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 >

Jinxing Niu^1,*, 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 >

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 >

MOHAMAD ZULKEFLEE SABRI¹, JOANNA BOJARSKA², FAI-CHU WONG^3,4, TSUN-THAI CHAI^3,4,*

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 (M^pro), and papain-like protease (PL^pro). These four proteins are… More > Graphic Abstract

LIJUN JIANG¹, WENMIN JI¹, YAJIE GONG², JIAJUN LI², JINCHUN LIU^1,*

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

Lilan Zou¹, Bo Liang¹, Xu Cheng², Shufa Li^1,*, Cong Lin^1,*

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

LIN QIU^1,#, ANQI TAO^1,#, XIAOQIAN SUN^4,5, FEI LIU¹, XIANPENG GE^2,3,*, CUIYING LI^1,*

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 >

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 >

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 >

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 >