Programmable bio-nanochip technology for the diagnosis of cardiovascular disease at the point-of-care.
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Cardiovascular disease remains the leading cause of death in the world and continues to serve as the major contributor to healthcare costs. Likewise, there is an ever-increasing need and demand for novel and more efficient diagnostic tools for the early detection of cardiovascular disease, especially at the point-of-care (POC). This article reviews the programmable bio-nanochip (P-BNC) system, a new medical microdevice approach with the capacity to deliver both high performance and reduced cost. This fully integrated, total analysis system leverages microelectronic components, microfabrication techniques, and nanotechnology to noninvasively measure multiple cardiac biomarkers in complex fluids, such as saliva, while offering diagnostic accuracy equal to laboratory-confined reference methods. This article profiles the P-BNC approach, describes its performance in real-world testing of clinical samples, and summarizes new opportunities for medical microdevices in the field of cardiac diagnostics. (+info)
The GENOTEND chip: a new tool to analyse gene expression in muscles of beef cattle for beef quality prediction.
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Crowd-sourced BioGames: managing the big data problem for next-generation lab-on-a-chip platforms.
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We describe a crowd-sourcing based solution for handling large quantities of data that are created by e.g., emerging digital imaging and sensing devices, including next generation lab-on-a-chip platforms. We show that in cases where the diagnosis is a binary decision (e.g., positive vs. negative, or infected vs. uninfected), it is possible to make accurate diagnosis by crowd-sourcing the raw data (e.g., microscopic images of specimens/cells) using entertaining digital games (i.e., ) that are played on PCs, tablets or mobile phones. We report the results and the analysis of a large-scale public experiment toward diagnosis of malaria infected human red blood cells (RBCs), where binary responses from approximately 1000 untrained individuals from more than 60 different countries are combined together (corresponding to more than 1 million cell diagnoses), resulting in an accuracy level that is comparable to those of expert medical professionals. This platform holds promise toward cost-effective and accurate tele-pathology, improved training of medical personnel, and can also be used to manage the "Big Data" problem that is emerging through next generation digital lab-on-a-chip devices. (+info)
Noncoding RNAs binding to the nucleoid protein HU in Escherichia coli.
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