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Advanced Molecular Detection and Health Risk Evaluation: From Food Hazards to Disease Biomarkers

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 857

Editors


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Guest Editor
College of Food Science and Engineering, Yangzhou University, Yangzhou 225001, China
Interests: fluorescence detection; molecular simulation; quantum computation; food risk analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Molecular detection technologies have evolved rapidly, providing essential tools for identifying foodborne hazards, evaluating endocrine‑disrupting effects, and monitoring biomarkers associated with major human diseases, including cancer. As both food safety challenges and disease risks grow increasingly complex, there is a heightened need for analytical strategies capable of achieving high sensitivity, strong specificity, and mechanistic insight across diverse biological systems.

This Special Issue highlights recent advances in molecular detection and health risk evaluation, spanning the full spectrum from food contaminants to disease and cancer biomarkers. We welcome contributions on the identification and assessment of chemical hazards, pathogenic factors, and emerging contaminants in foods, as well as studies investigating the molecular mechanisms of toxicity, endocrine disruption, and nutrition‑related health effects. Research involving cancer‑related pathways, tumor marker identification, or molecular mechanisms linking environmental exposures to carcinogenesis is particularly encouraged.

Submissions employing in vivo and in vitro methods for molecular detection, as well as studies that integrate molecular detection with health risk prediction, cancer biomarker discovery, or mechanistic modeling to elucidate how food hazards and molecular lesions contribute to disease development, are highly encouraged.

This Special Issue aims to advance the field of molecular detection and risk assessment, supporting safer food systems and improved strategies for preventing and monitoring human diseases, including cancer.

Dr. Tianzhu Guan
Prof. Dr. Jie Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • molecular detection
  • foodborne hazards
  • emerging contaminants
  • toxicity mechanisms
  • nuclear receptors
  • health risk evaluation
  • cancer biomarkers

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Published Papers (1 paper)

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Review

30 pages, 3957 KB  
Review
Recent Advances on Sensor Technologies for the Monitoring of Tumor Markers
by Yubang Dong, Qi Zhao, Yining Feng, Weikang Yang, Bo Wang, Yuqing Wang, Mingyuan Gao, Jie Zhang and Tianzhu Guan
Molecules 2026, 31(11), 1919; https://doi.org/10.3390/molecules31111919 - 2 Jun 2026
Cited by 1 | Viewed by 599
Abstract
Sensor technologies have been increasingly recognized as a cornerstone for advancing tumor diagnostics amid the global health challenge posed by cancer. Traditional diagnostic methods are often constrained by inherent tumor heterogeneity, while liquid biopsy has emerged as a transformative minimally invasive alternative, with [...] Read more.
Sensor technologies have been increasingly recognized as a cornerstone for advancing tumor diagnostics amid the global health challenge posed by cancer. Traditional diagnostic methods are often constrained by inherent tumor heterogeneity, while liquid biopsy has emerged as a transformative minimally invasive alternative, with biosensors playing a pivotal role in its clinical translation. This review summarizes the progress of tumor diagnostic biosensors, focusing on electrochemical and fluorescent sensors. Electrochemical sensors excel in quantitative precision, miniaturization, and point-of-care (POCT) applicability, enabling ultra-sensitive detection of biomarkers such as circulating tumor cells, circulating tumor DNA, and exosomes through nanomaterial modification and signal amplification strategies. Fluorescent sensors, meanwhile, offer superior multiplexing capability and in situ imaging performance, which are further enhanced by novel nanomaterials. Additionally, it covers other promising sensor types including Surface-Enhanced Raman Scattering, microfluidic, photoelectrochemical, field-effect transistor, and clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins-based sensors. Current research efforts are concentrated on multiplexed detection, point-of-care integration, and translation toward higher-order clinical functions such as cancer subtype discrimination, risk stratification, and prognosis. Future directions will focus on multimodal integration, intelligent data analysis, and prospective clinical validation against hard endpoints to facilitate the implementation of precision oncology. Full article
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