AIMC Topic: Microfluidics

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Deep Learning with Microfluidics for Biotechnology.

Trends in biotechnology
Advances in high-throughput and multiplexed microfluidics have rewarded biotechnology researchers with vast amounts of data but not necessarily the ability to analyze complex data effectively. Over the past few years, deep artificial neural networks ...

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...

Autonomous Magnetic Microrobots by Navigating Gates for Multiple Biomolecules Delivery.

Small (Weinheim an der Bergstrasse, Germany)
The precise delivery of biofunctionalized matters is of great interest from the fundamental and applied viewpoints. In spite of significant progress achieved during the last decade, a parallel and automated isolation and manipulation of rare analyte,...

Label-free detection of cellular drug responses by high-throughput bright-field imaging and machine learning.

Scientific reports
In the last decade, high-content screening based on multivariate single-cell imaging has been proven effective in drug discovery to evaluate drug-induced phenotypic variations. Unfortunately, this method inherently requires fluorescent labeling which...

Multiparameter mechanical and morphometric screening of cells.

Scientific reports
We introduce a label-free method to rapidly phenotype and classify cells purely based on physical properties. We extract 15 biophysical parameters from cells as they deform in a microfluidic stretching flow field via high-speed microscopy and apply m...

tarSVM: Improving the accuracy of variant calls derived from microfluidic PCR-based targeted next generation sequencing using a support vector machine.

BMC bioinformatics
BACKGROUND: Targeted sequencing of discrete gene sets is a cost effective strategy to screen subjects for monogenic forms of disease. One method to achieve this pairs microfluidic PCR with next generation sequencing. The PCR step of this pipeline cre...

Printing 2-dimentional droplet array for single-cell reverse transcription quantitative PCR assay with a microfluidic robot.

Scientific reports
This paper describes a nanoliter droplet array-based single-cell reverse transcription quantitative PCR (RT-qPCR) assay method for quantifying gene expression in individual cells. By sequentially printing nanoliter-scale droplets on microchip using a...

Understanding Networks of Computing Chemical Droplet Neurons Based on Information Flow.

International journal of neural systems
In this paper, we present general methods that can be used to explore the information processing potential of a medium composed of oscillating (self-exciting) droplets. Networks of Belousov-Zhabotinsky (BZ) droplets seem especially interesting as che...

Bacterial identification in SERS-integrated microfluidics using CNN-driven 2D classification of 1D spectra.

Talanta
Bacterial sensing involves complex and variable samples that require advanced handling and analytical methods. To address these challenges, machine learning-especially deep learning-and SERS-based microfluidics have shown great promise. While previou...

A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis.

Nature communications
Sepsis is a life-threatening organ dysfunction due to a dysfunctional response to infection. Delays in diagnosis have substantial impact on survival. Herein, blood samples from 586 in-house patients with suspected sepsis are used in conjunction with ...