We propose a new method for molecular detection that retains the sensitivity of fluorescence, but without requiring fluorescence labeling of the sample. The method works by spiking the sample solution with one or more labeled molecular species of known concentration. With proper choice of these "competitor" species, their binding kinetics can be used to quantitatively determine the concentration of unlabeled target species. This method can be applied to any fluorescence transduction mechanism that allows real-time signal acquisition, and represents an advance in mitigating certain sample processing steps. We demonstrate the method for the detection of a DNA sequence containing a single-nucleotide polymorphism (SNP).
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1364/oe.15.004390 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Testing an Electronic Patient-Reported Outcome Platform in the Context of Traumatic Brain Injury: PRiORiTy Usability Study.
JMIR Form Res
January 2025
Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom.
Background: Traumatic brain injury (TBI) is a significant public health issue and a leading cause of death and disability globally. Advances in clinical care have improved survival rates, leading to a growing population living with long-term effects of TBI, which can impact physical, cognitive, and emotional health. These effects often require continuous management and individualized care.
View Article and Find Full Text PDFGrading systems and perineural invasion in oral squamous cell carcinoma - a disease-specific survival analysis.
Med Oral Patol Oral Cir Bucal
January 2025
Department of Oral Diagnosis, Piracicaba Dental School University of Campinas, 901, Limeira Avenue Postcode: 13414-903. Piracicaba-SP, Brazil
Background: Oral squamous cell carcinoma (OSCC) is an aggressive cancer, with prognosis influenced by clinical variables as well grading systems and perineural invasion (PNI), which are associated to poorer outcomes, including higher rates of recurrence and metastasis. This study aims to evaluate OSCC using three grading systems and assess the impact of PNI and clinicopathologic parameters on patient survival.
Material And Methods: Eighty-one primary OSCC samples were analyzed.
How likely is it that a virus or bacteria is causing a patient's symptoms? A new approach to interpret the outcome from multi-pathogen PCR.
Infect Dis (Lond)
January 2025
Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA.
Background: Whether a detected virus or bacteria is a pathogen that may require treatment, or is merely a commensal 'passenger', remains confusing for many infections. This confusion is likely to increase with the wider use of multi-pathogen PCR.
Objectives: To propose a new statistical procedure to analyse and present data from case-control studies clarifying the probability of causality.
18F-Sodium Fluoride PET/CT as a Tool to Assess Enthesopathies in X-Linked Hypophosphatemia.
Calcif Tissue Int
January 2025
Endocrinology Department, School of Medicine, Pontificia Universidad Católica de Chile, Av. Diagonal Paraguay 262, Cuarto Piso, Santiago, Chile.
X-linked hypophosphatemia (XLH) is a rare metabolic disorder characterized by elevated FGF23 and chronic hypophosphatemia, leading to impaired skeletal mineralization and enthesopathies that are associated with pain, stiffness, and diminished quality of life. The natural history of enthesopathies in XLH remains poorly defined, partly due to absence of a sensitive quantitative tool for assessment and monitoring. This study investigates the utility of 18F-NaF PET/CT scans in characterizing enthesopathies in XLH subjects.
View Article and Find Full Text PDFAutomated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study.
Radiol Med
January 2025
Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Purpose: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.
Methods: On lateral full-spine radiographs of 295 consecutive patients, a two-staged region-based convolutional neural network (R-CNN) was trained to detect anatomical landmarks and calculate thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and sagittal vertical axis (SVA). Performance was evaluated on 65 radiographs not used for training, which were measured independently by 6 readers (3 radiologists, 3 surgeons), and the median per measurement was set as the reference standard.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!