non-local attention in the low spatial scale, while also preserving the high frequency components in the high spatial scales. Extensive experiments demonstrate the superior performance of the proposed spatial-angular attention network for reconstructing sparsely-sampled light fields with non-Lambertian effects., Comment: 15 pages, 13 figures and 5 tables, Accepted by IEEE Transactions on Image Processing (IEEE TIP)
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- 2020
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134. Zoom in to the details of human-centric videos
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Li, Guanghan, Zhao, Yaping, Ji, Mengqi, Yuan, Xiaoyun, and Fang, Lu
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Presenting high-resolution (HR) human appearance is always critical for the human-centric videos. However, current imagery equipment can hardly capture HR details all the time. Existing super-resolution algorithms barely mitigate the problem by only considering universal and low-level priors of im-age patches. In contrast, our algorithm is under bias towards the human body super-resolution by taking advantage of high-level prior defined by HR human appearance. Firstly, a motion analysis module extracts inherent motion pattern from the HR reference video to refine the pose estimation of the low-resolution (LR) sequence. Furthermore, a human body reconstruction module maps the HR texture in the reference frames onto a 3D mesh model. Consequently, the input LR videos get super-resolved HR human sequences are generated conditioned on the original LR videos as well as few HR reference frames. Experiments on an existing dataset and real-world data captured by hybrid cameras show that our approach generates superior visual quality of human body compared with the traditional method., Comment: 5 pages, 6 figures, accepted for presentation at IEEE ICIP 2020
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- 2020
135. SurfaceNet+: An End-to-end 3D Neural Network for Very Sparse Multi-view Stereopsis
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Ji, Mengqi, Zhang, Jinzhi, Dai, Qionghai, and Fang, Lu
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Multi-view stereopsis (MVS) tries to recover the 3D model from 2D images. As the observations become sparser, the significant 3D information loss makes the MVS problem more challenging. Instead of only focusing on densely sampled conditions, we investigate sparse-MVS with large baseline angles since the sparser sensation is more practical and more cost-efficient. By investigating various observation sparsities, we show that the classical depth-fusion pipeline becomes powerless for the case with a larger baseline angle that worsens the photo-consistency check. As another line of the solution, we present SurfaceNet+, a volumetric method to handle the 'incompleteness' and the 'inaccuracy' problems induced by a very sparse MVS setup. Specifically, the former problem is handled by a novel volume-wise view selection approach. It owns superiority in selecting valid views while discarding invalid occluded views by considering the geometric prior. Furthermore, the latter problem is handled via a multi-scale strategy that consequently refines the recovered geometry around the region with the repeating pattern. The experiments demonstrate the tremendous performance gap between SurfaceNet+ and state-of-the-art methods in terms of precision and recall. Under the extreme sparse-MVS settings in two datasets, where existing methods can only return very few points, SurfaceNet+ still works as well as in the dense MVS setting. The benchmark and the implementation are publicly available at https://github.com/mjiUST/SurfaceNet-plus., Comment: Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), May 2020
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- 2020
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136. MulayCap: Multi-layer Human Performance Capture Using A Monocular Video Camera
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Su, Zhaoqi, Wan, Weilin, Yu, Tao, Liu, Lingjie, Fang, Lu, Wang, Wenping, and Liu, Yebin
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We introduce MulayCap, a novel human performance capture method using a monocular video camera without the need for pre-scanning. The method uses "multi-layer" representations for geometry reconstruction and texture rendering, respectively. For geometry reconstruction, we decompose the clothed human into multiple geometry layers, namely a body mesh layer and a garment piece layer. The key technique behind is a Garment-from-Video (GfV) method for optimizing the garment shape and reconstructing the dynamic cloth to fit the input video sequence, based on a cloth simulation model which is effectively solved with gradient descent. For texture rendering, we decompose each input image frame into a shading layer and an albedo layer, and propose a method for fusing a fixed albedo map and solving for detailed garment geometry using the shading layer. Compared with existing single view human performance capture systems, our "multi-layer" approach bypasses the tedious and time consuming scanning step for obtaining a human specific mesh template. Experimental results demonstrate that MulayCap produces realistic rendering of dynamically changing details that has not been achieved in any previous monocular video camera systems. Benefiting from its fully semantic modeling, MulayCap can be applied to various important editing applications, such as cloth editing, re-targeting, relighting, and AR applications.
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- 2020
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137. OccuSeg: Occupancy-aware 3D Instance Segmentation
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Han, Lei, Zheng, Tian, Xu, Lan, and Fang, Lu
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Computer Science - Computer Vision and Pattern Recognition - Abstract
3D instance segmentation, with a variety of applications in robotics and augmented reality, is in large demands these days. Unlike 2D images that are projective observations of the environment, 3D models provide metric reconstruction of the scenes without occlusion or scale ambiguity. In this paper, we define "3D occupancy size", as the number of voxels occupied by each instance. It owns advantages of robustness in prediction, on which basis, OccuSeg, an occupancy-aware 3D instance segmentation scheme is proposed. Our multi-task learning produces both occupancy signal and embedding representations, where the training of spatial and feature embeddings varies with their difference in scale-aware. Our clustering scheme benefits from the reliable comparison between the predicted occupancy size and the clustered occupancy size, which encourages hard samples being correctly clustered and avoids over segmentation. The proposed approach achieves state-of-the-art performance on 3 real-world datasets, i.e. ScanNetV2, S3DIS and SceneNN, while maintaining high efficiency., Comment: CVPR 2020, video this https URL https://youtu.be/co7y6LQ7Kqc
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- 2020
138. PANDA: A Gigapixel-level Human-centric Video Dataset
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Wang, Xueyang, Zhang, Xiya, Zhu, Yinheng, Guo, Yuchen, Yuan, Xiaoyun, Xiang, Liuyu, Wang, Zerun, Ding, Guiguang, Brady, David J, Dai, Qionghai, and Fang, Lu
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We present PANDA, the first gigaPixel-level humAN-centric viDeo dAtaset, for large-scale, long-term, and multi-object visual analysis. The videos in PANDA were captured by a gigapixel camera and cover real-world scenes with both wide field-of-view (~1 square kilometer area) and high-resolution details (~gigapixel-level/frame). The scenes may contain 4k head counts with over 100x scale variation. PANDA provides enriched and hierarchical ground-truth annotations, including 15,974.6k bounding boxes, 111.8k fine-grained attribute labels, 12.7k trajectories, 2.2k groups and 2.9k interactions. We benchmark the human detection and tracking tasks. Due to the vast variance of pedestrian pose, scale, occlusion and trajectory, existing approaches are challenged by both accuracy and efficiency. Given the uniqueness of PANDA with both wide FoV and high resolution, a new task of interaction-aware group detection is introduced. We design a 'global-to-local zoom-in' framework, where global trajectories and local interactions are simultaneously encoded, yielding promising results. We believe PANDA will contribute to the community of artificial intelligence and praxeology by understanding human behaviors and interactions in large-scale real-world scenes. PANDA Website: http://www.panda-dataset.com., Comment: Accepted by IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020
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- 2020
139. Smart Cameras
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Brady, David J., Hu, Minghao, Wang, Chengyu, Yan, Xuefei, Fang, Lu, Zhu, Yiwnheng, Tan, Yang, Cheng, Ming, and Ma, Zhan
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Electrical Engineering and Systems Science - Image and Video Processing - Abstract
We review camera architecture in the age of artificial intelligence. Modern cameras use physical components and software to capture, compress and display image data. Over the past 5 years, deep learning solutions have become superior to traditional algorithms for each of these functions. Deep learning enables 10-100x reduction in electrical sensor power per pixel, 10x improvement in depth of field and dynamic range and 10-100x improvement in image pixel count. Deep learning enables multiframe and multiaperture solutions that fundamentally shift the goals of physical camera design. Here we review the state of the art of deep learning in camera operations and consider the impact of AI on the physical design of cameras.
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- 2020
140. Training large-scale optoelectronic neural networks with dual-neuron optical-artificial learning
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Yuan, Xiaoyun, Wang, Yong, Xu, Zhihao, Zhou, Tiankuang, and Fang, Lu
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- 2023
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141. Neuroprotective effect and possible mechanism of edaravone in rat models of spinal cord injury: a protocol for a systematic review and meta-analysis
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Wang, Xiao-bo, Zhou, Long-yun, Chen, Xu-qing, Li, Ran, Yu, Bin-bin, Pan, Meng-xiao, Fang, Lu, Li, Jian, Cui, Xue-jun, Yao, Min, and Lu, Xiao
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- 2023
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142. Large depth-of-field ultra-compact microscope by progressive optimization and deep learning
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Zhang, Yuanlong, Song, Xiaofei, Xie, Jiachen, Hu, Jing, Chen, Jiawei, Li, Xiang, Zhang, Haiyu, Zhou, Qiqun, Yuan, Lekang, Kong, Chui, Shen, Yibing, Wu, Jiamin, Fang, Lu, and Dai, Qionghai
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- 2023
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143. Enhancing the Sensitivity of the Virus BioResistor by Overoxidation: Detecting IgG Antibodies
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Bhasin, Apurva, Choi, Eric J, Drago, Nicholas P, Garrido, Jason E, Sanders, Emily C, Shin, Jihoon, Andoni, Ilektra, Kim, Dong-Hwan, Fang, Lu, Weiss, Gregory A, and Penner, Reginald M
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Biotechnology ,Biosensing Techniques ,Bridged Bicyclo Compounds ,Heterocyclic ,Humans ,Immunoglobulin G ,Limit of Detection ,Polymers ,Analytical Chemistry ,Other Chemical Sciences - Abstract
The Virus BioResistor (VBR) is a biosensor capable of rapid and sensitive detection of small protein disease markers using a simple dip-and-read modality. For example, the bladder cancer-associated protein DJ-1 (22 kDa) can be detected in human urine within 1.0 min with a limit of detection (LOD) of 10 pM. The VBR uses engineered virus particles as receptors to recognize and selectively bind the protein of interest. These virus particles are entrained in a conductive poly(3,4-ethylenedioxythiophene) or PEDOT channel. The electrical impedance of the channel increases when the target protein is bound by the virus particles. But VBRs exhibit a sensitivity that is inversely related to the molecular weight of the protein target. Thus, large proteins, such as IgG antibodies (150 kDa), can be undetectable even at high concentrations. We demonstrate that the electrochemical overoxidation of the VBR's PEDOT channel increases its electrical impedance, conferring enhanced sensitivity for both small and large proteins. Overoxidation makes possible the detection of two antibodies, undetectable at a normal VBR, with a limit of detection of 40 ng/mL (250 pM), and a dynamic range for quantitation extending to 600 ng/mL.
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- 2021
144. Prognostic role of E2F1 gene expression in human cancer: a meta-analysis
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Jingjing Li, Wen Bi, Fang Lu, Bei Pan, Mengqiu Xiong, Lubanga Nasifu, Zhenlin Nie, and Bangshun He
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E2F1 ,Cancer ,Breast cancer ,Prognosis ,Meta-analysis ,Gene expression ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Objective E2F1 has been confirmed to be highly expressed in a variety of cancers. To better understand the prognostic value of E2F1 in cancer patients, this study was conducted to comprehensively evaluate the prognostic value of E2F1 in cancer according to published data. Method PubMed, Web of Science and CNKI database were searched until May 31th, 2022 by using key words to retrieve the published essays on the role of E2F1 expression in the prognostic value of cancer. The essays were identified according to the inclusion and exclusion criteria. The pooled result of hazard ratio and 95% confidence interval was calculated with Stata17.0 software. Result A total of 17 articles were included in this study involved in 4481 cancer patients. The pooled results showed that higher E2F1 expression was significantly correlated with unfavorable overall survival (HR = 1.10, I 2 = 95.3%, *P Heterogeneity = 0.000) and disease-free survival (HR = 1.41, I 2 = 95.2%, *P Heterogeneity = 0.000) of cancer patients. Such a significant association of was maintained subgroup of sample size of patients (> 150: for OS, HR = 1.77, and for DFS, HR = 0.91; or
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- 2023
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145. Study on the weak decay between two heavy baryons $${\mathcal {B}}_i(\frac{1}{2}^+)\rightarrow {\mathcal {B}}_f(\frac{3}{2}^+)$$ B i ( 1 2 + ) → B f ( 3 2 + ) in the light-front quark model
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Fang Lu, Hong-Wei Ke, Xiao-Hai Liu, and Yan-Liang Shi
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Astrophysics ,QB460-466 ,Nuclear and particle physics. Atomic energy. Radioactivity ,QC770-798 - Abstract
Abstract In this work, we study the weak decay between two heavy baryons $${\mathcal {B}}_i(\frac{1}{2}^+)\rightarrow {\mathcal {B}}_f(\frac{3}{2}^+)$$ B i ( 1 2 + ) → B f ( 3 2 + ) in the light-front quark model where three-quark picture is employed for baryon. We derive general form of transition amplitude of $$ {\mathcal {B}}_i(\frac{1}{2}^+)\rightarrow {\mathcal {B}}_f(\frac{3}{2}^+)$$ B i ( 1 2 + ) → B f ( 3 2 + ) , and analyze two specific cases of transitions: the weak decays of single heavy baryon $$\Sigma _{b} \rightarrow \Sigma _{c}^*$$ Σ b → Σ c ∗ and the decays of double-charmed baryon $$\Xi _{cc}\rightarrow \Sigma _{c}^*(\Xi _{c}^*)$$ Ξ cc → Σ c ∗ ( Ξ c ∗ ) . We compute the hadronic form factors for the transitions and apply them to study the decay widths of the semi-leptonic $${\mathcal {B}}_i(\frac{1}{2}^+)\rightarrow {\mathcal {B}}_f(\frac{3}{2}^+) l\bar{\nu }_l$$ B i ( 1 2 + ) → B f ( 3 2 + ) l ν ¯ l and non-leptonic $${\mathcal {B}}_i(\frac{1}{2}^+)\rightarrow {\mathcal {B}}_f(\frac{3}{2}^+)M$$ B i ( 1 2 + ) → B f ( 3 2 + ) M . Previously we studied the transition $$\Sigma _{b} \rightarrow \Sigma _{c}^*$$ Σ b → Σ c ∗ with the quark–diquark picture of baryon in the light-front quark model. Here we revisit this transition with three-quark picture of baryon. At the quark level, the transition $$\Sigma _{b} \rightarrow \Sigma _{c}^*$$ Σ b → Σ c ∗ is induced by the $$b\rightarrow c$$ b → c transition.The subsystem of the two unchanged light quarks which possesses definite and same spin in initial and final state can be viewed as a spectator, so the spectator approximation can be applied directly. For the weak decay of doubly charmed baryon $$\Xi _{cc}$$ Ξ cc , a c quark decays to a light quark $$q_1$$ q 1 , so both the initial state cc and final state $$q_1q_2$$ q 1 q 2 ( $$q_1$$ q 1 and the original $$q_2$$ q 2 in initial state may be the same flavor quarks) which possess definite spin are no longer spectators. A rearrangement of quarks for initial and final states is adopted to isolate the unchanged subsystem $$cq_2$$ c q 2 which can be viewed as the spectator approximately. Future measurements on these channels will constrain the nonperturbative parameter in the wavefunctions and test the model predictions.
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- 2023
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146. Effectiveness and safety analysis of Danggui Shaoyao Powder for the treatment of non-alcoholic fatty liver disease: study protocol for a randomized, double-blind, placebo-controlled clinical trial
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Qian Huang, Ziming An, Xin Xin, Qinmei Sun, Siting Gao, Sheng Lv, Xiao Xu, Shuohui Yang, Fang Lu, Jie Yuan, Yu Zhao, Yiyang Hu, Ping Liu, and Qin Feng
- Subjects
Danggui Shaoyao Powder ,Non-alcoholic fatty liver disease ,Randomized controlled trial ,Traditional Chinese medicine ,Other systems of medicine ,RZ201-999 - Abstract
Abstract Background The incidence of non-alcoholic fatty liver disease (NAFLD) has been on the rise in recent years, and there are no effective drugs to treat NAFLD; therefore, effective prevention and treatment of NAFLD have become a new challenge. Danggui Shaoyao Powder (DGSY) is a classic prescription commonly used in clinical practice and has been shown to reduce hepatic steatosis in patients with NAFLD. In addition, previous studies have shown that DGSY can alleviate hepatic steatosis and inflammation in NAFLD mice. Although clinical practice and basic studies have shown that DGSY is effective in NAFLD, high levels of clinical evidence are lacking. Therefore, a standardized RCT study protocol is required to evaluate its clinical efficacy and safety. Methods and analysis This study will be a randomized, double-blind, placebo-controlled, and single-center trial. According to the random number table, NAFLD participants will be randomly divided into the DGSY or placebo group for 24 weeks. The follow-up period will be 6 weeks after drug withdrawal. The primary outcome is the relative change in MRI-proton density fat fraction (MRI-PDFF) from baseline to 24 weeks. Absolute changes in serum alanine aminotransferase (ALT), liver stiffness measurement (LSM), body mass index (BMI), blood lipid, blood glucose, and insulin resistance index will be selected as secondary outcomes to comprehensively evaluate the clinical efficacy of DGSY in the treatment of NAFLD. The safety of DGSY will be evaluated by renal function, routine blood and urine tests, and electrocardiogram. Discussion This study will provide evidence-based medical corroboration for the clinical application of DGSY and promote the development and application of this classic prescription. Trial registration http://www.chictr.org.cn . Trial number: ChiCTR2000029144. Registered on 15 Jan 2020.
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- 2023
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147. Laparoscopic Transcystic Common Bile Duct Exploration: 8-Year Experience at a Single Institution
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Huang, Jian, Hu, Wei, Liu, Jinghang, Tang, Xinguo, Fan, Yuting, Xu, Liangzhi, Liu, Tiande, Xiong, Hu, Li, Wen, Fu, Xiaowei, Liang, Bo, and Fang, Lu
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- 2023
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148. Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit
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Li, Xinyang, Li, Yixin, Zhou, Yiliang, Wu, Jiamin, Zhao, Zhifeng, Fan, Jiaqi, Deng, Fei, Wu, Zhaofa, Xiao, Guihua, He, Jing, Zhang, Yuanlong, Zhang, Guoxun, Hu, Xiaowan, Chen, Xingye, Zhang, Yi, Qiao, Hui, Xie, Hao, Li, Yulong, Wang, Haoqian, Fang, Lu, and Dai, Qionghai
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- 2023
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149. The Impact of Distant Hurricane on Local Housing Markets
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Fang, Lu, Li, Lingxiao, and Yavas, Abdullah
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- 2023
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150. OrthoVenn3: an integrated platform for exploring and visualizing orthologous data across genomes.
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Jiahe Sun, Fang Lu, Yongjiang Luo, Lingzi Bie, Ling Xu, and Yi Wang 0052
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- 2023
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