Unrepaired DNA damage can lead to mutation, cancer, and death of cells or organisms. However, due to the subtlety of DNA damage, it is difficult to sense the presence of damage repair with high selectivity and sensitivity. We have shown sensitive and selective electrochemical sensing of 8-oxoguanine and uracil repair glycosylase activity within DNA monolayers on gold by multiplexed analysis with silicon chips and low-cost electrospun nanofibers. Our approach compared the electrochemical signal of electroactive, probe-modified DNA monolayers containing a base defect versus the rational control of defect-free monolayers. We found damage-specific sensitivity thresholds on the order of femtomoles of proteins and dynamic ranges of over two orders of magnitude for each target. Temperature-dependent kinetics were extracted, showing exponential signal loss with time constants of seconds. Damage specific detection in a mixture of enzymes and in response to environmental oxidative damage was also demonstrated. Nanofibers were shown to behave similarly to conventional gold-on-silicon devices, showing the potential of these low-cost devices for sensing applications. This device approach achieves a sensitive, selective, and rapid assay of repair protein activity, enabling a biological interrogation of DNA damage repair.
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http://dx.doi.org/10.1016/j.bios.2013.11.034 | DOI Listing |
Discov Oncol
January 2025
Department of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, 415003, Hunan, China.
Purpose: Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma.
View Article and Find Full Text PDFFolia Microbiol (Praha)
January 2025
Department of Public Health, Faculty of Medicine, Masaryk University, Kamenice 753/5, 625 00, Brno, Czech Republic.
Medical students are exposed to the hospital environment and patients during their studies, increasing the risk of exposure to virulent and antibiotic-resistant isolates of Staphylococcus aureus. The aim of the study is to determine the prevalence of Staphylococcus aureus among medical students who have varying levels of exposure to the hospital environment to provide valuable insights into the risk of colonization and transmission. Nasal swabs and fingerprints were obtained and cultured on a selective medium for staphylococci.
View Article and Find Full Text PDFAllergol Int
January 2025
Research Division, Federal Institute for Drugs and Medical Devices (BfArM), Bonn, Germany; Department of Dermatology and Allergy, University Hospital Aachen, Aachen, Germany.
Background: The detection of drug-specific activation of T cells in the lymphocyte transformation test (LTT) is mainly based on cell proliferation or cytokine secretion. However, the LTT presents with a varying sensitivity and specificity. The aim of our study was to analyse the genome wide gene expression of PBMC to identify drug allergy-specific gene regulation patterns.
View Article and Find Full Text PDFUrol Oncol
January 2025
Department of Clinical Biochemistry, School of Medicine, Shahid Sadoughi University of Medical Sciences and Health Services, Yazd, Iran. Electronic address:
Background And Objective: Research into new noninvasive diagnostic tools for bladder cancer (BCa) with superior sensitivity and specificity to cystoscopy and cytology is promising. The current study evaluated a diagnostic panel of tumor progression-related mRNAs in urine samples of NMIBC patients and controls.
Methods: This study carefully selected 129 participants, including 67 NMIBC patients, 31 hematuria patients due to nonmalignant urological disorders, and 31 healthy individuals.
Global Spine J
January 2025
Department of Orthopaedics, Phramongkutklao Hospital and College of Medicine, Bangkok, Thailand.
Study Design: Systematic review.
Objective: Artificial intelligence (AI) and deep learning (DL) models have recently emerged as tools to improve fracture detection, mainly through imaging modalities such as computed tomography (CT) and radiographs. This systematic review evaluates the diagnostic performance of AI and DL models in detecting cervical spine fractures and assesses their potential role in clinical practice.
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