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Search Results (6)
  • Open Access

    ARTICLE

    Bronchoalveolar lavage fluid metagenomic next-generation sequencing assay for identifying pathogens in lung cancer patients

    JIYU WANG1,2, HUIXIA LI1,2, DEYUAN ZHOU1,2, LIHONG BAI1,2, KEJING TANG1,2,3,*

    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 based on electronic medical… More >

  • Open Access

    ARTICLE

    A Hybrid Deep Fused Learning Approach to Segregate Infectious Diseases

    Jawad Rasheed1,*, Shtwai Alsubai2

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4239-4259, 2023, DOI:10.32604/cmc.2023.031969

    Abstract Humankind is facing another deadliest pandemic of all times in history, caused by COVID-19. Apart from this challenging pandemic, World Health Organization (WHO) considers tuberculosis (TB) as a preeminent infectious disease due to its high infection rate. Generally, both TB and COVID-19 severely affect the lungs, thus hardening the job of medical practitioners who can often misidentify these diseases in the current situation. Therefore, the time of need calls for an immediate and meticulous automatic diagnostic tool that can accurately discriminate both diseases. As one of the preliminary smart health systems that examine three clinical states (COVID-19, TB, and normal… More >

  • Open Access

    ARTICLE

    Stochastic Epidemic Model of Covid-19 via the Reservoir-People Transmission Network

    Kazem Nouri1,*, Milad Fahimi1, Leila Torkzadeh1, Dumitru Baleanu2,3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1495-1514, 2022, DOI:10.32604/cmc.2022.024406

    Abstract The novel Coronavirus COVID-19 emerged in Wuhan, China in December 2019. COVID-19 has rapidly spread among human populations and other mammals. The outbreak of COVID-19 has become a global challenge. Mathematical models of epidemiological systems enable studying and predicting the potential spread of disease. Modeling and predicting the evolution of COVID-19 epidemics in near real-time is a scientific challenge, this requires a deep understanding of the dynamics of pandemics and the possibility that the diffusion process can be completely random. In this paper, we develop and analyze a model to simulate the Coronavirus transmission dynamics based on Reservoir-People transmission network.… More >

  • Open Access

    ARTICLE

    Modelling and Analysis of Bacteria Dependent Infectious Diseases with Variable Contact Rates

    J. B. Shukla1, Shikha Singh2, Jitendra Singh2, Sunil Kumar Sharma3,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1859-1875, 2021, DOI:10.32604/cmc.2021.012095

    Abstract In this research, we proposed a non-linear SIS model to study the effect of variable interaction rates and non-emigrating population of the human habitat on the spread of bacteria-infected diseases. It assumed that the growth of bacteria is logistic with an intrinsic growth rate is a linear function of infectives. In this model, we assume that contact rates between susceptibles and infectives as well as between susceptibles and bacteria depend on the density of the non-emigrating population and the total population of the habitat. The stability theory has been analyzed to analyzed to study the crucial role played by bacteria… More >

  • Open Access

    ARTICLE

    Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity

    Xiangao Jiang1, Megan Coffee2, 3, *, Anasse Bari4, *, Junzhang Wang4, Xinyue Jiang5, Jianping Huang1, Jichan Shi1, Jianyi Dai1, Jing Cai1, Tianxiao Zhang6, Zhengxing Wu1, Guiqing He1, Yitong Huang7

    CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 537-551, 2020, DOI:10.32604/cmc.2020.010691

    Abstract The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel disease and b) resource limitations… More >

  • Open Access

    ARTICLE

    Trypanosoma cruzi invasion in non-phagocytic cells: an ultrastructural study

    Juan Agustín CUETO3, Emile SANTOS BARRIAS6, Wanderley de SOUZA4, 5, Patricia Silvia ROMANO1, 2

    BIOCELL, Vol.42, No.3, pp. 105-108, 2018, DOI:10.32604/biocell.2018.07017

    Abstract Trypanosoma cruzi is the causative agent of Chagas disease. This parasite requires the intracellular niche in order to proliferate and disseminate the infection. After invasion, T. cruzi resides temporarily in an acidic vacuole which is lysed by a not well-understood mechanism. Transmission electron microscopy was used to describe the process of T. cruzi escape from the parasitophorous vacuole over the time. Using HeLa (non-professional phagocytic cells) as host cell, we observed that recently internalized parasites reside in a membrane-bounded vacuole. A few hours later, the first sign of vacuole disruption appeared as membrane discontinuities. This observation was followed by a… More >

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