Youshen Jiang¹, Tongqing Zhou¹, Zhilin Wang², Zhiping Cai^1,*, Qiang Ni³

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 585-597, 2024, DOI:10.32604/iasc.2023.030221

Abstract Due to the increasingly severe challenges brought by various epidemic diseases, people urgently need intelligent outbreak trend prediction. Predicting disease onset is very important to assist decision-making. Most of the existing work fails to make full use of the temporal and spatial characteristics of epidemics, and also relies on multivariate data for prediction. In this paper, we propose a Multi-Scale Location Attention Graph Neural Networks (MSLAGNN) based on a large number of Centers for Disease Control and Prevention (CDC) patient electronic medical records research sequence source data sets. In order to understand the geography and… More >

Rui Zhang^1,2, Tonghai Liu^1,2,*, Wenzheng Liu^1,2, Chaungchuang Yuan^1,2, Xiaoyue Seng^1,2, Tiantian Guo^1,2, Xue Wang^1,2

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1275-1296, 2024, DOI:10.32604/phyton.2024.052397

Abstract Rice diseases can adversely affect both the yield and quality of rice crops, leading to the increased use of pesticides and environmental pollution. Accurate detection of rice diseases in natural environments is crucial for both operational efficiency and quality assurance. Deep learning-based disease identification technologies have shown promise in automatically discerning disease types. However, effectively extracting early disease features in natural environments remains a challenging problem. To address this issue, this study proposes the YOLO-CRD method. This research selected images of common rice diseases, primarily bakanae disease, bacterial brown spot, leaf rice fever, and dry… More >

Ting Liu¹, Fang Liu¹, Lei-Wen Peng, Li Chang, Yong-Mei Jiang

Oncology Research, Vol.26, No.5, pp. 817-826, 2018, DOI:10.3727/096504017X15130753659625

Abstract Peritoneal macrophages (PMs) are the major cell type of peritoneal cells that participate in multiple aspects of innate and acquired immunity in the peritoneal cavity. PMs have an ability to release a large amount of proinflammatory and anti-inflammatory cytokines and therefore play a critical role in regulating the differentiation of innate immune cells and inflammatory T cells. Accumulating studies demonstrate that the immunological reactions and inflammatory responses of PMs are strongly related to the pathogenic processes of various inflammatory diseases and abdominal cancers. Consequently, the regulation of PM activation has gradually emerged as a promising More >

Nasser Sweilam¹, Seham Al-Mekhlafi^2,*, Aya Ahmed³, Ahoud Alsheri⁴, Emad Abo-Eldahab³

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1619-1645, 2024, DOI:10.32604/cmes.2024.047896

Abstract In this paper, two crossover hybrid variable-order derivatives of the cancer model are developed. Grünwald-Letnikov approximation is used to approximate the hybrid fractional and variable-order fractional operators. The existence, uniqueness, and stability of the proposed model are discussed. Adams Bashfourth’s fifth-step method with a hybrid variable-order fractional operator is developed to study the proposed models. Comparative studies with generalized fifth-order Runge-Kutta method are given. Numerical examples and comparative studies to verify the applicability of the used methods and to demonstrate the simplicity of these approximations are presented. We have showcased the efficiency of the proposed More >

Shuliang Xia^1,2,3,#, Huikang Tao^2,#, Shixin Su⁴, Xinxin Chen², Li Ma², Jianru Li⁵, Bei Gao⁶, Xumei Liu⁵, Lei Pi⁷, Jinqing Feng⁴, Fengxiang Li², Jia Li^4,*, Zhiwei Zhang^1,3,*

Congenital Heart Disease, Vol.19, No.2, pp. 247-256, 2024, DOI:10.32604/chd.2024.052583

Abstract Aims: Multiple genes and environmental factors are known to be involved in congenital heart disease (CHD), but epigenetic variation has received little attention. Monozygotic (MZ) twins with CHD provide a unique model for exploring this phenomenon. In order to investigate the potential role of Deoxyribonucleic Acid (DNA) methylation in CHD pathogenesis, the present study examined DNA methylation variation in MZ twins discordant for CHD, especially ventricular septal defect (VSD). Methods and Results: Using genome-wide DNA methylation profiles, we identified 4004 differentially methylated regions (DMRs) in 18 MZ twin pairs discordant for CHD, and 2826 genes were… More > Graphic Abstract

Yasir Maqsood¹, Syed Muhammad Usman^1,*, Musaed Alhussein², Khursheed Aurangzeb^2,*, Shehzad Khalid³, Muhammad Zubair⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2795-2811, 2024, DOI:10.32604/cmc.2024.049410

Abstract Wheat is a critical crop, extensively consumed worldwide, and its production enhancement is essential to meet escalating demand. The presence of diseases like stem rust, leaf rust, yellow rust, and tan spot significantly diminishes wheat yield, making the early and precise identification of these diseases vital for effective disease management. With advancements in deep learning algorithms, researchers have proposed many methods for the automated detection of disease pathogens; however, accurately detecting multiple disease pathogens simultaneously remains a challenge. This challenge arises due to the scarcity of RGB images for multiple diseases, class imbalance in existing… More >

Fatma Nese Efil¹, Sania Qureshi^1,2,3, Nezihal Gokbulut^1,4, Kamyar Hosseini^1,3, Evren Hincal^1,4,*, Amanullah Soomro²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 485-512, 2024, DOI:10.32604/cmes.2024.047907

Abstract The global population has been and will continue to be severely impacted by the COVID-19 epidemic. The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer, heart disease, and diabetes. Here, using ordinary differential equations (ODEs), two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease. After that, we highlight the stability assessments that can be applied to these models. Sensitivity analysis is used to examine how changes in… More >

YARA ALZGHOUL, HALA J. BANI ISSA, AHMAD K. SANAJLEH, TAQWA ALABDUH, FATIMAH RABABAH, MAHA AL-SHDAIFAT, EJLAL ABU-EL-RUB^*, FATIMAH ALMAHASNEH, RAMADA R. KHASAWNEH, AYMAN ALZU’BI, HUTHAIFA MAGABLEH

BIOCELL, Vol.48, No.4, pp. 559-569, 2024, DOI:10.32604/biocell.2024.048056

Abstract Mesenchymal stem cells (MSCs) are ideal candidates for treating many cardiovascular diseases. MSCs can modify the internal cardiac microenvironment to facilitate their immunomodulatory and differentiation abilities, which are essential to restore heart function. MSCs can be easily isolated from different sources, including bone marrow, adipose tissues, umbilical cord, and dental pulp. MSCs from various sources differ in their regenerative and therapeutic abilities for cardiovascular disorders. In this review, we will summarize the therapeutic potential of each MSC source for heart diseases and highlight the possible molecular mechanisms of each source to restore cardiac function. More >

JIYU WANG^1,2, HUIXIA LI^1,2, DEYUAN ZHOU^1,2, LIHONG BAI^1,2, KEJING TANG^1,2,3,*

BIOCELL, Vol.48, No.4, pp. 623-637, 2024, DOI:10.32604/biocell.2024.030420

Abstract Background: For patients with lung cancer, timely identification of new lung lesions as infectious or non-infectious, and accurate identification of pathogens is very important in improving OS of patients. As a new auxiliary examination, metagenomic next-generation sequencing (mNGS) is believed to be more accurate in diagnosing infectious diseases in patients without underlying diseases, compared with conventional microbial tests (CMTs). We designed this study to find out whether mNGS has better performance in distinguishing infectious and non-infectious diseases in lung cancer patients using bronchoalveolar lavage fluid (BALF). Materials and Methods: This study was a real-world retrospective review… More >

Mahmood A. Mahmood^1,2,*, Khalaf Alsalem¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3431-3448, 2024, DOI:10.32604/cmc.2024.047604

Abstract Olive trees are susceptible to a variety of diseases that can cause significant crop damage and economic losses. Early detection of these diseases is essential for effective management. We propose a novel transformed wavelet, feature-fused, pre-trained deep learning model for detecting olive leaf diseases. The proposed model combines wavelet transforms with pre-trained deep-learning models to extract discriminative features from olive leaf images. The model has four main phases: preprocessing using data augmentation, three-level wavelet transformation, learning using pre-trained deep learning models, and a fused deep learning model. In the preprocessing phase, the image dataset is… More >