AIMC Topic: Lab-On-A-Chip Devices

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A Noninvasive Glucose Monitoring SoC Based on Single Wavelength Photoplethysmography.

IEEE transactions on biomedical circuits and systems
Conventional glucose monitoring methods for the growing numbers of diabetic patients around the world are invasive, painful, costly and, time-consuming. Complications aroused due to the abnormal blood sugar levels in diabetic patients have created th...

Robotic fluidic coupling and interrogation of multiple vascularized organ chips.

Nature biomedical engineering
Organ chips can recapitulate organ-level (patho)physiology, yet pharmacokinetic and pharmacodynamic analyses require multi-organ systems linked by vascular perfusion. Here, we describe an 'interrogator' that employs liquid-handling robotics, custom s...

Biomimetic smoking robot for in vitro inhalation exposure compatible with microfluidic organ chips.

Nature protocols
Exposure of lung tissues to cigarette smoke is a major cause of human disease and death worldwide. Unfortunately, adequate model systems that can reliably recapitulate disease biogenesis in vitro, including exposure of the human lung airway to fresh ...

CD4+ versus CD8+ T-lymphocyte identification in an integrated microfluidic chip using light scattering and machine learning.

Lab on a chip
T lymphocytes are a group of cells representing the main effectors of human adaptive immunity. Characterization of the most representative T-lymphocyte subclasses, CD4+ and CD8+, is challenging, but has a significant impact on clinical decisions. Up ...

A practical guide to intelligent image-activated cell sorting.

Nature protocols
Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell s...

Setting Up a Surface-Enhanced Raman Scattering Database for Artificial-Intelligence-Based Label-Free Discrimination of Tumor Suppressor Genes.

Analytical chemistry
The quality of input data in deep learning is tightly associated with the ultimate performance of the machine learner. Taking advantage of the unique merits of surface-enhanced Raman scattering (SERS) methodology in the collection and construction of...

Kernel-Based Microfluidic Constriction Assay for Tumor Sample Identification.

ACS sensors
A high-throughput multiconstriction microfluidic channels device can distinguish human breast cancer cell lines (MDA-MB-231, HCC-1806, MCF-7) from immortalized breast cells (MCF-10A) with a confidence level of ∼81-85% at a rate of 50-70 cells/min bas...

Thread/paper- and paper-based microfluidic devices for glucose assays employing artificial neural networks.

Electrophoresis
This paper describes the fabrication of and data collection from two microfluidic devices: a microfluidic thread/paper based analytical device (μTPAD) and 3D microfluidic paper-based analytical device (μPAD). Flowing solutions of glucose oxidase (GOx...

Scalable Device for Automated Microbial Electroporation in a Digital Microfluidic Platform.

ACS synthetic biology
Electrowetting-on-dielectric (EWD) digital microfluidic laboratory-on-a-chip platforms demonstrate excellent performance in automating labor-intensive protocols. When coupled with an on-chip electroporation capability, these systems hold promise for ...

Designing a biochip following multiplex polymerase chain reaction for the detection of Salmonella serovars Typhimurium, Enteritidis, Infantis, Hadar, and Virchow in poultry products.

Journal of food and drug analysis
Salmonella-contaminated foods, especially poultry-derived foods (eggs, chicken meat), are the major source of salmonellosis. Not only in the European Union (EU), but also in the United States, Japan, and other countries, has salmonellosis been an iss...