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Elevated intraspinal pressure in traumatic spinal cord injury is a promising therapeutic target

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Neural Regeneration Research 2022年第8期17卷 1703-1710页

作者： Chao-Hua Yang Zheng-Xue Quan Gao-Ju Wang Tao He Zhi-Yu Chen Qiao-Chu Li Jin Yang Qing wang Department of Orthopedics The Affiliated Hospital of Southwest Medical UniversityLuzhouSichuan ProvinceChina Department of Orthopedics The First Affiliated Hospital of Chongqing Medical UniversityChongqingChina

The currently recommended management for acute traumatic spinal cord injury aims to reduce the incidence of secondary injury and promote functional recovery.Elevated intraspinal pressure(ISP)likely plays an important role in the processes involved in secondary spinal cord injury,and should not be overlooked.However,the factors and detailed time course contributing to elevated ISP and its impact on pathophysiology after traumatic spinal cord injury have not been reviewed in the literature.Here,we review the etiology and progression of elevated ISP,as well as potential therapeutic measures that target elevated ISP.Elevated ISP is a time-dependent process that is mainly caused by hemorrhage,edema,and blood-spinal cord barrier destruction and peaks at 3 days after traumatic spinal cord injury.Duraplasty and hypertonic saline may be promising treatments for reducing ISP within this time window.Other potential treatments such as decompression,spinal cord incision,hemostasis,and methylprednisolone treatment require further validation.

关键词： blood-spinal cord barrier decompression duraplasty durotomy edema hemorrhage intraspinal pressure myelotomy spinal cord injury therapeutic target

Partial advances in the diagnosis and treatment of gastrointestinal cancer

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Chronic Diseases and Translational Medicine 2023年第1期9卷 1-4页

作者： Mingguang ju Ziming gao Kai Li Zhenning wang Department of Surgical Oncology and General Surgery Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal TumorsMinistry of EducationThe First Affiliated Hospital of China Medical UniversityShenyangChina

Gastrointestinal cancers are difficult to be cured with a high recurrence rate accounting for more than 50%of global cancer-related morbidity and mortality.1 Many patients with gastrointestinal cancer are diagnosed at a late stage.Over the past few decades,basic and clinical research with new technologies have made significant progress in the diagnosis and treatment of gastrointestinal cancers,which significantly improved the quality of life and prolonged the survival of patients.Here,we briefly highlight several advances in diagnosing and treating gastrointestinal tumors,mainly gastric cancer and colorectal cancer from multiple perspectives.

关键词： advances diagnosis gastrointestinal cancer treatment

A Quaternion Two-Stream R-CNN Network for Pixel-Level Color Image Splicing Localization

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Chinese Journal of Electronics 2021年第6期30卷 1069-1079页

作者： CHEN Beijing ju Xingwang gao Ye wang Jinwei Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science &Technology School of Computer Nanjing University of Information Science & Technology Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET) Nanjing University of Information Science & Technology

Recently, Zhou et al. designed a twostream faster Region-Convolutional neural networks(RCNN) model RGB-N for color image splicing localization in CVPR2018. However, the RGB-N locates spliced regions only at block-level and ignores the entirety and inherent correlation of three channels. Therefore, an improved quaternion two-stream R-CNN model is proposed to solve these drawbacks: a mask branch combining fully convolutional network and condition random field is added for locating spliced regions at pixel-level; quaternion representation of color images is used to process color spliced images in a holistical way. In addition, feature pyramid network based on quaternion residual network is considered to extract multi-scale features for color spliced images; attention region proposal network is combined with attention mechanism and is designed to pay more attention to the spliced regions; a high-pass filter designed for image splicing detection specifically is adopted to replace steganalysis rich model filter in the RGB-N to obtain noise input for the noise stream. Experimental results on a new synthetic dataset and three standard forgery datasets demonstrate that the proposed method is superior to the existing methods in the abilities of localization, generalization, and robustness.

关键词： Color image Quaternion Image splicing localization R-CNN ResNet

Analysis on the spatial pattern and evolution of China's petroleum trade under the dual effect of international oil price and “Belt and Road” Framework

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Petroleum Science 2023年第6期20卷 3945-3953页

作者： Shuang-Ying wang Ya-Yao Hua Bao-ju Li Ping Wei Peng gao Business School Qingdao University of TechnologyQingdao266555ShandongChina Changdao Comprehensive Test Area Economic Development Bureau Yantai265800ShandongChina

“Belt and Road” is the important origin of oil import in China. Based on social network analysis and stochastic frontier gravity model, this paper studied the characteristic evolution and influence factor of oil import network between China and “Belt and Road” countries. Then by constructing a stochastic frontier gravity model including the crude oil future price and oil importing price, it found that the international crude oil future price, the oil importing price, the political situation, the trade agreements have the effects on the China's oil import from “Belt and Road” region. It provided suggestions for improving the spatial pattern of China's petroleum trade.

关键词： "Belt and Road" Oil import network Stochastic frontier gravity model International oil futures price

Differences in geochemistry and hydrocarbon generation of sourcerock samples dominated by telalginite and lamalginite: A case study on the Permian saline lacustrine source rocks in the Jimusaer Sag, NW China

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Petroleum Science 2023年第1期20卷 141-160页

作者： Shi-ju Liu Gang gao Wen-Zhe Gang Bao-Li Xiang Ming wang College of Geosciences China University of PetroleumNo.18 Fuxue RoadBeijing102249China State Key Laboratory of Petroleum Resource and Prospecting China University of PetroleumNo.18 Fuxue RoadBeijing102249China Experimental Testing Institute PetroChina Xinjiang Oilfield CompanyKaramayXinjiang834000China

The Middle Permian Lucaogou Formation in Northwestern China mainly contains typical saline lacustrine oil shale.To study the differences in geochemistry and hydrocarbon generation of source-rock samples in Lucaogou Formation in Jimusaer Sag,57 core samples from two boreholes were analyzed herein by performing total organic carbon(TOC)analysis,RockeEval pyrolysis,and gas chromatographicemass spectrometry experiments on saturated hydrocarbons.The kinetics of oil generation were studied using two samples comprising typical maceral components.The results showed that the hydrocarbons produced by telalginite are relatively rich in pristane(Pr),phytane(Ph),b-carotane,high-carbon normal alkanes,and C29 regular steranes.Hydrocarbons produced by lamalginite contain a significantly higher content of C20 tricyclic terpanes(TT),C21TT,C24 tetracyclic terpanes(TeT),C29 norhopane,and C28 regular sterane.Based on the pyrolysis and biomarker compound parameters,telalginite has a higher conversion rate for hydrocarbons than lamalginite in the low-mature to mature stage,which is consistent with their kinetic analysis.Lamalginite source rock displays a much narrower distribution of activation energies than telalginite source rocks.Such narrower activation energy distribution effectively narrows the main stage of hydrocarbon generation.In addition,the activation energy distribution of lamalginite concentrated in the high-value interval,indicating the characteristics of the relatively lagging hydrocarbon generation of lamalginite.

关键词： Maceral component Biomarker compounds Oil generation kinetics Activation energy Lucaogou formation

MouseVenue3D:A Markerless Three-Dimension Behavioral Tracking System for Matching Two-Photon Brain Imaging in Free-Moving Mice

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Neuroscience Bulletin 2022年第3期38卷 303-317页

作者： Yaning Han Kang Huang Ke Chen Hongli Pan Furong ju Yueyue Long gao gao Runlong Wu Aimin wang Liping wang Pengfei Wei Shenzhen Key Laboratory of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science Guangdong Provincial Key Laboratory of Brain Connectome and BehaviorCAS Center for Excellence in Brain Science and Intelligence TechnologyBrain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen-Hong Kong Institute of Brain ScienceShenzhen Fundamental Research InstitutionsShenzhen518055China University of Chinese Academy of Sciences Beijing100049China University of Rochester RochesterNY14627USA Honam University Gwangju62399South Korea State Key Laboratory of Membrane Biology Institute of Molecular MedicinePeking UniversityBeijing100101China Department of Electronics Peking UniversityBeijing100871China State Key Laboratory of Advanced Optical Communication Systems and Networks Peking UniversityBeijing100101China

Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system that focuses on rodents.Here,we present MouseVenue3D,an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents.We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module.Then,we validated this process in behavior recognition tasks,and showed that 3-D behavioral data achieved higher accuracy than 2-D data.Subsequently,MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse.Finally,we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice.Our findings reveal that subtle,spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.

关键词： Computational neuroethology Behavioral and neural recording 3-D pose estimation Multi-view cameras Automatic calibration

Influential factors and control of water inrush in a coal seam as the main aquifer

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International Journal of Mining Science and Technology 2018年第2期28卷 187-193页

作者： gao Rui Yan Hao ju Feng Mei Xianchen wang Xiulin Key Laboratory of Deep Coal Resource Mining Ministry of Education School of Mines China University of Mining and Technology State Key Laboratory for Geomechanics & Deep Underground Engineering China University of Mining and Technology Huadian Coal Industry Group Co. Ltd.

In this paper, a combination of field measurement, theoretical analysis and numerical simulation were used to study the main control factors of coal mine water inrush in a main aquifer coal seam and its control scheme. On the basis of revealing and analyzing the coal seam as the main aquifer in western coal mine of Xiao Jihan coal mine, the simulation software of PHASE-2D was applied to analyze the water inflow under different influencing factors. The results showed that water inflow increases logarithmically with the coal seam thickness, increases as a power function with the permeability coefficient of the coal seam, and increases linearly with the coal seam burial depth and the head pressure; The evaluation model for the factors of coal seam water inrush was gained by using nonlinear regression analysis with SPSS. The mine water inrush risk evaluation partition within the scope of the mining field was obtained,through the engineering application in Xiao Jihan coal mine. To ensure the safe and efficient production of the mine, we studied the coal mine water disaster prevention and control measures of a main aquifer coal seam in aspects of roadway driving and coal seam mining.

关键词： Coal seam Main aquifer Water inrush Influential factors Control

Ordering in liquid and its heredity impact on phase transformation of Mg-Al-Ca alloys

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镁合金学报(英文) 2023年第6期11卷 2006-2017页

作者： Jiang You Cheng wang Shun-Li Shang Yipeng gao Hong ju Hong Ning Yi wang Hui-Yuan wang Zi-Kui Liu State Key Laboratory of Automotive Simulation and Control&School of Materials Science and Engineering Jilin UniversityNanling Campus No.5988 enmin StreetChangchun 130025China International Center of Future Science Jilin UniversityChangchun 130012China Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPA 16802United States of America

It is a long-sought goal to achieve desired mechanical properties through tailoring phase formation in alloys,especially for complicated multi-phase alloys.In fact,unveiling nucleation of competitive crystalline phases during solidification hinges on the nature of liquid.Here we employ ab initio molecular dynamics simulations(AIMD)to reveal liquid configuration of the Mg-Al-Ca alloys and explore its effect on the transformation of Ca-containing Laves phase from Al2Ca to Mg_(2)Ca with increasing Ca/Al ratio(rCa/Al).There is structural similarity between liquid and crystalline phase in terms of the local arrangement environment,and the connection schemes of polyhedras.The forming signature of Mg_(2)Ca,as hinted by the topological and chemical short-range order originating from liquid,ascends monotonically with increasing rCa/Al.However,Al_(2)Ca crystal-like order increase at first and then decrease at the crossover of rCa/Al=0.74,corresponding to experimental composition of phase transition from Al_(2)Ca to Mg_(2)Ca.The origin of phase transformation across different compositions lies in the dense packing of atomic configurations and preferential bonding of chemical species in both liquid and solid.The present finding provides a feasible scenario for manipulating phase formation to achieve high performance alloys by tailoring the crystal-like order in liquid.

关键词： Liquid alloy Solidification Crystalembryo Short-rangeorder Ab initio molecular dynamics

Artificial intelligence recognition of pathological T stage and tumor invasion in rectal cancer based on large panoramic pathological sections

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Intelligent Medicine 2022年第3期2卷 141-151页

作者： Yiheng ju Longbo Zheng Peng Zhao Fangjie Xin Fengjiao wang Yuan gao Xianxiang Zhang Dongsheng wang Yun Lu Department of General Surgery Medical CenterAffiliated Hospital of Qingdao UniversityQingdaoShandong 266000China Department of Pathology Affiliated Hospital of Qingdao UniversityQingdaoShandong 266000China Shandong Key Laboratory of Digital Medicine and Computer Assisted Surgery QingdaoShandong 266071China Hainan Branch of Affiliated Hospital of Qingdao University Lingshui Li Autonomous CountyHainan 572400China

Background The incidence of colorectal cancer is increasing worldwide,and it currently ranks third among all cancers.Moreover,pathological diagnosis is becoming increasingly arduous.Artificial intelligence has demon-strated the ability to fully excavate image features and assist doctors in making decisions.Large panoramic patho-logical sections contain considerable amounts of pathological information.In this study,we used large panoramic pathological sections to establish a deep learning model to assist pathologists in identifying cancerous areas on whole-slide images of rectal cancer,as well as for T staging and prognostic analysis.Methods We collected 126 cases of primary rectal cancer from the Affiliated Hospital of Qingdao University West Coast Hospital District(internal dataset)and 42 cases from Shinan and Laoshan Hospital District(external dataset)that had tissue surgically removed from January to September 2019.After sectioning,staining,and scanning,a total of 2350 hematoxylin-eosin-stained whole-slide images were obtained.The patients in the internal dataset were randomly divided into a training cohort(n=88)and a test cohort(n=38)at a ratio of 7:3.We chose DeepLabV3+and ResNet50 as target models for our experiment.We used the Dice similarity coefficient,accuracy,sensitivity,specificity,receiver operating characteristic(ROC)curve,and area under the curve(AUC)to evaluate the performance of the artificial intelligence platform in the test set and validation set.Finally,we followed up patients and examined their prognosis and short-term survival to corroborate the value of T-staging investigations.Results In the test set,the accuracy of image segmentation was 95.8%,the Dice coefficient was 0.92,the accuracy of automatic T-staging recognition was 86%,and the ROC AUC value was 0.93.In the validation set,the accuracy of image segmentation was 95.3%,the Dice coefficient was 0.90,the accuracy of automatic classification was 85%,the ROC AUC value was 0.92,and the image analysis time was 0.2 s.There was a difference

关键词： Large panoramic pathological sections Rectal cancer Whole-slide imaging Deep learning Survival analysis