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  • Open Access

    ARTICLE

    Widely Untargeted Metabolome Profiling Provides Insight into Browning and Nutritional Quality Changes in Short-Term Stored Fresh-Cut Potato (Solanum tuberosum L.) Shreds

    Liping Hong, Enming He, Wenhui Zhang, Mingqiong Zheng, Jingwen Wu, Wenhua Wang*

    Phyton-International Journal of Experimental Botany, Vol.92, No.10, pp. 2785-2805, 2023, DOI:10.32604/phyton.2023.030928

    Abstract Potato (Solanum tuberosum L.) is susceptible to enzymatic browning after fresh processing, resulting in color change and potential alteration in the nutritional quality. In this study, a popular potato cultivar, Feiwuruita, was used to profile the metabolites involved in color and nutritional quality changes in fresh shreds stored at 0 and 4 h at 25°C (designated CK and CK4H, respectively). The shreds turned brown within 4 h of storage. In all, 723 metabolites consisting 12 classes of compounds were detected in the samples, largely lipids, phenolic acids, alkaloids, amino acids and derivatives, flavonoids, organic acids, nucleotides and derivatives. Of these,… More >

  • Open Access

    ARTICLE

    Underwater Waste Recognition and Localization Based on Improved YOLOv5

    Jinxing Niu1,*, Shaokui Gu1, Junmin Du2, Yongxing Hao1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2015-2031, 2023, DOI:10.32604/cmc.2023.040489

    Abstract With the continuous development of the economy and society, plastic pollution in rivers, lakes, oceans, and other bodies of water is increasingly severe, posing a serious challenge to underwater ecosystems. Effective cleaning up of underwater litter by robots relies on accurately identifying and locating the plastic waste. However, it often causes significant challenges such as noise interference, low contrast, and blurred textures in underwater optical images. A weighted fusion-based algorithm for enhancing the quality of underwater images is proposed, which combines weighted logarithmic transformations, adaptive gamma correction, improved multi-scale Retinex (MSR) algorithm, and the contrast limited adaptive histogram equalization (CLAHE)… More >

  • Open Access

    REVIEW

    Network biology: A promising approach for drug target identification against neurodevelopmental disorders

    WAYEZ NAQVI, ANANYA SINGH, PREKSHI GARG, PRACHI SRIVASTAVA*

    BIOCELL, Vol.47, No.8, pp. 1675-1687, 2023, DOI:10.32604/biocell.2023.029624

    Abstract Biological entities are involved in complicated and complex connections; hence, discovering biological information using network biology ideas is critical. In the past few years, network biology has emerged as an integrative and systems-level approach for understanding and interpreting these complex interactions. Biological network analysis is one method for reducing enormous data sets to clinically useful knowledge for disease diagnosis, prognosis, and treatment. The network of biological entities can help us predict drug targets for several diseases. The drug targets identified through the systems biology approach help in targeting the essential biological pathways that contribute to the progression and development of… More >

  • Open Access

    REVIEW

    Molecular dynamics-driven exploration of peptides targeting SARS-CoV-2, with special attention on ACE2, S protein, Mpro, and PLpro: A review

    MOHAMAD ZULKEFLEE SABRI1, JOANNA BOJARSKA2, FAI-CHU WONG3,4, TSUN-THAI CHAI3,4,*

    BIOCELL, Vol.47, No.8, pp. 1727-1742, 2023, DOI:10.32604/biocell.2023.029272

    Abstract Molecular dynamics (MD) simulation is a computational technique that analyzes the movement of a system of particles over a given period. MD can provide detailed information about the fluctuations and conformational changes of biomolecules at the atomic level over time. In recent years, MD has been widely applied to the discovery of peptides and peptide-like molecules that may serve as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibitors. This review summarizes recent advances in such explorations, focusing on four protein targets: angiotensin-converting enzyme 2 (ACE2), spike protein (S protein), main protease (Mpro), and papain-like protease (PLpro). These four proteins are… More > Graphic Abstract

    Molecular dynamics-driven exploration of peptides targeting SARS-CoV-2, with special attention on ACE2, S protein, M<sup>pro</sup>, and PL<sup>pro</sup>: A review

  • Open Access

    ARTICLE

    MiR-520f-3p inhibits epithelial-mesenchymal transition of colorectal cancer cells by targeting Yes-associated protein 1

    LIJUN JIANG1, WENMIN JI1, YAJIE GONG2, JIAJUN LI2, JINCHUN LIU1,*

    BIOCELL, Vol.47, No.8, pp. 1803-1810, 2023, DOI:10.32604/biocell.2023.029516

    Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies. Early diagnosis is the key to effective treatment of CRC. Since microRNAs (miRNAs) can be used as biomarkers of CRC, the objective of this work was to examine the effect of miR-520f-3p, which targets YAP1 (Yes-associated protein 1), on the ability of CRC cells to proliferate, invade, migrate, and undergo epithelial-mesenchymal transition (EMT). Methods: A miR-520f-3p mimic was used to overexpress miR-520f-3p in HT29 cells. To establish the tumor-bearing mouse model, transfected HT29 cells were subcutaneously implanted into BALB/c-nu nude mice, and YAP1 and miR-520f-3p levels were determined using… More > Graphic Abstract

    MiR-520f-3p inhibits epithelial-mesenchymal transition of colorectal cancer cells by targeting Yes-associated protein 1

  • Open Access

    ARTICLE

    Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

    Lilan Zou1, Bo Liang1, Xu Cheng2, Shufa Li1,*, Cong Lin1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2641-2659, 2023, DOI:10.32604/cmes.2023.028037

    Abstract Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment. In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment, we proposed a more effective and robust target detection framework based on deep learning, which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection. Firstly, the weighted box fusion method is adopted to generate a fusion box by weighted fusion of prediction boxes with… More > Graphic Abstract

    Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

  • Open Access

    ARTICLE

    Comprehensive bioinformatics analysis and experimental validation: An anoikis-related gene prognostic model for targeted drug development in head and neck squamous cell carcinoma

    LIN QIU1,#, ANQI TAO1,#, XIAOQIAN SUN4,5, FEI LIU1, XIANPENG GE2,3,*, CUIYING LI1,*

    Oncology Research, Vol.31, No.5, pp. 715-752, 2023, DOI:10.32604/or.2023.029443

    Abstract We analyzed RNA-sequencing (RNA-seq) and clinical data from head and neck squamous cell carcinoma (HNSCC) patients in The Cancer Genome Atlas (TCGA) Genomic Data Commons (GDC) portal to investigate the prognostic value of anoikis-related genes (ARGs) in HNSCC and develop new targeted drugs. Differentially expressed ARGs were screened using bioinformatics methods; subsequently, a prognostic model including three ARGs (CDKN2A, BIRC5, and PLAU) was constructed. Our results showed that the model-based risk score was a good prognostic indicator, and the potential of the three ARGs in HNSCC prognosis was validated by the TISCH database, the model’s accuracy was validated in two… More >

  • Open Access

    ARTICLE

    Faster RCNN Target Detection Algorithm Integrating CBAM and FPN

    Wenshun Sheng*, Xiongfeng Yu, Jiayan Lin, Xin Chen

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1549-1569, 2023, DOI:10.32604/csse.2023.039410

    Abstract Small targets and occluded targets will inevitably appear in the image during the shooting process due to the influence of angle, distance, complex scene, illumination intensity, and other factors. These targets have few effective pixels, few features, and no apparent features, which makes extracting their efficient features difficult and easily leads to false detection, missed detection, and repeated detection, affecting the performance of target detection models. An improved faster region convolutional neural network (RCNN) algorithm (CF-RCNN) integrating convolutional block attention module (CBAM) and feature pyramid networks (FPN) is proposed to improve the detection and recognition accuracy of small-size objects, occluded… More >

  • Open Access

    ARTICLE

    Multi-Target Tracking of Person Based on Deep Learning

    Xujun Li*, Guodong Fang, Liming Rao, Tengze Zhang

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2671-2688, 2023, DOI:10.32604/csse.2023.038154

    Abstract To improve the tracking accuracy of persons in the surveillance video, we proposed an algorithm for multi-target tracking persons based on deep learning. In this paper, we used You Only Look Once v5 (YOLOv5) to obtain person targets of each frame in the video and used Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT) to do cascade matching and Intersection Over Union (IOU) matching of person targets between different frames. To solve the IDSwitch problem caused by the low feature extraction ability of the Re-Identification (ReID) network in the process of cascade matching, we introduced Spatial Relation-aware… More >

  • Open Access

    ARTICLE

    Multitarget Flexible Grasping Detection Method for Robots in Unstructured Environments

    Qingsong Fan, Qijie Rao, Haisong Huang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1825-1848, 2023, DOI:10.32604/cmes.2023.028369

    Abstract In present-day industrial settings, where robot arms perform tasks in an unstructured environment, there may exist numerous objects of various shapes scattered in random positions, making it challenging for a robot arm to precisely attain the ideal pose to grasp the object. To solve this problem, a multistage robotic arm flexible grasp detection method based on deep learning is proposed. This method first improves the Faster RCNN target detection model, which significantly improves the detection ability of the model for multiscale grasped objects in unstructured scenes. Then, a Squeeze-and-Excitation module is introduced to design a multitarget grasping pose generation network… More >

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