Comparison between laparoscopic and abdominal radical hysterectomy for stage IB1 and tumor size <2 cm cervical cancer with visible or invisible tumors: a multicentre retrospective study

Pengfei Li,Lan Chen,Yan Ni,Jiaqi Liu,Donglin Li,Jianxin Guo,Zhihua Liu,Shuangling Jin,Yan Xu,Zhiqiang Li,Lu Wang,Xiaonong Bin,Jinghe Lang,Ping Liu,Chunlin Chen 대한부인종양학회 2021 Journal of Gynecologic Oncology Vol.32 No.2

Objective: To compare 5-year disease-free survival (DFS) and overall survival (OS) rates oflaparoscopic radical hysterectomy (LRH) and abdominal radical hysterectomy (ARH) forstage IB1 and tumor size <2 cm with visible or invisible tumors. Methods: We retrospectively compared the oncological outcomes of 1,484 cervical cancerpatients with IB1 and tumor size <2 cm on final pathology, who received ARH (n=899) or LRH(n=585) between January 2004 and December 2016. Patients were divided into visible tumorsubgroup (ARH: n=668, LRH: n=444) and invisible tumor subgroup (ARH: n=231, LRH:n=141) according to tumor type. Results: LRH and ARH showed similar 5-year DFS and OS rates (93.3% vs. 93.1%, p=0.997;96.2% vs. 97.5%, p=0.351) in total study population. LRH was not associated with worse5-year DFS rate (hazard ratio [HR]=0.96; 95% confidence interval [CI]=0.58–1.58; p=0.871)or OS rate (HR=1.37; 95% CI=0.65–2.89; p=0.409) by multivariable analysis. In the visibletumor subgroups, LRH and ARH showed similar 5-year DFS and OS rates (91.9% vs. 91.9%,p=0.933; 95.0% vs. 96.9%, p=0.276), and LRH was not associated with worse 5-year DFS orOS rate (p=0.804, p=0.324). In the invisible tumor subgroups, LRH and ARH also showedsimilar 5-year DFS and OS rates (97.3% vs. 97.1%, p=0.815; 100% vs. 99.5%, p=0.449), andLRH was not associated with worse 5-year DFS rate (p=0.723). Conclusions: Among patients with stage IB1 and tumor size <2 cm, whether the tumor isvisible or not, the oncological outcomes of LRH and ARH among cervical cancer patients arecomparable. This suggests that LRH may be suitable for stage IB1 and tumor size <2 cm withvisible or invisible tumors.Trial Registration: International Clinical Trials Registry Platform Identifier: CHiCTR180017778

Three-Dimensional Analysis of Chloroplast Structures Associated with Virus Infection

Jin, Xuejiao,Jiang, Zhihao,Zhang, Kun,Wang, Pengfei,Cao, Xiuling,Yue, Ning,Wang, Xueting,Zhang, Xuan,Li, Yunqin,Li, Dawei,Kang, Byung-Ho,Zhang, Yongliang American Society of Plant Biologists 2018 Plant Physiology Vol.176 No.1

<P>Three-dimensional visualization identifies structural remodeling in chloroplasts during barley stripe mosaic virus infection.</P><P>Chloroplasts are multifunctional organelles whose morphology is affected by environmental stresses. Although the three-dimensional (3D) architecture of thylakoid membranes has been reported previously, a 3D visualization of chloroplast under stress has not been explored. In this work, we used a positive-strand RNA ((+)RNA) virus, barley stripe mosaic virus (BSMV) to observe chloroplast structural changes during infection by electron tomography. The analyses revealed remodeling of the chloroplast membranes, characterized by the clustering of outer membrane-invaginated spherules in inner membrane-derived packets. Diverse morphologies of cytoplasmic invaginations (CIs) were evident with spherules at the periphery and different sized openings connecting the CIs to the cytoplasm. Immunoelectron microscopy of these viral components verified that the aberrant membrane structures were sites for BSMV replication. The BSMV αa replication protein localized at the surface of the chloroplasts and played a prominent role in eliciting chloroplast membrane rearrangements. In sum, our results have revealed the 3D structure of the chloroplasts induced by BSMV infection. These findings contribute to our understanding of chloroplast morphological changes under stress conditions and during assembly of plant (+)RNA virus replication complexes.</P>

Autonomous Driving Using Artificial Potential Function for Vehicle Collision Avoidance

Pengfei Lin,Woo Young Choi,Jin Ho Yang,Chung Choo Chung 제어로봇시스템학회 2020 제어로봇시스템학회 국내학술대회 논문집 Vol.2020 No.7

Research on Overload Monitoring and Alarming based on APP

Feng Pengfei,Jin Huiqing,Gu Jiangyang,Han Jian 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.11

As the acceleration of urban construction, the dump heavies(building soil-transporting vehicle) shuttle back and forth in urban road. For the sake of profits, the crazy overload transportation makes the vehicles lose braking control and steering ability in emergency state. The common occurrence of traffic disasters brings huge hidden trouble of urban traffic safety. Its harm is self-evident, causing serious damage to infrastructure, to threaten the safety of life and property of the people, to disrupt the market economic order, but also cause environmental pollution. In recent years, the traffic management departments and urban management departments jointly monitor the discharging heavy trucks in the forms of surveillance and reporting by the masses, installing camera and monitor, self-discipline and self-supervision of investors, etc. These forms are limited to the forms and surface, so they cannot effectively stop the overload of self-discharging trucks. How to better and accurately monitor and stop the over-load? The paper intends to achieve intelligent monitoring and alarming on the overload of dump heavy through internet + public transportation monitoring. First the controller is selected and the weighting sensing system is designed through selecting the weighting sensor and determining the installation position of weighting sensor. Then the construction of APP overload monitoring is finished by the three steps including constructing dual-core system, generating database and designing APP display module. Finally after finishing the design of intelligent overload detection system, the paper conducts experiments to validate its effectiveness. The results show that when considering no electromagnetic, the overload equipment and APP software system could receive the overload information timely and reliably.

Semantic Mapping Based on Image Feature Fusion in Indoor Environments

Cong Jin,Armagan Elibol,Pengfei Zhu,Nak Young Chong 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10

It is of the utmost importance for the robot to understand human semantic instructions in human-robot interaction. Combining semantic information with SLAM-based maps leads to a semantic map. Deep neural networks are able to extract useful information from the robot’s visual information. In this paper, we integrate the RGB feature information extracted by the classification network and the detection network to improve the robot’s scene recognition ability and make the acquired semantic information more accurate. The image segmentation algorithm labels the areas of interest in the metric map. Furthermore, the fusion algorithm is incorporated to obtain the semantic information of each area, and the detection algorithm recognizes the key objects in the area. We have demonstrated an efficient combination of semantic information with the occupancy grid map toward accurate semantic mapping.

Using GA - BP Coupling Algorithm to Predict the High-performance Concrete Mechanical Property

Libing Jin,Jie Duan,Tai Fan,Pengfei Jiao,Tianyun Dong,Qiang Wu 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.2

As a cementitious composite, concrete’s property depends on the matrix generated from cement hydration and the dispersed phases such as aggregates. Compression strength is an important mechanics performance index of concrete quality, especially the High-performance Concrete (HPC). However, owing to the expensive cost of test and the existence of high-dimensional nonlinear mapping between compression strength and basic materials, it is uneasiness to precisely forecast the compression strength value of HPC by general formula method. In this research, a novel machine learning system, Genetic Algorithm and BP Neural Network (GA-BPNN) coupling algorithm, is offered to predict the compression strength of HPC. GA-BPNN coupling algorithm model used 181 groups of HPC mixture data to determine 8 factors affecting its compression strength (i.e., Water, Portland Cement, Water-binder Ratio, Fine Aggregate Ratio, Air-entraining Agent, Fly Ash, Silica Fume, and Superplasticizer) as the input variables of the model, while compression strength was set as the output variable. In addition, 166 sets of training set data were segmented into training, validation and test set again, and BP neural network (BPNN) was compared with GA-BPNN to verify the generalizationcapacity of the model in this research. By forecasting the compression strength of 15 test sets, the average relative error is only 0.902%. Finally, the sensitivity of input variables of GA-BPNN model was analyzed by using Gray Relational analysis (GRA) method. Six models were established to research the impact of sensitivity and quantity of input variables on model performance by ignoring individual input variable. The research is shown that GA-BPNN model not only has the powerful nonlinear mapping ability of BPNN, but also has the global search optimization ability of GA, and showed stronger robustness and prediction potential in the assessment of compression strength value of HPC. The sensitivity analysis shows that, to compression strength of HPC, Cement, Water and Water-binder ratio has a sensitivity score of 0.8166, 0.70122, 0.66772, respectively while Fly Ash has the lowest sensitivity.

Ginsenoside Rd alleviates mouse acute renal ischemia/reperfusion injury by modulating macrophage phenotype

Ren, Kaixi,Jin, Chao,Ma, Pengfei,Ren, Qinyou,Jia, Zhansheng,Zhu, Daocheng The Korean Society of Ginseng 2016 Journal of Ginseng Research Vol.40 No.2

Background: Ginsenoside Rd (GSRd), a main component of the root of Panax ginseng, exhibits anti-inflammation functions and decreases infarct size in many injuries and ischemia diseases such as focal cerebral ischemia. M1 Macrophages are regarded as one of the key inflammatory cells having functions for disease progression. Methods: To investigate the effect of GSRd on renal ischemia/reperfusion injury (IRI) and macrophage functional status, and their regulatory role on mouse polarized macrophages in vitro, GSRd (10-100 mg/kg) and vehicle were applied to mice 30 min before renal IRI modeling. Renal functions were reflected by blood serum creatinine and blood urea nitrogen level and histopathological examination. M1 polarized macrophages infiltration was identified by flow cytometry analysis and immunofluorescence staining with $CD11b^+$, $iNOS^+$/interleukin-12/tumor necrosis factor-${\alpha}$ labeling. For the in vitro study, GSRd ($10-100{\mu}g/mL$) and vehicle were added in the culture medium of M1 macrophages to assess their regulatory function on polarization phenotype. Results: In vivo data showed a protective role of GSRd at 50 mg/kg on Day 3. Serum level of serum creatinine and blood urea nitrogen significantly dropped compared with other groups. Reduced renal tissue damage and M1 macrophage infiltration showed on hematoxylin-eosin staining and flow cytometry and immunofluorescence staining confirmed this improvement. With GSRd administration, in vitro cultured M1 macrophages secreted less inflammatory cytokines such as interleukin-12 and tumor necrosis factor-${\alpha}$. Furthermore, macrophage polarization-related pancake-like morphology gradually changed along with increasing concentration of GSRd in the medium. Conclusion: These findings demonstrate that GSRd possess a protective function against renal ischemia/reperfusion injury via downregulating M1 macrophage polarization.

Piezomagnetic Response to the Low- and High-Cycle Fatigue Behavior of X80 Pipeline Steel

Sheng Bao,Pengfei Jin,Zhengye Zhao,Yibin Gu 한국자기학회 2021 Journal of Magnetics Vol.26 No.1

Indoor 3D Dynamic Reconstruction Fingerprint Matching Algorithm in 5G Ultra-Dense Network

( Yuexia Zhang ),( Jiacheng Jin ),( Chong Liu ),( Pengfei Jia ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.1

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

Chemical inhibition of prometastatic lysyl-tRNA synthetase–laminin receptor interaction

Kim, Dae Gyu,Lee, Jin Young,Kwon, Nam Hoon,Fang, Pengfei,Zhang, Qian,Wang, Jing,Young, Nicolas L,Guo, Min,Cho, Hye Young,Mushtaq, Ameeq Ul,Jeon, Young Ho,Choi, Jin Woo,Han, Jung Min,Kang, Ho Woong,Joo NATURE PUBLISHING GROUP 2014 NATURE CHEMICAL BIOLOGY Vol. No.

Lysyl-tRNA synthetase (KRS), a protein synthesis enzyme in the cytosol, relocates to the plasma membrane after a laminin signal and stabilizes a 67-kDa laminin receptor (67LR) that is implicated in cancer metastasis; however, its potential as an antimetastatic therapeutic target has not been explored. We found that the small compound BC-K-YH16899, which binds KRS, impinged on the interaction of KRS with 67LR and suppressed metastasis in three different mouse models. The compound inhibited the KRS-67LR interaction in two ways. First, it directly blocked the association between KRS and 67LR. Second, it suppressed the dynamic movement of the N-terminal extension of KRS and reduced membrane localization of KRS. However, it did not affect the catalytic activity of KRS. Our results suggest that specific modulation of a cancer-related KRS-67LR interaction may offer a way to control metastasis while avoiding the toxicities associated with inhibition of the normal functions of KRS.