A biomimetic sensor for monitoring oxidative stress biomarker in point-of-care

1st ASPIC International Congress

Sarcosine oxidase composite screen-printed electrode for sarcosine determination in biological samples

XIX Meeting of the Portuguese Electrochemical Society - XVI Iberic Meeting of Electrochemistry

Sol-Gel Chemistry in Biosensing Devices of Electrical Transduction: Application to CEA Cancer Biomarker

Sol-gel chemistry allows the immobilization of organic molecules of biological origin on suibtable solid supports, permitting their integration into biosensing devices widening the possibility of local applications. The present work is an application of this principle, where the link between electrical receptor platform and the antibody acting as biorecognition element is made by sol-gel chemistry. The immunosensor design was targeted for carcinoembryonic antigen (CEA), an important biomarker for screening the colorectal cancer, by electrochemical techniques, namely electrochemical impedance spectroscopy (EIS) and square wave voltammetry (SVW). The device displayed linear behavior to CEA in EIS and in SWV assays ranging from 0.50 to 1.5ng/mL, and 0.25 to 1.5ng/mL, respectively. The corresponding detection limits were 0.42 and 0.043 ng/mL. Raman spectroscopy was used to characterize the surface modifications on the conductive platform (FTO glass). Overall, simple sol-gel chemistry was effective at the biosensing design and the presented approach can be a potential method for screening CEA in point-of-care, due to the simplicity of fabrication, short response time and low cost. - See more at: http://www.eurekaselect.com/127192/article#sthash.m1AWhINx.dpuf

A novel antibody-like material for breast cancer antigen CA15-3, used to track breast cancer by potentiometric transduction

This work presents the development of a low cost sensor device for the diagnosis of breast cancer in point-of-care, made with new synthetic biomimetic materials inside plasticized poly(vinyl chloride), PVC, membranes, for subsequent potentiometric detection. This concept was applied to target a conventional biomarker in breast cancer: Breast Cancer Antigen (CA15-3). The new biomimetic material was obtained by molecularly-imprinted technology. In this, a plastic antibody was obtained by polymerizing around the biomarker that acted as an obstacle to the growth of the polymeric matrix. The imprinted polymer was specifically synthetized by electropolymerization on an FTO conductive glass, by using cyclic voltammetry, including 40 cycles within -0.2 and 1.0 V. The reaction used for the polymerization included monomer (pyrrol, 5.0×10-3 mol/L) and protein (CA15-3, 100U/mL), all prepared in phosphate buffer saline (PBS), with a pH of 7.2 and 1% of ethylene glycol. The biomarker was removed from the imprinted sites by proteolytic action of proteinase K. The biomimetic material was employed in the construction of potentiometric sensors and tested with regard to its affinity and selectivity for binding CA15-3, by checking the analytical performance of the obtained electrodes. For this purpose, the biomimetic material was dispersed in plasticized PVC membranes, including or not a lipophilic ionic additive, and applied on a solid conductive support of graphite. The analytical behaviour was evaluated in buffer and in synthetic serum, with regard to linear range, limit of detection, repeatability, and reproducibility. This antibody-like material was tested in synthetic serum, and good results were obtained. The best devices were able to detect 5 times less CA15-3 than that required in clinical use. Selectivity assays were also performed, showing that the various serum components did not interfere with this biomarker. Overall, the potentiometric-based methods showed several advantages compared to other methods reported in the literature. The analytical process was simple, providing fast responses for a reduced amount of analyte, with low cost and feasible miniaturization. It also allowed the detection of a wide range of concentrations, diminishing the required efforts in previous sample pre-treating stages.

Sol-gel biomimetic material designed to target CEA cancer biomarker

1st ASPIC International Congress

A disposable glass-based immunosensor for monitoring the cancer biomarker CEA in urine

NanoPT 2014 International Conference, in Portugal, on February 12-14. Poster presentation based on topic Nanobio/Nanomedicine

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.