HAIYANG CHEN^1,2,#, JINGYAO SU^1,#, DANYANG CHEN^1,#, YUYE DU¹, RUILIN ZHENG¹, QINGLIN DENG², QIANQIAN DU³, BING ZHU^1,*, YINGHUA LI^1,*

BIOCELL, Vol.46, No.10, pp. 2267-2273, 2022, DOI:10.32604/biocell.2022.020218

Abstract At present, Hepatocarcinoma is one of the main causes of tumor related death all over the world. However, there are still many clinical restrictions on the treatment of liver cancer. Recently, L-Selenocystine has been shown to be a novel treatment for tumors, especially human glioma cells. But, the mechanism of L-Selenocystine against hepatocellular carcinoma remains unclear. Therefore, the main objective of this study was to investigate the effects of L-Selenocystine on HepG2 cell proliferation and activation of reactive oxygen species (ROS) mediated signaling pathway. L-Selenocystine can significantly inhibit HepG2 cell proliferation by activating caspase-3 and cleaving PARP to induce apoptosis.… More >

CARL RANDALL HARRELL^1,#, ANA VOLAREVIC^2,#,*, DRAGICA PAVLOVIC³, VALENTIN DJONOV⁴, VLADISLAV VOLAREVIC^4,5,*

BIOCELL, Vol.46, No.10, pp. 2195-2200, 2022, DOI:10.32604/biocell.2022.020175

Abstract Detrimental immune response has a crucially important role in the development and progression of inflammatory eye diseases. Inflammatory mediators and proteolytic enzymes released by activated immune cells induce serious injury of corneal epithelial cells and retinal ganglion cell which may result in the vision loss. Mesenchymal stem cells (MSCs) are regulatory cells which produce various immunosuppressive factors that modulate phenotype and function of inflammatory immune cells. However, several safety issues, including undesired differentiation and emboli formation, limit clinical use of MSCs. MSC-derived exosomes (MSC-Exos) are nano-sized extracellular vesicles which contain all MSC-derived immunoregulatory factors. Intraocular administration of MSC-Exos efficiently attenuated… More >

KANIZ FATEMA, ZACHARY LARSON, JARED BARROTT^*

BIOCELL, Vol.46, No.10, pp. 2177-2193, 2022, DOI:10.32604/biocell.2022.020141

Abstract Osteosarcoma is one of the most genomically complex cancers and as result, it has been difficult to assign genomic aberrations that contribute to disease progression and patient outcome consistently across samples. One potential source for correlating osteosarcoma and genomic biomarkers is within the non-coding regions of RNA that are differentially expressed. However, it is unsurprising that a cancer classification that is fraught with genomic instability is likely to have numerous studies correlating non-coding RNA expression and function have been published on the subject. This review undertakes the formidable task of evaluating the published literature of non-coding RNAs in osteosarcoma. This… More >

KI-TAEK LIM^#,*, TEJAL V. PATIL^#, DINESH K. PATEL, SAYAN DEB DUTTA, KEYA GANGULY, AAYUSHI RANDHAWA

BIOCELL, Vol.46, No.10, pp. 2201-2208, 2022, DOI:10.32604/biocell.2022.020013

Abstract Mesenchymal stem cells (MSCs) are multipotent cells usually isolated from bone marrow, endometrium, adipose tissues, skin, and dental pulp. MSCs played a crucial role in regenerative therapy and have been introduced as an interdisciplinary field between cell biology and material science. Recently, MSCs have been widely explored for their application in regenerative medicine and COVID-19 treatment. Different approaches to evaluate the future of biomaterials and stem cell properties have been developed. However, misconceptions and ethical issues still exist, such as MSCs being non-angiogenic, anti-apoptotic, and immunoregulatory competencies. Embryonic stem cells isolation primarily requires the consent of donors and can include… More >

Yun Tan^1,2, Weizhao Wu², Ling Tan³, Haikuo Peng², Jiaohua Qin^2,*

Journal of New Media, Vol.4, No.3, pp. 155-164, 2022, DOI:10.32604/jnm.2022.031113

Abstract At present, segmentation for medical image is mainly based on fully supervised model training, which consumes a lot of time and labor for dataset labeling. To address this issue, we propose a semi-supervised medical image segmentation model based on a generative adversarial network framework for automated segmentation of arteries. The network is mainly composed of two parts: a segmentation network for medical image segmentation and a discriminant network for evaluating segmentation results. In the initial stage of network training, a fully supervised training method is adopted to make the segmentation network and the discrimination network have certain segmentation and discrimination… More >

Ziyi Wang¹, Xiaoyan Zhao^1,*, Hongjun Rong¹, Ying Tong¹, Jingang Shi²

Journal of New Media, Vol.4, No.3, pp. 145-153, 2022, DOI:10.32604/jnm.2022.030178

Abstract Microphone array-based sound source localization (SSL) is widely used in a variety of occasions such as video conferencing, robotic hearing, speech enhancement, speech recognition and so on. The traditional SSL methods cannot achieve satisfactory performance in adverse noisy and reverberant environments. In order to improve localization performance, a novel SSL algorithm using convolutional residual network (CRN) is proposed in this paper. The spatial features including time difference of arrivals (TDOAs) between microphone pairs and steered response power-phase transform (SRP-PHAT) spatial spectrum are extracted in each Gammatone sub-band. The spatial features of different sub-bands with a frame are combine into a… More >

Xiaoyu^1,2, Tian Zhenzhen², Xin Zihao², Liu Suolan², Chen Fuhua³, Wang Hongyuan^2,*

Journal of New Media, Vol.4, No.3, pp. 137-143, 2022, DOI:10.32604/jnm.2022.027890

Abstract Recent advances in OCR show that end-to-end (E2E) training pipelines including detection and identification can achieve the best results. However, many existing methods usually focus on case insensitive English characters. In this paper, we apply an E2E approach, the multiplex multilingual mask TextSpotter, which performs script recognition at the word level and uses different recognition headers to process different scripts while maintaining uniform loss, thus optimizing script recognition and multiple recognition headers simultaneously. Experiments show that this method is superior to the single-head model with similar number of parameters in end-to-end identification tasks. More >

Lixiu Wu^1,*, Song Wang², Qingbing Sang³

Journal of New Media, Vol.4, No.3, pp. 125-135, 2022, DOI:10.32604/jnm.2022.027199

Abstract In order to apply the deep learning to the stereo image quality evaluation, two problems need to be solved: The first one is that we have a bit of training samples, another is how to input the dimensional image’s left view or right view. In this paper, we transfer the 2D image quality evaluation model to the stereo image quality evaluation, and this method solves the first problem; use the method of principal component analysis is used to fuse the left and right views into an input image in order to solve the second problem. At the same time, the… More >

Xi Chen¹, Yanpeng Wu^2,*, Chenxue Zhu², Hongjun Liu³

Journal of New Media, Vol.4, No.3, pp. 117-123, 2022, DOI:10.32604/jnm.2022.027060

Abstract The Hessian matrix has a wide range of applications in image processing, such as edge detection, feature point detection, etc. This paper proposes an image enhancement algorithm based on the Hessian matrix. First, the Hessian matrix is obtained by convolving the derivative of the Gaussian function. Then use the Hessian matrix to enhance the linear structure in the image. Experimental results show that the method proposed in this paper has strong robustness and accuracy. More >

Liguo Zhang^1,2, Zilin Tian¹, Yan Zhang^3,*, Tong Shuai⁴, Shuo Liang⁴, Zhuofei Wu⁵

Journal of New Media, Vol.4, No.2, pp. 59-71, 2022, DOI:10.32604/jnm.2022.029360

Abstract In recent years, deep learning algorithms have been popular in recognizing targets in synthetic aperture radar (SAR) images. However, due to the problem of overfitting, the performance of these models tends to worsen when just a small number of training data are available. In order to solve the problems of overfitting and an unsatisfied performance of the network model in the small sample remote sensing image target recognition, in this paper, we uses a deep residual network to autonomously acquire image features and proposes the Deep Feature Bayesian Classifier model (RBnet) for SAR image target recognition. In the RBnet, a… More >