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BACKGROUND: the problem in early diagnosis of sporadic cancer is understanding the individual's risk to develop disease. In response to this need, global scientific research is focusing on developing predictive models based on non-invasive screening tests. A tentative solution to the problem may be a cancer screening blood-based test able to discover those cell requirements triggering subclinical and clinical onset latency, at the stage when the cell disorder, i.e. atypical epithelial hyperplasia, is still in a subclinical stage of proliferative dysregulation. METHODS: a well-established procedure to identify proliferating circulating tumor cells was deployed to measure the cell proliferation of circulating non-haematological cells which may suggest tumor pathology. Moreover, the data collected were processed by a supervised machine learning model to make the prediction. RESULTS: the developed test combining circulating non-haematological cell proliferation data and artificial intelligence shows 98.8% of accuracy, 100% sensitivity, and 95% specificity. CONCLUSION: this proof of concept study demonstrates that integration of innovative non invasive methods and predictive-models can be decisive in assessing the health status of an individual, and achieve cutting-edge results in cancer prevention and management.
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Inteligencia Artificial , Neoplasias , HumanosRESUMEN
Saccharides displayed on the cell surface of pathogens play critical roles in many activities such as adhesion, recognition and pathogenesis, as well as in prokaryotic development. In this work, we report the synthesis of molecularly imprinted nanoparticles (nanoMIPs) against pathogen surface monosaccharides using an innovative solid-phase approach. These nanoMIPs can serve as robust and selective artificial lectins specific to one particular monosaccharide. The evaluation of their binding capabilities has been implemented against bacterial cells (E. coli and S. pneumoniae) as model pathogens. The nanoMIPs were produced against two different monosaccharides: mannose (Man), which is present mainly on the surface of Gram-negative bacteria, and N-acetylglucosamine (GlcNAc) exposed on the surface of the majority of bacteria. Herein, we assessed the potential use of nanoMIPs for pathogen cell imaging and detection via flow cytometry and confocal microscopy.
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Butyrylfentanyl is a new designer drug reported with growing use and related deaths. Routine toxicological analyses of this novel synthetic opioid drug have not been established yet. This work reports a fibre optic sensor that measures carboxyl-fentanyl which is the major metabolite of butyrylfentanyl presented in blood, providing a promising tool for detecting butyrylfentanyl intoxication. A long period fibre grating (LPG) sensor array operating at phase-matching condition is deployed in combination with a state-of-the-art molecular imprinting technique. Nano-sized molecularly imprinted polymers (nanoMIPs) are synthesised via a solid-phase approach and coated on the surface of an LPG array. An LPG array consists of two parts: a detection and a reference LPG. The former is functionalised with nanoMIPs prior to the measurements, whilst the latter is used to take into account the temperature response of the detection LPG. The developed sensor exhibits a gradual response over increasing concentrations of carboxyl-fentanyl from 0 to 1000 ng/mL with a minimal detected concentration of 50 ng/mL, that corresponds to a wavelength shift of 1.20 ± 0.2 nm. The Langmuir adsorption isotherm is applied to fit the analytical data which reveal a binding constant of 2.03 µM-1. The developed sensor shows high selectivity in detecting carboxyl-fentanyl among other drugs and potential interferents including morphine, cocaine, glucose and albumin. It shows a certain degree of cross-response to fentanyl which shares the same binding sites as carboxyl-fentanyl and therefore can be potentially used to detect fentanyl.
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Técnicas Biosensibles , Impresión Molecular , Nanopartículas , Fentanilo , Fibras ÓpticasRESUMEN
Protein A has long been used in different research fields due to its ability to specifically recognize immunoglobulins (Ig). The protein derived from Staphylococcus aureus binds Ig through the Fc region of the antibody, showing its strongest binding in immunoglobulin G (IgG), making it the most used protein in its purification and detection. The research presented here integrates, for the first time, protein A to a silicon surface patterned with gold nanoparticles for the oriented binding of IgG. The signal detection is conveyed through a metal enhanced fluorescence (MEF) system. Orienting immunoglobulins allows the exposition of the fragment antigen-binding (Fab) region for the binding to its antigen, substantially increasing the binding capacity per antibody immobilized. Antibodies orientation is of crucial importance in many diagnostics devices, particularly when either component is in limited quantities.