Andrew Omame^1,2,*, Mujahid Abbas^3,6, Dumitru Baleanu^4,5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2973-3012, 2024, DOI:10.32604/cmes.2023.029681

Abstract A patient co-infected with COVID-19 and viral hepatitis B can be at more risk of severe complications than the one infected with a single infection. This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19. The model is fitted to real COVID-19 data from Pakistan. The proposed model incorporates logistic growth and saturated incidence functions. Rigorous analyses using the tools of stochastic calculus, are performed to study appropriate conditions for the existence of unique global solutions, stationary distribution in the sense of ergodicity and disease… More >

PRIYADHARSHINI THANJAVUR SRIRAMAMOORTHI^1,2, GAYATHRI GOPAL^1,2, SHIBI MURALIDAR^1,2, SAI RAMANAN ESWARAN^1,2, DANUSH NARAYAN PANNEERSELVAM^1,2, BHUVANESWARAN MEIYANATHAN^1,2, SRICHANDRASEKAR THUTHIKKADU INDHUPRAKASH^1,2, SENTHIL VISAGA AMBI^1,2,*

BIOCELL, Vol.47, No.11, pp. 2335-2350, 2023, DOI:10.32604/biocell.2023.029379

Abstract The novel coronavirus pneumonia (COVID-19) is spreading worldwide and threatening people greatly. The routes by which SARS-CoV-2 causes lung injury have grown to be a major concern in the scientific community since patients with new Coronavirus, severe acute respiratory syndrome coronavirus (SARS-CoV-2) have a high likelihood of developing acute respiratory distress syndrome (ARDS) in severe cases. The mortality rate of COVID-19 has increased over the period due to rapid spread, and it becomes crucial to understand the disease epidemiology, pathogenic mechanisms, and suitable treatment strategies. ARDS is a respiratory disorder and is one of the clinical manifestations observed in patients… More > Graphic Abstract

HANYANG GUAN^1,#, YUE WU^2,#, LU LI^3,#, YABING YANG¹, SHENGHUI QIU¹, ZHAN ZHAO¹, XIAODONG CHU¹, JIASHUAI HE¹, ZUYANG CHEN¹, YIRAN ZHANG¹, HUI DING¹, JINGHUA PAN^1,*, YUNLONG PAN^1,*

Oncology Research, Vol.31, No.4, pp. 437-448, 2023, DOI:10.32604/or.2023.029924

Abstract Neoantigen-targeted immunotherapy is a rapidly advancing field that holds great promise for treating cancer. The recognition of antigens by immune cells is a crucial step in tumor-specific killing, and neoantigens generated by mutations in cancer cells possess high immunogenicity and are selectively expressed in tumor cells, making them an attractive therapeutic target. Currently, neoantigens find utility in various domains, primarily in the realm of neoantigen vaccines such as DC vaccines, nucleic acid vaccines, and synthetic long peptide vaccines. Additionally, they hold promise in adoptive cell therapy, encompassing tumor-infiltrating cells, T cell receptors, and chimeric antigen receptors which are expressed by… More > Graphic Abstract

JIAHENG XIE^1,#, MENGMENG OU^1,#, PAN YU^1,#, DAN WU^2,#, QIKAI TANG³, YUAN CAO⁴, JING HANG⁵, LU YIN¹, TINGHONG XIANG¹, MING WANG^1,*, JINGPING SHI^1,*

Oncology Research, Vol.31, No.3, pp. 389-403, 2023, DOI:10.32604/or.2023.029274

Abstract Purpose: To screen potential tumor antigens for melanoma vaccine development and identify different immune subtypes. Methods: Transcriptional data (HTSEQ-FPKM) and clinical information of a 472 Melanoma cohort GDC TCGA Melanoma (SKCM) were downloaded from the UCSC XENA website (). Subsequently, transcriptome data and clinical information of 210 melanoma cohort GSE65904 were downloaded from Gene Expression Omnibus (GEO), a large global public database. All the transcriptome expression data matrices were log2 transformed for subsequent analysis. GEPIA, TIMER, and IMMPORT databases are also used for analysis. Cell function experiments were performed to validate the role of the IDO1 gene in melanoma cell… More >

Asma Qaiser¹, Saman Hina¹, Abdul Karim Kazi^1,*, Saad Ahmed², Raheela Asif³

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 73-90, 2023, DOI:10.32604/iasc.2023.036784

Abstract In the past few years, social media and online news platforms have played an essential role in distributing news content rapidly. Consequently. verification of the authenticity of news has become a major challenge. During the COVID-19 outbreak, misinformation and fake news were major sources of confusion and insecurity among the general public. In the first quarter of the year 2020, around 800 people died due to fake news relevant to COVID-19. The major goal of this research was to discover the best learning model for achieving high accuracy and performance. A novel case study of the Fake News Classification using… More >

FERDINANDO CALABRIA¹, ANTONIO BAGNATO¹, GIULIANA GUADAGNINO², MARIA TOTEDA¹, ANTONIO LANZILLOTTA¹, STEFANIA CARDEI¹, ROSANNA TAVOLARO¹, MARIO LEPORACE^1,*

Oncology Research, Vol.31, No.2, pp. 117-124, 2023, DOI:10.32604/or.2023.027705

Abstract We observed several patients presenting 2-[¹⁸F]FDG uptake in the reactive axillary lymph node at PET/CT imaging, ipsilateral to the site of the COVID-19 vaccine injection. Analog finding was documented at [¹⁸F]Choline PET/CT. The aim of our study was to describe this source of false positive cases. All patients examined by PET/CT were included in the study. Data concerning patient anamnesis, laterality, and time interval from recent COVID-19 vaccination were recorded. SUVmax was measured in all lymph nodes expressing tracer uptake after vaccination. Among 712 PET/CT scans with 2-[¹⁸F]FDG, 104 were submitted to vaccination; 89/104 patients (85%) presented axillary and/or deltoid… More >

Walaa N. Ismail^1,2,*, Hessah A. Alsalamah^3,4, Ebtesam Mohamed²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3945-3976, 2023, DOI:10.32604/cmc.2023.031194

Abstract As a result of the increased number of COVID-19 cases, Ensemble Machine Learning (EML) would be an effective tool for combatting this pandemic outbreak. An ensemble of classifiers can improve the performance of single machine learning (ML) classifiers, especially stacking-based ensemble learning. Stacking utilizes heterogeneous-base learners trained in parallel and combines their predictions using a meta-model to determine the final prediction results. However, building an ensemble often causes the model performance to decrease due to the increasing number of learners that are not being properly selected. Therefore, the goal of this paper is to develop and evaluate a generic, data-independent… More >

Sandeep Kumar¹, Muhammad Badruddin Khan², Mozaherul Hoque Abul Hasanat², Abdul Khader Jilani Saudagar^2,*, Abdullah AlTameem², Mohammed AlKhathami²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 897-914, 2023, DOI:10.32604/cmc.2023.031867

Abstract Social media, like Twitter, is a data repository, and people exchange views on global issues like the COVID-19 pandemic. Social media has been shown to influence the low acceptance of vaccines. This work aims to identify public sentiments concerning the COVID-19 vaccines and better understand the individual’s sensitivities and feelings that lead to achievement. This work proposes a method to analyze the opinion of an individual’s tweet about the COVID-19 vaccines. This paper introduces a sigmoidal particle swarm optimization (SPSO) algorithm. First, the performance of SPSO is measured on a set of 12 benchmark problems, and later it is deployed… More >

Dongqing Wang^1,*, Heying Chen¹, Yi Hu^2,*

Oncologie, Vol.24, No.3, pp. 441-449, 2022, DOI:10.32604/oncologie.2022.024898

Abstract Immunotherapy is currently recognized as one of the most promising anticancer strategies. In the tumor microenvironment, tumor-associated macrophages are mainly M2-type macrophages with tumor-promoting effects. Therefore, the reprogramming of tumor-associated macrophages from M2 to M1 type is a potential strategy for cancer therapy. We have previously shown the anticancer effects of implantable allogeneic M1 macrophages in mice. Here, we further engineered autologous mouse bone marrow cells into M1 macrophages and then embedded them into a sodium alginate gel to prepare an implantable immunotherapeutic agent (M1@Gel). We demonstrate that M1@Gel repolarizes M2 macrophages to M1 type and activates the immune responses… More >

Indra Mamad Gandidi^1,*, Apri Wiyono¹, Nugroho Agung Pambudi^2,*, Rahmat Romadhon³, Alfan Sarifudin²

Energy Engineering, Vol.119, No.4, pp. 1403-1418, 2022, DOI:10.32604/ee.2022.019200

Abstract The rapid spread of COVID-19 pandemic has forced several countries in the world to store vaccines in cold storage towards ensuring their protection from being damaged and to maintain their stability. However, most remote clinics, especially those in the equator and islands, are faced with the challenges of hot climates and the inability to afford electricity resources needed to power the cold storage facility. Meanwhile, the hot equatorial region has abundant solar energy to power the vaccine cold storage but previous studies showed that several field workers do not have the ability to maintain the vaccine storage temperature as indicated… More >