Large-scale Plasmonic Microarray: A New Approach for Label-free High-throughput Biosensing and Screening

Author(s):  
Min Huang ◽  
Tsung-Yao Chang ◽  
Ahmet Ali Yanik ◽  
Hsin-Yu Tsai ◽  
Peng Shi ◽  
...  
2018 ◽  
Vol 24 (4) ◽  
pp. 457-465 ◽  
Author(s):  
Wataru Asano ◽  
Yu Takahashi ◽  
Motoaki Kawano ◽  
Yoshiji Hantani

Peripheral arterial disease (PAD) is an occlusive disease that can lead to atherosclerosis. The involvement of arginase II (Arg II) in PAD progression has been proposed. However, no promising drugs targeting Arg II have been developed to date for the treatment of PAD. In this study, we established a method for detecting the activity of Arg II via high-throughput label-free RapidFire mass spectrometry using hydrophilic interaction chromatography, which enables the direct measurement of l-ornithine produced by Arg II. This approach facilitated a robust high-concentration screening of fragment compounds and the identification of a fragment that inhibits the activity of Arg II. We further confirmed binding of the fragment to the potential allosteric site of Arg II using a surface plasmon resonance assay. We concluded that the identified fragment is a promising compound that may lead to novel drugs to treat PAD, and our method for detecting the activity of Arg II can be applied to large-scale high-throughput screening to identify other structural types of Arg II inhibitors.


Lab on a Chip ◽  
2011 ◽  
Vol 11 (21) ◽  
pp. 3596 ◽  
Author(s):  
Tsung-Yao Chang ◽  
Min Huang ◽  
Ahmet Ali Yanik ◽  
Hsin-Yu Tsai ◽  
Peng Shi ◽  
...  

2019 ◽  
Author(s):  
Kelvin C. M. Lee ◽  
Andy K. S. Lau ◽  
Anson H. L. Tang ◽  
Maolin Wang ◽  
Aaron T. Y. Mok ◽  
...  

AbstractA growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single cell precision to define cell identities in a large and heterogeneous population of cells – hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multi-ATOM that captures and processes quantitative label-free single-cell images at ultra-high throughput without compromising sub-cellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10,000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multi-variate, cell-type classification (e.g. breast cancer sub-types, and leukemic cells versus peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.


Nano LIFE ◽  
2013 ◽  
Vol 03 (02) ◽  
pp. 1350001 ◽  
Author(s):  
KARTIK KUMAR RAJAGOPALAN ◽  
JUAN CHEN ◽  
BAIYANG LU ◽  
SHENGNIAN WANG

Herein, we present a new flow-guided assembly approach to align and position DNA nanowires. Single or multiple drops of a λ-DNA solution were loaded from one side of template with micropad array and blown off by air flow. DNA molecules were aligned along the flow direction and well positioned under the guiding of pre-defined micropatterns. Different from other pioneering work, we focused on investigating the assembly quality, reliability and appropriateness for large-scale manufacturing. We correlated the assembly quality (alignment, patterning and the surface coverage) with the concentration of DNA in droplets and droplet evaporation and suggested appropriate process windows. With this new approach, the synthesis, alignment and patterning of nanowires may be done in a reliable and efficient manner and with high throughput.


2020 ◽  
Vol 11 (4) ◽  
pp. 1752 ◽  
Author(s):  
Kotaro Hiramatsu ◽  
Koji Yamada ◽  
Matthew Lindley ◽  
Kengo Suzuki ◽  
Keisuke Goda

2021 ◽  
pp. 247255522110281
Author(s):  
Roman P. Simon ◽  
Tim T. Häbe ◽  
Robert Ries ◽  
Martin Winter ◽  
Yuting Wang ◽  
...  

Acoustic droplet ejection (ADE)–open port interface (OPI)–mass spectrometry (MS) has recently been introduced as a versatile analytical method that combines fast and contactless acoustic sampling with sensitive and accurate electrospray ionization (ESI)–MS-based analyte detection. The potential of the technology to provide label-free measurements in subsecond analytical cycle times makes it an attractive option for high-throughput screening (HTS). Here, we report the first implementation of ADE-OPI-MS in a fully automated HTS environment, based on the example of a biochemical assay aiming at the identification of small-molecule inhibitors of the cyclic guanosine monophosphate–adenosine monophosphate (GMP-AMP) synthase (cGAS). First, we describe the optimization of the method to enable sensitive and accurate determination of enzyme activity and inhibition in miniaturized 1536-well microtiter plate format. Then we show both results from a validation single-concentration screen using a test set of 5500 compounds, and the subsequent concentration–response testing of selected hits in direct comparison with a previously established matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) readout. Finally, we present the development of an in-line OPI cleaning procedure aiming to match the instrument robustness required for large-scale HTS campaigns. Overall, this work points to critical method development parameters and provides guidance for the establishment of integrated ADE-OPI-MS as HTS-compatible technology for early drug discovery.


2019 ◽  
Author(s):  
Jakob Gierten ◽  
Christian Pylatiuk ◽  
Omar Hammouda ◽  
Christian Schock ◽  
Johannes Stegmaier ◽  
...  

AbstractRationaleAccurate and efficient quantification of heartbeats in small fish models is an important readout to study cardiovascular biology, disease states and pharmacology at large scale. However, dependence on anesthesia, laborious sample orientation or requirement for fluorescent reporters have hampered the establishment of high-throughput heartbeat analysis.ObjectiveTo overcome these limitations, we aimed to develop a high-throughput assay with automated heart rate scoring in medaka (Oryzias latipes) and zebrafish (Danio rerio) embryos under physiological conditions designed for genetic screens and drug discovery and validation.Methods and ResultsWe established an efficient screening assay employing automated label-free heart rate determination of randomly oriented, non-anesthetized specimen in microtiter plates. Automatically acquired bright-field data feeds into an easy-to-use HeartBeat software, a MATLAB algorithm with graphical user interface developed for automated quantification of heart rate and rhythm. Sensitivity of the assay and algorithm was demonstrated by profiling heart rates during entire embryonic development. Our analysis pipeline revealed acute temperature changes triggering rapid adaption of heart rates, which has implications for standardization of experimental layout. The approach is scalable and allows scoring of multiple embryos per well resulting in a throughput of >500 embryos per 96-well plate. In a proof of principle screen for compound testing, our assay captured concentration-dependent effects of nifedipine and terfenadine over time.ConclusionA novel workflow and HeartBeat software provide efficient means for reliable and direct quantification of heart rate and rhythm of small fish in a physiological environment. Importantly, confounding factors such as anesthetics or laborious mounting are eliminated. We provide detailed profiles of embryonic heart rate dynamics in medaka and zebrafish as reference for future assay development. Ease of sample handling, automated imaging, physiological conditions and software-assisted analysis now facilitate various large-scale applications ranging from phenotypic screening, interrogation of gene functions to cardiovascular drug development pipelines.


2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>


Author(s):  
V. Skibchyk ◽  
V. Dnes ◽  
R. Kudrynetskyi ◽  
O. Krypuch

Аnnotation Purpose. To increase the efficiency of technological processes of grain harvesting by large-scale agricultural producers due to the rational use of combine harvesters available on the farm. Methods. In the course of the research the methods of system analysis and synthesis, induction and deduction, system-factor and system-event approaches, graphic method were used. Results. Characteristic events that occur during the harvesting of grain crops, both within a single production unit and the entire agricultural producer are identified. A method for predicting time intervals of use and downtime of combine harvesters of production units has been developed. The roadmap of substantiation the rational seasonal scenario of the use of grain harvesters of large-scale agricultural producers is developed, which allows estimating the efficiency of each of the scenarios of multivariate placement of grain harvesters on fields taking into account influence of natural production and agrometeorological factors on the efficiency of technological cultures. Conclusions 1. Known scientific and methodological approaches to optimization of machine used in agriculture do not take into account the risks of losses of crops due to late harvesting, as well as seasonal natural and agrometeorological conditions of each production unit of the farmer, which requires a new approach to the rational use of rational seasonal combines of large agricultural producers. 2. The developed new approach to the substantiation of the rational seasonal scenario of the use of combined harvesters of large-scale agricultural producers allows taking into account the costs of harvesting of grain and the cost of the lost crop because of the lateness of harvesting at optimum variants of attraction of additional free combine harvesters. provides more profit. 3. The practical application of the developed road map will allow large-scale agricultural producers to use combine harvesters more efficiently and reduce harvesting costs. Keywords: combine harvesters, use, production divisions, risk, seasonal scenario, large-scale agricultural producers.


Author(s):  
S. Pragati ◽  
S. Kuldeep ◽  
S. Ashok ◽  
M. Satheesh

One of the situations in the treatment of disease is the delivery of efficacious medication of appropriate concentration to the site of action in a controlled and continual manner. Nanoparticle represents an important particulate carrier system, developed accordingly. Nanoparticles are solid colloidal particles ranging in size from 1 to 1000 nm and composed of macromolecular material. Nanoparticles could be polymeric or lipidic (SLNs). Industry estimates suggest that approximately 40% of lipophilic drug candidates fail due to solubility and formulation stability issues, prompting significant research activity in advanced lipophile delivery technologies. Solid lipid nanoparticle technology represents a promising new approach to lipophile drug delivery. Solid lipid nanoparticles (SLNs) are important advancement in this area. The bioacceptable and biodegradable nature of SLNs makes them less toxic as compared to polymeric nanoparticles. Supplemented with small size which prolongs the circulation time in blood, feasible scale up for large scale production and absence of burst effect makes them interesting candidates for study. In this present review this new approach is discussed in terms of their preparation, advantages, characterization and special features.


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