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Biosensor Based Advanced Cancer Diagnostics and Therapy

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 2336

Special Issue Editor


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Guest Editor
1. Department of Bioscience Technology, Chung Yuan Christian University, Taoyuan City 32023, Taiwan
2. Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA 30322, USA
Interests: cancer metastasis; diagnostics and therapy

Special Issue Information

Dear Colleagues,

Cancers are still a major cause of death because of limited success in therapy. The major obstacles are the lack of specific and reliable biomarkers to sense their emergence at the early stage, heterogeneous nature in terms of histology and morphology, as well as genomic variation and phenotypic manifestation, and specific targets for designing an efficacious means of individual therapy. Organ-specific sensors are rarely found, and even when they are found, they are not useful for predicting malignant potential, for example, PSA (prostate-specific antigen), and thus, they are not as commonly used as sensors for advanced cancer diagnostics and therapy. By contrast, tumor-associate antigens are commonly used for the same purposes. In the past decade, progressive development of better-affinity aptamers, antibodies, and engineered antibodies to disease biomarkers has been achieved, with concurrent advances in nanotechnology, which has stimulated and increased the development of nanomaterials-based biosensors to gradually replace the classical diagnostic methods and therapeutic means. In this issue, biomarkers/biosensors (e.g., signaling molecule, cell adhesion molecules, telomerase, tumor suppressors, microRNA, immune checkpoint, circular tumor marker DNA, tumor spheroid, tumor-related exosomes), as well as different types of transducers (e.g., electrochemical, optical, thermal, and piezoelectric) are used to fulfill the above needs. Therapeutic approaches, such as anticancer drug therapy, chem-photothermal therapy, and immune checkpoint therapy, are also included to meet the needs in the field.

Original research articles are preferred for this issue.

Prof. Dr. Guang-Jer Wu
Guest Editor

Manuscript Submission Information

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Keywords

  • signaling molecule
  • METCAM
  • microRNA
  • circular tumor marker DNA
  • tumor-related exosome
  • telomerase
  • tumor suppressor
  • tumor spheroid
  • LFIS
  • anticancer drug
  • chem-photothermal therapy
  • immune checkpoint therapy

Published Papers (1 paper)

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Research

16 pages, 724 KiB  
Article
Explainable Convolutional Neural Networks for Brain Cancer Detection and Localisation
by Francesco Mercaldo, Luca Brunese, Fabio Martinelli, Antonella Santone and Mario Cesarelli
Sensors 2023, 23(17), 7614; https://doi.org/10.3390/s23177614 - 2 Sep 2023
Cited by 1 | Viewed by 1737
Abstract
Brain cancer is widely recognised as one of the most aggressive types of tumors. In fact, approximately 70% of patients diagnosed with this malignant cancer do not survive. In this paper, we propose a method aimed to detect and localise brain cancer, starting [...] Read more.
Brain cancer is widely recognised as one of the most aggressive types of tumors. In fact, approximately 70% of patients diagnosed with this malignant cancer do not survive. In this paper, we propose a method aimed to detect and localise brain cancer, starting from the analysis of magnetic resonance images. The proposed method exploits deep learning, in particular convolutional neural networks and class activation mapping, in order to provide explainability by highlighting the areas of the medical image related to brain cancer (from the model point of view). We evaluate the proposed method with 3000 magnetic resonances using a free available dataset. The results we obtained are encouraging. We reach an accuracy ranging from 97.83% to 99.67% in brain cancer detection by exploiting four different models: VGG16, ResNet50, Alex_Net, and MobileNet, thus showing the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Biosensor Based Advanced Cancer Diagnostics and Therapy)
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