SPIM-fluid: open source light-sheet based platform for high-throughput imaging

PubMed Central

Gualda, Emilio J.; Pereira, Hugo; Vale, Tiago; Estrada, Marta Falcão; Brito, Catarina; Moreno, Nuno

2015-01-01

Light sheet fluorescence microscopy has recently emerged as the technique of choice for obtaining high quality 3D images of whole organisms/embryos with low photodamage and fast acquisition rates. Here we present an open source unified implementation based on Arduino and Micromanager, which is capable of operating Light Sheet Microscopes for automatized 3D high-throughput imaging on three-dimensional cell cultures and model organisms like zebrafish, oriented to massive drug screening. PMID:26601007

High-speed Fourier ptychographic microscopy based on programmable annular illuminations.

PubMed

Sun, Jiasong; Zuo, Chao; Zhang, Jialin; Fan, Yao; Chen, Qian

2018-05-16

High-throughput quantitative phase imaging (QPI) is essential to cellular phenotypes characterization as it allows high-content cell analysis and avoids adverse effects of staining reagents on cellular viability and cell signaling. Among different approaches, Fourier ptychographic microscopy (FPM) is probably the most promising technique to realize high-throughput QPI by synthesizing a wide-field, high-resolution complex image from multiple angle-variably illuminated, low-resolution images. However, the large dataset requirement in conventional FPM significantly limits its imaging speed, resulting in low temporal throughput. Moreover, the underlying theoretical mechanism as well as optimum illumination scheme for high-accuracy phase imaging in FPM remains unclear. Herein, we report a high-speed FPM technique based on programmable annular illuminations (AIFPM). The optical-transfer-function (OTF) analysis of FPM reveals that the low-frequency phase information can only be correctly recovered if the LEDs are precisely located at the edge of the objective numerical aperture (NA) in the frequency space. By using only 4 low-resolution images corresponding to 4 tilted illuminations matching a 10×, 0.4 NA objective, we present the high-speed imaging results of in vitro Hela cells mitosis and apoptosis at a frame rate of 25 Hz with a full-pitch resolution of 655 nm at a wavelength of 525 nm (effective NA = 0.8) across a wide field-of-view (FOV) of 1.77 mm 2 , corresponding to a space-bandwidth-time product of 411 megapixels per second. Our work reveals an important capability of FPM towards high-speed high-throughput imaging of in vitro live cells, achieving video-rate QPI performance across a wide range of scales, both spatial and temporal.

Photon-Counting H33D Detector for Biological Fluorescence Imaging

PubMed Central

Michalet, X.; Siegmund, O.H.W.; Vallerga, J.V.; Jelinsky, P.; Millaud, J.E.; Weiss, S.

2010-01-01

We have developed a photon-counting High-temporal and High-spatial resolution, High-throughput 3-Dimensional detector (H33D) for biological imaging of fluorescent samples. The design is based on a 25 mm diameter S20 photocathode followed by a 3-microchannel plate stack, and a cross delay line anode. We describe the bench performance of the H33D detector, as well as preliminary imaging results obtained with fluorescent beads, quantum dots and live cells and discuss applications of future generation detectors for single-molecule imaging and high-throughput study of biomolecular interactions. PMID:20151021

High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Wei; Shabbir, Faizan; Gong, Chao

2015-04-13

We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processingmore » units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.« less

Establishment of integrated protocols for automated high throughput kinetic chlorophyll fluorescence analyses.

PubMed

Tschiersch, Henning; Junker, Astrid; Meyer, Rhonda C; Altmann, Thomas

2017-01-01

Automated plant phenotyping has been established as a powerful new tool in studying plant growth, development and response to various types of biotic or abiotic stressors. Respective facilities mainly apply non-invasive imaging based methods, which enable the continuous quantification of the dynamics of plant growth and physiology during developmental progression. However, especially for plants of larger size, integrative, automated and high throughput measurements of complex physiological parameters such as photosystem II efficiency determined through kinetic chlorophyll fluorescence analysis remain a challenge. We present the technical installations and the establishment of experimental procedures that allow the integrated high throughput imaging of all commonly determined PSII parameters for small and large plants using kinetic chlorophyll fluorescence imaging systems (FluorCam, PSI) integrated into automated phenotyping facilities (Scanalyzer, LemnaTec). Besides determination of the maximum PSII efficiency, we focused on implementation of high throughput amenable protocols recording PSII operating efficiency (Φ PSII ). Using the presented setup, this parameter is shown to be reproducibly measured in differently sized plants despite the corresponding variation in distance between plants and light source that caused small differences in incident light intensity. Values of Φ PSII obtained with the automated chlorophyll fluorescence imaging setup correlated very well with conventionally determined data using a spot-measuring chlorophyll fluorometer. The established high throughput operating protocols enable the screening of up to 1080 small and 184 large plants per hour, respectively. The application of the implemented high throughput protocols is demonstrated in screening experiments performed with large Arabidopsis and maize populations assessing natural variation in PSII efficiency. The incorporation of imaging systems suitable for kinetic chlorophyll fluorescence analysis leads to a substantial extension of the feature spectrum to be assessed in the presented high throughput automated plant phenotyping platforms, thus enabling the simultaneous assessment of plant architectural and biomass-related traits and their relations to physiological features such as PSII operating efficiency. The implemented high throughput protocols are applicable to a broad spectrum of model and crop plants of different sizes (up to 1.80 m height) and architectures. The deeper understanding of the relation of plant architecture, biomass formation and photosynthetic efficiency has a great potential with respect to crop and yield improvement strategies.

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

PubMed

Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

2008-04-01

The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

Frequency Based Design Partitioning to Achieve Higher Throughput in Digital Cross Correlator for Aperture Synthesis Passive MMW Imager.

PubMed

Asif, Muhammad; Guo, Xiangzhou; Zhang, Jing; Miao, Jungang

2018-04-17

Digital cross-correlation is central to many applications including but not limited to Digital Image Processing, Satellite Navigation and Remote Sensing. With recent advancements in digital technology, the computational demands of such applications have increased enormously. In this paper we are presenting a high throughput digital cross correlator, capable of processing 1-bit digitized stream, at the rate of up to 2 GHz, simultaneously on 64 channels i.e., approximately 4 Trillion correlation and accumulation operations per second. In order to achieve higher throughput, we have focused on frequency based partitioning of our design and tried to minimize and localize high frequency operations. This correlator is designed for a Passive Millimeter Wave Imager intended for the detection of contraband items concealed on human body. The goals are to increase the system bandwidth, achieve video rate imaging, improve sensitivity and reduce the size. Design methodology is detailed in subsequent sections, elaborating the techniques enabling high throughput. The design is verified for Xilinx Kintex UltraScale device in simulation and the implementation results are given in terms of device utilization and power consumption estimates. Our results show considerable improvements in throughput as compared to our baseline design, while the correlator successfully meets the functional requirements.

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping1[C][W][OPEN

PubMed Central

Klukas, Christian; Chen, Dijun; Pape, Jean-Michel

2014-01-01

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays ‘Fernandez’) plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable. PMID:24760818

Detection and quantification of adulterants in milk powder using high-throughput Raman chemical imaging technique

USDA-ARS?s Scientific Manuscript database

Milk is a vulnerable target for economically motivated adulteration. In this study, a line-scan high-throughput Raman imaging system was used to authenticate milk powder. A 5 W 785 nm line laser (240 mm long and 1 mm wide) was used as a Raman excitation source. The system was used to acquire hypersp...

Spotsizer: High-throughput quantitative analysis of microbial growth.

PubMed

Bischof, Leanne; Převorovský, Martin; Rallis, Charalampos; Jeffares, Daniel C; Arzhaeva, Yulia; Bähler, Jürg

2016-10-01

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license.

Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics.

PubMed

Das, Abhiram; Schneider, Hannah; Burridge, James; Ascanio, Ana Karine Martinez; Wojciechowski, Tobias; Topp, Christopher N; Lynch, Jonathan P; Weitz, Joshua S; Bucksch, Alexander

2015-01-01

Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput. Here, we present an open-source phenomics platform "DIRT", as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. The DIRT platform seamlessly connects end-users with large-scale compute "commons" enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size. DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots. It enables scientists to store, manage and share crop root images with metadata and compute RSA traits from thousands of images in parallel. It makes high-throughput RSA trait computation available to the community with just a few button clicks. As such it enables plant scientists to spend more time on science rather than on technology. All stored and computed data is easily accessible to the public and broader scientific community. We hope that easy data accessibility will attract new tool developers and spur creative data usage that may even be applied to other fields of science.

Strain Library Imaging Protocol for high-throughput, automated single-cell microscopy of large bacterial collections arrayed on multiwell plates.

PubMed

Shi, Handuo; Colavin, Alexandre; Lee, Timothy K; Huang, Kerwyn Casey

2017-02-01

Single-cell microscopy is a powerful tool for studying gene functions using strain libraries, but it suffers from throughput limitations. Here we describe the Strain Library Imaging Protocol (SLIP), which is a high-throughput, automated microscopy workflow for large strain collections that requires minimal user involvement. SLIP involves transferring arrayed bacterial cultures from multiwell plates onto large agar pads using inexpensive replicator pins and automatically imaging the resulting single cells. The acquired images are subsequently reviewed and analyzed by custom MATLAB scripts that segment single-cell contours and extract quantitative metrics. SLIP yields rich data sets on cell morphology and gene expression that illustrate the function of certain genes and the connections among strains in a library. For a library arrayed on 96-well plates, image acquisition can be completed within 4 min per plate.

A high throughput spectral image microscopy system

NASA Astrophysics Data System (ADS)

Gesley, M.; Puri, R.

2018-01-01

A high throughput spectral image microscopy system is configured for rapid detection of rare cells in large populations. To overcome flow cytometry rates and use of fluorophore tags, a system architecture integrates sample mechanical handling, signal processors, and optics in a non-confocal version of light absorption and scattering spectroscopic microscopy. Spectral images with native contrast do not require the use of exogeneous stain to render cells with submicron resolution. Structure may be characterized without restriction to cell clusters of differentiation.

Large-scale microfluidics providing high-resolution and high-throughput screening of Caenorhabditis elegans poly-glutamine aggregation model

NASA Astrophysics Data System (ADS)

Mondal, Sudip; Hegarty, Evan; Martin, Chris; Gökçe, Sertan Kutal; Ghorashian, Navid; Ben-Yakar, Adela

2016-10-01

Next generation drug screening could benefit greatly from in vivo studies, using small animal models such as Caenorhabditis elegans for hit identification and lead optimization. Current in vivo assays can operate either at low throughput with high resolution or with low resolution at high throughput. To enable both high-throughput and high-resolution imaging of C. elegans, we developed an automated microfluidic platform. This platform can image 15 z-stacks of ~4,000 C. elegans from 96 different populations using a large-scale chip with a micron resolution in 16 min. Using this platform, we screened ~100,000 animals of the poly-glutamine aggregation model on 25 chips. We tested the efficacy of ~1,000 FDA-approved drugs in improving the aggregation phenotype of the model and identified four confirmed hits. This robust platform now enables high-content screening of various C. elegans disease models at the speed and cost of in vitro cell-based assays.

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Quantitative monitoring of Arabidopsis thaliana growth and development using high-throughput plant phenotyping

PubMed Central

Arend, Daniel; Lange, Matthias; Pape, Jean-Michel; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Mücke, Ingo; Klukas, Christian; Altmann, Thomas; Scholz, Uwe; Junker, Astrid

2016-01-01

With the implementation of novel automated, high throughput methods and facilities in the last years, plant phenomics has developed into a highly interdisciplinary research domain integrating biology, engineering and bioinformatics. Here we present a dataset of a non-invasive high throughput plant phenotyping experiment, which uses image- and image analysis- based approaches to monitor the growth and development of 484 Arabidopsis thaliana plants (thale cress). The result is a comprehensive dataset of images and extracted phenotypical features. Such datasets require detailed documentation, standardized description of experimental metadata as well as sustainable data storage and publication in order to ensure the reproducibility of experiments, data reuse and comparability among the scientific community. Therefore the here presented dataset has been annotated using the standardized ISA-Tab format and considering the recently published recommendations for the semantical description of plant phenotyping experiments. PMID:27529152

Quantitative monitoring of Arabidopsis thaliana growth and development using high-throughput plant phenotyping.

PubMed

Arend, Daniel; Lange, Matthias; Pape, Jean-Michel; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Mücke, Ingo; Klukas, Christian; Altmann, Thomas; Scholz, Uwe; Junker, Astrid

2016-08-16

With the implementation of novel automated, high throughput methods and facilities in the last years, plant phenomics has developed into a highly interdisciplinary research domain integrating biology, engineering and bioinformatics. Here we present a dataset of a non-invasive high throughput plant phenotyping experiment, which uses image- and image analysis- based approaches to monitor the growth and development of 484 Arabidopsis thaliana plants (thale cress). The result is a comprehensive dataset of images and extracted phenotypical features. Such datasets require detailed documentation, standardized description of experimental metadata as well as sustainable data storage and publication in order to ensure the reproducibility of experiments, data reuse and comparability among the scientific community. Therefore the here presented dataset has been annotated using the standardized ISA-Tab format and considering the recently published recommendations for the semantical description of plant phenotyping experiments.

Depth-resolved incoherent and coherent wide-field high-content imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

So, Peter T.

2016-03-01

Recent advances in depth-resolved wide-field imaging technique has enabled many high throughput applications in biology and medicine. Depth resolved imaging of incoherent signals can be readily accomplished with structured light illumination or nonlinear temporal focusing. The integration of these high throughput systems with novel spectroscopic resolving elements further enable high-content information extraction. We will introduce a novel near common-path interferometer and demonstrate its uses in toxicology and cancer biology applications. The extension of incoherent depth-resolved wide-field imaging to coherent modality is non-trivial. Here, we will cover recent advances in wide-field 3D resolved mapping of refractive index, absorbance, and vibronic components in biological specimens.

High-throughput imaging of adult fluorescent zebrafish with an LED fluorescence macroscope

PubMed Central

Blackburn, Jessica S; Liu, Sali; Raimondi, Aubrey R; Ignatius, Myron S; Salthouse, Christopher D; Langenau, David M

2011-01-01

Zebrafish are a useful vertebrate model for the study of development, behavior, disease and cancer. A major advantage of zebrafish is that large numbers of animals can be economically used for experimentation; however, high-throughput methods for imaging live adult zebrafish had not been developed. Here, we describe protocols for building a light-emitting diode (LED) fluorescence macroscope and for using it to simultaneously image up to 30 adult animals that transgenically express a fluorescent protein, are transplanted with fluorescently labeled tumor cells or are tagged with fluorescent elastomers. These protocols show that the LED fluorescence macroscope is capable of distinguishing five fluorescent proteins and can image unanesthetized swimming adult zebrafish in multiple fluorescent channels simultaneously. The macroscope can be built and used for imaging within 1 day, whereas creating fluorescently labeled adult zebrafish requires 1 hour to several months, depending on the method chosen. The LED fluorescence macroscope provides a low-cost, high-throughput method to rapidly screen adult fluorescent zebrafish and it will be useful for imaging transgenic animals, screening for tumor engraftment, and tagging individual fish for long-term analysis. PMID:21293462

High-Throughput Light Sheet Microscopy for the Automated Live Imaging of Larval Zebrafish

NASA Astrophysics Data System (ADS)

Baker, Ryan; Logan, Savannah; Dudley, Christopher; Parthasarathy, Raghuveer

The zebrafish is a model organism with a variety of useful properties; it is small and optically transparent, it reproduces quickly, it is a vertebrate, and there are a large variety of transgenic animals available. Because of these properties, the zebrafish is well suited to study using a variety of optical technologies including light sheet fluorescence microscopy (LSFM), which provides high-resolution three-dimensional imaging over large fields of view. Research progress, however, is often not limited by optical techniques but instead by the number of samples one can examine over the course of an experiment, which in the case of light sheet imaging has so far been severely limited. Here we present an integrated fluidic circuit and microscope which provides rapid, automated imaging of zebrafish using several imaging modes, including LSFM, Hyperspectral Imaging, and Differential Interference Contrast Microscopy. Using this system, we show that we can increase our imaging throughput by a factor of 10 compared to previous techniques. We also show preliminary results visualizing zebrafish immune response, which is sensitive to gut microbiota composition, and which shows a strong variability between individuals that highlights the utility of high throughput imaging. National Science Foundation, Award No. DBI-1427957.

Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip.

PubMed

Heo, Young Jin; Lee, Donghyeon; Kang, Junsu; Lee, Keondo; Chung, Wan Kyun

2017-09-14

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

Quantitative digital image analysis of chromogenic assays for high throughput screening of alpha-amylase mutant libraries.

PubMed

Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

2009-08-01

An image analysis-based method for high throughput screening of an alpha-amylase mutant library using chromogenic assays was developed. Assays were performed in microplates and high resolution images of the assay plates were read using the Virtual Microplate Reader (VMR) script to quantify the concentration of the chromogen. This method is fast and sensitive in quantifying 0.025-0.3 mg starch/ml as well as 0.05-0.75 mg glucose/ml. It was also an effective screening method for improved alpha-amylase activity with a coefficient of variance of 18%.

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM).

PubMed

Tang, Anson H L; Lai, Queenie T K; Chung, Bob M F; Lee, Kelvin C M; Mok, Aaron T Y; Yip, G K; Shum, Anderson H C; Wong, Kenneth K Y; Tsia, Kevin K

2017-06-28

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the main trend in the advanced development of flow cytometry. Notably, adding high-resolution imaging capabilities allows for the complex morphological analysis of cellular/sub-cellular structures. This is not possible with standard flow cytometers. However, it is valuable for advancing our knowledge of cellular functions and can benefit life science research, clinical diagnostics, and environmental monitoring. Incorporating imaging capabilities into flow cytometry compromises the assay throughput, primarily due to the limitations on speed and sensitivity in the camera technologies. To overcome this speed or throughput challenge facing imaging flow cytometry while preserving the image quality, asymmetric-detection time-stretch optical microscopy (ATOM) has been demonstrated to enable high-contrast, single-cell imaging with sub-cellular resolution, at an imaging throughput as high as 100,000 cells/s. Based on the imaging concept of conventional time-stretch imaging, which relies on all-optical image encoding and retrieval through the use of ultrafast broadband laser pulses, ATOM further advances imaging performance by enhancing the image contrast of unlabeled/unstained cells. This is achieved by accessing the phase-gradient information of the cells, which is spectrally encoded into single-shot broadband pulses. Hence, ATOM is particularly advantageous in high-throughput measurements of single-cell morphology and texture - information indicative of cell types, states, and even functions. Ultimately, this could become a powerful imaging flow cytometry platform for the biophysical phenotyping of cells, complementing the current state-of-the-art biochemical-marker-based cellular assay. This work describes a protocol to establish the key modules of an ATOM system (from optical frontend to data processing and visualization backend), as well as the workflow of imaging flow cytometry based on ATOM, using human cells and micro-algae as the examples.

Ultrafast Microfluidic Cellular Imaging by Optical Time-Stretch.

PubMed

Lau, Andy K S; Wong, Terence T W; Shum, Ho Cheung; Wong, Kenneth K Y; Tsia, Kevin K

2016-01-01

There is an unmet need in biomedicine for measuring a multitude of parameters of individual cells (i.e., high content) in a large population efficiently (i.e., high throughput). This is particularly driven by the emerging interest in bringing Big-Data analysis into this arena, encompassing pathology, drug discovery, rare cancer cell detection, emulsion microdroplet assays, to name a few. This momentum is particularly evident in recent advancements in flow cytometry. They include scaling of the number of measurable colors from the labeled cells and incorporation of imaging capability to access the morphological information of the cells. However, an unspoken predicament appears in the current technologies: higher content comes at the expense of lower throughput, and vice versa. For example, accessing additional spatial information of individual cells, imaging flow cytometers only achieve an imaging throughput ~1000 cells/s, orders of magnitude slower than the non-imaging flow cytometers. In this chapter, we introduce an entirely new imaging platform, namely optical time-stretch microscopy, for ultrahigh speed and high contrast label-free single-cell (in a ultrafast microfluidic flow up to 10 m/s) imaging and analysis with an ultra-fast imaging line-scan rate as high as tens of MHz. Based on this technique, not only morphological information of the individual cells can be obtained in an ultrafast manner, quantitative evaluation of cellular information (e.g., cell volume, mass, refractive index, stiffness, membrane tension) at nanometer scale based on the optical phase is also possible. The technology can also be integrated with conventional fluorescence measurements widely adopted in the non-imaging flow cytometers. Therefore, these two combinatorial and complementary measurement capabilities in long run is an attractive platform for addressing the pressing need for expanding the "parameter space" in high-throughput single-cell analysis. This chapter provides the general guidelines of constructing the optical system for time stretch imaging, fabrication and design of the microfluidic chip for ultrafast fluidic flow, as well as the image acquisition and processing.

Custom Super-Resolution Microscope for the Structural Analysis of Nanostructures

DTIC Science & Technology

2018-05-29

research community. As part of our validation of the new design approach, we performed two - color imaging of pairs of adjacent oligo probes hybridized...nanostructures and biological targets. Our microscope features a large field of view and custom optics that facilitate 3D imaging and enhanced contrast in...our imaging throughput by creating two microscopy platforms for high-throughput, super-resolution materials characterization, with the AO set-up being

QR-on-a-chip: a computer-recognizable micro-pattern engraved microfluidic device for high-throughput image acquisition.

PubMed

Yun, Kyungwon; Lee, Hyunjae; Bang, Hyunwoo; Jeon, Noo Li

2016-02-21

This study proposes a novel way to achieve high-throughput image acquisition based on a computer-recognizable micro-pattern implemented on a microfluidic device. We integrated the QR code, a two-dimensional barcode system, onto the microfluidic device to simplify imaging of multiple ROIs (regions of interest). A standard QR code pattern was modified to arrays of cylindrical structures of polydimethylsiloxane (PDMS). Utilizing the recognition of the micro-pattern, the proposed system enables: (1) device identification, which allows referencing additional information of the device, such as device imaging sequences or the ROIs and (2) composing a coordinate system for an arbitrarily located microfluidic device with respect to the stage. Based on these functionalities, the proposed method performs one-step high-throughput imaging for data acquisition in microfluidic devices without further manual exploration and locating of the desired ROIs. In our experience, the proposed method significantly reduced the time for the preparation of an acquisition. We expect that the method will innovatively improve the prototype device data acquisition and analysis.

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system.

PubMed

Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

NASA Astrophysics Data System (ADS)

Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

Automatic Segmentation of High-Throughput RNAi Fluorescent Cellular Images

PubMed Central

Yan, Pingkum; Zhou, Xiaobo; Shah, Mubarak; Wong, Stephen T. C.

2010-01-01

High-throughput genome-wide RNA interference (RNAi) screening is emerging as an essential tool to assist biologists in understanding complex cellular processes. The large number of images produced in each study make manual analysis intractable; hence, automatic cellular image analysis becomes an urgent need, where segmentation is the first and one of the most important steps. In this paper, a fully automatic method for segmentation of cells from genome-wide RNAi screening images is proposed. Nuclei are first extracted from the DNA channel by using a modified watershed algorithm. Cells are then extracted by modeling the interaction between them as well as combining both gradient and region information in the Actin and Rac channels. A new energy functional is formulated based on a novel interaction model for segmenting tightly clustered cells with significant intensity variance and specific phenotypes. The energy functional is minimized by using a multiphase level set method, which leads to a highly effective cell segmentation method. Promising experimental results demonstrate that automatic segmentation of high-throughput genome-wide multichannel screening can be achieved by using the proposed method, which may also be extended to other multichannel image segmentation problems. PMID:18270043

Recent advances in high-throughput QCL-based infrared microspectral imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Rowlette, Jeremy A.; Fotheringham, Edeline; Nichols, David; Weida, Miles J.; Kane, Justin; Priest, Allen; Arnone, David B.; Bird, Benjamin; Chapman, William B.; Caffey, David B.; Larson, Paul; Day, Timothy

2017-02-01

The field of infrared spectral imaging and microscopy is advancing rapidly due in large measure to the recent commercialization of the first high-throughput, high-spatial-definition quantum cascade laser (QCL) microscope. Having speed, resolution and noise performance advantages while also eliminating the need for cryogenic cooling, its introduction has established a clear path to translating the well-established diagnostic capability of infrared spectroscopy into clinical and pre-clinical histology, cytology and hematology workflows. Demand for even higher throughput while maintaining high-spectral fidelity and low-noise performance continues to drive innovation in QCL-based spectral imaging instrumentation. In this talk, we will present for the first time, recent technological advances in tunable QCL photonics which have led to an additional 10X enhancement in spectral image data collection speed while preserving the high spectral fidelity and SNR exhibited by the first generation of QCL microscopes. This new approach continues to leverage the benefits of uncooled microbolometer focal plane array cameras, which we find to be essential for ensuring both reproducibility of data across instruments and achieving the high-reliability needed in clinical applications. We will discuss the physics underlying these technological advancements as well as the new biomedical applications these advancements are enabling, including automated whole-slide infrared chemical imaging on clinically relevant timescales.

An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

PubMed

Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

2018-01-01

A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

Comparison of Human Induced Pluripotent Stem Cell-Derived Neurons and Rat Primary CorticalNeurons as In Vitro Models of Neurite Outgrowth

EPA Science Inventory

High-throughput assays that can quantify chemical-induced changes at the cellular and molecular level have been recommended for use in chemical safety assessment. High-throughput, high content imaging assays for the key cellular events of neurodevelopment have been proposed to ra...

Raspberry Pi-powered imaging for plant phenotyping.

PubMed

Tovar, Jose C; Hoyer, J Steen; Lin, Andy; Tielking, Allison; Callen, Steven T; Elizabeth Castillo, S; Miller, Michael; Tessman, Monica; Fahlgren, Noah; Carrington, James C; Nusinow, Dmitri A; Gehan, Malia A

2018-03-01

Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data. We used low-cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi-controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (e.g., shape, area, height, color) en masse using open-source image processing software such as PlantCV. This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs.

A Review of Imaging Techniques for Plant Phenotyping

PubMed Central

Li, Lei; Zhang, Qin; Huang, Danfeng

2014-01-01

Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phenotyping platforms, a variety of imaging methodologies are being used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress (disease, insects, drought and salinity). These imaging techniques include visible imaging (machine vision), imaging spectroscopy (multispectral and hyperspectral remote sensing), thermal infrared imaging, fluorescence imaging, 3D imaging and tomographic imaging (MRT, PET and CT). This paper presents a brief review on these imaging techniques and their applications in plant phenotyping. The features used to apply these imaging techniques to plant phenotyping are described and discussed in this review. PMID:25347588

Real-time Full-spectral Imaging and Affinity Measurements from 50 Microfluidic Channels using Nanohole Surface Plasmon Resonance†

PubMed Central

Lee, Si Hoon; Lindquist, Nathan C.; Wittenberg, Nathan J.; Jordan, Luke R.; Oh, Sang-Hyun

2012-01-01

With recent advances in high-throughput proteomics and systems biology, there is a growing demand for new instruments that can precisely quantify a wide range of receptor-ligand binding kinetics in a high-throughput fashion. Here we demonstrate a surface plasmon resonance (SPR) imaging spectroscopy instrument capable of extracting binding kinetics and affinities from 50 parallel microfluidic channels simultaneously. The instrument utilizes large-area (~cm2) metallic nanohole arrays as SPR sensing substrates and combines a broadband light source, a high-resolution imaging spectrometer and a low-noise CCD camera to extract spectral information from every channel in real time with a refractive index resolution of 7.7 × 10−6. To demonstrate the utility of our instrument for quantifying a wide range of biomolecular interactions, each parallel microfluidic channel is coated with a biomimetic supported lipid membrane containing ganglioside (GM1) receptors. The binding kinetics of cholera toxin b (CTX-b) to GM1 are then measured in a single experiment from 50 channels. By combining the highly parallel microfluidic device with large-area periodic nanohole array chips, our SPR imaging spectrometer system enables high-throughput, label-free, real-time SPR biosensing, and its full-spectral imaging capability combined with nanohole arrays could enable integration of SPR imaging with concurrent surface-enhanced Raman spectroscopy. PMID:22895607

Fluorescence imaging technology (FI) for high-throughput screening of selenide-modified nano-TiO2 catalysts.

PubMed

Wang, Liping; Lee, Jianchao; Zhang, Meijuan; Duan, Qiannan; Zhang, Jiarui; Qi, Hailang

2016-02-18

A high-throughput screening (HTS) method based on fluorescence imaging (FI) was implemented to evaluate the catalytic performance of selenide-modified nano-TiO2. Chemical ink-jet printing (IJP) technology was reformed to fabricate a catalyst library comprising 1405 (Ni(a)Cu(b)Cd(c)Ce(d)In(e)Y(f))Se(x)/TiO2 (M6Se/Ti) composite photocatalysts. Nineteen M6Se/Tis were screened out from the 1405 candidates efficiently.

Three applications of backscatter x-ray imaging technology to homeland defense

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2005-05-01

A brief review of backscatter x-ray imaging and a description of three systems currently applying it to homeland defense missions (BodySearch, ZBV and ZBP). These missions include detection of concealed weapons, explosives and contraband on personnel, in vehicles and large cargo containers. An overview of the x-ray imaging subsystems is provided as well as sample images from each system. Key features such as x-ray safety, throughput and detection are discussed. Recent trends in operational modes are described that facilitate 100% inspection at high throughput chokepoints.

Comprehensive optical and data management infrastructure for high-throughput light-sheet microscopy of whole mouse brains.

PubMed

Müllenbroich, M Caroline; Silvestri, Ludovico; Onofri, Leonardo; Costantini, Irene; Hoff, Marcel Van't; Sacconi, Leonardo; Iannello, Giulio; Pavone, Francesco S

2015-10-01

Comprehensive mapping and quantification of neuronal projections in the central nervous system requires high-throughput imaging of large volumes with microscopic resolution. To this end, we have developed a confocal light-sheet microscope that has been optimized for three-dimensional (3-D) imaging of structurally intact clarified whole-mount mouse brains. We describe the optical and electromechanical arrangement of the microscope and give details on the organization of the microscope management software. The software orchestrates all components of the microscope, coordinates critical timing and synchronization, and has been written in a versatile and modular structure using the LabVIEW language. It can easily be adapted and integrated to other microscope systems and has been made freely available to the light-sheet community. The tremendous amount of data routinely generated by light-sheet microscopy further requires novel strategies for data handling and storage. To complete the full imaging pipeline of our high-throughput microscope, we further elaborate on big data management from streaming of raw images up to stitching of 3-D datasets. The mesoscale neuroanatomy imaged at micron-scale resolution in those datasets allows characterization and quantification of neuronal projections in unsectioned mouse brains.

Automated image-based phenotypic analysis in zebrafish embryos

PubMed Central

Vogt, Andreas; Cholewinski, Andrzej; Shen, Xiaoqiang; Nelson, Scott; Lazo, John S.; Tsang, Michael; Hukriede, Neil A.

2009-01-01

Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high-throughput chemical screens, and optical transparency makes them potentially suited for image-based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to utilizing the zebrafish as a high-throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi-well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high-content reader and analyzed using an artificial intelligence-based image analysis method termed Cognition Network Technology (CNT). CNT reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)y1) arrayed in 96-well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image-based high-content screening methodology to measure complex whole organism phenotypes. PMID:19235725

High throughput secondary electron imaging of organic residues on a graphene surface

NASA Astrophysics Data System (ADS)

Zhou, Yangbo; O'Connell, Robert; Maguire, Pierce; Zhang, Hongzhou

2014-11-01

Surface organic residues inhibit the extraordinary electronic properties of graphene, hindering the development of graphene electronics. However, fundamental understanding of the residue morphology is still absent due to a lack of high-throughput and high-resolution surface characterization methods. Here, we demonstrate that secondary electron (SE) imaging in the scanning electron microscope (SEM) and helium ion microscope (HIM) can provide sub-nanometer information of a graphene surface and reveal the morphology of surface contaminants. Nanoscale polymethyl methacrylate (PMMA) residues are visible in the SE imaging, but their contrast, i.e. the apparent lateral dimension, varies with the imaging conditions. We have demonstrated a quantitative approach to readily obtain the physical size of the surface features regardless of the contrast variation. The fidelity of SE imaging is ultimately determined by the probe size of the primary beam. HIM is thus evaluated to be a superior SE imaging technique in terms of surface sensitivity and image fidelity. A highly efficient method to reveal the residues on a graphene surface has therefore been established.

High resolution light-sheet based high-throughput imaging cytometry system enables visualization of intra-cellular organelles

NASA Astrophysics Data System (ADS)

Regmi, Raju; Mohan, Kavya; Mondal, Partha Pratim

2014-09-01

Visualization of intracellular organelles is achieved using a newly developed high throughput imaging cytometry system. This system interrogates the microfluidic channel using a sheet of light rather than the existing point-based scanning techniques. The advantages of the developed system are many, including, single-shot scanning of specimens flowing through the microfluidic channel at flow rate ranging from micro- to nano- lit./min. Moreover, this opens-up in-vivo imaging of sub-cellular structures and simultaneous cell counting in an imaging cytometry system. We recorded a maximum count of 2400 cells/min at a flow-rate of 700 nl/min, and simultaneous visualization of fluorescently-labeled mitochondrial network in HeLa cells during flow. The developed imaging cytometry system may find immediate application in biotechnology, fluorescence microscopy and nano-medicine.

A Method of High Throughput Monitoring Crop Physiology Using Chlorophyll Fluorescence and Multispectral Imaging.

PubMed

Wang, Heng; Qian, Xiangjie; Zhang, Lan; Xu, Sailong; Li, Haifeng; Xia, Xiaojian; Dai, Liankui; Xu, Liang; Yu, Jingquan; Liu, Xu

2018-01-01

We present a high throughput crop physiology condition monitoring system and corresponding monitoring method. The monitoring system can perform large-area chlorophyll fluorescence imaging and multispectral imaging. The monitoring method can determine the crop current condition continuously and non-destructively. We choose chlorophyll fluorescence parameters and relative reflectance of multispectral as the indicators of crop physiological status. Using tomato as experiment subject, the typical crop physiological stress, such as drought, nutrition deficiency and plant disease can be distinguished by the monitoring method. Furthermore, we have studied the correlation between the physiological indicators and the degree of stress. Besides realizing the continuous monitoring of crop physiology, the monitoring system and method provide the possibility of machine automatic diagnosis of the plant physiology. Highlights: A newly designed high throughput crop physiology monitoring system and the corresponding monitoring method are described in this study. Different types of stress can induce distinct fluorescence and spectral characteristics, which can be used to evaluate the physiological status of plants.

Strategies for high-throughput focused-beam ptychography

DOE PAGES

Jacobsen, Chris; Deng, Junjing; Nashed, Youssef

2017-08-08

X-ray ptychography is being utilized for a wide range of imaging experiments with a resolution beyond the limit of the X-ray optics used. Introducing a parameter for the ptychographic resolution gainG p(the ratio of the beam size over the achieved pixel size in the reconstructed image), strategies for data sampling and for increasing imaging throughput when the specimen is at the focus of an X-ray beam are considered. As a result, the tradeoffs between large and small illumination spots are examined.

Strategies for high-throughput focused-beam ptychography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacobsen, Chris; Deng, Junjing; Nashed, Youssef

X-ray ptychography is being utilized for a wide range of imaging experiments with a resolution beyond the limit of the X-ray optics used. Introducing a parameter for the ptychographic resolution gainG p(the ratio of the beam size over the achieved pixel size in the reconstructed image), strategies for data sampling and for increasing imaging throughput when the specimen is at the focus of an X-ray beam are considered. As a result, the tradeoffs between large and small illumination spots are examined.

Quantitative Live-Cell Confocal Imaging of 3D Spheroids in a High-Throughput Format.

PubMed

Leary, Elizabeth; Rhee, Claire; Wilks, Benjamin T; Morgan, Jeffrey R

2018-06-01

Accurately predicting the human response to new compounds is critical to a wide variety of industries. Standard screening pipelines (including both in vitro and in vivo models) often lack predictive power. Three-dimensional (3D) culture systems of human cells, a more physiologically relevant platform, could provide a high-throughput, automated means to test the efficacy and/or toxicity of novel substances. However, the challenge of obtaining high-magnification, confocal z stacks of 3D spheroids and understanding their respective quantitative limitations must be overcome first. To address this challenge, we developed a method to form spheroids of reproducible size at precise spatial locations across a 96-well plate. Spheroids of variable radii were labeled with four different fluorescent dyes and imaged with a high-throughput confocal microscope. 3D renderings of the spheroid had a complex bowl-like appearance. We systematically analyzed these confocal z stacks to determine the depth of imaging and the effect of spheroid size and dyes on quantitation. Furthermore, we have shown that this loss of fluorescence can be addressed through the use of ratio imaging. Overall, understanding both the limitations of confocal imaging and the tools to correct for these limits is critical for developing accurate quantitative assays using 3D spheroids.

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods

PubMed Central

Wells, Darren M.; French, Andrew P.; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein; Bennett, Malcolm J.; Pridmore, Tony P.

2012-01-01

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana. PMID:22527394

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods.

PubMed

Wells, Darren M; French, Andrew P; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein I; Hijazi, Hussein; Bennett, Malcolm J; Pridmore, Tony P

2012-06-05

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana.

Pipeline for illumination correction of images for high-throughput microscopy.

PubMed

Singh, S; Bray, M-A; Jones, T R; Carpenter, A E

2014-12-01

The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z'-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. © 2014 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

A compact imaging spectroscopic system for biomolecular detections on plasmonic chips.

PubMed

Lo, Shu-Cheng; Lin, En-Hung; Wei, Pei-Kuen; Tsai, Wan-Shao

2016-10-17

In this study, we demonstrate a compact imaging spectroscopic system for high-throughput detection of biomolecular interactions on plasmonic chips, based on a curved grating as the key element of light diffraction and light focusing. Both the curved grating and the plasmonic chips are fabricated on flexible plastic substrates using a gas-assisted thermal-embossing method. A fiber-coupled broadband light source and a camera are included in the system. Spectral resolution within 1 nm is achieved in sensing environmental index solutions and protein bindings. The detected sensitivities of the plasmonic chip are comparable with a commercial spectrometer. An extra one-dimensional scanning stage enables high-throughput detection of protein binding on a designed plasmonic chip consisting of several nanoslit arrays with different periods. The detected resonance wavelengths match well with the grating equation under an air environment. Wavelength shifts between 1 and 9 nm are detected for antigens of various concentrations binding with antibodies. A simple, mass-productive and cost-effective method has been demonstrated on the imaging spectroscopic system for real-time, label-free, highly sensitive and high-throughput screening of biomolecular interactions.

High throughput imaging and analysis for biological interpretation of agricultural plants and environmental interaction

NASA Astrophysics Data System (ADS)

Hong, Hyundae; Benac, Jasenka; Riggsbee, Daniel; Koutsky, Keith

2014-03-01

High throughput (HT) phenotyping of crops is essential to increase yield in environments deteriorated by climate change. The controlled environment of a greenhouse offers an ideal platform to study the genotype to phenotype linkages for crop screening. Advanced imaging technologies are used to study plants' responses to resource limitations such as water and nutrient deficiency. Advanced imaging technologies coupled with automation make HT phenotyping in the greenhouse not only feasible, but practical. Monsanto has a state of the art automated greenhouse (AGH) facility. Handling of the soil, pots water and nutrients are all completely automated. Images of the plants are acquired by multiple hyperspectral and broadband cameras. The hyperspectral cameras cover wavelengths from visible light through short wave infra-red (SWIR). Inhouse developed software analyzes the images to measure plant morphological and biochemical properties. We measure phenotypic metrics like plant area, height, and width as well as biomass. Hyperspectral imaging allows us to measure biochemcical metrics such as chlorophyll, anthocyanin, and foliar water content. The last 4 years of AGH operations on crops like corn, soybean, and cotton have demonstrated successful application of imaging and analysis technologies for high throughput plant phenotyping. Using HT phenotyping, scientists have been showing strong correlations to environmental conditions, such as water and nutrient deficits, as well as the ability to tease apart distinct differences in the genetic backgrounds of crops.

Optimized Negative Staining: a High-throughput Protocol for Examining Small and Asymmetric Protein Structure by Electron Microscopy

DOE PAGES

Rames, Matthew; Yu, Yadong; Ren, Gang

2014-08-15

Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of natural proteins have a molecular mass between 40 - 200 kDa, a robust and high-throughput method with a nanometer resolution capability is needed. Negative staining (NS) electron microscopy (EM) is an easy, rapid, and qualitative approach which has frequently been used in research laboratories to examine protein structure and protein-protein interactions. Unfortunately, conventional NS protocols often generate structural artifacts on proteins, especially with lipoproteins that usually form presenting rouleaux artifacts. By using images of lipoproteins from cryo-electronmore » microscopy (cryo-EM) as a standard, the key parameters in NS specimen preparation conditions were recently screened and reported as the optimized NS protocol (OpNS), a modified conventional NS protocol. Artifacts like rouleaux can be greatly limited by OpNS, additionally providing high contrast along with reasonably high-resolution (near 1 nm) images of small and asymmetric proteins. These high-resolution and high contrast images are even favorable for an individual protein (a single object, no average) 3D reconstruction, such as a 160 kDa antibody, through the method of electron tomography. Moreover, OpNS can be a high-throughput tool to examine hundreds of samples of small proteins. For example, the previously published mechanism of 53 kDa cholesteryl ester transfer protein (CETP) involved the screening and imaging of hundreds of samples. Considering cryo-EM rarely successfully images proteins less than 200 kDa has yet to publish any study involving screening over one hundred sample conditions, it is fair to call OpNS a high-throughput method for studying small proteins. Hopefully the OpNS protocol presented here can be a useful tool to push the boundaries of EM and accelerate EM studies into small protein structure, dynamics and mechanisms.« less

Diamond Turned High Precision PIAA Optics and Four Mirror PIAA System for High Contrast Imaging of Exo-planets

NASA Technical Reports Server (NTRS)

Balasubramanian, Kunjithapatham; Cady, Eric; Pueyo, Laurent; Ana, Xin; Shaklan, Stuart; Guyon, Olivier; Belikov, Ruslan

2011-01-01

Off-axis, high-sag PIAA optics for high contrast imaging present challenges in manufacturing and testing. With smaller form factors and consequently smaller surface deformations (< 80 microns), diamond turned fabrication of these mirrors becomes feasible. Though such a design reduces the system throughput, it still provides 2(lambda)D inner working angle. We report on the design, fabrication, measurements, and initial assessment of the novel PIAA optics in a coronagraph testbed. We also describe, for the first time, a four mirror PIAA coronagraph that relaxes apodizer requirements and significantly improves throughput while preserving the low-cost benefits.

High-throughput quantum cascade laser (QCL) spectral histopathology: a practical approach towards clinical translation.

PubMed

Pilling, Michael J; Henderson, Alex; Bird, Benjamin; Brown, Mick D; Clarke, Noel W; Gardner, Peter

2016-06-23

Infrared microscopy has become one of the key techniques in the biomedical research field for interrogating tissue. In partnership with multivariate analysis and machine learning techniques, it has become widely accepted as a method that can distinguish between normal and cancerous tissue with both high sensitivity and high specificity. While spectral histopathology (SHP) is highly promising for improved clinical diagnosis, several practical barriers currently exist, which need to be addressed before successful implementation in the clinic. Sample throughput and speed of acquisition are key barriers and have been driven by the high volume of samples awaiting histopathological examination. FTIR chemical imaging utilising FPA technology is currently state-of-the-art for infrared chemical imaging, and recent advances in its technology have dramatically reduced acquisition times. Despite this, infrared microscopy measurements on a tissue microarray (TMA), often encompassing several million spectra, takes several hours to acquire. The problem lies with the vast quantities of data that FTIR collects; each pixel in a chemical image is derived from a full infrared spectrum, itself composed of thousands of individual data points. Furthermore, data management is quickly becoming a barrier to clinical translation and poses the question of how to store these incessantly growing data sets. Recently, doubts have been raised as to whether the full spectral range is actually required for accurate disease diagnosis using SHP. These studies suggest that once spectral biomarkers have been predetermined it may be possible to diagnose disease based on a limited number of discrete spectral features. In this current study, we explore the possibility of utilising discrete frequency chemical imaging for acquiring high-throughput, high-resolution chemical images. Utilising a quantum cascade laser imaging microscope with discrete frequency collection at key diagnostic wavelengths, we demonstrate that we can diagnose prostate cancer with high sensitivity and specificity. Finally we extend the study to a large patient dataset utilising tissue microarrays, and show that high sensitivity and specificity can be achieved using high-throughput, rapid data collection, thereby paving the way for practical implementation in the clinic.

An Automated Method for High-Throughput Screening of Arabidopsis Rosette Growth in Multi-Well Plates and Its Validation in Stress Conditions.

PubMed

De Diego, Nuria; Fürst, Tomáš; Humplík, Jan F; Ugena, Lydia; Podlešáková, Kateřina; Spíchal, Lukáš

2017-01-01

High-throughput plant phenotyping platforms provide new possibilities for automated, fast scoring of several plant growth and development traits, followed over time using non-invasive sensors. Using Arabidops is as a model offers important advantages for high-throughput screening with the opportunity to extrapolate the results obtained to other crops of commercial interest. In this study we describe the development of a highly reproducible high-throughput Arabidopsis in vitro bioassay established using our OloPhen platform, suitable for analysis of rosette growth in multi-well plates. This method was successfully validated on example of multivariate analysis of Arabidopsis rosette growth in different salt concentrations and the interaction with varying nutritional composition of the growth medium. Several traits such as changes in the rosette area, relative growth rate, survival rate and homogeneity of the population are scored using fully automated RGB imaging and subsequent image analysis. The assay can be used for fast screening of the biological activity of chemical libraries, phenotypes of transgenic or recombinant inbred lines, or to search for potential quantitative trait loci. It is especially valuable for selecting genotypes or growth conditions that improve plant stress tolerance.

High-throughput ultraviolet photoacoustic microscopy with multifocal excitation

NASA Astrophysics Data System (ADS)

Imai, Toru; Shi, Junhui; Wong, Terence T. W.; Li, Lei; Zhu, Liren; Wang, Lihong V.

2018-03-01

Ultraviolet photoacoustic microscopy (UV-PAM) is a promising intraoperative tool for surgical margin assessment (SMA), one that can provide label-free histology-like images with high resolution. In this study, using a microlens array and a one-dimensional (1-D) array ultrasonic transducer, we developed a high-throughput multifocal UV-PAM (MF-UV-PAM). Our new system achieved a 1.6 ± 0.2 μm lateral resolution and produced images 40 times faster than the previously developed point-by-point scanning UV-PAM. MF-UV-PAM provided a readily comprehensible photoacoustic image of a mouse brain slice with specific absorption contrast in ˜16 min, highlighting cell nuclei. Individual cell nuclei could be clearly resolved, showing its practical potential for intraoperative SMA.

High throughput dual-wavelength temperature distribution imaging via compressive imaging

NASA Astrophysics Data System (ADS)

Yao, Xu-Ri; Lan, Ruo-Ming; Liu, Xue-Feng; Zhu, Ge; Zheng, Fu; Yu, Wen-Kai; Zhai, Guang-Jie

2018-03-01

Thermal imaging is an essential tool in a wide variety of research areas. In this work we demonstrate high-throughput double-wavelength temperature distribution imaging using a modified single-pixel camera without the requirement of a beam splitter (BS). A digital micro-mirror device (DMD) is utilized to display binary masks and split the incident radiation, which eliminates the necessity of a BS. Because the spatial resolution is dictated by the DMD, this thermal imaging system has the advantage of perfect spatial registration between the two images, which limits the need for the pixel registration and fine adjustments. Two bucket detectors, which measures the total light intensity reflected from the DMD, are employed in this system and yield an improvement in the detection efficiency of the narrow-band radiation. A compressive imaging algorithm is utilized to achieve under-sampling recovery. A proof-of-principle experiment was presented to demonstrate the feasibility of this structure.

A simple and sensitive high-throughput GFP screening in woody and herbaceous plants.

PubMed

Hily, Jean-Michel; Liu, Zongrang

2009-03-01

Green fluorescent protein (GFP) has been used widely as a powerful bioluminescent reporter, but its visualization by existing methods in tissues or whole plants and its utilization for high-throughput screening remains challenging in many species. Here, we report a fluorescence image analyzer-based method for GFP detection and its utility for high-throughput screening of transformed plants. Of three detection methods tested, the Typhoon fluorescence scanner was able to detect GFP fluorescence in all Arabidopsis thaliana tissues and apple leaves, while regular fluorescence microscopy detected it only in Arabidopsis flowers and siliques but barely in the leaves of either Arabidopsis or apple. The hand-held UV illumination method failed in all tissues of both species. Additionally, the Typhoon imager was able to detect GFP fluorescence in both green and non-green tissues of Arabidopsis seedlings as well as in imbibed seeds, qualifying it as a high-throughput screening tool, which was further demonstrated by screening the seedlings of primary transformed T(0) seeds. Of the 30,000 germinating Arabidopsis seedlings screened, at least 69 GFP-positive lines were identified, accounting for an approximately 0.23% transformation efficiency. About 14,000 seedlings grown in 16 Petri plates could be screened within an hour, making the screening process significantly more efficient and robust than any other existing high-throughput screening method for transgenic plants.

HiCTMap: Detection and analysis of chromosome territory structure and position by high-throughput imaging.

PubMed

Jowhar, Ziad; Gudla, Prabhakar R; Shachar, Sigal; Wangsa, Darawalee; Russ, Jill L; Pegoraro, Gianluca; Ried, Thomas; Raznahan, Armin; Misteli, Tom

2018-06-01

The spatial organization of chromosomes in the nuclear space is an extensively studied field that relies on measurements of structural features and 3D positions of chromosomes with high precision and robustness. However, no tools are currently available to image and analyze chromosome territories in a high-throughput format. Here, we have developed High-throughput Chromosome Territory Mapping (HiCTMap), a method for the robust and rapid analysis of 2D and 3D chromosome territory positioning in mammalian cells. HiCTMap is a high-throughput imaging-based chromosome detection method which enables routine analysis of chromosome structure and nuclear position. Using an optimized FISH staining protocol in a 384-well plate format in conjunction with a bespoke automated image analysis workflow, HiCTMap faithfully detects chromosome territories and their position in 2D and 3D in a large population of cells per experimental condition. We apply this novel technique to visualize chromosomes 18, X, and Y in male and female primary human skin fibroblasts, and show accurate detection of the correct number of chromosomes in the respective genotypes. Given the ability to visualize and quantitatively analyze large numbers of nuclei, we use HiCTMap to measure chromosome territory area and volume with high precision and determine the radial position of chromosome territories using either centroid or equidistant-shell analysis. The HiCTMap protocol is also compatible with RNA FISH as demonstrated by simultaneous labeling of X chromosomes and Xist RNA in female cells. We suggest HiCTMap will be a useful tool for routine precision mapping of chromosome territories in a wide range of cell types and tissues. Published by Elsevier Inc.

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

PubMed

Gopakumar, G; Hari Babu, K; Mishra, Deepak; Gorthi, Sai Siva; Sai Subrahmanyam, Gorthi R K

2017-01-01

Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing process. Several neural network architectures were designed to provide human expertise to machines. In this paper, we explore and propose the feasibility of using deep-learning networks for cytopathologic analysis by performing the classification of three important unlabeled, unstained leukemia cell lines (K562, MOLT, and HL60). The cell images used in the classification are captured using a low-cost, high-throughput cell imaging technique: microfluidics-based imaging flow cytometry. We demonstrate that without any conventional fine segmentation followed by explicit feature extraction, the proposed deep-learning algorithms effectively classify the coarsely localized cell lines. We show that the designed deep belief network as well as the deeply pretrained convolutional neural network outperform the conventionally used decision systems and are important in the medical domain, where the availability of labeled data is limited for training. We hope that our work enables the development of a clinically significant high-throughput microfluidic microscopy-based tool for disease screening/triaging, especially in resource-limited settings.

Breast cancer diagnosis using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2015-11-01

The standard practice in histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope to diagnose whether a lesion is benign or malignant. This determination is made based on a manual, qualitative inspection, making it subject to investigator bias and resulting in low throughput. Hence, a quantitative, label-free, and high-throughput diagnosis method is highly desirable. We present here preliminary results showing the potential of quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated phase maps of unstained breast tissue biopsies using spatial light interference microscopy (SLIM). As a first step toward quantitative diagnosis based on SLIM, we carried out a qualitative evaluation of our label-free images. These images were shown to two pathologists who classified each case as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on corresponding H&E stained tissue images and the number of agreements were counted. The agreement between SLIM and H&E based diagnosis was 88% for the first pathologist and 87% for the second. Our results demonstrate the potential and promise of SLIM for quantitative, label-free, and high-throughput diagnosis.

Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity

PubMed Central

Zhong, Qing; Rüschoff, Jan H.; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J.; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J.; Rupp, Niels J.; Fankhauser, Christian; Buhmann, Joachim M.; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A.; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C.; Jochum, Wolfram; Wild, Peter J.

2016-01-01

Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility. PMID:27052161

Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.

PubMed

Zhong, Qing; Rüschoff, Jan H; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J; Rupp, Niels J; Fankhauser, Christian; Buhmann, Joachim M; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C; Jochum, Wolfram; Wild, Peter J

2016-04-07

Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility.

SmartGrain: high-throughput phenotyping software for measuring seed shape through image analysis.

PubMed

Tanabata, Takanari; Shibaya, Taeko; Hori, Kiyosumi; Ebana, Kaworu; Yano, Masahiro

2012-12-01

Seed shape and size are among the most important agronomic traits because they affect yield and market price. To obtain accurate seed size data, a large number of measurements are needed because there is little difference in size among seeds from one plant. To promote genetic analysis and selection for seed shape in plant breeding, efficient, reliable, high-throughput seed phenotyping methods are required. We developed SmartGrain software for high-throughput measurement of seed shape. This software uses a new image analysis method to reduce the time taken in the preparation of seeds and in image capture. Outlines of seeds are automatically recognized from digital images, and several shape parameters, such as seed length, width, area, and perimeter length, are calculated. To validate the software, we performed a quantitative trait locus (QTL) analysis for rice (Oryza sativa) seed shape using backcrossed inbred lines derived from a cross between japonica cultivars Koshihikari and Nipponbare, which showed small differences in seed shape. SmartGrain removed areas of awns and pedicels automatically, and several QTLs were detected for six shape parameters. The allelic effect of a QTL for seed length detected on chromosome 11 was confirmed in advanced backcross progeny; the cv Nipponbare allele increased seed length and, thus, seed weight. High-throughput measurement with SmartGrain reduced sampling error and made it possible to distinguish between lines with small differences in seed shape. SmartGrain could accurately recognize seed not only of rice but also of several other species, including Arabidopsis (Arabidopsis thaliana). The software is free to researchers.

Optimizing ultrafast illumination for multiphoton-excited fluorescence imaging

PubMed Central

Stoltzfus, Caleb R.; Rebane, Aleksander

2016-01-01

We study the optimal conditions for high throughput two-photon excited fluorescence (2PEF) and three-photon excited fluorescence (3PEF) imaging using femtosecond lasers. We derive relations that allow maximization of the rate of imaging depending on the average power, pulse repetition rate, and noise characteristics of the laser, as well as on the size and structure of the sample. We perform our analysis using ~100 MHz, ~1 MHz and 1 kHz pulse rates and using both a tightly-focused illumination beam with diffraction-limited image resolution, as well loosely focused illumination with a relatively low image resolution, where the latter utilizes separate illumination and fluorescence detection beam paths. Our theoretical estimates agree with the experiments, which makes our approach especially useful for optimizing high throughput imaging of large samples with a field-of-view up to 10x10 cm2. PMID:27231620

Quantitative high-throughput population dynamics in continuous-culture by automated microscopy.

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

We present a high-throughput method to measure abundance dynamics in microbial communities sustained in continuous-culture. Our method uses custom epi-fluorescence microscopes to automatically image single cells drawn from a continuously-cultured population while precisely controlling culture conditions. For clonal populations of Escherichia coli our instrument reveals history-dependent resilience and growth rate dependent aggregation.

RhizoTubes as a new tool for high throughput imaging of plant root development and architecture: test, comparison with pot grown plants and validation.

PubMed

Jeudy, Christian; Adrian, Marielle; Baussard, Christophe; Bernard, Céline; Bernaud, Eric; Bourion, Virginie; Busset, Hughes; Cabrera-Bosquet, Llorenç; Cointault, Frédéric; Han, Simeng; Lamboeuf, Mickael; Moreau, Delphine; Pivato, Barbara; Prudent, Marion; Trouvelot, Sophie; Truong, Hoai Nam; Vernoud, Vanessa; Voisin, Anne-Sophie; Wipf, Daniel; Salon, Christophe

2016-01-01

In order to maintain high yields while saving water and preserving non-renewable resources and thus limiting the use of chemical fertilizer, it is crucial to select plants with more efficient root systems. This could be achieved through an optimization of both root architecture and root uptake ability and/or through the improvement of positive plant interactions with microorganisms in the rhizosphere. The development of devices suitable for high-throughput phenotyping of root structures remains a major bottleneck. Rhizotrons suitable for plant growth in controlled conditions and non-invasive image acquisition of plant shoot and root systems (RhizoTubes) are described. These RhizoTubes allow growing one to six plants simultaneously, having a maximum height of 1.1 m, up to 8 weeks, depending on plant species. Both shoot and root compartment can be imaged automatically and non-destructively throughout the experiment thanks to an imaging cabin (RhizoCab). RhizoCab contains robots and imaging equipment for obtaining high-resolution pictures of plant roots. Using this versatile experimental setup, we illustrate how some morphometric root traits can be determined for various species including model (Medicago truncatula), crops (Pisum sativum, Brassica napus, Vitis vinifera, Triticum aestivum) and weed (Vulpia myuros) species grown under non-limiting conditions or submitted to various abiotic and biotic constraints. The measurement of the root phenotypic traits using this system was compared to that obtained using "classic" growth conditions in pots. This integrated system, to include 1200 Rhizotubes, will allow high-throughput phenotyping of plant shoots and roots under various abiotic and biotic environmental conditions. Our system allows an easy visualization or extraction of roots and measurement of root traits for high-throughput or kinetic analyses. The utility of this system for studying root system architecture will greatly facilitate the identification of genetic and environmental determinants of key root traits involved in crop responses to stresses, including interactions with soil microorganisms.

Use of a Fluorometric Imaging Plate Reader in high-throughput screening

NASA Astrophysics Data System (ADS)

Groebe, Duncan R.; Gopalakrishnan, Sujatha; Hahn, Holly; Warrior, Usha; Traphagen, Linda; Burns, David J.

1999-04-01

High-throughput screening (HTS) efforts at Abbott Laboratories have been greatly facilitated by the use of a Fluorometric Imaging Plate Reader. The FLIPR consists of an incubated cabinet with integrated 96-channel pipettor and fluorometer. An argon laser is used to excite fluorophores in a 96-well microtiter plate and the emitted fluorometer. An argon laser is used to excite fluorophores in a 96-well microtiter plate and the emitted fluorescence is imaged by a cooled CCD camera. The image data is downloaded from the camera and processed to average the signal form each well of the microtiter pate for each time point. The data is presented in real time on the computer screen, facilitating interpretation and trouble-shooting. In addition to fluorescence, the camera can also detect luminescence form firefly luciferase.

A high-throughput in vitro ring assay for vasoactivity using magnetic 3D bioprinting

PubMed Central

Tseng, Hubert; Gage, Jacob A.; Haisler, William L.; Neeley, Shane K.; Shen, Tsaiwei; Hebel, Chris; Barthlow, Herbert G.; Wagoner, Matthew; Souza, Glauco R.

2016-01-01

Vasoactive liabilities are typically assayed using wire myography, which is limited by its high cost and low throughput. To meet the demand for higher throughput in vitro alternatives, this study introduces a magnetic 3D bioprinting-based vasoactivity assay. The principle behind this assay is the magnetic printing of vascular smooth muscle cells into 3D rings that functionally represent blood vessel segments, whose contraction can be altered by vasodilators and vasoconstrictors. A cost-effective imaging modality employing a mobile device is used to capture contraction with high throughput. The goal of this study was to validate ring contraction as a measure of vasoactivity, using a small panel of known vasoactive drugs. In vitro responses of the rings matched outcomes predicted by in vivo pharmacology, and were supported by immunohistochemistry. Altogether, this ring assay robustly models vasoactivity, which could meet the need for higher throughput in vitro alternatives. PMID:27477945

3D imaging of optically cleared tissue using a simplified CLARITY method and on-chip microscopy

PubMed Central

Zhang, Yibo; Shin, Yoonjung; Sung, Kevin; Yang, Sam; Chen, Harrison; Wang, Hongda; Teng, Da; Rivenson, Yair; Kulkarni, Rajan P.; Ozcan, Aydogan

2017-01-01

High-throughput sectioning and optical imaging of tissue samples using traditional immunohistochemical techniques can be costly and inaccessible in resource-limited areas. We demonstrate three-dimensional (3D) imaging and phenotyping in optically transparent tissue using lens-free holographic on-chip microscopy as a low-cost, simple, and high-throughput alternative to conventional approaches. The tissue sample is passively cleared using a simplified CLARITY method and stained using 3,3′-diaminobenzidine to target cells of interest, enabling bright-field optical imaging and 3D sectioning of thick samples. The lens-free computational microscope uses pixel super-resolution and multi-height phase recovery algorithms to digitally refocus throughout the cleared tissue and obtain a 3D stack of complex-valued images of the sample, containing both phase and amplitude information. We optimized the tissue-clearing and imaging system by finding the optimal illumination wavelength, tissue thickness, sample preparation parameters, and the number of heights of the lens-free image acquisition and implemented a sparsity-based denoising algorithm to maximize the imaging volume and minimize the amount of the acquired data while also preserving the contrast-to-noise ratio of the reconstructed images. As a proof of concept, we achieved 3D imaging of neurons in a 200-μm-thick cleared mouse brain tissue over a wide field of view of 20.5 mm2. The lens-free microscope also achieved more than an order-of-magnitude reduction in raw data compared to a conventional scanning optical microscope imaging the same sample volume. Being low cost, simple, high-throughput, and data-efficient, we believe that this CLARITY-enabled computational tissue imaging technique could find numerous applications in biomedical diagnosis and research in low-resource settings. PMID:28819645

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

High-Throughput Phenotyping of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes and Neurons Using Electric Field Stimulation and High-Speed Fluorescence Imaging

PubMed Central

Daily, Neil J.; Du, Zhong-Wei

2017-01-01

Abstract Electrophysiology of excitable cells, including muscle cells and neurons, has been measured by making direct contact with a single cell using a micropipette electrode. To increase the assay throughput, optical devices such as microscopes and microplate readers have been used to analyze electrophysiology of multiple cells. We have established a high-throughput (HTP) analysis of action potentials (APs) in highly enriched motor neurons and cardiomyocytes (CMs) that are differentiated from human induced pluripotent stem cells (iPSCs). A multichannel electric field stimulation (EFS) device enabled the ability to electrically stimulate cells and measure dynamic changes in APs of excitable cells ultra-rapidly (>100 data points per second) by imaging entire 96-well plates. We found that the activities of both neurons and CMs and their response to EFS and chemicals are readily discerned by our fluorescence imaging-based HTP phenotyping assay. The latest generation of calcium (Ca2+) indicator dyes, FLIPR Calcium 6 and Cal-520, with the HTP device enables physiological analysis of human iPSC-derived samples highlighting its potential application for understanding disease mechanisms and discovering new therapeutic treatments. PMID:28525289

A High-Content Live-Cell Viability Assay and Its Validation on a Diverse 12K Compound Screen.

PubMed

Chiaravalli, Jeanne; Glickman, J Fraser

2017-08-01

We have developed a new high-content cytotoxicity assay using live cells, called "ImageTOX." We used a high-throughput fluorescence microscope system, image segmentation software, and the combination of Hoechst 33342 and SYTO 17 to simultaneously score the relative size and the intensity of the nuclei, the nuclear membrane permeability, and the cell number in a 384-well microplate format. We then performed a screen of 12,668 diverse compounds and compared the results to a standard cytotoxicity assay. The ImageTOX assay identified similar sets of compounds to the standard cytotoxicity assay, while identifying more compounds having adverse effects on cell structure, earlier in treatment time. The ImageTOX assay uses inexpensive commercially available reagents and facilitates the use of live cells in toxicity screens. Furthermore, we show that we can measure the kinetic profile of compound toxicity in a high-content, high-throughput format, following the same set of cells over an extended period of time.

A review of snapshot multidimensional optical imaging: measuring photon tags in parallel

PubMed Central

Gao, Liang; Wang, Lihong V.

2015-01-01

Multidimensional optical imaging has seen remarkable growth in the past decade. Rather than measuring only the two-dimensional spatial distribution of light, as in conventional photography, multidimensional optical imaging captures light in up to nine dimensions, providing unprecedented information about incident photons’ spatial coordinates, emittance angles, wavelength, time, and polarization. Multidimensional optical imaging can be accomplished either by scanning or parallel acquisition. Compared with scanning-based imagers, parallel acquisition—also dubbed snapshot imaging—has a prominent advantage in maximizing optical throughput, particularly when measuring a datacube of high dimensions. Here, we first categorize snapshot multidimensional imagers based on their acquisition and image reconstruction strategies, then highlight the snapshot advantage in the context of optical throughput, and finally we discuss their state-of-the-art implementations and applications. PMID:27134340

Diagnosis of breast cancer biopsies using quantitative phase imaging

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2015-03-01

The standard practice in the histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope. The pathologist looks at certain morphological features, visible under the stain, to diagnose whether a tumor is benign or malignant. This determination is made based on qualitative inspection making it subject to investigator bias. Furthermore, since this method requires a microscopic examination by the pathologist it suffers from low throughput. A quantitative, label-free and high throughput method for detection of these morphological features from images of tissue biopsies is, hence, highly desirable as it would assist the pathologist in making a quicker and more accurate diagnosis of cancers. We present here preliminary results showing the potential of using quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated optical path length maps of unstained breast tissue biopsies using Spatial Light Interference Microscopy (SLIM). As a first step towards diagnosis based on quantitative phase imaging, we carried out a qualitative evaluation of the imaging resolution and contrast of our label-free phase images. These images were shown to two pathologists who marked the tumors present in tissue as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on H&E stained tissue images and the number of agreements were counted. In our experiment, the agreement between SLIM and H&E based diagnosis was measured to be 88%. Our preliminary results demonstrate the potential and promise of SLIM for a push in the future towards quantitative, label-free and high throughput diagnosis.

All-passive pixel super-resolution of time-stretch imaging

PubMed Central

Chan, Antony C. S.; Ng, Ho-Cheung; Bogaraju, Sharat C. V.; So, Hayden K. H.; Lam, Edmund Y.; Tsia, Kevin K.

2017-01-01

Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate — hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (≈2–5 GSa/s)—more than four times lower than the originally required readout rate (20 GSa/s) — is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time-stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing. PMID:28303936

Cellular resolution functional imaging in behaving rats using voluntary head restraint

PubMed Central

Scott, Benjamin B.; Brody, Carlos D.; Tank, David W.

2013-01-01

SUMMARY High-throughput operant conditioning systems for rodents provide efficient training on sophisticated behavioral tasks. Combining these systems with technologies for cellular resolution functional imaging would provide a powerful approach to study neural dynamics during behavior. Here we describe an integrated two-photon microscope and behavioral apparatus that allows cellular resolution functional imaging of cortical regions during epochs of voluntary head restraint. Rats were trained to initiate periods of restraint up to 8 seconds in duration, which provided the mechanical stability necessary for in vivo imaging while allowing free movement between behavioral trials. A mechanical registration system repositioned the head to within a few microns, allowing the same neuronal populations to be imaged on each trial. In proof-of-principle experiments, calcium dependent fluorescence transients were recorded from GCaMP-labeled cortical neurons. In contrast to previous methods for head restraint, this system can also be incorporated into high-throughput operant conditioning systems. PMID:24055015

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

PubMed

Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua

2015-09-01

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.

Real-time traffic sign detection and recognition

NASA Astrophysics Data System (ADS)

Herbschleb, Ernst; de With, Peter H. N.

2009-01-01

The continuous growth of imaging databases increasingly requires analysis tools for extraction of features. In this paper, a new architecture for the detection of traffic signs is proposed. The architecture is designed to process a large database with tens of millions of images with a resolution up to 4,800x2,400 pixels. Because of the size of the database, a high reliability as well as a high throughput is required. The novel architecture consists of a three-stage algorithm with multiple steps per stage, combining both color and specific spatial information. The first stage contains an area-limitation step which is performance critical in both the detection rate as the overall processing time. The second stage locates suggestions for traffic signs using recently published feature processing. The third stage contains a validation step to enhance reliability of the algorithm. During this stage, the traffic signs are recognized. Experiments show a convincing detection rate of 99%. With respect to computational speed, the throughput for line-of-sight images of 800×600 pixels is 35 Hz and for panorama images it is 4 Hz. Our novel architecture outperforms existing algorithms, with respect to both detection rate and throughput

Achieving High Throughput for Data Transfer over ATM Networks

NASA Technical Reports Server (NTRS)

Johnson, Marjory J.; Townsend, Jeffrey N.

1996-01-01

File-transfer rates for ftp are often reported to be relatively slow, compared to the raw bandwidth available in emerging gigabit networks. While a major bottleneck is disk I/O, protocol issues impact performance as well. Ftp was developed and optimized for use over the TCP/IP protocol stack of the Internet. However, TCP has been shown to run inefficiently over ATM. In an effort to maximize network throughput, data-transfer protocols can be developed to run over UDP or directly over IP, rather than over TCP. If error-free transmission is required, techniques for achieving reliable transmission can be included as part of the transfer protocol. However, selected image-processing applications can tolerate a low level of errors in images that are transmitted over a network. In this paper we report on experimental work to develop a high-throughput protocol for unreliable data transfer over ATM networks. We attempt to maximize throughput by keeping the communications pipe full, but still keep packet loss under five percent. We use the Bay Area Gigabit Network Testbed as our experimental platform.

Three-dimensional Imaging and Scanning: Current and Future Applications for Pathology

PubMed Central

Farahani, Navid; Braun, Alex; Jutt, Dylan; Huffman, Todd; Reder, Nick; Liu, Zheng; Yagi, Yukako; Pantanowitz, Liron

2017-01-01

Imaging is vital for the assessment of physiologic and phenotypic details. In the past, biomedical imaging was heavily reliant on analog, low-throughput methods, which would produce two-dimensional images. However, newer, digital, and high-throughput three-dimensional (3D) imaging methods, which rely on computer vision and computer graphics, are transforming the way biomedical professionals practice. 3D imaging has been useful in diagnostic, prognostic, and therapeutic decision-making for the medical and biomedical professions. Herein, we summarize current imaging methods that enable optimal 3D histopathologic reconstruction: Scanning, 3D scanning, and whole slide imaging. Briefly mentioned are emerging platforms, which combine robotics, sectioning, and imaging in their pursuit to digitize and automate the entire microscopy workflow. Finally, both current and emerging 3D imaging methods are discussed in relation to current and future applications within the context of pathology. PMID:28966836

Development and Validation of an Automated High-Throughput System for Zebrafish In Vivo Screenings

PubMed Central

Virto, Juan M.; Holgado, Olaia; Diez, Maria; Izpisua Belmonte, Juan Carlos; Callol-Massot, Carles

2012-01-01

The zebrafish is a vertebrate model compatible with the paradigms of drug discovery. The small size and transparency of zebrafish embryos make them amenable for the automation necessary in high-throughput screenings. We have developed an automated high-throughput platform for in vivo chemical screenings on zebrafish embryos that includes automated methods for embryo dispensation, compound delivery, incubation, imaging and analysis of the results. At present, two different assays to detect cardiotoxic compounds and angiogenesis inhibitors can be automatically run in the platform, showing the versatility of the system. A validation of these two assays with known positive and negative compounds, as well as a screening for the detection of unknown anti-angiogenic compounds, have been successfully carried out in the system developed. We present a totally automated platform that allows for high-throughput screenings in a vertebrate organism. PMID:22615792

Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins

PubMed Central

Handfield, Louis-François; Chong, Yolanda T.; Simmons, Jibril; Andrews, Brenda J.; Moses, Alan M.

2013-01-01

Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images. Our analysis is based on 7 biologically interpretable features which are evaluated on automatically identified cells, and whose cell-stage dependency is captured by a continuous model for cell growth. We show that it is possible to identify most previously identified localization patterns in a cluster analysis based on these features and that similarities between the inferred expression patterns contain more information about protein function than can be explained by a previous manual categorization of subcellular localization. Furthermore, the inferred cell-stage associated to each fluorescence measurement allows us to visualize large groups of proteins entering the bud at specific stages of bud growth. These correspond to proteins localized to organelles, revealing that the organelles must be entering the bud in a stereotypical order. We also identify and organize a smaller group of proteins that show subtle differences in the way they move around the bud during growth. Our results suggest that biologically interpretable features based on explicit models of cell morphology will yield unprecedented power for pattern discovery in high-resolution, high-throughput microscopy images. PMID:23785265

Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis.

PubMed

Mei, Feng; Fancy, Stephen P J; Shen, Yun-An A; Niu, Jianqin; Zhao, Chao; Presley, Bryan; Miao, Edna; Lee, Seonok; Mayoral, Sonia R; Redmond, Stephanie A; Etxeberria, Ainhoa; Xiao, Lan; Franklin, Robin J M; Green, Ari; Hauser, Stephen L; Chan, Jonah R

2014-08-01

Functional screening for compounds that promote remyelination represents a major hurdle in the development of rational therapeutics for multiple sclerosis. Screening for remyelination is problematic, as myelination requires the presence of axons. Standard methods do not resolve cell-autonomous effects and are not suited for high-throughput formats. Here we describe a binary indicant for myelination using micropillar arrays (BIMA). Engineered with conical dimensions, micropillars permit resolution of the extent and length of membrane wrapping from a single two-dimensional image. Confocal imaging acquired from the base to the tip of the pillars allows for detection of concentric wrapping observed as 'rings' of myelin. The platform is formatted in 96-well plates, amenable to semiautomated random acquisition and automated detection and quantification. Upon screening 1,000 bioactive molecules, we identified a cluster of antimuscarinic compounds that enhance oligodendrocyte differentiation and remyelination. Our findings demonstrate a new high-throughput screening platform for potential regenerative therapeutics in multiple sclerosis.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

PubMed

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

PubMed Central

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

High-throughput two-dimensional root system phenotyping platform facilitates genetic analysis of root growth and development.

PubMed

Clark, Randy T; Famoso, Adam N; Zhao, Keyan; Shaff, Jon E; Craft, Eric J; Bustamante, Carlos D; McCouch, Susan R; Aneshansley, Daniel J; Kochian, Leon V

2013-02-01

High-throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user-guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large-scale phenotyping studies. To demonstrate the unique capabilities and high-throughput capacity of this phenotyping platform for studying root systems, genome-wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population. © 2012 Blackwell Publishing Ltd.

Using high-content imaging data from ToxCast to analyze toxicological tipping points (TDS)

EPA Science Inventory

Translating results obtained from high-throughput screening to risk assessment is vital for reducing dependence on animal testing. We studied the effects of 976 chemicals (ToxCast Phase I and II) in HepG2 cells using high-content imaging (HCI) to measure dose and time-depende...

A compact high-resolution 3-D imaging spectrometer for discovering Oases on Mars

USGS Publications Warehouse

Ge, J.; Ren, D.; Lunine, J.I.; Brown, R.H.; Yelle, R.V.; Soderblom, L.A.; ,

2002-01-01

A new design for a very lightweight, very high throughput reflectance sectrometer enabled by two new technologies being developed is presented. These new technologies include integral field unit optics to enable simultaneous imaging and spectroscopy at high spatial resolution with an infrared (IR) array, and silicon grisms to enable compact and high-resolution spectroscopy.

A Versatile Cell Death Screening Assay Using Dye-Stained Cells and Multivariate Image Analysis.

PubMed

Collins, Tony J; Ylanko, Jarkko; Geng, Fei; Andrews, David W

2015-11-01

A novel dye-based method for measuring cell death in image-based screens is presented. Unlike conventional high- and medium-throughput cell death assays that measure only one form of cell death accurately, using multivariate analysis of micrographs of cells stained with the inexpensive mix, red dye nonyl acridine orange, and a nuclear stain, it was possible to quantify cell death induced by a variety of different agonists even without a positive control. Surprisingly, using a single known cytotoxic agent as a positive control for training a multivariate classifier allowed accurate quantification of cytotoxicity for mechanistically unrelated compounds enabling generation of dose-response curves. Comparison with low throughput biochemical methods suggested that cell death was accurately distinguished from cell stress induced by low concentrations of the bioactive compounds Tunicamycin and Brefeldin A. High-throughput image-based format analyses of more than 300 kinase inhibitors correctly identified 11 as cytotoxic with only 1 false positive. The simplicity and robustness of this dye-based assay makes it particularly suited to live cell screening for toxic compounds.

A Versatile Cell Death Screening Assay Using Dye-Stained Cells and Multivariate Image Analysis

PubMed Central

Collins, Tony J.; Ylanko, Jarkko; Geng, Fei

2015-01-01

Abstract A novel dye-based method for measuring cell death in image-based screens is presented. Unlike conventional high- and medium-throughput cell death assays that measure only one form of cell death accurately, using multivariate analysis of micrographs of cells stained with the inexpensive mix, red dye nonyl acridine orange, and a nuclear stain, it was possible to quantify cell death induced by a variety of different agonists even without a positive control. Surprisingly, using a single known cytotoxic agent as a positive control for training a multivariate classifier allowed accurate quantification of cytotoxicity for mechanistically unrelated compounds enabling generation of dose–response curves. Comparison with low throughput biochemical methods suggested that cell death was accurately distinguished from cell stress induced by low concentrations of the bioactive compounds Tunicamycin and Brefeldin A. High-throughput image-based format analyses of more than 300 kinase inhibitors correctly identified 11 as cytotoxic with only 1 false positive. The simplicity and robustness of this dye-based assay makes it particularly suited to live cell screening for toxic compounds. PMID:26422066

Automated sample area definition for high-throughput microscopy.

PubMed

Zeder, M; Ellrott, A; Amann, R

2011-04-01

High-throughput screening platforms based on epifluorescence microscopy are powerful tools in a variety of scientific fields. Although some applications are based on imaging geometrically defined samples such as microtiter plates, multiwell slides, or spotted gene arrays, others need to cope with inhomogeneously located samples on glass slides. The analysis of microbial communities in aquatic systems by sample filtration on membrane filters followed by multiple fluorescent staining, or the investigation of tissue sections are examples. Therefore, we developed a strategy for flexible and fast definition of sample locations by the acquisition of whole slide overview images and automated sample recognition by image analysis. Our approach was tested on different microscopes and the computer programs are freely available (http://www.technobiology.ch). Copyright © 2011 International Society for Advancement of Cytometry.

Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens

PubMed Central

Yin, Zheng; Zhou, Xiaobo; Bakal, Chris; Li, Fuhai; Sun, Youxian; Perrimon, Norbert; Wong, Stephen TC

2008-01-01

Background The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens. Results Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms. Conclusion We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens. PMID:18534020

Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time

PubMed Central

Neilson, E. H.; Edwards, A. M.; Blomstedt, C. K.; Berger, B.; Møller, B. Lindberg; Gleadow, R. M.

2015-01-01

The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator® at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf ‘greenness’ correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants. PMID:25697789

Assessing Morphological and Physiological Properties of Forest Species Using High Throughput Plant Phenotyping and Imaging Techniques

NASA Astrophysics Data System (ADS)

Mazis, A.; Hiller, J.; Morgan, P.; Awada, T.; Stoerger, V.

2017-12-01

High throughput plant phenotyping is increasingly being used to assess morphological and biophysical traits of economically important crops in agriculture. In this study, the potential application of this technique in natural resources management, through the characterization of woody plants regeneration, establishment, growth, and responses to water and nutrient manipulations was assessed. Two woody species were selected for this study, Quercus prinoides and Quercus bicolor. Seeds were collected from trees growing at the edge of their natural distribution in Nebraska and Missouri, USA. Seeds were germinated in the greenhouse and transferred to the Nebraska Innovation Campus Lemnatec3D High Throughput facility at the University of Nebraska-Lincoln. Seedlings subjected to water and N manipulations, were imaged twice or three times a week using four cameras (Visible, Fluorescence, Infrared and Hyperspectral), throughout the growing season. Traditional leaf to plant levels ecophysiological measurements were concurrently acquired to assess the relationship between these two techniques. These include gas exchange (LI 6400 and LI 6800, LICOR Inc., Lincoln NE), chlorophyll content, optical characteristics (Ocean Optics USB200), water and osmotic potentials, leaf area and weight and carbon isotope ratio. In the presentation, we highlight results on the potential use of high throughput plant phenotyping techniques to assess the morphology and physiology of woody species including responses to water availability and nutrient manipulation, and its broader application under field conditions and natural resources management. Also, we explore the different capabilities imaging provides us for modeling the plant physiological and morphological growth and how it can complement the current techniques

Improved high-throughput quantification of luminescent microplate assays using a common Western-blot imaging system.

PubMed

Hawkins, Liam J; Storey, Kenneth B

2017-01-01

Common Western-blot imaging systems have previously been adapted to measure signals from luminescent microplate assays. This can be a cost saving measure as Western-blot imaging systems are common laboratory equipment and could substitute a dedicated luminometer if one is not otherwise available. One previously unrecognized limitation is that the signals captured by the cameras in these systems are not equal for all wells. Signals are dependent on the angle of incidence to the camera, and thus the location of the well on the microplate. Here we show that: •The position of a well on a microplate significantly affects the signal captured by a common Western-blot imaging system from a luminescent assay.•The effect of well position can easily be corrected for.•This method can be applied to commercially available luminescent assays, allowing for high-throughput quantification of a wide range of biological processes and biochemical reactions.

CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging.

PubMed

Held, Michael; Schmitz, Michael H A; Fischer, Bernd; Walter, Thomas; Neumann, Beate; Olma, Michael H; Peter, Matthias; Ellenberg, Jan; Gerlich, Daniel W

2010-09-01

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

A high-throughput three-dimensional cell migration assay for toxicity screening with mobile device-based macroscopic image analysis

PubMed Central

Timm, David M.; Chen, Jianbo; Sing, David; Gage, Jacob A.; Haisler, William L.; Neeley, Shane K.; Raphael, Robert M.; Dehghani, Mehdi; Rosenblatt, Kevin P.; Killian, T. C.; Tseng, Hubert; Souza, Glauco R.

2013-01-01

There is a growing demand for in vitro assays for toxicity screening in three-dimensional (3D) environments. In this study, 3D cell culture using magnetic levitation was used to create an assay in which cells were patterned into 3D rings that close over time. The rate of closure was determined from time-lapse images taken with a mobile device and related to drug concentration. Rings of human embryonic kidney cells (HEK293) and tracheal smooth muscle cells (SMCs) were tested with ibuprofen and sodium dodecyl sulfate (SDS). Ring closure correlated with the viability and migration of cells in two dimensions (2D). Images taken using a mobile device were similar in analysis to images taken with a microscope. Ring closure may serve as a promising label-free and quantitative assay for high-throughput in vivo toxicity in 3D cultures. PMID:24141454

Targeted post-mortem computed tomography cardiac angiography: proof of concept.

PubMed

Saunders, Sarah L; Morgan, Bruno; Raj, Vimal; Robinson, Claire E; Rutty, Guy N

2011-07-01

With the increasing use and availability of multi-detector computed tomography and magnetic resonance imaging in autopsy practice, there has been an international push towards the development of the so-called near virtual autopsy. However, currently, a significant obstacle to the consideration as to whether or not near virtual autopsies could one day replace the conventional invasive autopsy is the failure of post-mortem imaging to yield detailed information concerning the coronary arteries. To date, a cost-effective, practical solution to allow high throughput imaging has not been presented within the forensic literature. We present a proof of concept paper describing a simple, quick, cost-effective, manual, targeted in situ post-mortem cardiac angiography method using a minimally invasive approach, to be used with multi-detector computed tomography for high throughput cadaveric imaging which can be used in permanent or temporary mortuaries.

Lensless on-chip imaging of cells provides a new tool for high-throughput cell-biology and medical diagnostics.

PubMed

Mudanyali, Onur; Erlinger, Anthony; Seo, Sungkyu; Su, Ting-Wei; Tseng, Derek; Ozcan, Aydogan

2009-12-14

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite effective, this classical approach has certain limitations for miniaturization of the imaging platform to make it compatible with the advanced state of the art in microfluidics. In this report, we introduce experimental details of a lensless on-chip imaging concept termed LUCAS (Lensless Ultra-wide field-of-view Cell monitoring Array platform based on Shadow imaging) that does not require any microscope objectives or other bulky optical components to image a heterogeneous cell solution over an ultra-wide field of view that can span as large as approximately 18 cm(2). Moreover, unlike conventional microscopes, LUCAS can image a heterogeneous cell solution of interest over a depth-of-field of approximately 5 mm without the need for refocusing which corresponds to up to approximately 9 mL sample volume. This imaging platform records the shadows (i.e., lensless digital holograms) of each cell of interest within its field of view, and automated digital processing of these cell shadows can determine the type, the count and the relative positions of cells within the solution. Because it does not require any bulky optical components or mechanical scanning stages it offers a significantly miniaturized platform that at the same time reduces the cost, which is quite important for especially point of care diagnostic tools. Furthermore, the imaging throughput of this platform is orders of magnitude better than conventional optical microscopes, which could be exceedingly valuable for high-throughput cell-biology experiments.

Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics

PubMed Central

Mudanyali, Onur; Erlinger, Anthony; Seo, Sungkyu; Su, Ting-Wei; Tseng, Derek; Ozcan, Aydogan

2009-01-01

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite effective, this classical approach has certain limitations for miniaturization of the imaging platform to make it compatible with the advanced state of the art in microfluidics. In this report, we introduce experimental details of a lensless on-chip imaging concept termed LUCAS (Lensless Ultra-wide field-of-view Cell monitoring Array platform based on Shadow imaging) that does not require any microscope objectives or other bulky optical components to image a heterogeneous cell solution over an ultra-wide field of view that can span as large as ~18 cm2. Moreover, unlike conventional microscopes, LUCAS can image a heterogeneous cell solution of interest over a depth-of-field of ~5 mm without the need for refocusing which corresponds to up to ~9 mL sample volume. This imaging platform records the shadows (i.e., lensless digital holograms) of each cell of interest within its field of view, and automated digital processing of these cell shadows can determine the type, the count and the relative positions of cells within the solution. Because it does not require any bulky optical components or mechanical scanning stages it offers a significantly miniaturized platform that at the same time reduces the cost, which is quite important for especially point of care diagnostic tools. Furthermore, the imaging throughput of this platform is orders of magnitude better than conventional optical microscopes, which could be exceedingly valuable for high-throughput cell-biology experiments. PMID:20010542

Microscale Laminar Vortices for High-Purity Extraction and Release of Circulating Tumor Cells.

PubMed

Hur, Soojung Claire; Che, James; Di Carlo, Dino

2017-01-01

Circulating tumor cells (CTCs) are disseminated tumor cells that reflect the tumors of origin and can provide a liquid biopsy that would potentially enable noninvasive tumor profiling, treatment monitoring, and identification of targeted treatments. Accurate and rapid purification of CTCs holds great potential to improve cancer care but the task remains technically challenging. Microfluidic isolation of CTCs within microscale vortices enables high-throughput and size-based purification of rare CTCs from bodily fluids. Collected cells are highly pure, viable, and easily accessible, allowing seamless integration with various downstream applications. Here, we describe how to fabricate the High-Throughput Vortex Chip (Vortex-HT) and to process diluted whole blood for CTC collection. Lastly, immunostaining and imaging protocols for CTC classification and corresponding CTC image galleries are reported.

Conventional and hyperspectral time-series imaging of maize lines widely used in field trials

PubMed Central

Liang, Zhikai; Pandey, Piyush; Stoerger, Vincent; Xu, Yuhang; Qiu, Yumou; Ge, Yufeng

2018-01-01

Abstract Background Maize (Zea mays ssp. mays) is 1 of 3 crops, along with rice and wheat, responsible for more than one-half of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping are currently the largest constraints on plant breeding efforts. Datasets linking new types of high-throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision–based tools. Findings A set of maize inbreds—primarily recently off patent lines—were phenotyped using a high-throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high-density genotyping and scored for a core set of 13 phenotypes in field trials across 13 North American states in 2 years by the Genomes 2 Fields Consortium. A total of 485 GB of image data including RGB, hyperspectral, fluorescence, and thermal infrared photos has been released. Conclusions Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, naive approaches to measuring traits such as biomass can introduce nonrandom measurement errors confounded with genotype variation. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors that influence yield plasticity. PMID:29186425

Conventional and hyperspectral time-series imaging of maize lines widely used in field trials.

PubMed

Liang, Zhikai; Pandey, Piyush; Stoerger, Vincent; Xu, Yuhang; Qiu, Yumou; Ge, Yufeng; Schnable, James C

2018-02-01

Maize (Zea mays ssp. mays) is 1 of 3 crops, along with rice and wheat, responsible for more than one-half of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping are currently the largest constraints on plant breeding efforts. Datasets linking new types of high-throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision-based tools. A set of maize inbreds-primarily recently off patent lines-were phenotyped using a high-throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high-density genotyping and scored for a core set of 13 phenotypes in field trials across 13 North American states in 2 years by the Genomes 2 Fields Consortium. A total of 485 GB of image data including RGB, hyperspectral, fluorescence, and thermal infrared photos has been released. Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, naive approaches to measuring traits such as biomass can introduce nonrandom measurement errors confounded with genotype variation. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors that influence yield plasticity. © The Authors 2017. Published by Oxford University Press.

Whole-animal imaging with high spatio-temporal resolution

NASA Astrophysics Data System (ADS)

Chhetri, Raghav; Amat, Fernando; Wan, Yinan; Höckendorf, Burkhard; Lemon, William C.; Keller, Philipp J.

2016-03-01

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

A novel high-throughput imaging system for automated analyses of avoidance behavior in zebrafish larvae

PubMed Central

Pelkowski, Sean D.; Kapoor, Mrinal; Richendrfer, Holly A.; Wang, Xingyue; Colwill, Ruth M.; Creton, Robbert

2011-01-01

Early brain development can be influenced by numerous genetic and environmental factors, with long-lasting effects on brain function and behavior. The identification of these factors is facilitated by recent innovations in high-throughput screening. However, large-scale screening in whole organisms remains challenging, in particular when studying changes in brain function or behavior in vertebrate model systems. In this study, we present a novel imaging system for high-throughput analyses of behavior in zebrafish larvae. The three-camera system can image twelve multiwell plates simultaneously and is unique in its ability to provide local visual stimuli in the wells of a multiwell plate. The acquired images are converted into a series of coordinates, which characterize the location and orientation of the larvae. The developed imaging techniques were tested by measuring avoidance behaviors in seven-day-old zebrafish larvae. The system effectively quantified larval avoidance and revealed an increased edge preference in response to a blue or red ‘bouncing ball’ stimulus. Larvae also avoid a bouncing ball stimulus when it is counter-balanced with a stationary ball, but do not avoid blinking balls counter-balanced with a stationary ball. These results indicate that the seven-day-old larvae respond specifically to movement, rather than color, size, or local changes in light intensity. The imaging system and assays for measuring avoidance behavior may be used to screen for genetic and environmental factors that cause developmental brain disorders and for novel drugs that could prevent or treat these disorders. PMID:21549762

A novel high-throughput imaging system for automated analyses of avoidance behavior in zebrafish larvae.

PubMed

Pelkowski, Sean D; Kapoor, Mrinal; Richendrfer, Holly A; Wang, Xingyue; Colwill, Ruth M; Creton, Robbert

2011-09-30

Early brain development can be influenced by numerous genetic and environmental factors, with long-lasting effects on brain function and behavior. The identification of these factors is facilitated by recent innovations in high-throughput screening. However, large-scale screening in whole organisms remains challenging, in particular when studying changes in brain function or behavior in vertebrate model systems. In this study, we present a novel imaging system for high-throughput analyses of behavior in zebrafish larvae. The three-camera system can image 12 multiwell plates simultaneously and is unique in its ability to provide local visual stimuli in the wells of a multiwell plate. The acquired images are converted into a series of coordinates, which characterize the location and orientation of the larvae. The developed imaging techniques were tested by measuring avoidance behaviors in seven-day-old zebrafish larvae. The system effectively quantified larval avoidance and revealed an increased edge preference in response to a blue or red 'bouncing ball' stimulus. Larvae also avoid a bouncing ball stimulus when it is counter-balanced with a stationary ball, but do not avoid blinking balls counter-balanced with a stationary ball. These results indicate that the seven-day-old larvae respond specifically to movement, rather than color, size, or local changes in light intensity. The imaging system and assays for measuring avoidance behavior may be used to screen for genetic and environmental factors that cause developmental brain disorders and for novel drugs that could prevent or treat these disorders. Copyright © 2011 Elsevier B.V. All rights reserved.

The impact of the condenser on cytogenetic image quality in digital microscope system.

PubMed

Ren, Liqiang; Li, Zheng; Li, Yuhua; Zheng, Bin; Li, Shibo; Chen, Xiaodong; Liu, Hong

2013-01-01

Optimizing operational parameters of the digital microscope system is an important technique to acquire high quality cytogenetic images and facilitate the process of karyotyping so that the efficiency and accuracy of diagnosis can be improved. This study investigated the impact of the condenser on cytogenetic image quality and system working performance using a prototype digital microscope image scanning system. Both theoretical analysis and experimental validations through objectively evaluating a resolution test chart and subjectively observing large numbers of specimen were conducted. The results show that the optimal image quality and large depth of field (DOF) are simultaneously obtained when the numerical aperture of condenser is set as 60%-70% of the corresponding objective. Under this condition, more analyzable chromosomes and diagnostic information are obtained. As a result, the system shows higher working stability and less restriction for the implementation of algorithms such as autofocusing especially when the system is designed to achieve high throughput continuous image scanning. Although the above quantitative results were obtained using a specific prototype system under the experimental conditions reported in this paper, the presented evaluation methodologies can provide valuable guidelines for optimizing operational parameters in cytogenetic imaging using the high throughput continuous scanning microscopes in clinical practice.

High-Throughput Image Analysis of Fibrillar Materials: A Case Study on Polymer Nanofiber Packing, Alignment, and Defects in Organic Field Effect Transistors.

PubMed

Persson, Nils E; Rafshoon, Joshua; Naghshpour, Kaylie; Fast, Tony; Chu, Ping-Hsun; McBride, Michael; Risteen, Bailey; Grover, Martha; Reichmanis, Elsa

2017-10-18

High-throughput discovery of process-structure-property relationships in materials through an informatics-enabled empirical approach is an increasingly utilized technique in materials research due to the rapidly expanding availability of data. Here, process-structure-property relationships are extracted for the nucleation, growth, and deposition of semiconducting poly(3-hexylthiophene) (P3HT) nanofibers used in organic field effect transistors, via high-throughput image analysis. This study is performed using an automated image analysis pipeline combining existing open-source software and new algorithms, enabling the rapid evaluation of structural metrics for images of fibrillar materials, including local orientational order, fiber length density, and fiber length distributions. We observe that microfluidic processing leads to fibers that pack with unusually high density, while sonication yields fibers that pack sparsely with low alignment. This is attributed to differences in their crystallization mechanisms. P3HT nanofiber packing during thin film deposition exhibits behavior suggesting that fibers are confined to packing in two-dimensional layers. We find that fiber alignment, a feature correlated with charge carrier mobility, is driven by increasing fiber length, and that shorter fibers tend to segregate to the buried dielectric interface during deposition, creating potentially performance-limiting defects in alignment. Another barrier to perfect alignment is the curvature of P3HT fibers; we propose a mechanistic simulation of fiber growth that reconciles both this curvature and the log-normal distribution of fiber lengths inherent to the fiber populations under consideration.

High-throughput electrical characterization for robust overlay lithography control

NASA Astrophysics Data System (ADS)

Devender, Devender; Shen, Xumin; Duggan, Mark; Singh, Sunil; Rullan, Jonathan; Choo, Jae; Mehta, Sohan; Tang, Teck Jung; Reidy, Sean; Holt, Jonathan; Kim, Hyung Woo; Fox, Robert; Sohn, D. K.

2017-03-01

Realizing sensitive, high throughput and robust overlay measurement is a challenge in current 14nm and advanced upcoming nodes with transition to 300mm and upcoming 450mm semiconductor manufacturing, where slight deviation in overlay has significant impact on reliability and yield1). Exponentially increasing number of critical masks in multi-patterning lithoetch, litho-etch (LELE) and subsequent LELELE semiconductor processes require even tighter overlay specification2). Here, we discuss limitations of current image- and diffraction- based overlay measurement techniques to meet these stringent processing requirements due to sensitivity, throughput and low contrast3). We demonstrate a new electrical measurement based technique where resistance is measured for a macro with intentional misalignment between two layers. Overlay is quantified by a parabolic fitting model to resistance where minima and inflection points are extracted to characterize overlay control and process window, respectively. Analyses using transmission electron microscopy show good correlation between actual overlay performance and overlay obtained from fitting. Additionally, excellent correlation of overlay from electrical measurements to existing image- and diffraction- based techniques is found. We also discuss challenges of integrating electrical measurement based approach in semiconductor manufacturing from Back End of Line (BEOL) perspective. Our findings open up a new pathway for accessing simultaneous overlay as well as process window and margins from a robust, high throughput and electrical measurement approach.

High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging

PubMed Central

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C.

2017-01-01

Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo. These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [R2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily (R2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy (R2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily (R2 < 0.3 and RPD < 1.2). This study suggested the potential usefulness of hyperspectral imaging as a high-throughput phenotyping technology for plant chemical traits. Future research is needed to test the method more thoroughly by designing experiments to vary plant nutrients individually and cover more plant species, genotypes, and growth stages. PMID:28824683

High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging.

PubMed

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C

2017-01-01

Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo . These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [ R 2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily ( R 2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy ( R 2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily ( R 2 < 0.3 and RPD < 1.2). This study suggested the potential usefulness of hyperspectral imaging as a high-throughput phenotyping technology for plant chemical traits. Future research is needed to test the method more thoroughly by designing experiments to vary plant nutrients individually and cover more plant species, genotypes, and growth stages.

Automated Analysis of siRNA Screens of Virus Infected Cells Based on Immunofluorescence Microscopy

NASA Astrophysics Data System (ADS)

Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl

We present an image analysis approach as part of a high-throughput microscopy screening system based on cell arrays for the identification of genes involved in Hepatitis C and Dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in cells, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behavior of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.

High-resolution, high-throughput imaging with a multibeam scanning electron microscope.

PubMed

Eberle, A L; Mikula, S; Schalek, R; Lichtman, J; Knothe Tate, M L; Zeidler, D

2015-08-01

Electron-electron interactions and detector bandwidth limit the maximal imaging speed of single-beam scanning electron microscopes. We use multiple electron beams in a single column and detect secondary electrons in parallel to increase the imaging speed by close to two orders of magnitude and demonstrate imaging for a variety of samples ranging from biological brain tissue to semiconductor wafers. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Automated vector selection of SIVQ and parallel computing integration MATLAB™: Innovations supporting large-scale and high-throughput image analysis studies.

PubMed

Cheng, Jerome; Hipp, Jason; Monaco, James; Lucas, David R; Madabhushi, Anant; Balis, Ulysses J

2011-01-01

Spatially invariant vector quantization (SIVQ) is a texture and color-based image matching algorithm that queries the image space through the use of ring vectors. In prior studies, the selection of one or more optimal vectors for a particular feature of interest required a manual process, with the user initially stochastically selecting candidate vectors and subsequently testing them upon other regions of the image to verify the vector's sensitivity and specificity properties (typically by reviewing a resultant heat map). In carrying out the prior efforts, the SIVQ algorithm was noted to exhibit highly scalable computational properties, where each region of analysis can take place independently of others, making a compelling case for the exploration of its deployment on high-throughput computing platforms, with the hypothesis that such an exercise will result in performance gains that scale linearly with increasing processor count. An automated process was developed for the selection of optimal ring vectors to serve as the predicate matching operator in defining histopathological features of interest. Briefly, candidate vectors were generated from every possible coordinate origin within a user-defined vector selection area (VSA) and subsequently compared against user-identified positive and negative "ground truth" regions on the same image. Each vector from the VSA was assessed for its goodness-of-fit to both the positive and negative areas via the use of the receiver operating characteristic (ROC) transfer function, with each assessment resulting in an associated area-under-the-curve (AUC) figure of merit. Use of the above-mentioned automated vector selection process was demonstrated in two cases of use: First, to identify malignant colonic epithelium, and second, to identify soft tissue sarcoma. For both examples, a very satisfactory optimized vector was identified, as defined by the AUC metric. Finally, as an additional effort directed towards attaining high-throughput capability for the SIVQ algorithm, we demonstrated the successful incorporation of it with the MATrix LABoratory (MATLAB™) application interface. The SIVQ algorithm is suitable for automated vector selection settings and high throughput computation.

Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Hui

2001-01-01

Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitablymore » designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm 2 for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection.« less

Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

PubMed

Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

2017-10-01

Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

Automated processing of zebrafish imaging data: a survey.

PubMed

Mikut, Ralf; Dickmeis, Thomas; Driever, Wolfgang; Geurts, Pierre; Hamprecht, Fred A; Kausler, Bernhard X; Ledesma-Carbayo, María J; Marée, Raphaël; Mikula, Karol; Pantazis, Periklis; Ronneberger, Olaf; Santos, Andres; Stotzka, Rainer; Strähle, Uwe; Peyriéras, Nadine

2013-09-01

Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

Automated Processing of Zebrafish Imaging Data: A Survey

PubMed Central

Dickmeis, Thomas; Driever, Wolfgang; Geurts, Pierre; Hamprecht, Fred A.; Kausler, Bernhard X.; Ledesma-Carbayo, María J.; Marée, Raphaël; Mikula, Karol; Pantazis, Periklis; Ronneberger, Olaf; Santos, Andres; Stotzka, Rainer; Strähle, Uwe; Peyriéras, Nadine

2013-01-01

Abstract Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines. PMID:23758125

Label-free high-throughput detection and quantification of circulating melanoma tumor cell clusters by linear-array-based photoacoustic tomography

NASA Astrophysics Data System (ADS)

Hai, Pengfei; Zhou, Yong; Zhang, Ruiying; Ma, Jun; Li, Yang; Shao, Jin-Yu; Wang, Lihong V.

2017-04-01

Circulating tumor cell (CTC) clusters, arising from multicellular groupings in a primary tumor, greatly elevate the metastatic potential of cancer compared with single CTCs. High-throughput detection and quantification of CTC clusters are important for understanding the tumor metastatic process and improving cancer therapy. Here, we applied a linear-array-based photoacoustic tomography (LA-PAT) system and improved the image reconstruction for label-free high-throughput CTC cluster detection and quantification in vivo. The feasibility was first demonstrated by imaging CTC cluster ex vivo. The relationship between the contrast-to-noise ratios (CNRs) and the number of cells in melanoma tumor cell clusters was investigated and verified. Melanoma CTC clusters with a minimum of four cells could be detected, and the number of cells could be computed from the CNR. Finally, we demonstrated imaging of injected melanoma CTC clusters in rats in vivo. Similarly, the number of cells in the melanoma CTC clusters could be quantified. The data showed that larger CTC clusters had faster clearance rates in the bloodstream, which agreed with the literature. The results demonstrated the capability of LA-PAT to detect and quantify melanoma CTC clusters in vivo and showed its potential for tumor metastasis study and cancer therapy.

GPU Lossless Hyperspectral Data Compression System

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh I.; Keymeulen, Didier; Kiely, Aaron B.; Klimesh, Matthew A.

2014-01-01

Hyperspectral imaging systems onboard aircraft or spacecraft can acquire large amounts of data, putting a strain on limited downlink and storage resources. Onboard data compression can mitigate this problem but may require a system capable of a high throughput. In order to achieve a high throughput with a software compressor, a graphics processing unit (GPU) implementation of a compressor was developed targeting the current state-of-the-art GPUs from NVIDIA(R). The implementation is based on the fast lossless (FL) compression algorithm reported in "Fast Lossless Compression of Multispectral-Image Data" (NPO- 42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which operates on hyperspectral data and achieves excellent compression performance while having low complexity. The FL compressor uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. The new Consultative Committee for Space Data Systems (CCSDS) Standard for Lossless Multispectral & Hyperspectral image compression (CCSDS 123) is based on the FL compressor. The software makes use of the highly-parallel processing capability of GPUs to achieve a throughput at least six times higher than that of a software implementation running on a single-core CPU. This implementation provides a practical real-time solution for compression of data from airborne hyperspectral instruments.

Automation of Technology for Cancer Research.

PubMed

van der Ent, Wietske; Veneman, Wouter J; Groenewoud, Arwin; Chen, Lanpeng; Tulotta, Claudia; Hogendoorn, Pancras C W; Spaink, Herman P; Snaar-Jagalska, B Ewa

2016-01-01

Zebrafish embryos can be obtained for research purposes in large numbers at low cost and embryos develop externally in limited space, making them highly suitable for high-throughput cancer studies and drug screens. Non-invasive live imaging of various processes within the larvae is possible due to their transparency during development, and a multitude of available fluorescent transgenic reporter lines.To perform high-throughput studies, handling large amounts of embryos and larvae is required. With such high number of individuals, even minute tasks may become time-consuming and arduous. In this chapter, an overview is given of the developments in the automation of various steps of large scale zebrafish cancer research for discovering important cancer pathways and drugs for the treatment of human disease. The focus lies on various tools developed for cancer cell implantation, embryo handling and sorting, microfluidic systems for imaging and drug treatment, and image acquisition and analysis. Examples will be given of employment of these technologies within the fields of toxicology research and cancer research.

G protein-coupled receptor internalization assays in the high-content screening format.

PubMed

Haasen, Dorothea; Schnapp, Andreas; Valler, Martin J; Heilker, Ralf

2006-01-01

High-content screening (HCS), a combination of fluorescence microscopic imaging and automated image analysis, has become a frequently applied tool to study test compound effects in cellular disease-modeling systems. This chapter describes the measurement of G protein-coupled receptor (GPCR) internalization in the HCS format using a high-throughput, confocal cellular imaging device. GPCRs are the most successful group of therapeutic targets on the pharmaceutical market. Accordingly, the search for compounds that interfere with GPCR function in a specific and selective way is a major focus of the pharmaceutical industry today. This chapter describes methods for the ligand-induced internalization of GPCRs labeled previously with either a fluorophore-conjugated ligand or an antibody directed against an N-terminal tag of the GPCR. Both labeling techniques produce robust assay formats. Complementary to other functional GPCR drug discovery assays, internalization assays enable a pharmacological analysis of test compounds. We conclude that GPCR internalization assays represent a valuable medium/high-throughput screening format to determine the cellular activity of GPCR ligands.

Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems.

PubMed

Choi, Hyungsuk; Choi, Woohyuk; Quan, Tran Minh; Hildebrand, David G C; Pfister, Hanspeter; Jeong, Won-Ki

2014-12-01

As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and GPU accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing GPU clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi's Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.

A high-throughput two channel discrete wavelet transform architecture for the JPEG2000 standard

NASA Astrophysics Data System (ADS)

Badakhshannoory, Hossein; Hashemi, Mahmoud R.; Aminlou, Alireza; Fatemi, Omid

2005-07-01

The Discrete Wavelet Transform (DWT) is increasingly recognized in image and video compression standards, as indicated by its use in JPEG2000. The lifting scheme algorithm is an alternative DWT implementation that has a lower computational complexity and reduced resource requirement. In the JPEG2000 standard two lifting scheme based filter banks are introduced: the 5/3 and 9/7. In this paper a high throughput, two channel DWT architecture for both of the JPEG2000 DWT filters is presented. The proposed pipelined architecture has two separate input channels that process the incoming samples simultaneously with minimum memory requirement for each channel. The architecture had been implemented in VHDL and synthesized on a Xilinx Virtex2 XCV1000. The proposed architecture applies DWT on a 2K by 1K image at 33 fps with a 75 MHZ clock frequency. This performance is achieved with 70% less resources than two independent single channel modules. The high throughput and reduced resource requirement has made this architecture the proper choice for real time applications such as Digital Cinema.

Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Hui

2001-01-01

Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, the author introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties ofmore » suitably designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, they demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm 2 for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection. In the second part of this dissertation, the author used laser-induced native fluorescence coupled with capillary electrophoresis (LINF-CE) and microscope imaging to study the single cell degranulation. On the basis of good temporal correlation with events observed through an optical microscope, they have identified individual peaks in the fluorescence electropherograms as serotonin released from the granular core on contact with the surrounding fluid.« less

Development of a High-Throughput Microwave Imaging System for Concealed Weapons Detection

DTIC Science & Technology

2016-07-15

hardware. Index Terms—Microwave imaging, multistatic radar, Fast Fourier Transform (FFT). I. INTRODUCTION Near-field microwave imaging is a non-ionizing...configuration, but its computational demands are extreme. Fast Fourier Transform (FFT) imaging has long been used to efficiently construct images sampled with...Simulated image of 25 point scatterers imaged at range 1.5m, with array layout depicted in Fig. 3. Left: image formed with Equation (5) ( Fourier

Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

PubMed

Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

2002-01-01

Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.

PubMed

Rahaman, Md Matiur; Ahsan, Md Asif; Gillani, Zeeshan; Chen, Ming

2017-09-01

Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant biomass of individual plants from their digital images is becoming more important. In this paper, we propose an approach to biomass estimation based on image derived phenotypic traits. Several image-based biomass studies state that the estimation of plant biomass is only a linear function of the projected plant area in images. However, we modeled the plant volume as a function of plant area, plant compactness, and plant age to generalize the linear biomass model. The obtained results confirm the proposed model and can explain most of the observed variance during image-derived biomass estimation. Moreover, a small difference was observed between actual and estimated digital biomass, which indicates that our proposed approach can be used to estimate digital biomass accurately.

Automated analysis of siRNA screens of cells infected by hepatitis C and dengue viruses based on immunofluorescence microscopy images

NASA Astrophysics Data System (ADS)

Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl

2008-03-01

We present an image analysis approach as part of a high-throughput microscopy siRNA-based screening system using cell arrays for the identification of cellular genes involved in hepatitis C and dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in the neighborhood of segmented cell nuclei, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment and single images. In particular, we propose a novel approach for the localization of regions of transfected cells within cell array images, which combines model-based circle fitting and grid fitting. By this scheme we integrate information from single cell array images and knowledge from the complete cell arrays. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behaviour of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.

A High-Throughput Automated Microfluidic Platform for Calcium Imaging of Taste Sensing.

PubMed

Hsiao, Yi-Hsing; Hsu, Chia-Hsien; Chen, Chihchen

2016-07-08

The human enteroendocrine L cell line NCI-H716, expressing taste receptors and taste signaling elements, constitutes a unique model for the studies of cellular responses to glucose, appetite regulation, gastrointestinal motility, and insulin secretion. Targeting these gut taste receptors may provide novel treatments for diabetes and obesity. However, NCI-H716 cells are cultured in suspension and tend to form multicellular aggregates, preventing high-throughput calcium imaging due to interferences caused by laborious immobilization and stimulus delivery procedures. Here, we have developed an automated microfluidic platform that is capable of trapping more than 500 single cells into microwells with a loading efficiency of 77% within two minutes, delivering multiple chemical stimuli and performing calcium imaging with enhanced spatial and temporal resolutions when compared to bath perfusion systems. Results revealed the presence of heterogeneity in cellular responses to the type, concentration, and order of applied sweet and bitter stimuli. Sucralose and denatonium benzoate elicited robust increases in the intracellular Ca(2+) concentration. However, glucose evoked a rapid elevation of intracellular Ca(2+) followed by reduced responses to subsequent glucose stimulation. Using Gymnema sylvestre as a blocking agent for the sweet taste receptor confirmed that different taste receptors were utilized for sweet and bitter tastes. This automated microfluidic platform is cost-effective, easy to fabricate and operate, and may be generally applicable for high-throughput and high-content single-cell analysis and drug screening.

Fluorescent and Lanthanide Labeling for Ligand Screens, Assays, and Imaging

PubMed Central

Josan, Jatinder S.; De Silva, Channa R.; Yoo, Byunghee; Lynch, Ronald M.; Pagel, Mark D.; Vagner, Josef; Hruby, Victor J.

2012-01-01

The use of fluorescent (or luminescent) and metal contrast agents in high-throughput screens, in vitro assays, and molecular imaging procedures has rapidly expanded in recent years. Here we describe the development and utility of high-affinity ligands for cancer theranostics and other in vitro screening studies. In this context, we also illustrate the syntheses and use of heteromultivalent ligands as targeted imaging agents. PMID:21318902

Quantitative detection of benzoyl peroxide in wheat flour by line-scan macro-scale Raman chemical imaging

USDA-ARS?s Scientific Manuscript database

A high-throughput Raman chemical imaging method was developed for direct inspection of benzoyl peroxide (BPO) mixed in wheat flour. A 5 W 785 nm line laser (240 mm long and 1 mm wide) was used as a Raman excitation source in a push-broom Raman imaging system. Hyperspectral Raman images were collecte...

Fully-automated, high-throughput micro-computed tomography analysis of body composition enables therapeutic efficacy monitoring in preclinical models.

PubMed

Wyatt, S K; Barck, K H; Kates, L; Zavala-Solorio, J; Ross, J; Kolumam, G; Sonoda, J; Carano, R A D

2015-11-01

The ability to non-invasively measure body composition in mouse models of obesity and obesity-related disorders is essential for elucidating mechanisms of metabolic regulation and monitoring the effects of novel treatments. These studies aimed to develop a fully automated, high-throughput micro-computed tomography (micro-CT)-based image analysis technique for longitudinal quantitation of adipose, non-adipose and lean tissue as well as bone and demonstrate utility for assessing the effects of two distinct treatments. An initial validation study was performed in diet-induced obesity (DIO) and control mice on a vivaCT 75 micro-CT system. Subsequently, four groups of DIO mice were imaged pre- and post-treatment with an experimental agonistic antibody specific for anti-fibroblast growth factor receptor 1 (anti-FGFR1, R1MAb1), control immunoglobulin G antibody, a known anorectic antiobesity drug (rimonabant, SR141716), or solvent control. The body composition analysis technique was then ported to a faster micro-CT system (CT120) to markedly increase throughput as well as to evaluate the use of micro-CT image intensity for hepatic lipid content in DIO and control mice. Ex vivo chemical analysis and colorimetric analysis of the liver triglycerides were performed as the standard metrics for correlation with body composition and hepatic lipid status, respectively. Micro-CT-based body composition measures correlate with ex vivo chemical analysis metrics and enable distinction between DIO and control mice. R1MAb1 and rimonabant have differing effects on body composition as assessed by micro-CT. High-throughput body composition imaging is possible using a modified CT120 system. Micro-CT also provides a non-invasive assessment of hepatic lipid content. This work describes, validates and demonstrates utility of a fully automated image analysis technique to quantify in vivo micro-CT-derived measures of adipose, non-adipose and lean tissue, as well as bone. These body composition metrics highly correlate with standard ex vivo chemical analysis and enable longitudinal evaluation of body composition and therapeutic efficacy monitoring.

The Impact of the Condenser on Cytogenetic Image Quality in Digital Microscope System

PubMed Central

Ren, Liqiang; Li, Zheng; Li, Yuhua; Zheng, Bin; Li, Shibo; Chen, Xiaodong; Liu, Hong

2013-01-01

Background: Optimizing operational parameters of the digital microscope system is an important technique to acquire high quality cytogenetic images and facilitate the process of karyotyping so that the efficiency and accuracy of diagnosis can be improved. OBJECTIVE: This study investigated the impact of the condenser on cytogenetic image quality and system working performance using a prototype digital microscope image scanning system. Methods: Both theoretical analysis and experimental validations through objectively evaluating a resolution test chart and subjectively observing large numbers of specimen were conducted. Results: The results show that the optimal image quality and large depth of field (DOF) are simultaneously obtained when the numerical aperture of condenser is set as 60%–70% of the corresponding objective. Under this condition, more analyzable chromosomes and diagnostic information are obtained. As a result, the system shows higher working stability and less restriction for the implementation of algorithms such as autofocusing especially when the system is designed to achieve high throughput continuous image scanning. Conclusions: Although the above quantitative results were obtained using a specific prototype system under the experimental conditions reported in this paper, the presented evaluation methodologies can provide valuable guidelines for optimizing operational parameters in cytogenetic imaging using the high throughput continuous scanning microscopes in clinical practice. PMID:23676284

Lessons From Paired Data From exPVP Maize Lines in Agronomic Field Trials and RGB And Hyperspectral Time-Series Imaging In Controlled Environments

NASA Astrophysics Data System (ADS)

Schnable, J. C.; Pandey, P.; Ge, Y.; Xu, Y.; Qiu, Y.; Liang, Z.

2017-12-01

Maize Zea mays ssp. mays is one of three crops, along with rice and wheat, responsible for more than 1/2 of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping is currently the largest constraint on plant breeding efforts. Datasets linking new types of high throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision based tools. A set of maize inbreds and hybrids - primarily recently off patent lines - were phenotyped using a high throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high density genotyping, and scored for a core set of 13 phenotypes in field trials across 13 North American states in 2014, 2015, 2016, and 2017. Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, we demonstrate that naive approaches to measuring traits such as biomass where are developed without integrating genotypic information can introduce nonrandom measurement errors which are confounded with variation between plant accessions. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue which were not identified using aerial imagry. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors influencing yield plasticity.

High-Resolution X-Ray Telescopes

NASA Technical Reports Server (NTRS)

ODell, Stephen L.; Brissenden, Roger J.; Davis, William; Elsner, Ronald F.; Elvis, Martin; Freeman, Mark; Gaetz, Terry; Gorenstein, Paul; Gubarev, Mikhail V.

2010-01-01

Fundamental needs for future x-ray telescopes: a) Sharp images => excellent angular resolution. b) High throughput => large aperture areas. Generation-X optics technical challenges: a) High resolution => precision mirrors & alignment. b) Large apertures => lots of lightweight mirrors. Innovation needed for technical readiness: a) 4 top-level error terms contribute to image size. b) There are approaches to controlling those errors. Innovation needed for manufacturing readiness. Programmatic issues are comparably challenging.

FBI Fingerprint Image Capture System High-Speed-Front-End throughput modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rathke, P.M.

1993-09-01

The Federal Bureau of Investigation (FBI) has undertaken a major modernization effort called the Integrated Automated Fingerprint Identification System (IAFISS). This system will provide centralized identification services using automated fingerprint, subject descriptor, mugshot, and document processing. A high-speed Fingerprint Image Capture System (FICS) is under development as part of the IAFIS program. The FICS will capture digital and microfilm images of FBI fingerprint cards for input into a central database. One FICS design supports two front-end scanning subsystems, known as the High-Speed-Front-End (HSFE) and Low-Speed-Front-End, to supply image data to a common data processing subsystem. The production rate of themore » HSFE is critical to meeting the FBI`s fingerprint card processing schedule. A model of the HSFE has been developed to help identify the issues driving the production rate, assist in the development of component specifications, and guide the evolution of an operations plan. A description of the model development is given, the assumptions are presented, and some HSFE throughput analysis is performed.« less

RootGraph: a graphic optimization tool for automated image analysis of plant roots

PubMed Central

Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N.; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J.

2015-01-01

This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. PMID:26224880

Optofluidic time-stretch quantitative phase microscopy.

PubMed

Guo, Baoshan; Lei, Cheng; Wu, Yi; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Lee, Sangwook; Isozaki, Akihiro; Li, Ming; Jiang, Yiyue; Yasumoto, Atsushi; Di Carlo, Dino; Tanaka, Yo; Yatomi, Yutaka; Ozeki, Yasuyuki; Goda, Keisuke

2018-03-01

Innovations in optical microscopy have opened new windows onto scientific research, industrial quality control, and medical practice over the last few decades. One of such innovations is optofluidic time-stretch quantitative phase microscopy - an emerging method for high-throughput quantitative phase imaging that builds on the interference between temporally stretched signal and reference pulses by using dispersive properties of light in both spatial and temporal domains in an interferometric configuration on a microfluidic platform. It achieves the continuous acquisition of both intensity and phase images with a high throughput of more than 10,000 particles or cells per second by overcoming speed limitations that exist in conventional quantitative phase imaging methods. Applications enabled by such capabilities are versatile and include characterization of cancer cells and microalgal cultures. In this paper, we review the principles and applications of optofluidic time-stretch quantitative phase microscopy and discuss its future perspective. Copyright © 2017 Elsevier Inc. All rights reserved.

Affordable Imaging Lab for Noninvasive Analysis of Biomass and Early Vigour in Cereal Crops

PubMed Central

2018-01-01

Plant phenotyping by imaging allows automated analysis of plants for various morphological and physiological traits. In this work, we developed a low-cost RGB imaging phenotyping lab (LCP lab) for low-throughput imaging and analysis using affordable imaging equipment and freely available software. LCP lab comprising RGB imaging and analysis pipeline is set up and demonstrated with early vigour analysis in wheat. Using this lab, a few hundred pots can be photographed in a day and the pots are tracked with QR codes. The software pipeline for both imaging and analysis is built from freely available software. The LCP lab was evaluated for early vigour analysis of five wheat cultivars. A high coefficient of determination (R2 0.94) was obtained between the dry weight and the projected leaf area of 20-day-old wheat plants and R2 of 0.9 for the relative growth rate between 10 and 20 days of plant growth. Detailed description for setting up such a lab is provided together with custom scripts built for imaging and analysis. The LCP lab is an affordable alternative for analysis of cereal crops when access to a high-throughput phenotyping facility is unavailable or when the experiments require growing plants in highly controlled climate chambers. The protocols described in this work are useful for building affordable imaging system for small-scale research projects and for education. PMID:29850536

Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes

DOE PAGES

Cruz, Jeffrey A.; Savage, Linda J.; Zegarac, Robert; ...

2016-06-22

Understanding and improving the productivity and robustness of plant photosynthesis requires high-throughput phenotyping under environmental conditions that are relevant to the field. Here we demonstrate the dynamic environmental photosynthesis imager (DEPI), an experimental platform for integrated, continuous, and high-throughput measurements of photosynthetic parameters during plant growth under reproducible yet dynamic environmental conditions. Using parallel imagers obviates the need to move plants or sensors, reducing artifacts and allowing simultaneous measurement on large numbers of plants. As a result, DEPI can reveal phenotypes that are not evident under standard laboratory conditions but emerge under progressively more dynamic illumination. We show examples inmore » mutants of Arabidopsis of such “emergent phenotypes” that are highly transient and heterogeneous, appearing in different leaves under different conditions and depending in complex ways on both environmental conditions and plant developmental age. Finally, these emergent phenotypes appear to be caused by a range of phenomena, suggesting that such previously unseen processes are critical for plant responses to dynamic environments.« less

Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis

PubMed Central

Paintdakhi, Ahmad; Parry, Bradley; Campos, Manuel; Irnov, Irnov; Elf, Johan; Surovtsev, Ivan; Jacobs-Wagner, Christine

2016-01-01

Summary With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today’s single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals, and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis, and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills. PMID:26538279

Quantifying collagen orientation in breast tissue biopsies using SLIM (Conference Presentation)

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Okoro, Chukwuemeka; Balla, Andre; Toussaint, Kimani C.; Popescu, Gabriel

2017-02-01

Breast cancer is a major public health problem worldwide, being the most common type of cancer among women according to the World Health Organization (WHO). The WHO has further stressed the importance of an early determination of the disease course through prognostic markers. Recent studies have shown that the alignment of collagen fibers in tumor adjacent stroma correlate with poorer health outcomes in patients. Such studies have typically been carried out using Second-Harmonic Generation (SHG) microscopy. SHG images are very useful for quantifying collagen fiber orientation due their specificity to non-centrosymmetric structures in tissue, leading to high contrast in collagen rich areas. However, the imaging throughput in SHG microscopy is limited by its point scanning geometry. In this work, we show that SLIM, a wide-field high-throughput QPI technique, can be used to obtain the same information on collagen fiber orientation as is obtainable through SHG microscopy. We imaged a tissue microarray containing both benign and malignant cores using both SHG microscopy and SLIM. The cellular (non-collagenous) structures in the SLIM images were next segmented out using an algorithm developed in-house. Using the previously published Fourier Transform Second Harmonic Generation (FT-SHG) tool, the fiber orientations in SHG and segmented SLIM images were then quantified. The resulting histograms of fiber orientation angles showed that both SHG and SLIM generate similar measurements of collagen fiber orientation. The SLIM modality, however, can generate these results at much higher throughput due to its wide-field, whole-slide scanning capabilities.

AI-augmented time stretch microscopy

NASA Astrophysics Data System (ADS)

Mahjoubfar, Ata; Chen, Claire L.; Lin, Jiahao; Jalali, Bahram

2017-02-01

Cell reagents used in biomedical analysis often change behavior of the cells that they are attached to, inhibiting their native signaling. On the other hand, label-free cell analysis techniques have long been viewed as challenging either due to insufficient accuracy by limited features, or because of low throughput as a sacrifice of improved precision. We present a recently developed artificial-intelligence augmented microscope, which builds upon high-throughput time stretch quantitative phase imaging (TS-QPI) and deep learning to perform label-free cell classification with record high-accuracy. Our system captures quantitative optical phase and intensity images simultaneously by frequency multiplexing, extracts multiple biophysical features of the individual cells from these images fused, and feeds these features into a supervised machine learning model for classification. The enhanced performance of our system compared to other label-free assays is demonstrated by classification of white blood T-cells versus colon cancer cells and lipid accumulating algal strains for biofuel production, which is as much as five-fold reduction in inaccuracy. This system obtains the accuracy required in practical applications such as personalized drug development, while the cells remain intact and the throughput is not sacrificed. Here, we introduce a data acquisition scheme based on quadrature phase demodulation that enables interruptionless storage of TS-QPI cell images. Our proof of principle demonstration is capable of saving 40 TB of cell images in about four hours, i.e. pictures of every single cell in 10 mL of a sample.

High-throughput microfluidic line scan imaging for cytological characterization

NASA Astrophysics Data System (ADS)

Hutcheson, Joshua A.; Powless, Amy J.; Majid, Aneeka A.; Claycomb, Adair; Fritsch, Ingrid; Balachandran, Kartik; Muldoon, Timothy J.

2015-03-01

Imaging cells in a microfluidic chamber with an area scan camera is difficult due to motion blur and data loss during frame readout causing discontinuity of data acquisition as cells move at relatively high speeds through the chamber. We have developed a method to continuously acquire high-resolution images of cells in motion through a microfluidics chamber using a high-speed line scan camera. The sensor acquires images in a line-by-line fashion in order to continuously image moving objects without motion blur. The optical setup comprises an epi-illuminated microscope with a 40X oil immersion, 1.4 NA objective and a 150 mm tube lens focused on a microfluidic channel. Samples containing suspended cells fluorescently stained with 0.01% (w/v) proflavine in saline are introduced into the microfluidics chamber via a syringe pump; illumination is provided by a blue LED (455 nm). Images were taken of samples at the focal plane using an ELiiXA+ 8k/4k monochrome line-scan camera at a line rate of up to 40 kHz. The system's line rate and fluid velocity are tightly controlled to reduce image distortion and are validated using fluorescent microspheres. Image acquisition was controlled via MATLAB's Image Acquisition toolbox. Data sets comprise discrete images of every detectable cell which may be subsequently mined for morphological statistics and definable features by a custom texture analysis algorithm. This high-throughput screening method, comparable to cell counting by flow cytometry, provided efficient examination including counting, classification, and differentiation of saliva, blood, and cultured human cancer cells.

Transfer, imaging, and analysis plate for facile handling of 384 hanging drop 3D tissue spheroids.

PubMed

Cavnar, Stephen P; Salomonsson, Emma; Luker, Kathryn E; Luker, Gary D; Takayama, Shuichi

2014-04-01

Three-dimensional culture systems bridge the experimental gap between in vivo and in vitro physiology. However, nonstandardized formation and limited downstream adaptability of 3D cultures have hindered mainstream adoption of these systems for biological applications, especially for low- and moderate-throughput assays commonly used in biomedical research. Here we build on our recent development of a 384-well hanging drop plate for spheroid culture to design a complementary spheroid transfer and imaging (TRIM) plate. The low-aspect ratio wells of the TRIM plate facilitated high-fidelity, user-independent, contact-based collection of hanging drop spheroids. Using the TRIM plate, we demonstrated several downstream analyses, including bulk tissue collection for flow cytometry, high-resolution low working-distance immersion imaging, and timely reagent delivery for enzymatic studies. Low working-distance multiphoton imaging revealed a cell type-dependent, macroscopic spheroid structure. Unlike ovarian cancer spheroids, which formed loose, disk-shaped spheroids, human mammary fibroblasts formed tight, spherical, and nutrient-limited spheroids. Beyond the applications we describe here, we expect the hanging drop spheroid plate and complementary TRIM plate to facilitate analyses of spheroids across the spectrum of throughput, particularly for bulk collection of spheroids and high-content imaging.

Lensless digital holographic microscopy and its applications in biomedicine and environmental monitoring.

PubMed

Wu, Yichen; Ozcan, Aydogan

2018-03-01

Optical compound microscope has been a major tool in biomedical imaging for centuries. Its performance relies on relatively complicated, bulky and expensive lenses and alignment mechanics. In contrast, the lensless microscope digitally reconstructs microscopic images of specimens without using any lenses, as a result of which it can be made much smaller, lighter and lower-cost. Furthermore, the limited space-bandwidth product of objective lenses in a conventional microscope can be significantly surpassed by a lensless microscope. Such lensless imaging designs have enabled high-resolution and high-throughput imaging of specimens using compact, portable and cost-effective devices to potentially address various point-of-care, global-health and telemedicine related challenges. In this review, we discuss the operation principles and the methods behind lensless digital holographic on-chip microscopy. We also go over various applications that are enabled by cost-effective and compact implementations of lensless microscopy, including some recent work on air quality monitoring, which utilized machine learning for high-throughput and accurate quantification of particulate matter in air. Finally, we conclude with a brief future outlook of this computational imaging technology. Copyright © 2017 Elsevier Inc. All rights reserved.

A high-throughput lab-on-a-chip interface for zebrafish embryo tests in drug discovery and ecotoxicology

NASA Astrophysics Data System (ADS)

Zhu, Feng; Akagi, Jin; Hall, Chris J.; Crosier, Kathryn E.; Crosier, Philip S.; Delaage, Pierre; Wlodkowic, Donald

2013-12-01

Drug discovery screenings performed on zebrafish embryos mirror with a high level of accuracy. The tests usually performed on mammalian animal models, and the fish embryo toxicity assay (FET) is one of the most promising alternative approaches to acute ecotoxicity testing with adult fish. Notwithstanding this, conventional methods utilising 96-well microtiter plates and manual dispensing of fish embryos are very time-consuming. They rely on laborious and iterative manual pipetting that is a main source of analytical errors and low throughput. In this work, we present development of a miniaturised and high-throughput Lab-on-a-Chip (LOC) platform for automation of FET assays. The 3D high-density LOC array was fabricated in poly-methyl methacrylate (PMMA) transparent thermoplastic using infrared laser micromachining while the off-chip interfaces were fabricated using additive manufacturing processes (FDM and SLA). The system's design facilitates rapid loading and immobilization of a large number of embryos in predefined clusters of traps during continuous microperfusion of drugs/toxins. It has been conceptually designed to seamlessly interface with both upright and inverted fluorescent imaging systems and also to directly interface with conventional microtiter plate readers that accept 96-well plates. We also present proof-of-concept interfacing with a high-speed imaging cytometer Plate RUNNER HD® capable of multispectral image acquisition with resolution of up to 8192 x 8192 pixels and depth of field of about 40 μm. Furthermore, we developed a miniaturized and self-contained analytical device interfaced with a miniaturized USB microscope. This system modification is capable of performing rapid imaging of multiple embryos at a low resolution for drug toxicity analysis.

High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

PubMed

Rajkomar, Alvin; Lingam, Sneha; Taylor, Andrew G; Blum, Michael; Mongan, John

2017-02-01

The study aimed to determine if computer vision techniques rooted in deep learning can use a small set of radiographs to perform clinically relevant image classification with high fidelity. One thousand eight hundred eighty-five chest radiographs on 909 patients obtained between January 2013 and July 2015 at our institution were retrieved and anonymized. The source images were manually annotated as frontal or lateral and randomly divided into training, validation, and test sets. Training and validation sets were augmented to over 150,000 images using standard image manipulations. We then pre-trained a series of deep convolutional networks based on the open-source GoogLeNet with various transformations of the open-source ImageNet (non-radiology) images. These trained networks were then fine-tuned using the original and augmented radiology images. The model with highest validation accuracy was applied to our institutional test set and a publicly available set. Accuracy was assessed by using the Youden Index to set a binary cutoff for frontal or lateral classification. This retrospective study was IRB approved prior to initiation. A network pre-trained on 1.2 million greyscale ImageNet images and fine-tuned on augmented radiographs was chosen. The binary classification method correctly classified 100 % (95 % CI 99.73-100 %) of both our test set and the publicly available images. Classification was rapid, at 38 images per second. A deep convolutional neural network created using non-radiological images, and an augmented set of radiographs is effective in highly accurate classification of chest radiograph view type and is a feasible, rapid method for high-throughput annotation.

Adverse outcome pathway (AOP) development II: Best practices

EPA Science Inventory

Organization of existing and emerging toxicological knowledge into adverse outcome pathway (AOP) descriptions can facilitate greater application of mechanistic data, including high throughput in vitro, high content omics and imaging, and biomarkers, in risk-based decision-making....

A Novel, Poly-Etalon, Fabry-Perot for Planetary Research

NASA Technical Reports Server (NTRS)

Kerr, Robert B.; Doe, Richard; Noto, John

1997-01-01

In an effort to develop a mechanically robust, high throughput and solid state spectrometer several liquid crystal Fabry-Perot etalons were constructed. The etalons were tested for spectral response, radiation resistance and optical transmission. The first year of this project was spent developing and understanding the properties of the liquid crystal etalons; in the second year an intensified all-sky imaging system was developed around a pair of LC etalons. The imaging system, developed jointly with SRI International represents a unique brassboard to demonstrate the use of LC etalons as tunable filters. The first set of etalons constructed in year one of this project were tested for spectral response and throughput while etalon surrogates were exposed to proton radiation simulating the exposure of an object in Low Earth Orbit (LEO). The 2" diameter etalons had a measure finesse of approximately 10 and were tunable over five orders. Liquid crystals exposed to proton irradiation showed no signs of damage. In year two two larger diameter (3") etalons were constructed with gaps of 3 and 5 microns. This pair of etalons is for use in a high resolution, all-sky spectral imager. The WATUMI imager system follows the heritage of all sky, narrow band, intensified imagers however it includes two LC Fabry-Perot etalons to provide tunability and the ability to switch wavelengths rapidly, an import consideration in auroral airglow imaging. This work also resulted in two publications and one poster presentation. The instrument will be uniquely capable, with superior throughput and speed, to measure optical airglow of multiple emission lines in harsh conditions.

High Throughput Multispectral Image Processing with Applications in Food Science.

PubMed

Tsakanikas, Panagiotis; Pavlidis, Dimitris; Nychas, George-John

2015-01-01

Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

High performance computing environment for multidimensional image analysis

PubMed Central

Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

2007-01-01

Background The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. Results We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478× speedup. Conclusion Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets. PMID:17634099

High performance computing environment for multidimensional image analysis.

PubMed

Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

2007-07-10

The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478x speedup. Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets.

Development of a diffraction imaging flow cytometer

PubMed Central

Jacobs, Kenneth M.; Lu, Jun Q.

2013-01-01

Diffraction images record angle-resolved distribution of scattered light from a particle excited by coherent light and can correlate highly with the 3D morphology of a particle. We present a jet-in-fluid design of flow chamber for acquisition of clear diffraction images in a laminar flow. Diffraction images of polystyrene spheres of different diameters were acquired and found to correlate highly with the calculated ones based on the Mie theory. Fast Fourier transform analysis indicated that the measured images can be used to extract sphere diameter values. These results demonstrate the significant potentials of high-throughput diffraction imaging flow cytometry for extracting 3D morphological features of cells. PMID:19794790

Uninterrupted monitoring of drug effects in human-induced pluripotent stem cell-derived cardiomyocytes with bioluminescence Ca2+ microscopy.

PubMed

Suzuki, Kazushi; Onishi, Takahito; Nakada, Chieko; Takei, Shunsuke; Daniels, Matthew J; Nakano, Masahiro; Matsuda, Tomoki; Nagai, Takeharu

2018-05-18

Cardiomyocytes derived from human-induced pluripotent stem cells are a powerful platform for high-throughput drug screening in vitro. However, current modalities for drug testing, such as electrophysiology and fluorescence imaging have inherent drawbacks. To circumvent these problems, we report the development of a bioluminescent Ca 2+ indicator GmNL(Ca 2+ ), and its application in a customized microscope for high-throughput drug screening. GmNL(Ca 2+ ) gives a 140% signal change with Ca 2+ , and can image drug-induced changes of Ca 2+ dynamics in cultured cells. Since bioluminescence requires application of a chemical substrate, which is consumed over ~ 30 min we made a dedicated microscope with automated drug dispensing inside a light-tight box, to control drug addition. To overcome thermal instability of the luminescent substrate, or small molecule, dual climate control enables distinct temperature settings in the drug reservoir and the biological sample. By combining GmNL(Ca 2+ ) with this adaptation, we could image spontaneous Ca 2+ transients in cultured cardiomyocytes and phenotype their response to well-known drugs without accessing the sample directly. In addition, the bioluminescent strategy demonstrates minimal perturbation of contractile parameters and long-term observation attributable to lack of phototoxicity and photobleaching. Overall, bioluminescence may enable more accurate drug screening in a high-throughput manner.

Interleaved diffusion-weighted EPI improved by adaptive partial-Fourier and multi-band multiplexed sensitivity-encoding reconstruction

PubMed Central

Chang, Hing-Chiu; Guhaniyogi, Shayan; Chen, Nan-kuei

2014-01-01

Purpose We report a series of techniques to reliably eliminate artifacts in interleaved echo-planar imaging (EPI) based diffusion weighted imaging (DWI). Methods First, we integrate the previously reported multiplexed sensitivity encoding (MUSE) algorithm with a new adaptive Homodyne partial-Fourier reconstruction algorithm, so that images reconstructed from interleaved partial-Fourier DWI data are free from artifacts even in the presence of either a) motion-induced k-space energy peak displacement, or b) susceptibility field gradient induced fast phase changes. Second, we generalize the previously reported single-band MUSE framework to multi-band MUSE, so that both through-plane and in-plane aliasing artifacts in multi-band multi-shot interleaved DWI data can be effectively eliminated. Results The new adaptive Homodyne-MUSE reconstruction algorithm reliably produces high-quality and high-resolution DWI, eliminating residual artifacts in images reconstructed with previously reported methods. Furthermore, the generalized MUSE algorithm is compatible with multi-band and high-throughput DWI. Conclusion The integration of the multi-band and adaptive Homodyne-MUSE algorithms significantly improves the spatial-resolution, image quality, and scan throughput of interleaved DWI. We expect that the reported reconstruction framework will play an important role in enabling high-resolution DWI for both neuroscience research and clinical uses. PMID:24925000

External optical imaging of freely moving mice with green fluorescent protein-expressing metastatic tumors

NASA Astrophysics Data System (ADS)

Yang, Meng; Baranov, Eugene; Shimada, Hiroshi; Moossa, A. R.; Hoffman, Robert M.

2000-04-01

We report here a new approach to genetically engineering tumors to become fluorescence such that they can be imaged externally in freely-moving animals. We describe here external high-resolution real-time fluorescent optical imaging of metastatic tumors in live mice. Stable high-level green flourescent protein (GFP)-expressing human and rodent cell lines enable tumors and metastasis is formed from them to be externally imaged from freely-moving mice. Real-time tumor and metastatic growth were quantitated from whole-body real-time imaging in GFP-expressing melanoma and colon carcinoma models. This GFP optical imaging system is highly appropriate for high throughput in vivo drug screening.

Dissecting the Phenotypic Components of Crop Plant Growth and Drought Responses Based on High-Throughput Image Analysis[W][OPEN

PubMed Central

Chen, Dijun; Neumann, Kerstin; Friedel, Swetlana; Kilian, Benjamin; Chen, Ming; Altmann, Thomas; Klukas, Christian

2014-01-01

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues. PMID:25501589

Rapid identification of salmonella serotypes with stereo and hyperspectral microscope imaging Methods

USDA-ARS?s Scientific Manuscript database

The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

Rapid Identification of Salmonella Serotypes with Stereo and Hyperspectral Microscope Imaging Methods

USDA-ARS?s Scientific Manuscript database

The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

FIM, a Novel FTIR-Based Imaging Method for High Throughput Locomotion Analysis

PubMed Central

Otto, Nils; Löpmeier, Tim; Valkov, Dimitar; Jiang, Xiaoyi; Klämbt, Christian

2013-01-01

We designed a novel imaging technique based on frustrated total internal reflection (FTIR) to obtain high resolution and high contrast movies. This FTIR-based Imaging Method (FIM) is suitable for a wide range of biological applications and a wide range of organisms. It operates at all wavelengths permitting the in vivo detection of fluorescent proteins. To demonstrate the benefits of FIM, we analyzed large groups of crawling Drosophila larvae. The number of analyzable locomotion tracks was increased by implementing a new software module capable of preserving larval identity during most collision events. This module is integrated in our new tracking program named FIMTrack which subsequently extracts a number of features required for the analysis of complex locomotion phenotypes. FIM enables high throughput screening for even subtle behavioral phenotypes. We tested this newly developed setup by analyzing locomotion deficits caused by the glial knockdown of several genes. Suppression of kinesin heavy chain (khc) or rab30 function led to contraction pattern or head sweeping defects, which escaped in previous analysis. Thus, FIM permits forward genetic screens aimed to unravel the neural basis of behavior. PMID:23349775

Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.

PubMed

Sheik-Khalil, Enas; Bray, Mark-Anthony; Özkaya Şahin, Gülsen; Scarlatti, Gabriella; Jansson, Marianne; Carpenter, Anne E; Fenyö, Eva Maria

2014-08-30

Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.

A Fully Automated High-Throughput Zebrafish Behavioral Ototoxicity Assay.

PubMed

Todd, Douglas W; Philip, Rohit C; Niihori, Maki; Ringle, Ryan A; Coyle, Kelsey R; Zehri, Sobia F; Zabala, Leanne; Mudery, Jordan A; Francis, Ross H; Rodriguez, Jeffrey J; Jacob, Abraham

2017-08-01

Zebrafish animal models lend themselves to behavioral assays that can facilitate rapid screening of ototoxic, otoprotective, and otoregenerative drugs. Structurally similar to human inner ear hair cells, the mechanosensory hair cells on their lateral line allow the zebrafish to sense water flow and orient head-to-current in a behavior called rheotaxis. This rheotaxis behavior deteriorates in a dose-dependent manner with increased exposure to the ototoxin cisplatin, thereby establishing itself as an excellent biomarker for anatomic damage to lateral line hair cells. Building on work by our group and others, we have built a new, fully automated high-throughput behavioral assay system that uses automated image analysis techniques to quantify rheotaxis behavior. This novel system consists of a custom-designed swimming apparatus and imaging system consisting of network-controlled Raspberry Pi microcomputers capturing infrared video. Automated analysis techniques detect individual zebrafish, compute their orientation, and quantify the rheotaxis behavior of a zebrafish test population, producing a powerful, high-throughput behavioral assay. Using our fully automated biological assay to test a standardized ototoxic dose of cisplatin against varying doses of compounds that protect or regenerate hair cells may facilitate rapid translation of candidate drugs into preclinical mammalian models of hearing loss.

Application Of Empirical Phase Diagrams For Multidimensional Data Visualization Of High Throughput Microbatch Crystallization Experiments.

PubMed

Klijn, Marieke E; Hubbuch, Jürgen

2018-04-27

Protein phase diagrams are a tool to investigate cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphological features, such as crystal size, as well as kinetic features, such as crystal growth time. Common used data visualization techniques include individual line graphs or symbols-based phase diagrams. These techniques have limitations in terms of handling large datasets, comprehensiveness or completeness. To eliminate these limitations, morphological and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram (EPD) method. Morphological features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the EPD method can support high throughput crystallization experiments in its data amount as well as its data complexity. Copyright © 2018. Published by Elsevier Inc.

High-Throughput In Vivo Genotoxicity Testing: An Automated Readout System for the Somatic Mutation and Recombination Test (SMART)

PubMed Central

Kwak, Jihoon; Genovesio, Auguste; Kang, Myungjoo; Hansen, Michael Adsett Edberg; Han, Sung-Jun

2015-01-01

Genotoxicity testing is an important component of toxicity assessment. As illustrated by the European registration, evaluation, authorization, and restriction of chemicals (REACH) directive, it concerns all the chemicals used in industry. The commonly used in vivo mammalian tests appear to be ill adapted to tackle the large compound sets involved, due to throughput, cost, and ethical issues. The somatic mutation and recombination test (SMART) represents a more scalable alternative, since it uses Drosophila, which develops faster and requires less infrastructure. Despite these advantages, the manual scoring of the hairs on Drosophila wings required for the SMART limits its usage. To overcome this limitation, we have developed an automated SMART readout. It consists of automated imaging, followed by an image analysis pipeline that measures individual wing genotoxicity scores. Finally, we have developed a wing score-based dose-dependency approach that can provide genotoxicity profiles. We have validated our method using 6 compounds, obtaining profiles almost identical to those obtained from manual measures, even for low-genotoxicity compounds such as urethane. The automated SMART, with its faster and more reliable readout, fulfills the need for a high-throughput in vivo test. The flexible imaging strategy we describe and the analysis tools we provide should facilitate the optimization and dissemination of our methods. PMID:25830368

Massively Parallel Rogue Cell Detection Using Serial Time-Encoded Amplified Microscopy of Inertially Ordered Cells in High-Throughput Flow

DTIC Science & Technology

2012-08-01

techniques and STEAM imager. It couples the high-speed capability of the STEAM imager and differential phase contrast imaging of DIC / Nomarski microscopy...On 10 TPE chips, we obtained 9 homogenous and strong bonds, the failed bond being due to operator error and presence of air bubbles in the TPE...instruments, structural dynamics, and microelectromechanical systems (MEMS) via laser-scanning surface vibrometry , and observation of biomechanical motility

High-throughput live-imaging of embryos in microwell arrays using a modular specimen mounting system.

PubMed

Donoughe, Seth; Kim, Chiyoung; Extavour, Cassandra G

2018-04-30

High-throughput live-imaging of embryos is an essential technique in developmental biology, but it is difficult and costly to mount and image embryos in consistent conditions. Here, we present OMMAwell, a simple, reusable device to easily mount dozens of embryos in arrays of agarose microwells with customizable dimensions and spacing. OMMAwell can be configured to mount specimens for upright or inverted microscopes, and includes a reservoir to hold live-imaging medium to maintain constant moisture and osmolarity of specimens during time-lapse imaging. All device components can be fabricated by cutting pieces from a sheet of acrylic using a laser cutter or by making them with a 3D printer. We demonstrate how to design a custom mold and use it to live-image dozens of embryos at a time. We include descriptions, schematics, and design files for 13 additional molds for nine animal species, including most major traditional laboratory models and a number of emerging model systems. Finally, we provide instructions for researchers to customize OMMAwell inserts for embryos or tissues not described herein. © 2018. Published by The Company of Biologists Ltd.

High content screening of ToxCast compounds using Vala Sciences’ complex cell culturing systems (SOT)

EPA Science Inventory

US EPA’s ToxCast research program evaluates bioactivity for thousands of chemicals utilizing high-throughput screening assays to inform chemical testing decisions. Vala Sciences provides high content, multiplexed assays that utilize quantitative cell-based digital image analysis....

High-throughput multiple-mouse imaging with micro-PET/CT for whole-skeleton assessment.

PubMed

Yagi, Masashi; Arentsen, Luke; Shanley, Ryan M; Hui, Susanta K

2014-11-01

Recent studies have proven that skeleton-wide functional assessment is essential to comprehensively understand physiological aspects of the skeletal system. Therefore, in contrast to regional imaging studies utilizing a multiple-animal holder (mouse hotel), we attempted to develop and characterize a multiple-mouse imaging system with micro-PET/CT for high-throughput whole-skeleton assessment. Using items found in a laboratory, a simple mouse hotel that houses four mice linked with gas anesthesia was constructed. A mouse-simulating phantom was used to measure uniformity in a cross sectional area and flatness (Amax/Amin*100) along the axial, radial and tangential directions, where Amax and Amin are maximum and minimum activity concentration in the profile, respectively. Fourteen mice were used for single- or multiple-micro-PET/CT scans. NaF uptake was measured at eight skeletal sites (skull to tibia). Skeletal (18)F activities measured with mice in the mouse hotel were within 1.6 ± 4% (mean ± standard deviation) of those measured with mice in the single-mouse holder. Single-holder scanning yields slightly better uniformity and flatness over the hotel. Compared to use of the single-mouse holder, scanning with the mouse hotel reduced study time (by 65%), decreased the number of scans (four-fold), reduced cost, required less computer storage space (40%), and maximized (18)F usage. The mouse hotel allows high-throughput, quantitatively equivalent scanning compared to the single-mouse holder for micro-PET/CT imaging for whole-skeleton assessment of mice. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

The Portable Remote Imaging Spectrometer (PRISM) Coastal Ocean Sensor

NASA Technical Reports Server (NTRS)

Mouroulis, Pantazis; VanGorp, Byron E.; Green, Robert O.; Eastwppd, Michael; Wilson, Daniel W.; Richardson, Brandon; Dierssen, Heidi

2012-01-01

PRISM is an airborne pushbroom imaging spectrometer intended to address the needs of airborne coastal ocean science research. Its critical characteristics are high throughput and signal-to-noise ratio, high uniformity of response to reduce spectral artifacts, and low polarization sensitivity. We give a brief overview of the instrument and results from laboratory calibration measurements regarding the spatial, spectral, radiometric and polarization characteristics.

Fast Infrared Chemical Imaging with a Quantum Cascade Laser

PubMed Central

2015-01-01

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm–1) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues. PMID:25474546

Fast infrared chemical imaging with a quantum cascade laser.

PubMed

Yeh, Kevin; Kenkel, Seth; Liu, Jui-Nung; Bhargava, Rohit

2015-01-06

Infrared (IR) spectroscopic imaging systems are a powerful tool for visualizing molecular microstructure of a sample without the need for dyes or stains. Table-top Fourier transform infrared (FT-IR) imaging spectrometers, the current established technology, can record broadband spectral data efficiently but requires scanning the entire spectrum with a low throughput source. The advent of high-intensity, broadly tunable quantum cascade lasers (QCL) has now accelerated IR imaging but results in a fundamentally different type of instrument and approach, namely, discrete frequency IR (DF-IR) spectral imaging. While the higher intensity of the source provides a higher signal per channel, the absence of spectral multiplexing also provides new opportunities and challenges. Here, we couple a rapidly tunable QCL with a high performance microscope equipped with a cooled focal plane array (FPA) detector. Our optical system is conceptualized to provide optimal performance based on recent theory and design rules for high-definition (HD) IR imaging. Multiple QCL units are multiplexed together to provide spectral coverage across the fingerprint region (776.9 to 1904.4 cm(-1)) in our DF-IR microscope capable of broad spectral coverage, wide-field detection, and diffraction-limited spectral imaging. We demonstrate that the spectral and spatial fidelity of this system is at least as good as the best FT-IR imaging systems. Our configuration provides a speedup for equivalent spectral signal-to-noise ratio (SNR) compared to the best spectral quality from a high-performance linear array system that has 10-fold larger pixels. Compared to the fastest available HD FT-IR imaging system, we demonstrate scanning of large tissue microarrays (TMA) in 3-orders of magnitude smaller time per essential spectral frequency. These advances offer new opportunities for high throughput IR chemical imaging, especially for the measurement of cells and tissues.

Integrating medical imaging analyses through a high-throughput bundled resource imaging system

NASA Astrophysics Data System (ADS)

Covington, Kelsie; Welch, E. Brian; Jeong, Ha-Kyu; Landman, Bennett A.

2011-03-01

Exploitation of advanced, PACS-centric image analysis and interpretation pipelines provides well-developed storage, retrieval, and archival capabilities along with state-of-the-art data providence, visualization, and clinical collaboration technologies. However, pursuit of integrated medical imaging analysis through a PACS environment can be limiting in terms of the overhead required to validate, evaluate and integrate emerging research technologies. Herein, we address this challenge through presentation of a high-throughput bundled resource imaging system (HUBRIS) as an extension to the Philips Research Imaging Development Environment (PRIDE). HUBRIS enables PACS-connected medical imaging equipment to invoke tools provided by the Java Imaging Science Toolkit (JIST) so that a medical imaging platform (e.g., a magnetic resonance imaging scanner) can pass images and parameters to a server, which communicates with a grid computing facility to invoke the selected algorithms. Generated images are passed back to the server and subsequently to the imaging platform from which the images can be sent to a PACS. JIST makes use of an open application program interface layer so that research technologies can be implemented in any language capable of communicating through a system shell environment (e.g., Matlab, Java, C/C++, Perl, LISP, etc.). As demonstrated in this proof-of-concept approach, HUBRIS enables evaluation and analysis of emerging technologies within well-developed PACS systems with minimal adaptation of research software, which simplifies evaluation of new technologies in clinical research and provides a more convenient use of PACS technology by imaging scientists.

Optimization of wide-area ATM and local-area ethernet/FDDI network configurations for high-speed telemedicine communications employing NASA's ACTS.

PubMed

McDermott, W R; Tri, J L; Mitchell, M P; Levens, S P; Wondrow, M A; Huie, L M; Khandheria, B K; Gilbert, B K

1999-01-01

A high data rate terrestrial and satellite network was implemented to transfer medical images and data. This article describes the a optimization of the workstations and switching equipment incorporated into the network. Topics discussed in this article include tuning of the network software, the configuration of the Sun Microsystems workstations, the FORE Systems asynchronous transfer mode switches, as well as the throughput results of two telemedicine experiments undertaken by Mayo's physician staff. The technical staff was successful in achieving the data throughput needed by the telemedicine software; particularly important was the proper determination of peak throughput and TCP window sizes to ensure optimum use of the resources available on the Sun Microsystems and Hewlett Packard workstations.

High-throughput measurement of rice tillers using a conveyor equipped with x-ray computed tomography

NASA Astrophysics Data System (ADS)

Yang, Wanneng; Xu, Xiaochun; Duan, Lingfeng; Luo, Qingming; Chen, Shangbin; Zeng, Shaoqun; Liu, Qian

2011-02-01

Tillering is one of the most important agronomic traits because the number of shoots per plant determines panicle number, a key component of grain yield. The conventional method of counting tillers is still manual. Under the condition of mass measurement, the accuracy and efficiency could be gradually degraded along with fatigue of experienced staff. Thus, manual measurement, including counting and recording, is not only time consuming but also lack objectivity. To automate this process, we developed a high-throughput facility, dubbed high-throughput system for measuring automatically rice tillers (H-SMART), for measuring rice tillers based on a conventional x-ray computed tomography (CT) system and industrial conveyor. Each pot-grown rice plant was delivered into the CT system for scanning via the conveyor equipment. A filtered back-projection algorithm was used to reconstruct the transverse section image of the rice culms. The number of tillers was then automatically extracted by image segmentation. To evaluate the accuracy of this system, three batches of rice at different growth stages (tillering, heading, or filling) were tested, yielding absolute mean absolute errors of 0.22, 0.36, and 0.36, respectively. Subsequently, the complete machine was used under industry conditions to estimate its efficiency, which was 4320 pots per continuous 24 h workday. Thus, the H-SMART could determine the number of tillers of pot-grown rice plants, providing three advantages over the manual tillering method: absence of human disturbance, automation, and high throughput. This facility expands the application of agricultural photonics in plant phenomics.

High-throughput measurement of rice tillers using a conveyor equipped with x-ray computed tomography.

PubMed

Yang, Wanneng; Xu, Xiaochun; Duan, Lingfeng; Luo, Qingming; Chen, Shangbin; Zeng, Shaoqun; Liu, Qian

2011-02-01

Tillering is one of the most important agronomic traits because the number of shoots per plant determines panicle number, a key component of grain yield. The conventional method of counting tillers is still manual. Under the condition of mass measurement, the accuracy and efficiency could be gradually degraded along with fatigue of experienced staff. Thus, manual measurement, including counting and recording, is not only time consuming but also lack objectivity. To automate this process, we developed a high-throughput facility, dubbed high-throughput system for measuring automatically rice tillers (H-SMART), for measuring rice tillers based on a conventional x-ray computed tomography (CT) system and industrial conveyor. Each pot-grown rice plant was delivered into the CT system for scanning via the conveyor equipment. A filtered back-projection algorithm was used to reconstruct the transverse section image of the rice culms. The number of tillers was then automatically extracted by image segmentation. To evaluate the accuracy of this system, three batches of rice at different growth stages (tillering, heading, or filling) were tested, yielding absolute mean absolute errors of 0.22, 0.36, and 0.36, respectively. Subsequently, the complete machine was used under industry conditions to estimate its efficiency, which was 4320 pots per continuous 24 h workday. Thus, the H-SMART could determine the number of tillers of pot-grown rice plants, providing three advantages over the manual tillering method: absence of human disturbance, automation, and high throughput. This facility expands the application of agricultural photonics in plant phenomics.

A space- and time-resolved single photon counting detector for fluorescence microscopy and spectroscopy

PubMed Central

Michalet, X.; Siegmund, O.H.W.; Vallerga, J.V.; Jelinsky, P.; Millaud, J.E.; Weiss, S.

2017-01-01

We have recently developed a wide-field photon-counting detector having high-temporal and high-spatial resolutions and capable of high-throughput (the H33D detector). Its design is based on a 25 mm diameter multi-alkali photocathode producing one photo electron per detected photon, which are then multiplied up to 107 times by a 3-microchannel plate stack. The resulting electron cloud is proximity focused on a cross delay line anode, which allows determining the incident photon position with high accuracy. The imaging and fluorescence lifetime measurement performances of the H33D detector installed on a standard epifluorescence microscope will be presented. We compare them to those of standard single-molecule detectors such as single-photon avalanche photodiode (SPAD) or electron-multiplying camera using model samples (fluorescent beads, quantum dots and live cells). Finally, we discuss the design and applications of future generation of H33D detectors for single-molecule imaging and high-throughput study of biomolecular interactions. PMID:29479130

Synthetic Biomaterials to Rival Nature's Complexity-a Path Forward with Combinatorics, High-Throughput Discovery, and High-Content Analysis.

PubMed

Zhang, Douglas; Lee, Junmin; Kilian, Kristopher A

2017-10-01

Cells in tissue receive a host of soluble and insoluble signals in a context-dependent fashion, where integration of these cues through a complex network of signal transduction cascades will define a particular outcome. Biomaterials scientists and engineers are tasked with designing materials that can at least partially recreate this complex signaling milieu towards new materials for biomedical applications. In this progress report, recent advances in high throughput techniques and high content imaging approaches that are facilitating the discovery of efficacious biomaterials are described. From microarrays of synthetic polymers, peptides and full-length proteins, to designer cell culture systems that present multiple biophysical and biochemical cues in tandem, it is discussed how the integration of combinatorics with high content imaging and analysis is essential to extracting biologically meaningful information from large scale cellular screens to inform the design of next generation biomaterials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High Throughput, High Yield Fabrication of High Quantum Efficiency Back-Illuminated Photon Counting, Far UV, UV, and Visible Detector Arrays

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh; Hoenk, M. E.; Carver, A. G.; Jones, T. J.; Greer, F.; Hamden, E.; Goodsall, T.

2013-01-01

In this paper we discuss the high throughput end-to-end post fabrication processing of high performance delta-doped and superlattice-doped silicon imagers for UV, visible, and NIR applications. As an example, we present our results on far ultraviolet and ultraviolet quantum efficiency (QE) in a photon counting, detector array. We have improved the QE by nearly an order of magnitude over microchannel plates (MCPs) that are the state-of-the-art UV detectors for many NASA space missions as well as defense applications. These achievements are made possible by precision interface band engineering of Molecular Beam Epitaxy (MBE) and Atomic Layer Deposition (ALD).

Machine vision for digital microfluidics

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun; Lee, Jeong-Bong

2010-01-01

Machine vision is widely used in an industrial environment today. It can perform various tasks, such as inspecting and controlling production processes, that may require humanlike intelligence. The importance of imaging technology for biological research or medical diagnosis is greater than ever. For example, fluorescent reporter imaging enables scientists to study the dynamics of gene networks with high spatial and temporal resolution. Such high-throughput imaging is increasingly demanding the use of machine vision for real-time analysis and control. Digital microfluidics is a relatively new technology with expectations of becoming a true lab-on-a-chip platform. Utilizing digital microfluidics, only small amounts of biological samples are required and the experimental procedures can be automatically controlled. There is a strong need for the development of a digital microfluidics system integrated with machine vision for innovative biological research today. In this paper, we show how machine vision can be applied to digital microfluidics by demonstrating two applications: machine vision-based measurement of the kinetics of biomolecular interactions and machine vision-based droplet motion control. It is expected that digital microfluidics-based machine vision system will add intelligence and automation to high-throughput biological imaging in the future.

High throughput phenotyping of tomato spotted wilt disease in peanuts using unmanned aerial systems and multispectral imaging

USDA-ARS?s Scientific Manuscript database

The amount of visible and near infrared light reflected by plants varies depending on their health. In this study, multispectral images were acquired by quadcopter for detecting tomato spot wilt virus amongst twenty genetic varieties of peanuts. The plants were visually assessed to acquire ground ...

Advances in single-cell experimental design made possible by automated imaging platforms with feedback through segmentation.

PubMed

Crick, Alex J; Cammarota, Eugenia; Moulang, Katie; Kotar, Jurij; Cicuta, Pietro

2015-01-01

Live optical microscopy has become an essential tool for studying the dynamical behaviors and variability of single cells, and cell-cell interactions. However, experiments and data analysis in this area are often extremely labor intensive, and it has often not been achievable or practical to perform properly standardized experiments on a statistically viable scale. We have addressed this challenge by developing automated live imaging platforms, to help standardize experiments, increasing throughput, and unlocking previously impossible ones. Our real-time cell tracking programs communicate in feedback with microscope and camera control software, and they are highly customizable, flexible, and efficient. As examples of our current research which utilize these automated platforms, we describe two quite different applications: egress-invasion interactions of malaria parasites and red blood cells, and imaging of immune cells which possess high motility and internal dynamics. The automated imaging platforms are able to track a large number of motile cells simultaneously, over hours or even days at a time, greatly increasing data throughput and opening up new experimental possibilities. Copyright © 2015 Elsevier Inc. All rights reserved.

Intellicount: High-Throughput Quantification of Fluorescent Synaptic Protein Puncta by Machine Learning

PubMed Central

Fantuzzo, J. A.; Mirabella, V. R.; Zahn, J. D.

2017-01-01

Abstract Synapse formation analyses can be performed by imaging and quantifying fluorescent signals of synaptic markers. Traditionally, these analyses are done using simple or multiple thresholding and segmentation approaches or by labor-intensive manual analysis by a human observer. Here, we describe Intellicount, a high-throughput, fully-automated synapse quantification program which applies a novel machine learning (ML)-based image processing algorithm to systematically improve region of interest (ROI) identification over simple thresholding techniques. Through processing large datasets from both human and mouse neurons, we demonstrate that this approach allows image processing to proceed independently of carefully set thresholds, thus reducing the need for human intervention. As a result, this method can efficiently and accurately process large image datasets with minimal interaction by the experimenter, making it less prone to bias and less liable to human error. Furthermore, Intellicount is integrated into an intuitive graphical user interface (GUI) that provides a set of valuable features, including automated and multifunctional figure generation, routine statistical analyses, and the ability to run full datasets through nested folders, greatly expediting the data analysis process. PMID:29218324

High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level

PubMed Central

Gong, Hui; Xu, Dongli; Yuan, Jing; Li, Xiangning; Guo, Congdi; Peng, Jie; Li, Yuxin; Schwarz, Lindsay A.; Li, Anan; Hu, Bihe; Xiong, Benyi; Sun, Qingtao; Zhang, Yalun; Liu, Jiepeng; Zhong, Qiuyuan; Xu, Tonghui; Zeng, Shaoqun; Luo, Qingming

2016-01-01

The precise annotation and accurate identification of neural structures are prerequisites for studying mammalian brain function. The orientation of neurons and neural circuits is usually determined by mapping brain images to coarse axial-sampling planar reference atlases. However, individual differences at the cellular level likely lead to position errors and an inability to orient neural projections at single-cell resolution. Here, we present a high-throughput precision imaging method that can acquire a co-localized brain-wide data set of both fluorescent-labelled neurons and counterstained cell bodies at a voxel size of 0.32 × 0.32 × 2.0 μm in 3 days for a single mouse brain. We acquire mouse whole-brain imaging data sets of multiple types of neurons and projections with anatomical annotation at single-neuron resolution. The results show that the simultaneous acquisition of labelled neural structures and cytoarchitecture reference in the same brain greatly facilitates precise tracing of long-range projections and accurate locating of nuclei. PMID:27374071

An Image-Based Algorithm for Precise and Accurate High Throughput Assessment of Drug Activity against the Human Parasite Trypanosoma cruzi

PubMed Central

Moraes, Carolina Borsoi; Yang, Gyongseon; Kang, Myungjoo; Freitas-Junior, Lucio H.; Hansen, Michael A. E.

2014-01-01

We present a customized high content (image-based) and high throughput screening algorithm for the quantification of Trypanosoma cruzi infection in host cells. Based solely on DNA staining and single-channel images, the algorithm precisely segments and identifies the nuclei and cytoplasm of mammalian host cells as well as the intracellular parasites infecting the cells. The algorithm outputs statistical parameters including the total number of cells, number of infected cells and the total number of parasites per image, the average number of parasites per infected cell, and the infection ratio (defined as the number of infected cells divided by the total number of cells). Accurate and precise estimation of these parameters allow for both quantification of compound activity against parasites, as well as the compound cytotoxicity, thus eliminating the need for an additional toxicity-assay, hereby reducing screening costs significantly. We validate the performance of the algorithm using two known drugs against T.cruzi: Benznidazole and Nifurtimox. Also, we have checked the performance of the cell detection with manual inspection of the images. Finally, from the titration of the two compounds, we confirm that the algorithm provides the expected half maximal effective concentration (EC50) of the anti-T. cruzi activity. PMID:24503652

High Throughput Screening Identifies Novel Lead Compounds with Activity against Larval, Juvenile and Adult Schistosoma mansoni

PubMed Central

Gardner, J. Mark F.; Bell, Andrew S.; Parkinson, Tanya; Bickle, Quentin

2016-01-01

An estimated 600 million people are affected by the helminth disease schistosomiasis caused by parasites of the genus Schistosoma. There is currently only one drug recommended for treating schistosomiasis, praziquantel (PZQ), which is effective against adult worms but not against the juvenile stage. In an attempt to identify improved drugs for treating the disease, we have carried out high throughput screening of a number of small molecule libraries with the aim of identifying lead compounds with balanced activity against all life stages of Schistosoma. A total of almost 300,000 compounds were screened using a high throughput assay based on motility of worm larvae and image analysis of assay plates. Hits were screened against juvenile and adult worms to identify broadly active compounds and against a mammalian cell line to assess cytotoxicity. A number of compounds were identified as promising leads for further chemical optimization. PMID:27128493

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

PubMed

Ching, Travers; Zhu, Xun; Garmire, Lana X

2018-04-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

High-throughput microscopy must re-invent the microscope rather than speed up its functions

PubMed Central

Oheim, M

2007-01-01

Knowledge gained from the revolutions in genomics and proteomics has helped to identify many of the key molecules involved in cellular signalling. Researchers, both in academia and in the pharmaceutical industry, now screen, at a sub-cellular level, where and when these proteins interact. Fluorescence imaging and molecular labelling combine to provide a powerful tool for real-time functional biochemistry with molecular resolution. However, they traditionally have been work-intensive, required trained personnel, and suffered from low through-put due to sample preparation, loading and handling. The need for speeding up microscopy is apparent from the tremendous complexity of cellular signalling pathways, the inherent biological variability, as well as the possibility that the same molecule plays different roles in different sub-cellular compartments. Research institutes and companies have teamed up to develop imaging cytometers of ever-increasing complexity. However, to truly go high-speed, sub-cellular imaging must free itself from the rigid framework of current microscopes. PMID:17603553

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

Imaging flow cytometry for the screening of compounds that disrupt the Plasmodium falciparum digestive vacuole.

PubMed

Chia, Wan Ni; Lee, Yan Quan; Tan, Kevin Shyong-Wei

2017-01-01

Malaria, despite being one of the world's oldest infectious diseases, remains difficult to eradicate because the parasite is rapidly developing resistance to frontline chemotherapies. Previous studies have shown that the parasite exhibits features resembling programmed cell death upon treatment with drugs that disrupt its digestive vacuole (DV), providing a phenotypic readout that can be detected using the imaging flow cytometer. Large compound collections can thus be screened to identify drugs that are able to disrupt the DV of the malaria parasite using this high-content high-throughput screening platform. As a proof-of-concept, 4440 compounds were screened using this platform in 4months and 254 hits (5.7% hit rate) were obtained. Additionally, 25 compounds (0.6% top hit rate) were observed to retain potent DV disruption activity that was comparable to the canonical DV disruptive drug chloroquine when tested at a ten-fold lower concentration from the original screen. This pilot study demonstrates the robustness and high-throughput capability of the imaging flow cytometer and we report herein the methodology of this screening assay. Copyright © 2016 Elsevier Inc. All rights reserved.

A Dedicated Micro-Tomography Beamline For The Australian Synchrotron

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayo, Sheridan C.; Stevenson, Andrew W.; Wilkins, Stephen W.

2010-07-23

A dedicated micro-tomography beamline is proposed for the Australian Synchrotron. It will enable high-resolution micro-tomography with resolution below a micron and supporting phase-contrast imaging modes. A key feature of the beamline will be high-throughput/high-speed operation enabling near real-time micro-tomography.

Transfer, Imaging, and Analysis Plate for Facile Handling of 384 Hanging Drop 3D Tissue Spheroids

PubMed Central

Cavnar, Stephen P.; Salomonsson, Emma; Luker, Kathryn E.; Luker, Gary D.; Takayama, Shuichi

2014-01-01

Three-dimensional culture systems bridge the experimental gap between in vivo and in vitro physiology. However, nonstandardized formation and limited downstream adaptability of 3D cultures have hindered mainstream adoption of these systems for biological applications, especially for low- and moderate-throughput assays commonly used in biomedical research. Here we build on our recent development of a 384-well hanging drop plate for spheroid culture to design a complementary spheroid transfer and imaging (TRIM) plate. The low-aspect ratio wells of the TRIM plate facilitated highfidelity, user-independent, contact-based collection of hanging drop spheroids. Using the TRIM plate, we demonstrated several downstream analyses, including bulk tissue collection for flow cytometry, high-resolution low working-distance immersion imaging, and timely reagent delivery for enzymatic studies. Low working-distance multiphoton imaging revealed a cell type–dependent, macroscopic spheroid structure. Unlike ovarian cancer spheroids, which formed loose, disk-shaped spheroids, human mammary fibroblasts formed tight, spherical, and nutrient-limited spheroids. Beyond the applications we describe here, we expect the hanging drop spheroid plate and complementary TRIM plate to facilitate analyses of spheroids across the spectrum of throughput, particularly for bulk collection of spheroids and high-content imaging. PMID:24051516

High throughput analysis of samples in flowing liquid

DOEpatents

Ambrose, W. Patrick; Grace, W. Kevin; Goodwin, Peter M.; Jett, James H.; Orden, Alan Van; Keller, Richard A.

2001-01-01

Apparatus and method enable imaging multiple fluorescent sample particles in a single flow channel. A flow channel defines a flow direction for samples in a flow stream and has a viewing plane perpendicular to the flow direction. A laser beam is formed as a ribbon having a width effective to cover the viewing plane. Imaging optics are arranged to view the viewing plane to form an image of the fluorescent sample particles in the flow stream, and a camera records the image formed by the imaging optics.

Coherent imaging at the diffraction limit

PubMed Central

Thibault, Pierre; Guizar-Sicairos, Manuel; Menzel, Andreas

2014-01-01

X-ray ptychography, a scanning coherent diffractive imaging technique, holds promise for imaging with dose-limited resolution and sensitivity. If the foreseen increase of coherent flux by orders of magnitude can be matched by additional technological and analytical advances, ptychography may approach imaging speeds familiar from full-field methods while retaining its inherently quantitative nature and metrological versatility. Beyond promises of high throughput, spectroscopic applications in three dimensions become feasible, as do measurements of sample dynamics through time-resolved imaging or careful characterization of decoherence effects. PMID:25177990

Coherent imaging at the diffraction limit.

PubMed

Thibault, Pierre; Guizar-Sicairos, Manuel; Menzel, Andreas

2014-09-01

X-ray ptychography, a scanning coherent diffractive imaging technique, holds promise for imaging with dose-limited resolution and sensitivity. If the foreseen increase of coherent flux by orders of magnitude can be matched by additional technological and analytical advances, ptychography may approach imaging speeds familiar from full-field methods while retaining its inherently quantitative nature and metrological versatility. Beyond promises of high throughput, spectroscopic applications in three dimensions become feasible, as do measurements of sample dynamics through time-resolved imaging or careful characterization of decoherence effects.

Evaluating chemical safety: ToxCast, Tipping Points and Virtual Tissues (Tamburro Symposium)

EPA Science Inventory

This presentation provides an overview of high-throughput toxicology at the NCCT using high-content imaging and computational models for analyzing chemical safety. In In particular, this work outlines the derivation of toxicological "tipping points" from in vitro concentration- a...

Non-Gaussian Distribution of DNA Barcode Extension In Nanochannels Using High-throughput Imaging

NASA Astrophysics Data System (ADS)

Sheats, Julian; Reinhart, Wesley; Reifenberger, Jeff; Gupta, Damini; Muralidhar, Abhiram; Cao, Han; Dorfman, Kevin

2015-03-01

We present experimental data for the extension of internal segments of highly confined DNA using a high-­throughput experimental setup. Barcode­-labeled E. coli genomic DNA molecules were imaged at a high areal density in square nanochannels with sizes ranging from 40 nm to 51 nm in width. Over 25,000 molecules were used to obtain more than 1,000,000 measurements for genomic distances between 2,500 bp and 100,000 bp. The distribution of extensions has positive excess kurtosis and is skew­ left due to weak backfolding in the channel. As a result, the two Odijk theories for the chain extension and variance bracket the experimental data. We compared to predictions of a harmonic approximation for the confinement free energy and show that it produces a substantial error in the variance. These results suggest an inherent error associated with any statistical analysis of barcoded DNA that relies on harmonic models for chain extension. Present address: Department of Chemical and Biological Engineering, Princeton University.

Acquisition of gamma camera and physiological data by computer.

PubMed

Hack, S N; Chang, M; Line, B R; Cooper, J A; Robeson, G H

1986-11-01

We have designed, implemented, and tested a new Research Data Acquisition System (RDAS) that permits a general purpose digital computer to acquire signals from both gamma camera sources and physiological signal sources concurrently. This system overcomes the limited multi-source, high speed data acquisition capabilities found in most clinically oriented nuclear medicine computers. The RDAS can simultaneously input signals from up to four gamma camera sources with a throughput of 200 kHz per source and from up to eight physiological signal sources with an aggregate throughput of 50 kHz. Rigorous testing has found the RDAS to exhibit acceptable linearity and timing characteristics. In addition, flood images obtained by this system were compared with flood images acquired by a commercial nuclear medicine computer system. National Electrical Manufacturers Association performance standards of the flood images were found to be comparable.

A high throughput array microscope for the mechanical characterization of biomaterials

NASA Astrophysics Data System (ADS)

Cribb, Jeremy; Osborne, Lukas D.; Hsiao, Joe Ping-Lin; Vicci, Leandra; Meshram, Alok; O'Brien, E. Tim; Spero, Richard Chasen; Taylor, Russell; Superfine, Richard

2015-02-01

In the last decade, the emergence of high throughput screening has enabled the development of novel drug therapies and elucidated many complex cellular processes. Concurrently, the mechanobiology community has developed tools and methods to show that the dysregulation of biophysical properties and the biochemical mechanisms controlling those properties contribute significantly to many human diseases. Despite these advances, a complete understanding of the connection between biomechanics and disease will require advances in instrumentation that enable parallelized, high throughput assays capable of probing complex signaling pathways, studying biology in physiologically relevant conditions, and capturing specimen and mechanical heterogeneity. Traditional biophysical instruments are unable to meet this need. To address the challenge of large-scale, parallelized biophysical measurements, we have developed an automated array high-throughput microscope system that utilizes passive microbead diffusion to characterize mechanical properties of biomaterials. The instrument is capable of acquiring data on twelve-channels simultaneously, where each channel in the system can independently drive two-channel fluorescence imaging at up to 50 frames per second. We employ this system to measure the concentration-dependent apparent viscosity of hyaluronan, an essential polymer found in connective tissue and whose expression has been implicated in cancer progression.

THE RABIT: A RAPID AUTOMATED BIODOSIMETRY TOOL FOR RADIOLOGICAL TRIAGE

PubMed Central

Garty, Guy; Chen, Youhua; Salerno, Alessio; Turner, Helen; Zhang, Jian; Lyulko, Oleksandra; Bertucci, Antonella; Xu, Yanping; Wang, Hongliang; Simaan, Nabil; Randers-Pehrson, Gerhard; Yao, Y. Lawrence; Amundson, Sally A.; Brenner, David J.

2010-01-01

In response to the recognized need for high throughput biodosimetry methods for use after large scale radiological events, a logical approach is complete automation of standard biodosimetric assays that are currently performed manually. We describe progress to date on the RABIT (Rapid Automated BIodosimetry Tool), designed to score micronuclei or γ-H2AX fluorescence in lymphocytes derived from a single drop of blood from a fingerstick. The RABIT system is designed to be completely automated, from the input of the capillary blood sample into the machine, to the output of a dose estimate. Improvements in throughput are achieved through use of a single drop of blood, optimization of the biological protocols for in-situ analysis in multi-well plates, implementation of robotic plate and liquid handling, and new developments in high-speed imaging. Automating well-established bioassays represents a promising approach to high-throughput radiation biodosimetry, both because high throughputs can be achieved, but also because the time to deployment is potentially much shorter than for a new biological assay. Here we describe the development of each of the individual modules of the RABIT system, and show preliminary data from key modules. Ongoing is system integration, followed by calibration and validation. PMID:20065685

The high throughput virtual slit enables compact, inexpensive Raman spectral imagers

NASA Astrophysics Data System (ADS)

Gooding, Edward; Deutsch, Erik R.; Huehnerhoff, Joseph; Hajian, Arsen R.

2018-02-01

Raman spectral imaging is increasingly becoming the tool of choice for field-based applications such as threat, narcotics and hazmat detection; air, soil and water quality monitoring; and material ID. Conventional fiber-coupled point source Raman spectrometers effectively interrogate a small sample area and identify bulk samples via spectral library matching. However, these devices are very slow at mapping over macroscopic areas. In addition, the spatial averaging performed by instruments that collect binned spectra, particularly when used in combination with orbital raster scanning, tends to dilute the spectra of trace particles in a mixture. Our design, employing free space line illumination combined with area imaging, reveals both the spectral and spatial content of heterogeneous mixtures. This approach is well suited to applications such as detecting explosives and narcotics trace particle detection in fingerprints. The patented High Throughput Virtual Slit1 is an innovative optical design that enables compact, inexpensive handheld Raman spectral imagers. HTVS-based instruments achieve significantly higher spectral resolution than can be obtained with conventional designs of the same size. Alternatively, they can be used to build instruments with comparable resolution to large spectrometers, but substantially smaller size, weight and unit cost, all while maintaining high sensitivity. When used in combination with laser line imaging, this design eliminates sample photobleaching and unwanted photochemistry while greatly enhancing mapping speed, all with high selectivity and sensitivity. We will present spectral image data and discuss applications that are made possible by low cost HTVS-enabled instruments.

A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos.

PubMed

Arbelle, Assaf; Reyes, Jose; Chen, Jia-Yun; Lahav, Galit; Riklin Raviv, Tammy

2018-04-22

We present a novel computational framework for the analysis of high-throughput microscopy videos of living cells. The proposed framework is generally useful and can be applied to different datasets acquired in a variety of laboratory settings. This is accomplished by tying together two fundamental aspects of cell lineage construction, namely cell segmentation and tracking, via a Bayesian inference of dynamic models. In contrast to most existing approaches, which aim to be general, no assumption of cell shape is made. Spatial, temporal, and cross-sectional variation of the analysed data are accommodated by two key contributions. First, time series analysis is exploited to estimate the temporal cell shape uncertainty in addition to cell trajectory. Second, a fast marching (FM) algorithm is used to integrate the inferred cell properties with the observed image measurements in order to obtain image likelihood for cell segmentation, and association. The proposed approach has been tested on eight different time-lapse microscopy data sets, some of which are high-throughput, demonstrating promising results for the detection, segmentation and association of planar cells. Our results surpass the state of the art for the Fluo-C2DL-MSC data set of the Cell Tracking Challenge (Maška et al., 2014). Copyright © 2018 Elsevier B.V. All rights reserved.

Development and evaluation of a novel high-throughput image-based fluorescent neutralization test for detection of Zika virus infection.

PubMed

Koishi, Andrea Cristine; Suzukawa, Andréia Akemi; Zanluca, Camila; Camacho, Daria Elena; Comach, Guillermo; Duarte Dos Santos, Claudia Nunes

2018-03-01

Zika virus (ZIKV) is an emerging arbovirus belonging to the genus flavivirus that comprises other important public health viruses, such as dengue (DENV) and yellow fever (YFV). In general, ZIKV infection is a self-limiting disease, however cases of Guillain-Barré syndrome and congenital brain abnormalities in newborn infants have been reported. Diagnosing ZIKV infection remains a challenge, as viral RNA detection is only applicable until a few days after the onset of symptoms. After that, serological tests must be applied, and, as expected, high cross-reactivity between ZIKV and other flavivirus serology is observed. Plaque reduction neutralization test (PRNT) is indicated to confirm positive samples for being more specific, however it is laborious intensive and time consuming, representing a major bottleneck for patient diagnosis. To overcome this limitation, we developed a high-throughput image-based fluorescent neutralization test for ZIKV infection by serological detection. Using 226 human specimens, we showed that the new test presented higher throughput than traditional PRNT, maintaining the correlation between results. Furthermore, when tested with dengue virus samples, it showed 50.53% less cross reactivity than MAC-ELISA. This fluorescent neutralization test could be used for clinical diagnosis confirmation of ZIKV infection, as well as for vaccine clinical trials and seroprevalence studies.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

On-chip ultraviolet holography for high-throughput nanoparticle and biomolecule detection

NASA Astrophysics Data System (ADS)

Daloglu, Mustafa Ugur; Ray, Aniruddha; Gorocs, Zoltán.; Xiong, Matthew; Malik, Ravinder; Bitan, Gal; McLeod, Euan; Ozcan, Aydogan

2018-02-01

Nanoparticle and biomolecule imaging has become an important need for various applications. In an effort to find a higher throughput alternative to existing devices, we have designed a lensfree on-chip holographic imaging platform operating at an ultraviolet (UV) wavelength of 266 nm. With a custom-designed free-space light delivery system to illuminate the sample that is placed very close (<0.5 mm) to an opto-electronic image sensor chip, without any imaging lenses in between, the full active area of the imager chip (>16 mm2 ) was utilized as the imaging field-of-view (FOV) capturing holographic signatures of target objects on a chip. These holograms were then digitally back propagated to extract both the amplitude and phase information of the sample. The increased forward scattering from nanoparticles due to this shorter illumination wavelength has enabled us to image individual particles that are smaller than 30 nm over an FOV of >16 mm2 . Our platform was further utilized in high-contrast imaging of nanoscopic biomolecule aggregates since 266 nm illumination light is strongly absorbed by biomolecules including proteins and nucleic acids. Aggregates of Cu/Zn-superoxide dismutase (SOD1), which has been linked to a fatal neurodegenerative disease, ALS (amyotrophic lateral sclerosis), have been imaged with significantly improved contrast compared to imaging at visible wavelengths. This unique UV imaging modality could be valuable for biomedical applications (e.g., viral load measurements) and environmental monitoring including air and water quality monitoring.

Dual-modality NIRF-MRI cubosomes and hexosomes: High throughput formulation and in vivo biodistribution.

PubMed

Tran, Nhiem; Bye, Nicole; Moffat, Bradford A; Wright, David K; Cuddihy, Andrew; Hinton, Tracey M; Hawley, Adrian M; Reynolds, Nicholas P; Waddington, Lynne J; Mulet, Xavier; Turnley, Ann M; Morganti-Kossmann, M Cristina; Muir, Benjamin W

2017-02-01

Engineered nanoparticles with multiple complementary imaging modalities are of great benefit to the rapid treatment and diagnosis of disease in various organs. Herein, we report the formulation of cubosomes and hexosomes that carry multiple amphiphilic imaging contrast agents in their self-assembled lipid bilayers. This is the first report of the use of both near infrared fluorescent (NIRF) imaging and gadolinium lipid based magnetic resonance (MR) imaging modalities in cubosomes and hexosomes. High-throughput screening was used to rapidly optimize formulations with desirable nano-architectures and low in vitro cytotoxicity. The dual-modal imaging nanoparticles in vivo biodistribution and organ specific contrast enhancement were then studied. The NIRF in vivo imaging results indicated accumulation of both cubosomes and hexosomes in the liver and spleen of mice up to 20h post-injection. Remarkably, the biodistribution of the nanoparticle formulations was affected by the mesophase (i.e. cubic or hexagonal), a finding of significant importance for the future use of these compounds, with hexosomes showing higher accumulation in the spleen than the liver compared to cubosomes. Furthermore, in vivo MRI data of animals injected with either type of lyotropic liquid crystal nanoparticle displayed enhanced contrast in the liver and spleen. Copyright © 2016 Elsevier B.V. All rights reserved.

Arraycount, an algorithm for automatic cell counting in microwell arrays.

PubMed

Kachouie, Nezamoddin; Kang, Lifeng; Khademhosseini, Ali

2009-09-01

Microscale technologies have emerged as a powerful tool for studying and manipulating biological systems and miniaturizing experiments. However, the lack of software complementing these techniques has made it difficult to apply them for many high-throughput experiments. This work establishes Arraycount, an approach to automatically count cells in microwell arrays. The procedure consists of fluorescent microscope imaging of cells that are seeded in microwells of a microarray system and then analyzing images via computer to recognize the array and count cells inside each microwell. To start counting, green and red fluorescent images (representing live and dead cells, respectively) are extracted from the original image and processed separately. A template-matching algorithm is proposed in which pre-defined well and cell templates are matched against the red and green images to locate microwells and cells. Subsequently, local maxima in the correlation maps are determined and local maxima maps are thresholded. At the end, the software records the cell counts for each detected microwell on the original image in high-throughput. The automated counting was shown to be accurate compared with manual counting, with a difference of approximately 1-2 cells per microwell: based on cell concentration, the absolute difference between manual and automatic counting measurements was 2.5-13%.

1-Million droplet array with wide-field fluorescence imaging for digital PCR.

PubMed

Hatch, Andrew C; Fisher, Jeffrey S; Tovar, Armando R; Hsieh, Albert T; Lin, Robert; Pentoney, Stephen L; Yang, David L; Lee, Abraham P

2011-11-21

Digital droplet reactors are useful as chemical and biological containers to discretize reagents into picolitre or nanolitre volumes for analysis of single cells, organisms, or molecules. However, most DNA based assays require processing of samples on the order of tens of microlitres and contain as few as one to as many as millions of fragments to be detected. Presented in this work is a droplet microfluidic platform and fluorescence imaging setup designed to better meet the needs of the high-throughput and high-dynamic-range by integrating multiple high-throughput droplet processing schemes on the chip. The design is capable of generating over 1-million, monodisperse, 50 picolitre droplets in 2-7 minutes that then self-assemble into high density 3-dimensional sphere packing configurations in a large viewing chamber for visualization and analysis. This device then undergoes on-chip polymerase chain reaction (PCR) amplification and fluorescence detection to digitally quantify the sample's nucleic acid contents. Wide-field fluorescence images are captured using a low cost 21-megapixel digital camera and macro-lens with an 8-12 cm(2) field-of-view at 1× to 0.85× magnification, respectively. We demonstrate both end-point and real-time imaging ability to perform on-chip quantitative digital PCR analysis of the entire droplet array. Compared to previous work, this highly integrated design yields a 100-fold increase in the number of on-chip digitized reactors with simultaneous fluorescence imaging for digital PCR based assays.

Imaging of Cell-Cell Communication in a Vertical Orientation Reveals High-Resolution Structure of Immunological Synapse and Novel PD-1 Dynamics

PubMed Central

Jang, Joon Hee; Huang, Yu; Zheng, Peilin; Jo, Myeong Chan; Bertolet, Grant; Qin, Lidong; Liu, Dongfang

2015-01-01

The immunological synapse (IS) is one of the most pivotal communication strategies in immune cells. Understanding the molecular basis of the IS provides critical information regarding how immune cells mount an effective immune response. Fluorescence microscopy provides a fundamental tool to study the IS. However, current imaging techniques for studying the IS cannot sufficiently achieve high resolution in real cell-cell conjugates. Here we present a new device that allows for high-resolution imaging of the IS with conventional confocal microscopy in a high-throughput manner. Combining micropits and single cell trap arrays, we have developed a new microfluidic platform that allows visualization of the IS in vertically “stacked” cells. Using this vertical cell pairing (VCP) system, we investigated the dynamics of the inhibitory synapse mediated by an inhibitory receptor, programed death protein-1 (PD-1) and the cytotoxic synapse at the single cell level. In addition to the technique innovation, we demonstrated novel biological findings by this VCP device, including novel distribution of F-actin and cytolytic granules at the IS, PD-1 microclusters in the NK IS, and kinetics of cytotoxicity. We propose that this high-throughput, cost-effective, easy-to-use VCP system, along with conventional imaging techniques, can be used to address a number of significant biological questions in a variety of disciplines. PMID:26123352

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

PubMed Central

Ludovisi, Riccardo; Tauro, Flavia; Salvati, Riccardo; Khoury, Sacha; Mugnozza Scarascia, Giuseppe; Harfouche, Antoine

2017-01-01

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F2 partially inbred population (termed here ‘POP6’), whose F1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (Tc) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. Tc derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance (gs) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress. PMID:29021803

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought.

PubMed

Ludovisi, Riccardo; Tauro, Flavia; Salvati, Riccardo; Khoury, Sacha; Mugnozza Scarascia, Giuseppe; Harfouche, Antoine

2017-01-01

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F 2 partially inbred population (termed here 'POP6'), whose F 1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature ( T c ) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. T c derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance ( g s ) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.

Effect-size measures as descriptors of assay quality in high-content screening: A brief review of some available methodologies

USDA-ARS?s Scientific Manuscript database

The field of high-content screening (HCS) typically uses measures of screen quality conceived for fairly straightforward high-throughput screening (HTS) scenarios. However, in contrast to HTS, image-based HCS systems rely on multidimensional readouts reporting biological responses associated with co...

NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis.

PubMed

Markiewicz, Pawel J; Ehrhardt, Matthias J; Erlandsson, Kjell; Noonan, Philip J; Barnes, Anna; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Ourselin, Sebastien

2018-01-01

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

PubMed

Guo, Qinghua; Wu, Fangfang; Pang, Shuxin; Zhao, Xiaoqian; Chen, Linhai; Liu, Jin; Xue, Baolin; Xu, Guangcai; Li, Le; Jing, Haichun; Chu, Chengcai

2018-03-01

With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis. As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging (LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional (3D) data accurately, and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China, we developed a high-throughput crop phenotyping platform, named Crop 3D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs, functions and testing results of the Crop 3D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.

Integrated, multi-scale, spatial-temporal cell biology--A next step in the post genomic era.

PubMed

Horwitz, Rick

2016-03-01

New microscopic approaches, high-throughput imaging, and gene editing promise major new insights into cellular behaviors. When coupled with genomic and other 'omic information and "mined" for correlations and associations, a new breed of powerful and useful cellular models should emerge. These top down, coarse-grained, and statistical models, in turn, can be used to form hypotheses merging with fine-grained, bottom up mechanistic studies and models that are the back bone of cell biology. The goal of the Allen Institute for Cell Science is to develop the top down approach by developing a high throughput microscopy pipeline that is integrated with modeling, using gene edited hiPS cell lines in various physiological and pathological contexts. The output of these experiments and models will be an "animated" cell, capable of integrating and analyzing image data generated from experiments and models. Copyright © 2015 Elsevier Inc. All rights reserved.

High-Throughput Particle Uptake Analysis by Imaging Flow Cytometry

PubMed Central

Smirnov, Asya; Solga, Michael D.; Lannigan, Joanne; Criss, Alison K.

2017-01-01

Quantifying the efficiency of particle uptake by host cells is important in fields including infectious diseases, autoimmunity, cancer, developmental biology, and drug delivery. Here we present a protocol for high-throughput analysis of particle uptake using imaging flow cytometry, using the bacterium Neisseria gonorrhoeae attached and internalized to neutrophils as an example. Cells are exposed to fluorescently labeled bacteria, fixed, and stained with a bacteria-specific antibody of a different fluorophore. Thus in the absence of a permeabilizing agent, extracellular bacteria are double-labeled with two fluorophores while intracellular bacteria remain single-labeled. A spot count algorithm is used to determine the number of single- and double-labeled bacteria in individual cells, to calculate the percent of cells associated with bacteria, percent of cells with internalized bacteria, and percent of cell-associated bacteria that are internalized. These analyses quantify bacterial association and internalization across thousands of cells and can be applied to diverse experimental systems. PMID:28369762

Raman microspectrometer combined with scattering microscopy and lensless imaging for bacteria identification

NASA Astrophysics Data System (ADS)

Strola, S. A.; Schultz, E.; Allier, C. P.; DesRoches, B.; Lemmonier, J.; Dinten, J.-M.

2013-03-01

In this paper, we report on a compact prototype capable both of lensfree imaging, Raman spectrometry and scattering microscopy from bacteria samples. This instrument allows high-throughput real-time characterization without the need of markers, making it potentially suitable to field label-free biomedical and environmental applications. Samples are illuminated from above with a focused-collimated 532nm laser beam and can be x-y-z scanned. The bacteria detection is based on emerging lensfree imaging technology able to localize cells of interest over a large field-of-view of 24mm2. Raman signal and scattered light are then collected by separate measurement arms simultaneously. In the first arm the emission light is fed by a fiber into a prototype spectrometer, developed by Tornado Spectral System based on Tornado's High Throughput Virtual Slit (HTVS) novel technology. The enhanced light throughput in the spectral region of interest (500-1800 cm-1) reduces Raman acquisition time down to few seconds, thus facilitating experimental protocols and avoiding the bacteria deterioration induced by laser thermal heating. Scattered light impinging in the second arm is collected onto a charge-coupled-device. The reconstructed image allows studying the single bacteria diffraction pattern and their specific structural features. The characterization and identification of different bacteria have been performed to validate and optimize the acquisition system and the component setup. The results obtained demonstrate the benefits of these three techniques combination by providing the precise bacteria localization, their chemical composition and a morphology description. The procedure for a rapid identification of particular pathogen bacteria in a sample is illustrated.

Using ToxCast data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure

EPA Science Inventory

AbstractBackground. High-throughput in vitro screening is an important tool for evaluating the potential biological activity of the thousands of existing chemicals in commerce and the hundreds more introduced each year. Among the assay technologies available, high-content imaging...

A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

NASA Astrophysics Data System (ADS)

Herold, Julia; Abouna, Sylvie; Zhou, Luxian; Pelengaris, Stella; Epstein, David B. A.; Khan, Michael; Nattkemper, Tim W.

2009-02-01

In the last years, bioimaging has turned from qualitative measurements towards a high-throughput and highcontent modality, providing multiple variables for each biological sample analyzed. We present a system which combines machine learning based semantic image annotation and visual data mining to analyze such new multivariate bioimage data. Machine learning is employed for automatic semantic annotation of regions of interest. The annotation is the prerequisite for a biological object-oriented exploration of the feature space derived from the image variables. With the aid of visual data mining, the obtained data can be explored simultaneously in the image as well as in the feature domain. Especially when little is known of the underlying data, for example in the case of exploring the effects of a drug treatment, visual data mining can greatly aid the process of data evaluation. We demonstrate how our system is used for image evaluation to obtain information relevant to diabetes study and screening of new anti-diabetes treatments. Cells of the Islet of Langerhans and whole pancreas in pancreas tissue samples are annotated and object specific molecular features are extracted from aligned multichannel fluorescence images. These are interactively evaluated for cell type classification in order to determine the cell number and mass. Only few parameters need to be specified which makes it usable also for non computer experts and allows for high-throughput analysis.

Mapping whole-brain activity with cellular resolution by light-sheet microscopy and high-throughput image analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Silvestri, Ludovico; Rudinskiy, Nikita; Paciscopi, Marco; Müllenbroich, Marie Caroline; Costantini, Irene; Sacconi, Leonardo; Frasconi, Paolo; Hyman, Bradley T.; Pavone, Francesco S.

2016-03-01

Mapping neuronal activity patterns across the whole brain with cellular resolution is a challenging task for state-of-the-art imaging methods. Indeed, despite a number of technological efforts, quantitative cellular-resolution activation maps of the whole brain have not yet been obtained. Many techniques are limited by coarse resolution or by a narrow field of view. High-throughput imaging methods, such as light sheet microscopy, can be used to image large specimens with high resolution and in reasonable times. However, the bottleneck is then moved from image acquisition to image analysis, since many TeraBytes of data have to be processed to extract meaningful information. Here, we present a full experimental pipeline to quantify neuronal activity in the entire mouse brain with cellular resolution, based on a combination of genetics, optics and computer science. We used a transgenic mouse strain (Arc-dVenus mouse) in which neurons which have been active in the last hours before brain fixation are fluorescently labelled. Samples were cleared with CLARITY and imaged with a custom-made confocal light sheet microscope. To perform an automatic localization of fluorescent cells on the large images produced, we used a novel computational approach called semantic deconvolution. The combined approach presented here allows quantifying the amount of Arc-expressing neurons throughout the whole mouse brain. When applied to cohorts of mice subject to different stimuli and/or environmental conditions, this method helps finding correlations in activity between different neuronal populations, opening the possibility to infer a sort of brain-wide 'functional connectivity' with cellular resolution.

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

PubMed

Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

2018-05-17

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural network Hilbert transform based filtered backprojection for fast inline x-ray inspection

NASA Astrophysics Data System (ADS)

Janssens, Eline; De Beenhouwer, Jan; Van Dael, Mattias; De Schryver, Thomas; Van Hoorebeke, Luc; Verboven, Pieter; Nicolai, Bart; Sijbers, Jan

2018-03-01

X-ray imaging is an important tool for quality control since it allows to inspect the interior of products in a non-destructive way. Conventional x-ray imaging, however, is slow and expensive. Inline x-ray inspection, on the other hand, can pave the way towards fast and individual quality control, provided that a sufficiently high throughput can be achieved at a minimal cost. To meet these criteria, an inline inspection acquisition geometry is proposed where the object moves and rotates on a conveyor belt while it passes a fixed source and detector. Moreover, for this acquisition geometry, a new neural-network-based reconstruction algorithm is introduced: the neural network Hilbert transform based filtered backprojection. The proposed algorithm is evaluated both on simulated and real inline x-ray data and has shown to generate high quality reconstructions of 400  ×  400 reconstruction pixels within 200 ms, thereby meeting the high throughput criteria.

High Content Imaging (HCI) on Miniaturized Three-Dimensional (3D) Cell Cultures

PubMed Central

Joshi, Pranav; Lee, Moo-Yeal

2015-01-01

High content imaging (HCI) is a multiplexed cell staining assay developed for better understanding of complex biological functions and mechanisms of drug action, and it has become an important tool for toxicity and efficacy screening of drug candidates. Conventional HCI assays have been carried out on two-dimensional (2D) cell monolayer cultures, which in turn limit predictability of drug toxicity/efficacy in vivo; thus, there has been an urgent need to perform HCI assays on three-dimensional (3D) cell cultures. Although 3D cell cultures better mimic in vivo microenvironments of human tissues and provide an in-depth understanding of the morphological and functional features of tissues, they are also limited by having relatively low throughput and thus are not amenable to high-throughput screening (HTS). One attempt of making 3D cell culture amenable for HTS is to utilize miniaturized cell culture platforms. This review aims to highlight miniaturized 3D cell culture platforms compatible with current HCI technology. PMID:26694477

High-throughput high-volume nuclear imaging for preclinical in vivo compound screening§.

PubMed

Macholl, Sven; Finucane, Ciara M; Hesterman, Jacob; Mather, Stephen J; Pauplis, Rachel; Scully, Deirdre; Sosabowski, Jane K; Jouannot, Erwan

2017-12-01

Preclinical single-photon emission computed tomography (SPECT)/CT imaging studies are hampered by low throughput, hence are found typically within small volume feasibility studies. Here, imaging and image analysis procedures are presented that allow profiling of a large volume of radiolabelled compounds within a reasonably short total study time. Particular emphasis was put on quality control (QC) and on fast and unbiased image analysis. 2-3 His-tagged proteins were simultaneously radiolabelled by 99m Tc-tricarbonyl methodology and injected intravenously (20 nmol/kg; 100 MBq; n = 3) into patient-derived xenograft (PDX) mouse models. Whole-body SPECT/CT images of 3 mice simultaneously were acquired 1, 4, and 24 h post-injection, extended to 48 h and/or by 0-2 h dynamic SPECT for pre-selected compounds. Organ uptake was quantified by automated multi-atlas and manual segmentations. Data were plotted automatically, quality controlled and stored on a collaborative image management platform. Ex vivo uptake data were collected semi-automatically and analysis performed as for imaging data. >500 single animal SPECT images were acquired for 25 proteins over 5 weeks, eventually generating >3500 ROI and >1000 items of tissue data. SPECT/CT images clearly visualized uptake in tumour and other tissues even at 48 h post-injection. Intersubject uptake variability was typically 13% (coefficient of variation, COV). Imaging results correlated well with ex vivo data. The large data set of tumour, background and systemic uptake/clearance data from 75 mice for 25 compounds allows identification of compounds of interest. The number of animals required was reduced considerably by longitudinal imaging compared to dissection experiments. All experimental work and analyses were accomplished within 3 months expected to be compatible with drug development programmes. QC along all workflow steps, blinding of the imaging contract research organization to compound properties and automation provide confidence in the data set. Additional ex vivo data were useful as a control but could be omitted from future studies in the same centre. For even larger compound libraries, radiolabelling could be expedited and the number of imaging time points adapted to increase weekly throughput. Multi-atlas segmentation could be expanded via SPECT/MRI; however, this would require an MRI-compatible mouse hotel. Finally, analysis of nuclear images of radiopharmaceuticals in clinical trials may benefit from the automated analysis procedures developed.

Multiplex Staining by Sequential Immunostaining and Antibody Removal on Routine Tissue Sections.

PubMed

Bolognesi, Maddalena Maria; Manzoni, Marco; Scalia, Carla Rossana; Zannella, Stefano; Bosisio, Francesca Maria; Faretta, Mario; Cattoretti, Giorgio

2017-08-01

Multiplexing, labeling for multiple immunostains in the very same cell or tissue section in situ, has raised considerable interest. The methods proposed include the use of labeled primary antibodies, spectral separation of fluorochromes, bleaching of the fluorophores or chromogens, blocking of previous antibody layers, all in various combinations. The major obstacles to the diffusion of this technique are high costs in custom antibodies and instruments, low throughput, and scarcity of specialized skills or facilities. We have validated a method based on common primary and secondary antibodies and diffusely available fluorescent image scanners. It entails rounds of four-color indirect immunofluorescence, image acquisition, and removal (stripping) of the antibodies, before another stain is applied. The images are digitally registered and the autofluorescence is subtracted. Removal of antibodies is accomplished by disulfide cleavage and a detergent or by a chaotropic salt treatment, this latter followed by antigen refolding. More than 30 different antibody stains can be applied to one single section from routinely fixed and embedded tissue. This method requires a modest investment in hardware and materials and uses freeware image analysis software. Multiplexing on routine tissue sections is a high throughput tool for in situ characterization of neoplastic, reactive, inflammatory, and normal cells.

Projection Reduction Exposure with Variable Axis Immersion Lenses (PREVAIL)-A High Throughput E-Beam Projection Approach for Next Generation Lithography

NASA Astrophysics Data System (ADS)

Pfeiffer, Hans

1999-12-01

Projection reduction exposure with variable axis immersion lenses (PREVAIL) represents the high throughput e-beam projection approach to next generation lithography (NGL), which IBM is pursuing in cooperation with Nikon Corporation as an alliance partner. This paper discusses the challenges and accomplishments of the PREVAIL project. The supreme challenge facing all e-beam lithography approaches has been and still is throughput. Since the throughput of e-beam projection systems is severely limited by the available optical field size, the key to success is the ability to overcome this limitation. The PREVAIL technique overcomes field-limiting off-axis aberrations through the use of variable axis lenses, which electronically shift the optical axis simultaneously with the deflected beam, so that the beam effectively remains on axis. The resist images obtained with the proof-of-concept (POC) system demonstrate that PREVAIL effectively eliminates off-axis aberrations affecting both the resolution and placement accuracy of pixels. As part of the POC system a high emittance gun has been developed to provide uniform illumination of the patterned subfield, and to fill the large numerical aperture projection optics designed to significantly reduce beam blur caused by Coulombinteraction.

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

PubMed

Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott

2018-05-01

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Ultra-high throughput detection of single cell β-galactosidase activity in droplets using micro-optical lens array

NASA Astrophysics Data System (ADS)

Lim, Jiseok; Vrignon, Jérémy; Gruner, Philipp; Karamitros, Christos S.; Konrad, Manfred; Baret, Jean-Christophe

2013-11-01

We demonstrate the use of a hybrid microfluidic-micro-optical system for the screening of enzymatic activity at the single cell level. Escherichia coli β-galactosidase activity is revealed by a fluorogenic assay in 100 pl droplets. Individual droplets containing cells are screened by measuring their fluorescence signal using a high-speed camera. The measurement is parallelized over 100 channels equipped with microlenses and analyzed by image processing. A reinjection rate of 1 ml of emulsion per minute was reached corresponding to more than 105 droplets per second, an analytical throughput larger than those obtained using flow cytometry.

A Dual-Mode Large-Arrayed CMOS ISFET Sensor for Accurate and High-Throughput pH Sensing in Biomedical Diagnosis.

PubMed

Huang, Xiwei; Yu, Hao; Liu, Xu; Jiang, Yu; Yan, Mei; Wu, Dongping

2015-09-01

The existing ISFET-based DNA sequencing detects hydrogen ions released during the polymerization of DNA strands on microbeads, which are scattered into microwell array above the ISFET sensor with unknown distribution. However, false pH detection happens at empty microwells due to crosstalk from neighboring microbeads. In this paper, a dual-mode CMOS ISFET sensor is proposed to have accurate pH detection toward DNA sequencing. Dual-mode sensing, optical and chemical modes, is realized by integrating a CMOS image sensor (CIS) with ISFET pH sensor, and is fabricated in a standard 0.18-μm CIS process. With accurate determination of microbead physical locations with CIS pixel by contact imaging, the dual-mode sensor can correlate local pH for one DNA slice at one location-determined microbead, which can result in improved pH detection accuracy. Moreover, toward a high-throughput DNA sequencing, a correlated-double-sampling readout that supports large array for both modes is deployed to reduce pixel-to-pixel nonuniformity such as threshold voltage mismatch. The proposed CMOS dual-mode sensor is experimentally examined to show a well correlated pH map and optical image for microbeads with a pH sensitivity of 26.2 mV/pH, a fixed pattern noise (FPN) reduction from 4% to 0.3%, and a readout speed of 1200 frames/s. A dual-mode CMOS ISFET sensor with suppressed FPN for accurate large-arrayed pH sensing is proposed and demonstrated with state-of-the-art measured results toward accurate and high-throughput DNA sequencing. The developed dual-mode CMOS ISFET sensor has great potential for future personal genome diagnostics with high accuracy and low cost.

ACS Data Handbook v.6.0

NASA Astrophysics Data System (ADS)

Gonzaga, S.; et al.

2011-03-01

ACS was designed to provide a deep, wide-field survey capability from the visible to near-IR using the Wide Field Camera (WFC), high resolution imaging from the near-UV to near-IR with the now-defunct High Resolution Camera (HRC), and solar-blind far-UV imaging using the Solar Blind Camera (SBC). The discovery efficiency of ACS's Wide Field Channel (i.e., the product of WFC's field of view and throughput) is 10 times greater than that of WFPC2. The failure of ACS's CCD electronics in January 2007 brought a temporary halt to CCD imaging until Servicing Mission 4 in May 2009, when WFC functionality was restored. Unfortunately, the high-resolution optical imaging capability of HRC was not recovered.

Ultra-high-speed variable focus optics for novel applications in advanced imaging

NASA Astrophysics Data System (ADS)

Kang, S.; Dotsenko, E.; Amrhein, D.; Theriault, C.; Arnold, C. B.

2018-02-01

With the advancement of ultra-fast manufacturing technologies, high speed imaging with high 3D resolution has become increasingly important. Here we show the use of an ultra-high-speed variable focus optical element, the TAG Lens, to enable new ways to acquire 3D information from an object. The TAG Lens uses sound to adjust the index of refraction profile in a liquid and thereby can achieve focal scanning rates greater than 100 kHz. When combined with a high-speed pulsed LED and a high-speed camera, we can exploit this phenomenon to achieve high-resolution imaging through large depths. By combining the image acquisition with digital image processing, we can extract relevant parameters such as tilt and angle information from objects in the image. Due to the high speeds at which images can be collected and processed, we believe this technique can be used as an efficient method of industrial inspection and metrology for high throughput applications.

An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

PubMed

Lu, Alex Xijie; Moses, Alan M

2016-01-01

Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

High throughput operando studies using Fourier transform infrared imaging and Raman spectroscopy.

PubMed

Li, Guosheng; Hu, Dehong; Xia, Guanguang; White, J M; Zhang, Conrad

2008-07-01

A prototype high throughput operando (HTO) reactor designed and built for catalyst screening and characterization combines Fourier transform infrared (FT-IR) imaging and Raman spectroscopy in operando conditions. Using a focal plane array detector (HgCdTe focal plane array, 128x128 pixels, and 1610 Hz frame rate) for the FT-IR imaging system, the catalyst activity and selectivity of all parallel reaction channels can be simultaneously followed. Each image data set possesses 16 384 IR spectra with a spectral range of 800-4000 cm(-1) and with an 8 cm(-1) resolution. Depending on the signal-to-noise ratio, 2-20 s are needed to generate a full image of all reaction channels for a data set. Results on reactant conversion and product selectivity are obtained from FT-IR spectral analysis. Six novel Raman probes, one for each reaction channel, were specially designed and house built at Pacific Northwest National Laboratory, to simultaneously collect Raman spectra of the catalysts and possible reaction intermediates on the catalyst surface under operando conditions. As a model system, methanol partial oxidation reaction on silica-supported molybdenum oxide (MoO3SiO2) catalysts has been studied under different reaction conditions to demonstrate the performance of the HTO reactor.

High-throughput sample processing and sample management; the functional evolution of classical cytogenetic assay towards automation.

PubMed

Ramakumar, Adarsh; Subramanian, Uma; Prasanna, Pataje G S

2015-11-01

High-throughput individual diagnostic dose assessment is essential for medical management of radiation-exposed subjects after a mass casualty. Cytogenetic assays such as the Dicentric Chromosome Assay (DCA) are recognized as the gold standard by international regulatory authorities. DCA is a multi-step and multi-day bioassay. DCA, as described in the IAEA manual, can be used to assess dose up to 4-6 weeks post-exposure quite accurately but throughput is still a major issue and automation is very essential. The throughput is limited, both in terms of sample preparation as well as analysis of chromosome aberrations. Thus, there is a need to design and develop novel solutions that could utilize extensive laboratory automation for sample preparation, and bioinformatics approaches for chromosome-aberration analysis to overcome throughput issues. We have transitioned the bench-based cytogenetic DCA to a coherent process performing high-throughput automated biodosimetry for individual dose assessment ensuring quality control (QC) and quality assurance (QA) aspects in accordance with international harmonized protocols. A Laboratory Information Management System (LIMS) is designed, implemented and adapted to manage increased sample processing capacity, develop and maintain standard operating procedures (SOP) for robotic instruments, avoid data transcription errors during processing, and automate analysis of chromosome-aberrations using an image analysis platform. Our efforts described in this paper intend to bridge the current technological gaps and enhance the potential application of DCA for a dose-based stratification of subjects following a mass casualty. This paper describes one such potential integrated automated laboratory system and functional evolution of the classical DCA towards increasing critically needed throughput. Published by Elsevier B.V.

An Automated High-throughput Array Microscope for Cancer Cell Mechanics

NASA Astrophysics Data System (ADS)

Cribb, Jeremy A.; Osborne, Lukas D.; Beicker, Kellie; Psioda, Matthew; Chen, Jian; O'Brien, E. Timothy; Taylor, Russell M., II; Vicci, Leandra; Hsiao, Joe Ping-Lin; Shao, Chong; Falvo, Michael; Ibrahim, Joseph G.; Wood, Kris C.; Blobe, Gerard C.; Superfine, Richard

2016-06-01

Changes in cellular mechanical properties correlate with the progression of metastatic cancer along the epithelial-to-mesenchymal transition (EMT). Few high-throughput methodologies exist that measure cell compliance, which can be used to understand the impact of genetic alterations or to screen the efficacy of chemotherapeutic agents. We have developed a novel array high-throughput microscope (AHTM) system that combines the convenience of the standard 96-well plate with the ability to image cultured cells and membrane-bound microbeads in twelve independently-focusing channels simultaneously, visiting all wells in eight steps. We use the AHTM and passive bead rheology techniques to determine the relative compliance of human pancreatic ductal epithelial (HPDE) cells, h-TERT transformed HPDE cells (HPNE), and four gain-of-function constructs related to EMT. The AHTM found HPNE, H-ras, Myr-AKT, and Bcl2 transfected cells more compliant relative to controls, consistent with parallel tests using atomic force microscopy and invasion assays, proving the AHTM capable of screening for changes in mechanical phenotype.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

PubMed Central

Ching, Travers; Zhu, Xun

2018-01-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet. PMID:29634719

High-Throughput Density Measurement Using Magnetic Levitation.

PubMed

Ge, Shencheng; Wang, Yunzhe; Deshler, Nicolas J; Preston, Daniel J; Whitesides, George M

2018-06-20

This work describes the development of an integrated analytical system that enables high-throughput density measurements of diamagnetic particles (including cells) using magnetic levitation (MagLev), 96-well plates, and a flatbed scanner. MagLev is a simple and useful technique with which to carry out density-based analysis and separation of a broad range of diamagnetic materials with different physical forms (e.g., liquids, solids, gels, pastes, gums, etc.); one major limitation, however, is the capacity to perform high-throughput density measurements. This work addresses this limitation by (i) re-engineering the shape of the magnetic fields so that the MagLev system is compatible with 96-well plates, and (ii) integrating a flatbed scanner (and simple optical components) to carry out imaging of the samples that levitate in the system. The resulting system is compatible with both biological samples (human erythrocytes) and nonbiological samples (simple liquids and solids, such as 3-chlorotoluene, cholesterol crystals, glass beads, copper powder, and polymer beads). The high-throughput capacity of this integrated MagLev system will enable new applications in chemistry (e.g., analysis and separation of materials) and biochemistry (e.g., cellular responses under environmental stresses) in a simple and label-free format on the basis of a universal property of all matter, i.e., density.

A computational image analysis glossary for biologists.

PubMed

Roeder, Adrienne H K; Cunha, Alexandre; Burl, Michael C; Meyerowitz, Elliot M

2012-09-01

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging.

PubMed

Chang, Hing-Chiu; Gaur, Pooja; Chou, Ying-hui; Chu, Mei-Lan; Chen, Nan-kuei

2014-01-01

Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.

Advances in Automated Plankton Imaging: Enhanced Throughput, Automated Staining, and Extended Deployment Modes for Imaging FlowCytobot

NASA Astrophysics Data System (ADS)

Sosik, H. M.; Olson, R. J.; Brownlee, E.; Brosnahan, M.; Crockford, E. T.; Peacock, E.; Shalapyonok, A.

2016-12-01

Imaging FlowCytobot (IFCB) was developed to fill a need for automated identification and monitoring of nano- and microplankton, especially phytoplankton in the size range 10 200 micrometer, which are important in coastal blooms (including harmful algal blooms). IFCB uses a combination of flow cytometric and video technology to capture high resolution (1 micrometer) images of suspended particles. This proven, now commercially available, submersible instrument technology has been deployed in fixed time series locations for extended periods (months to years) and in shipboard laboratories where underway water is automatically analyzed during surveys. Building from these successes, we have now constructed and evaluated three new prototype IFCB designs that extend measurement and deployment capabilities. To improve cell counting statistics without degrading image quality, a high throughput version (IFCB-HT) incorporates in-flow acoustic focusing to non-disruptively pre-concentrate cells before the measurement area of the flow cell. To extend imaging to all heterotrophic cells (even those that do not exhibit chlorophyll fluorescence), Staining IFCB (IFCB-S) incorporates automated addition of a live-cell fluorescent stain (fluorescein diacetate) to samples before analysis. A horizontally-oriented IFCB-AV design addresses the need for spatial surveying from surface autonomous vehicles, including design features that reliably eliminate air bubbles and mitigate wave motion impacts. Laboratory evaluation and test deployments in waters near Woods Hole show the efficacy of each of these enhanced IFCB designs.

High-throughput methods for electron crystallography.

PubMed

Stokes, David L; Ubarretxena-Belandia, Iban; Gonen, Tamir; Engel, Andreas

2013-01-01

Membrane proteins play a tremendously important role in cell physiology and serve as a target for an increasing number of drugs. Structural information is key to understanding their function and for developing new strategies for combating disease. However, the complex physical chemistry associated with membrane proteins has made them more difficult to study than their soluble cousins. Electron crystallography has historically been a successful method for solving membrane protein structures and has the advantage of providing a native lipid environment for these proteins. Specifically, when membrane proteins form two-dimensional arrays within a lipid bilayer, electron microscopy can be used to collect images and diffraction and the corresponding data can be combined to produce a three-dimensional reconstruction, which under favorable conditions can extend to atomic resolution. Like X-ray crystallography, the quality of the structures are very much dependent on the order and size of the crystals. However, unlike X-ray crystallography, high-throughput methods for screening crystallization trials for electron crystallography are not in general use. In this chapter, we describe two alternative methods for high-throughput screening of membrane protein crystallization within the lipid bilayer. The first method relies on the conventional use of dialysis for removing detergent and thus reconstituting the bilayer; an array of dialysis wells in the standard 96-well format allows the use of a liquid-handling robot and greatly increases throughput. The second method relies on titration of cyclodextrin as a chelating agent for detergent; a specialized pipetting robot has been designed not only to add cyclodextrin in a systematic way, but to use light scattering to monitor the reconstitution process. In addition, the use of liquid-handling robots for making negatively stained grids and methods for automatically imaging samples in the electron microscope are described.

High definition infrared chemical imaging of colorectal tissue using a Spero QCL microscope.

PubMed

Bird, B; Rowlette, J

2017-04-10

Mid-infrared microscopy has become a key technique in the field of biomedical science and spectroscopy. This label-free, non-destructive technique permits the visualisation of a wide range of intrinsic biochemical markers in tissues, cells and biofluids by detection of the vibrational modes of the constituent molecules. Together, infrared microscopy and chemometrics is a widely accepted method that can distinguish healthy and diseased states with high accuracy. However, despite the exponential growth of the field and its research world-wide, several barriers currently exist for its full translation into the clinical sphere, namely sample throughput and data management. The advent and incorporation of quantum cascade lasers (QCLs) into infrared microscopes could help propel the field over these remaining hurdles. Such systems offer several advantages over their FT-IR counterparts, a simpler instrument architecture, improved photon flux, use of room temperature camera systems, and the flexibility of a tunable illumination source. In this current study we explore the use of a QCL infrared microscope to produce high definition, high throughput chemical images useful for the screening of biopsied colorectal tissue.

Normal-incidence EXtreme-Ultraviolet imaging Spectrometer - NEXUS

NASA Astrophysics Data System (ADS)

Dere, K. P.

2003-05-01

NEXUS is the result of a breakthrough optical design that incorporates new technologies to achieve high optical throughput at high spatial (1 arcsec) and spectral (1-2 km s-1) resolution over a wide field of view in an optimal extreme-ultraviolet spectral band. This achievement was made possible primarily by two technical developments. First, a coating of boron-carbide deposited onto a layer of iridium provided a greatly enhanced reflectivity at EUV wavelengths that would enable NEXUS to observe the Sun over a wide temperature range at high cadence. The reflectivity of these coatings have been measured and demonstrated in the laboratory. The second key development was the use of a variable-line-spaced toroidal grating spectrometer. The spectrometer design allowed the Sun to be imaged at high spatial and spectral resolution along a 1 solar radius-long slit and over a wavelength range from 450 to 800 Å, nearly an entire spectral order. Because the spectrograph provided a magnification of about a factor of 6, only 2 optical elements are required to achieved the desired imaging performance. Throughput was enhanced by the use of only 2 reflections. The could all be accomodated within a total instrument length of 1.5m. We would like to acknowledge support from ONR

CCR researchers identify pathway critical for preventing premature aging | Center for Cancer Research

Cancer.gov

Hutchinson-Gilford progeria syndrome (HGPS) is a rare, fatal disease in which patients age prematurely. To identify primary HGPS driver mechanisms, Nard Kubben, Ph.D., a Research Fellow in the laboratory of Tom Misteli, Ph.D., in CCR’s Laboratory of Receptor Biology and Gene Expression, and colleagues in the NCI High-throughput Imaging Facility developed an imaging-based

Development and operation of a high-throughput accurate-wavelength lens-based spectrometer a)

DOE PAGES

Bell, Ronald E.

2014-07-11

A high-throughput spectrometer for the 400-820 nm wavelength range has been developed for charge exchange recombination spectroscopy or general spectroscopy. A large 2160 mm -1 grating is matched with fast f /1.8 200 mm lenses, which provide stigmatic imaging. A precision optical encoder measures the grating angle with an accuracy ≤ 0.075 arc seconds. A high quantum efficiency low-etaloning CCD detector allows operation at longer wavelengths. A patch panel allows input fibers to interface with interchangeable fiber holders that attach to a kinematic mount behind the entrance slit. The computer-controlled hardware allows automated control of wavelength, timing, f-number, automated datamore » collection, and wavelength calibration.« less

Optical Layout Analysis of Polarization Interference Imaging Spectrometer by Jones Calculus in View of both Optical Throughput and Interference Fringe Visibility

NASA Astrophysics Data System (ADS)

Zhang, Xuanni; Zhang, Chunmin

2013-01-01

A polarization interference imaging spectrometer based on Savart polariscope was presented. Its optical throughput was analyzed by Jones calculus. The throughput expression was given, and clearly showed that the optical throughput mainly depended on the intensity of incident light, transmissivity, refractive index and the layout of optical system. The simulation and analysis gave the optimum layout in view of both optical throughput and interference fringe visibility, and verified that the layout of our former design was optimum. The simulation showed that a small deviation from the optimum layout influenced interference fringe visibility little for the optimum one, but influenced severely for others, so a small deviation is admissible in the optimum, and this can mitigate the manufacture difficulty. These results pave the way for further research and engineering design.

High performance gel imaging with a commercial single lens reflex camera

NASA Astrophysics Data System (ADS)

Slobodan, J.; Corbett, R.; Wye, N.; Schein, J. E.; Marra, M. A.; Coope, R. J. N.

2011-03-01

A high performance gel imaging system was constructed using a digital single lens reflex camera with epi-illumination to image 19 × 23 cm agarose gels with up to 10,000 DNA bands each. It was found to give equivalent performance to a laser scanner in this high throughput DNA fingerprinting application using the fluorophore SYBR Green®. The specificity and sensitivity of the imager and scanner were within 1% using the same band identification software. Low and high cost color filters were also compared and it was found that with care, good results could be obtained with inexpensive dyed acrylic filters in combination with more costly dielectric interference filters, but that very poor combinations were also possible. Methods for determining resolution, dynamic range, and optical efficiency for imagers are also proposed to facilitate comparison between systems.

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

PubMed Central

Teodoro, George; Pan, Tony; Kurc, Tahsin M.; Kong, Jun; Cooper, Lee A. D.; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H.

2014-01-01

Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system. PMID:25419546

BioImageXD: an open, general-purpose and high-throughput image-processing platform.

PubMed

Kankaanpää, Pasi; Paavolainen, Lassi; Tiitta, Silja; Karjalainen, Mikko; Päivärinne, Joacim; Nieminen, Jonna; Marjomäki, Varpu; Heino, Jyrki; White, Daniel J

2012-06-28

BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes. We demonstrate its performance in a study of integrin clustering in response to selected inhibitors.

UAV-based high-throughput phenotyping in legume crops

NASA Astrophysics Data System (ADS)

Sankaran, Sindhuja; Khot, Lav R.; Quirós, Juan; Vandemark, George J.; McGee, Rebecca J.

2016-05-01

In plant breeding, one of the biggest obstacles in genetic improvement is the lack of proven rapid methods for measuring plant responses in field conditions. Therefore, the major objective of this research was to evaluate the feasibility of utilizing high-throughput remote sensing technology for rapid measurement of phenotyping traits in legume crops. The plant responses of several chickpea and peas varieties to the environment were assessed with an unmanned aerial vehicle (UAV) integrated with multispectral imaging sensors. Our preliminary assessment showed that the vegetation indices are strongly correlated (p<0.05) with seed yield of legume crops. Results endorse the potential of UAS-based sensing technology to rapidly measure those phenotyping traits.

Wavelength-Scanning SPR Imaging Sensors Based on an Acousto-Optic Tunable Filter and a White Light Laser

PubMed Central

Zeng, Youjun; Wang, Lei; Wu, Shu-Yuen; He, Jianan; Qu, Junle; Li, Xuejin; Ho, Ho-Pui; Gu, Dayong; Gao, Bruce Zhi; Shao, Yonghong

2017-01-01

A fast surface plasmon resonance (SPR) imaging biosensor system based on wavelength interrogation using an acousto-optic tunable filter (AOTF) and a white light laser is presented. The system combines the merits of a wide-dynamic detection range and high sensitivity offered by the spectral approach with multiplexed high-throughput data collection and a two-dimensional (2D) biosensor array. The key feature is the use of AOTF to realize wavelength scan from a white laser source and thus to achieve fast tracking of the SPR dip movement caused by target molecules binding to the sensor surface. Experimental results show that the system is capable of completing a SPR dip measurement within 0.35 s. To the best of our knowledge, this is the fastest time ever reported in the literature for imaging spectral interrogation. Based on a spectral window with a width of approximately 100 nm, a dynamic detection range and resolution of 4.63 × 10−2 refractive index unit (RIU) and 1.27 × 10−6 RIU achieved in a 2D-array sensor is reported here. The spectral SPR imaging sensor scheme has the capability of performing fast high-throughput detection of biomolecular interactions from 2D sensor arrays. The design has no mechanical moving parts, thus making the scheme completely solid-state. PMID:28067766

Performance of the SIR-B digital image processing subsystem

NASA Technical Reports Server (NTRS)

Curlander, J. C.

1986-01-01

A ground-based system to generate digital SAR image products has been developed and implemented in support of the SIR-B mission. This system is designed to achieve the maximum throughput while meeting strict image fidelity criteria. Its capabilities include: automated radiometric and geometric correction of the output imagery; high-precision absolute location without tiepoint registration; filtering of the raw data to remove spurious signals from alien radars; and automated catologing to maintain a full set of radar and image production facility in support of the SIR-B science investigators routinely produces over 80 image frames per week.

GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping

PubMed Central

Diaz-Garcia, Luis; Covarrubias-Pazaran, Giovanny; Schlautman, Brandon; Zalapa, Juan

2016-01-01

Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed, but most of them are expensive, species-dependent, complex to use, and available only for major crops. To overcome such limitations, we present the open-source software GiNA, which is a simple and free tool for measuring horticultural traits such as shape- and color-related parameters of fruits, vegetables, and seeds. GiNA is multiplatform software available in both R and MATLAB® programming languages and uses conventional images from digital cameras with minimal requirements. It can process up to 11 different horticultural morphological traits such as length, width, two-dimensional area, volume, projected skin, surface area, RGB color, among other parameters. Different validation tests produced highly consistent results under different lighting conditions and camera setups making GiNA a very reliable platform for high-throughput phenotyping. In addition, five-fold cross validation between manually generated and GiNA measurements for length and width in cranberry fruits were 0.97 and 0.92. In addition, the same strategy yielded prediction accuracies above 0.83 for color estimates produced from images of cranberries analyzed with GiNA compared to total anthocyanin content (TAcy) of the same fruits measured with the standard methodology of the industry. Our platform provides a scalable, easy-to-use and affordable tool for massive acquisition of phenotypic data of fruits, seeds, and vegetables. PMID:27529547

GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping.

PubMed

Diaz-Garcia, Luis; Covarrubias-Pazaran, Giovanny; Schlautman, Brandon; Zalapa, Juan

2016-01-01

Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed, but most of them are expensive, species-dependent, complex to use, and available only for major crops. To overcome such limitations, we present the open-source software GiNA, which is a simple and free tool for measuring horticultural traits such as shape- and color-related parameters of fruits, vegetables, and seeds. GiNA is multiplatform software available in both R and MATLAB® programming languages and uses conventional images from digital cameras with minimal requirements. It can process up to 11 different horticultural morphological traits such as length, width, two-dimensional area, volume, projected skin, surface area, RGB color, among other parameters. Different validation tests produced highly consistent results under different lighting conditions and camera setups making GiNA a very reliable platform for high-throughput phenotyping. In addition, five-fold cross validation between manually generated and GiNA measurements for length and width in cranberry fruits were 0.97 and 0.92. In addition, the same strategy yielded prediction accuracies above 0.83 for color estimates produced from images of cranberries analyzed with GiNA compared to total anthocyanin content (TAcy) of the same fruits measured with the standard methodology of the industry. Our platform provides a scalable, easy-to-use and affordable tool for massive acquisition of phenotypic data of fruits, seeds, and vegetables.

Adapting the γ-H2AX assay for automated processing in human lymphocytes. 1. Technological aspects.

PubMed

Turner, Helen C; Brenner, David J; Chen, Youhua; Bertucci, Antonella; Zhang, Jian; Wang, Hongliang; Lyulko, Oleksandra V; Xu, Yanping; Shuryak, Igor; Schaefer, Julia; Simaan, Nabil; Randers-Pehrson, Gerhard; Yao, Y Lawrence; Amundson, Sally A; Garty, Guy

2011-03-01

The immunofluorescence-based detection of γ-H2AX is a reliable and sensitive method for quantitatively measuring DNA double-strand breaks (DSBs) in irradiated samples. Since H2AX phosphorylation is highly linear with radiation dose, this well-established biomarker is in current use in radiation biodosimetry. At the Center for High-Throughput Minimally Invasive Radiation Biodosimetry, we have developed a fully automated high-throughput system, the RABIT (Rapid Automated Biodosimetry Tool), that can be used to measure γ-H2AX yields from fingerstick-derived samples of blood. The RABIT workstation has been designed to fully automate the γ-H2AX immunocytochemical protocol, from the isolation of human blood lymphocytes in heparin-coated PVC capillaries to the immunolabeling of γ-H2AX protein and image acquisition to determine fluorescence yield. High throughput is achieved through the use of purpose-built robotics, lymphocyte handling in 96-well filter-bottomed plates, and high-speed imaging. The goal of the present study was to optimize and validate the performance of the RABIT system for the reproducible and quantitative detection of γ-H2AX total fluorescence in lymphocytes in a multiwell format. Validation of our biodosimetry platform was achieved by the linear detection of a dose-dependent increase in γ-H2AX fluorescence in peripheral blood samples irradiated ex vivo with γ rays over the range 0 to 8 Gy. This study demonstrates for the first time the optimization and use of our robotically based biodosimetry workstation to successfully quantify γ-H2AX total fluorescence in irradiated peripheral lymphocytes.

Towards building high performance medical image management system for clinical trials

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel

2011-03-01

Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving images from a centralized image repository to workstations to markup and annotate images. In such environment, it is critical to provide a high performance image management system that supports efficient concurrent image retrievals in a distributed environment. There are several major challenges: high throughput of large scale image data over the Internet from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our experiments show promising results of our methods, and our work provides a guideline for building enterprise level high performance medical image management systems.

High-Content, High-Throughput Screening for the Identification of Cytotoxic Compounds Based on Cell Morphology and Cell Proliferation Markers

PubMed Central

Martin, Heather L.; Adams, Matthew; Higgins, Julie; Bond, Jacquelyn; Morrison, Ewan E.; Bell, Sandra M.; Warriner, Stuart; Nelson, Adam; Tomlinson, Darren C.

2014-01-01

Toxicity is a major cause of failure in drug discovery and development, and whilst robust toxicological testing occurs, efficiency could be improved if compounds with cytotoxic characteristics were identified during primary compound screening. The use of high-content imaging in primary screening is becoming more widespread, and by utilising phenotypic approaches it should be possible to incorporate cytotoxicity counter-screens into primary screens. Here we present a novel phenotypic assay that can be used as a counter-screen to identify compounds with adverse cellular effects. This assay has been developed using U2OS cells, the PerkinElmer Operetta high-content/high-throughput imaging system and Columbus image analysis software. In Columbus, algorithms were devised to identify changes in nuclear morphology, cell shape and proliferation using DAPI, TOTO-3 and phosphohistone H3 staining, respectively. The algorithms were developed and tested on cells treated with doxorubicin, taxol and nocodazole. The assay was then used to screen a novel, chemical library, rich in natural product-like molecules of over 300 compounds, 13.6% of which were identified as having adverse cellular effects. This assay provides a relatively cheap and rapid approach for identifying compounds with adverse cellular effects during screening assays, potentially reducing compound rejection due to toxicity in subsequent in vitro and in vivo assays. PMID:24505478

Micro-patterned agarose gel devices for single-cell high-throughput microscopy of E. coli cells.

PubMed

Priest, David G; Tanaka, Nobuyuki; Tanaka, Yo; Taniguchi, Yuichi

2017-12-21

High-throughput microscopy of bacterial cells elucidated fundamental cellular processes including cellular heterogeneity and cell division homeostasis. Polydimethylsiloxane (PDMS)-based microfluidic devices provide advantages including precise positioning of cells and throughput, however device fabrication is time-consuming and requires specialised skills. Agarose pads are a popular alternative, however cells often clump together, which hinders single cell quantitation. Here, we imprint agarose pads with micro-patterned 'capsules', to trap individual cells and 'lines', to direct cellular growth outwards in a straight line. We implement this micro-patterning into multi-pad devices called CapsuleHotel and LineHotel for high-throughput imaging. CapsuleHotel provides ~65,000 capsule structures per mm 2 that isolate individual Escherichia coli cells. In contrast, LineHotel provides ~300 line structures per mm that direct growth of micro-colonies. With CapsuleHotel, a quantitative single cell dataset of ~10,000 cells across 24 samples can be acquired and analysed in under 1 hour. LineHotel allows tracking growth of > 10 micro-colonies across 24 samples simultaneously for up to 4 generations. These easy-to-use devices can be provided in kit format, and will accelerate discoveries in diverse fields ranging from microbiology to systems and synthetic biology.

20180312 - Application of a Multiplexed High Content Imaging (HCI) Based Cell Viability and Apoptosis Chemical Screening Assay with Results in MCF-7 Cells (SOT)

EPA Science Inventory

The NCCT high throughput transcriptomics (HTTr) screening program uses whole transcriptome profiling assay in human-derived cells to collect concentration-response data for large numbers (100s-1000s) of environmental chemicals. To contextualize HTTr data, chemical effects on cell...

Automatic high throughput empty ISO container verification

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2007-04-01

Encouraging results are presented for the automatic analysis of radiographic images of a continuous stream of ISO containers to confirm they are truly empty. A series of image processing algorithms are described that process real-time data acquired during the actual inspection of each container and assigns each to one of the classes "empty", "not empty" or "suspect threat". This research is one step towards achieving fully automated analysis of cargo containers.

Computational imaging of sperm locomotion.

PubMed

Daloglu, Mustafa Ugur; Ozcan, Aydogan

2017-08-01

Not only essential for scientific research, but also in the analysis of male fertility and for animal husbandry, sperm tracking and characterization techniques have been greatly benefiting from computational imaging. Digital image sensors, in combination with optical microscopy tools and powerful computers, have enabled the use of advanced detection and tracking algorithms that automatically map sperm trajectories and calculate various motility parameters across large data sets. Computational techniques are driving the field even further, facilitating the development of unconventional sperm imaging and tracking methods that do not rely on standard optical microscopes and objective lenses, which limit the field of view and volume of the semen sample that can be imaged. As an example, a holographic on-chip sperm imaging platform, only composed of a light-emitting diode and an opto-electronic image sensor, has emerged as a high-throughput, low-cost and portable alternative to lens-based traditional sperm imaging and tracking methods. In this approach, the sample is placed very close to the image sensor chip, which captures lensfree holograms generated by the interference of the background illumination with the light scattered from sperm cells. These holographic patterns are then digitally processed to extract both the amplitude and phase information of the spermatozoa, effectively replacing the microscope objective lens with computation. This platform has further enabled high-throughput 3D imaging of spermatozoa with submicron 3D positioning accuracy in large sample volumes, revealing various rare locomotion patterns. We believe that computational chip-scale sperm imaging and 3D tracking techniques will find numerous opportunities in both sperm related research and commercial applications. © The Authors 2017. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Rapid analysis and exploration of fluorescence microscopy images.

PubMed

Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

2014-03-19

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

FPGA Implementation of Stereo Disparity with High Throughput for Mobility Applications

NASA Technical Reports Server (NTRS)

Villalpando, Carlos Y.; Morfopolous, Arin; Matthies, Larry; Goldberg, Steven

2011-01-01

High speed stereo vision can allow unmanned robotic systems to navigate safely in unstructured terrain, but the computational cost can exceed the capacity of typical embedded CPUs. In this paper, we describe an end-to-end stereo computation co-processing system optimized for fast throughput that has been implemented on a single Virtex 4 LX160 FPGA. This system is capable of operating on images from a 1024 x 768 3CCD (true RGB) camera pair at 15 Hz. Data enters the FPGA directly from the cameras via Camera Link and is rectified, pre-filtered and converted into a disparity image all within the FPGA, incurring no CPU load. Once complete, a rectified image and the final disparity image are read out over the PCI bus, for a bandwidth cost of 68 MB/sec. Within the FPGA there are 4 distinct algorithms: Camera Link capture, Bilinear rectification, Bilateral subtraction pre-filtering and the Sum of Absolute Difference (SAD) disparity. Each module will be described in brief along with the data flow and control logic for the system. The system has been successfully fielded upon the Carnegie Mellon University's National Robotics Engineering Center (NREC) Crusher system during extensive field trials in 2007 and 2008 and is being implemented for other surface mobility systems at JPL.

Multifocal multiphoton microscopy with adaptive optical correction

NASA Astrophysics Data System (ADS)

Coelho, Simao; Poland, Simon; Krstajic, Nikola; Li, David; Monypenny, James; Walker, Richard; Tyndall, David; Ng, Tony; Henderson, Robert; Ameer-Beg, Simon

2013-02-01

Fluorescence lifetime imaging microscopy (FLIM) is a well established approach for measuring dynamic signalling events inside living cells, including detection of protein-protein interactions. The improvement in optical penetration of infrared light compared with linear excitation due to Rayleigh scattering and low absorption have provided imaging depths of up to 1mm in brain tissue but significant image degradation occurs as samples distort (aberrate) the infrared excitation beam. Multiphoton time-correlated single photon counting (TCSPC) FLIM is a method for obtaining functional, high resolution images of biological structures. In order to achieve good statistical accuracy TCSPC typically requires long acquisition times. We report the development of a multifocal multiphoton microscope (MMM), titled MegaFLI. Beam parallelization performed via a 3D Gerchberg-Saxton (GS) algorithm using a Spatial Light Modulator (SLM), increases TCSPC count rate proportional to the number of beamlets produced. A weighted 3D GS algorithm is employed to improve homogeneity. An added benefit is the implementation of flexible and adaptive optical correction. Adaptive optics performed by means of Zernike polynomials are used to correct for system induced aberrations. Here we present results with significant improvement in throughput obtained using a novel complementary metal-oxide-semiconductor (CMOS) 1024 pixel single-photon avalanche diode (SPAD) array, opening the way to truly high-throughput FLIM.

A data set from flash X-ray imaging of carboxysomes

NASA Astrophysics Data System (ADS)

Hantke, Max F.; Hasse, Dirk; Ekeberg, Tomas; John, Katja; Svenda, Martin; Loh, Duane; Martin, Andrew V.; Timneanu, Nicusor; Larsson, Daniel S. D.; van der Schot, Gijs; Carlsson, Gunilla H.; Ingelman, Margareta; Andreasson, Jakob; Westphal, Daniel; Iwan, Bianca; Uetrecht, Charlotte; Bielecki, Johan; Liang, Mengning; Stellato, Francesco; Deponte, Daniel P.; Bari, Sadia; Hartmann, Robert; Kimmel, Nils; Kirian, Richard A.; Seibert, M. Marvin; Mühlig, Kerstin; Schorb, Sebastian; Ferguson, Ken; Bostedt, Christoph; Carron, Sebastian; Bozek, John D.; Rolles, Daniel; Rudenko, Artem; Foucar, Lutz; Epp, Sascha W.; Chapman, Henry N.; Barty, Anton; Andersson, Inger; Hajdu, Janos; Maia, Filipe R. N. C.

2016-08-01

Ultra-intense femtosecond X-ray pulses from X-ray lasers permit structural studies on single particles and biomolecules without crystals. We present a large data set on inherently heterogeneous, polyhedral carboxysome particles. Carboxysomes are cell organelles that vary in size and facilitate up to 40% of Earth’s carbon fixation by cyanobacteria and certain proteobacteria. Variation in size hinders crystallization. Carboxysomes appear icosahedral in the electron microscope. A protein shell encapsulates a large number of Rubisco molecules in paracrystalline arrays inside the organelle. We used carboxysomes with a mean diameter of 115±26 nm from Halothiobacillus neapolitanus. A new aerosol sample-injector allowed us to record 70,000 low-noise diffraction patterns in 12 min. Every diffraction pattern is a unique structure measurement and high-throughput imaging allows sampling the space of structural variability. The different structures can be separated and phased directly from the diffraction data and open a way for accurate, high-throughput studies on structures and structural heterogeneity in biology and elsewhere.

Quasi-random array imaging collimator

DOEpatents

Fenimore, E.E.

1980-08-20

A hexagonally shaped quasi-random no-two-holes-touching imaging collimator. The quasi-random array imaging collimator eliminates contamination from small angle off-axis rays by using a no-two-holes-touching pattern which simultaneously provides for a self-supporting array increasing throughput by elimination of a substrate. The present invention also provides maximum throughput using hexagonally shaped holes in a hexagonal lattice pattern for diffraction limited applications. Mosaicking is also disclosed for reducing fabrication effort.

Development of a phenotyping platform for high throughput screening of nodal root angle in sorghum.

PubMed

Joshi, Dinesh C; Singh, Vijaya; Hunt, Colleen; Mace, Emma; van Oosterom, Erik; Sulman, Richard; Jordan, David; Hammer, Graeme

2017-01-01

In sorghum, the growth angle of nodal roots is a major component of root system architecture. It strongly influences the spatial distribution of roots of mature plants in the soil profile, which can impact drought adaptation. However, selection for nodal root angle in sorghum breeding programs has been restricted by the absence of a suitable high throughput phenotyping platform. The aim of this study was to develop a phenotyping platform for the rapid, non-destructive and digital measurement of nodal root angle of sorghum at the seedling stage. The phenotyping platform comprises of 500 soil filled root chambers (50 × 45 × 0.3 cm in size), made of transparent perspex sheets that were placed in metal tubs and covered with polycarbonate sheets. Around 3 weeks after sowing, once the first flush of nodal roots was visible, roots were imaged in situ using an imaging box that included two digital cameras that were remotely controlled by two android tablets. Free software ( openGelPhoto.tcl ) allowed precise measurement of nodal root angle from the digital images. The reliability and efficiency of the platform was evaluated by screening a large nested association mapping population of sorghum and a set of hybrids in six independent experimental runs that included up to 500 plants each. The platform revealed extensive genetic variation and high heritability (repeatability) for nodal root angle. High genetic correlations and consistent ranking of genotypes across experimental runs confirmed the reproducibility of the platform. This low cost, high throughput root phenotyping platform requires no sophisticated equipment, is adaptable to most glasshouse environments and is well suited to dissect the genetic control of nodal root angle of sorghum. The platform is suitable for use in sorghum breeding programs aiming to improve drought adaptation through root system architecture manipulation.

Bimodal imprint chips for peptide screening: integration of high-throughput sequencing by MS and affinity analyses by surface plasmon resonance imaging.

PubMed

Wang, Weizhi; Li, Menglin; Wei, Zewen; Wang, Zihua; Bu, Xiangli; Lai, Wenjia; Yang, Shu; Gong, He; Zheng, Hui; Wang, Yuqiao; Liu, Ying; Li, Qin; Fang, Qiaojun; Hu, Zhiyuan

2014-04-15

Peptide probes and drugs have widespread applications in disease diagnostics and therapy. The demand for peptides ligands with high affinity and high specificity toward various targets has surged in the biomedical field in recent years. The traditional peptide screening procedure involves selection, sequencing, and characterization steps, and each step is manual and tedious. Herein, we developed a bimodal imprint microarray system to embrace the whole peptide screening process. Silver-sputtered silicon chip fabricated with microwell array can trap and pattern the candidate peptide beads in a one-well-one-bead manner. Peptides on beads were photocleaved in situ. A portion of the peptide in each well was transferred to a gold-coated chip to print the peptide array for high-throughput affinity analyses by surface plasmon resonance imaging (SPRi), and the peptide left in the silver-sputtered chip was ready for in situ single bead sequencing by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Using the bimodal imprint chip system, affinity peptides toward AHA were efficiently screened out from the 7 × 10(4) peptide library. The method provides a solution for high efficiency peptide screening.

Lens-free computational imaging of capillary morphogenesis within three-dimensional substrates

NASA Astrophysics Data System (ADS)

Weidling, John; Isikman, Serhan O.; Greenbaum, Alon; Ozcan, Aydogan; Botvinick, Elliot

2012-12-01

Endothelial cells cultured in three-dimensional (3-D) extracellular matrices spontaneously form microvessels in response to soluble and matrix-bound factors. Such cultures are common for the study of angiogenesis and may find widespread use in drug discovery. Vascular networks are imaged over weeks to measure the distribution of vessel morphogenic parameters. Measurements require micron-scale spatial resolution, which for light microscopy comes at the cost of limited field-of-view (FOV) and shallow depth-of-focus (DOF). Small FOVs and DOFs necessitate lateral and axial mechanical scanning, thus limiting imaging throughput. We present a lens-free holographic on-chip microscopy technique to rapidly image microvessels within a Petri dish over a large volume without any mechanical scanning. This on-chip method uses partially coherent illumination and a CMOS sensor to record in-line holographic images of the sample. For digital reconstruction of the measured holograms, we implement a multiheight phase recovery method to obtain phase images of capillary morphogenesis over a large FOV (24 mm2) with ˜1.5 μm spatial resolution. On average, measured capillary length in our method was within approximately 2% of lengths measured using a 10× microscope objective. These results suggest lens-free on-chip imaging is a useful toolset for high-throughput monitoring and quantitative analysis of microvascular 3-D networks.

Identifying apicoplast-targeting antimalarials using high-throughput compatible approaches

PubMed Central

Ekland, Eric H.; Schneider, Jessica; Fidock, David A.

2011-01-01

Malarial parasites have evolved resistance to all previously used therapies, and recent evidence suggests emerging resistance to the first-line artemisinins. To identify antimalarials with novel mechanisms of action, we have developed a high-throughput screen targeting the apicoplast organelle of Plasmodium falciparum. Antibiotics known to interfere with this organelle, such as azithromycin, exhibit an unusual phenotype whereby the progeny of drug-treated parasites die. Our screen exploits this phenomenon by assaying for “delayed death” compounds that exhibit a higher potency after two cycles of intraerythrocytic development compared to one. We report a primary assay employing parasites with an integrated copy of a firefly luciferase reporter gene and a secondary flow cytometry-based assay using a nucleic acid stain paired with a mitochondrial vital dye. Screening of the U.S. National Institutes of Health Clinical Collection identified known and novel antimalarials including kitasamycin. This inexpensive macrolide, used for agricultural applications, exhibited an in vitro IC50 in the 50 nM range, comparable to the 30 nM activity of our control drug, azithromycin. Imaging and pharmacologic studies confirmed kitasamycin action against the apicoplast, and in vivo activity was observed in a murine malaria model. These assays provide the foundation for high-throughput campaigns to identify novel chemotypes for combination therapies to treat multidrug-resistant malaria.—Ekland, E. H., Schneider, J., Fidock, D. A. Identifying apicoplast-targeting antimalarials using high-throughput compatible approaches. PMID:21746861

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms

PubMed Central

Perez-Sanz, Fernando; Navarro, Pedro J

2017-01-01

Abstract The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. PMID:29048559

Automated imaging of cellular spheroids with selective plane illumination microscopy on a chip (Conference Presentation)

NASA Astrophysics Data System (ADS)

Paiè, Petra; Bassi, Andrea; Bragheri, Francesca; Osellame, Roberto

2017-02-01

Selective plane illumination microscopy (SPIM) is an optical sectioning technique that allows imaging of biological samples at high spatio-temporal resolution. Standard SPIM devices require dedicated set-ups, complex sample preparation and accurate system alignment, thus limiting the automation of the technique, its accessibility and throughput. We present a millimeter-scaled optofluidic device that incorporates selective plane illumination and fully automatic sample delivery and scanning. To this end an integrated cylindrical lens and a three-dimensional fluidic network were fabricated by femtosecond laser micromachining into a single glass chip. This device can upgrade any standard fluorescence microscope to a SPIM system. We used SPIM on a CHIP to automatically scan biological samples under a conventional microscope, without the need of any motorized stage: tissue spheroids expressing fluorescent proteins were flowed in the microchannel at constant speed and their sections were acquired while passing through the light sheet. We demonstrate high-throughput imaging of the entire sample volume (with a rate of 30 samples/min), segmentation and quantification in thick (100-300 μm diameter) cellular spheroids. This optofluidic device gives access to SPIM analyses to non-expert end-users, opening the way to automatic and fast screening of a high number of samples at subcellular resolution.

Imaging ATUM ultrathin section libraries with WaferMapper: a multi-scale approach to EM reconstruction of neural circuits

PubMed Central

Hayworth, Kenneth J.; Morgan, Josh L.; Schalek, Richard; Berger, Daniel R.; Hildebrand, David G. C.; Lichtman, Jeff W.

2014-01-01

The automated tape-collecting ultramicrotome (ATUM) makes it possible to collect large numbers of ultrathin sections quickly—the equivalent of a petabyte of high resolution images each day. However, even high throughput image acquisition strategies generate images far more slowly (at present ~1 terabyte per day). We therefore developed WaferMapper, a software package that takes a multi-resolution approach to mapping and imaging select regions within a library of ultrathin sections. This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library (UTSL) that may contain many thousands of sections. Using WaferMapper, it is possible to map thousands of tissue sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical landmarks. The program can also be used to expand previously imaged regions, acquire data under different imaging conditions, or re-image after additional tissue treatments. PMID:25018701

Large-scale Topographical Screen for Investigation of Physical Neural-Guidance Cues

NASA Astrophysics Data System (ADS)

Li, Wei; Tang, Qing Yuan; Jadhav, Amol D.; Narang, Ankit; Qian, Wei Xian; Shi, Peng; Pang, Stella W.

2015-03-01

A combinatorial approach was used to present primary neurons with a large library of topographical features in the form of micropatterned substrate for high-throughput screening of physical neural-guidance cues that can effectively promote different aspects of neuronal development, including axon and dendritic outgrowth. Notably, the neuronal-guidance capability of specific features was automatically identified using a customized image processing software, thus significantly increasing the screening throughput with minimal subjective bias. Our results indicate that the anisotropic topographies promote axonal and in some cases dendritic extension relative to the isotropic topographies, while dendritic branching showed preference to plain substrates over the microscale features. The results from this work can be readily applied towards engineering novel biomaterials with precise surface topography that can serve as guidance conduits for neuro-regenerative applications. This novel topographical screening strategy combined with the automated processing capability can also be used for high-throughput screening of chemical or genetic regulatory factors in primary neurons.

High-throughput sensing and noninvasive imaging of protein nuclear transport by using reconstitution of split Renilla luciferase.

PubMed

Kim, Sung Bae; Ozawa, Takeaki; Watanabe, Shigeaki; Umezawa, Yoshio

2004-08-10

Nucleocytoplasmic trafficking of functional proteins plays a key role in regulating gene expressions in response to extracellular signals. We developed a genetically encoded bioluminescent indicator for monitoring the nuclear trafficking of target proteins in vitro and in vivo. The principle is based on reconstitution of split fragments of Renilla reniformis (Rluc) by protein splicing with a DnaE intein (a catalytic subunit of DNA polymerase III). A target cytosolic protein fused to the N-terminal half of Rluc is expressed in mammalian cells. If the protein translocates into the nucleus, the Rluc moiety meets the C-terminal half of Rluc, and full-length Rluc is reconstituted by protein splicing. We demonstrated quantitative cell-based in vitro sensing of ligand-induced translocation of androgen receptor, which allowed high-throughput screening of exo- and endogenous agonists and antagonists. Furthermore, the indicator enabled noninvasive in vivo imaging of the androgen receptor translocation in the brains of living mice with a charge-coupled device imaging system. These rapid and quantitative analyses in vitro and in vivo provide a wide variety of applications for screening pharmacological or toxicological compounds and testing them in living animals.

Ultra-high frequency ultrasound biomicroscopy and high throughput cardiovascular phenotyping in a large scale mouse mutagenesis screen

NASA Astrophysics Data System (ADS)

Liu, Xiaoqin; Francis, Richard; Tobita, Kimimasa; Kim, Andy; Leatherbury, Linda; Lo, Cecilia W.

2013-02-01

Ultrasound biomicroscopy (UBM) is ideally suited for phenotyping fetal mice for congenital heart disease (CHD), as imaging can be carried out noninvasively to provide both hemodynamic and structural information essential for CHD diagnosis. Using the UBM (Vevo 2100; 40Hz) in conjunction with the clinical ultrasound system (Acuson Sequioa C512; 15Hz), we developed a two-step screening protocol to scan thousands fetuses derived from ENU mutagenized pedigrees. A wide spectrum of CHD was detected by the UBM, which were subsequently confirmed with follow-up necropsy and histopathology examination with episcopic fluorescence image capture. CHD observed included outflow anomalies, left/right heart obstructive lesions, septal/valvular defects and cardiac situs anomalies. Meanwhile, various extracardiac defects were found, such as polydactyly, craniofacial defects, exencephaly, omphalocele-cleft palate, most of which were associated with cardiac defects. Our analyses showed the UBM was better at assessing cardiac structure and blood flow profiles, while conventional ultrasound allowed higher throughput low-resolution screening. Our study showed the integration of conventional clinical ultrasound imaging with the UBM for fetal mouse cardiovascular phenotyping can maximize the detection and recovery of CHD mutants.

Mechanical phenotyping of tumor cells using a microfluidic cell squeezer device

NASA Astrophysics Data System (ADS)

Khan, Zeina S.; Kamyabi, Nabiollah; Vanapalli, Siva A.

2013-03-01

Studies have indicated that cancer cells have distinct mechanical properties compared to healthy cells. We are investigating the potential of cell mechanics as a biophysical marker for diagnostics and prognosis of cancer. To establish the significance of mechanical properties for cancer diagnostics, a high throughput method is desired. Although techniques such as atomic force microscopy are very precise, they are limited in throughput for cellular mechanical property measurements. To develop a device for high throughput mechanical characterization of tumor cells, we have fabricated a microfludic cell squeezer device that contains narrow micrometer-scale pores. Fluid flow is used to drive cells into these pores mimicking the flow-induced passage of circulating tumor cells through microvasculature. By integrating high speed imaging, the device allows for the simultaneous characterization of five different parameters including the blockage pressure, cell velocity, cell size, elongation and the entry time into squeezer. We have tested a variety of in vitro cell lines, including brain and prostate cancer cell lines, and have found that the entry time is the most sensitive measurement capable of differentiating between cell lines with differing invasiveness.

Nile Red Detection of Bacterial Hydrocarbons and Ketones in a High-Throughput Format

PubMed Central

Pinzon, Neissa M.; Aukema, Kelly G.; Gralnick, Jeffrey A.; Wackett, Lawrence P.

2011-01-01

ABSTRACT A method for use in high-throughput screening of bacteria for the production of long-chain hydrocarbons and ketones by monitoring fluorescent light emission in the presence of Nile red is described. Nile red has previously been used to screen for polyhydroxybutyrate (PHB) and fatty acid esters, but this is the first report of screening for recombinant bacteria making hydrocarbons or ketones. The microtiter plate assay was evaluated using wild-type and recombinant strains of Shewanella oneidensis and Escherichia coli expressing the enzyme OleA, previously shown to initiate hydrocarbon biosynthesis. The strains expressing exogenous Stenotrophomonas maltophilia oleA, with increased levels of ketone production as determined by gas chromatography-mass spectrometry, were distinguished with Nile red fluorescence. Confocal microscopy images of S. oneidensis oleA-expressing strains stained with Nile red were consistent with a membrane localization of the ketones. This differed from Nile red staining of bacterial PHB or algal lipid droplets that showed intracellular inclusion bodies. These results demonstrated the applicability of Nile red in a high-throughput technique for the detection of bacterial hydrocarbons and ketones. PMID:21712420

Novel Peptide Sequence (“IQ-tag”) with High Affinity for NIR Fluorochromes Allows Protein and Cell Specific Labeling for In Vivo Imaging

PubMed Central

McCarthy, Jason R.; Weissleder, Ralph

2007-01-01

Background Probes that allow site-specific protein labeling have become critical tools for visualizing biological processes. Methods Here we used phage display to identify a novel peptide sequence with nanomolar affinity for near infrared (NIR) (benz)indolium fluorochromes. The developed peptide sequence (“IQ-tag”) allows detection of NIR dyes in a wide range of assays including ELISA, flow cytometry, high throughput screens, microscopy, and optical in vivo imaging. Significance The described method is expected to have broad utility in numerous applications, namely site-specific protein imaging, target identification, cell tracking, and drug development. PMID:17653285

Imaging and identification of waterborne parasites using a chip-scale microscope.

PubMed

Lee, Seung Ah; Erath, Jessey; Zheng, Guoan; Ou, Xiaoze; Willems, Phil; Eichinger, Daniel; Rodriguez, Ana; Yang, Changhuei

2014-01-01

We demonstrate a compact portable imaging system for the detection of waterborne parasites in resource-limited settings. The previously demonstrated sub-pixel sweeping microscopy (SPSM) technique is a lens-less imaging scheme that can achieve high-resolution (<1 µm) bright-field imaging over a large field-of-view (5.7 mm×4.3 mm). A chip-scale microscope system, based on the SPSM technique, can be used for automated and high-throughput imaging of protozoan parasite cysts for the effective diagnosis of waterborne enteric parasite infection. We successfully imaged and identified three major types of enteric parasite cysts, Giardia, Cryptosporidium, and Entamoeba, which can be found in fecal samples from infected patients. We believe that this compact imaging system can serve well as a diagnostic device in challenging environments, such as rural settings or emergency outbreaks.

Extendibility of chemically amplified resists: another brick wall?

NASA Astrophysics Data System (ADS)

Hinsberg, William D.; Houle, Frances A.; Sanchez, Martha I.; Hoffnagle, John A.; Wallraff, Gregory M.; Medeiros, David R.; Gallatin, Gregg M.; Cobb, Jonathan L.

2003-06-01

The chemically amplified resist concept, first described two decades past and originally targeted for the 1000 nm device generation, has proved to have remarkable versatility. The semiconductor industry has come to rely on the properties of CA resists to achieve high resolution, high aspect ratio imaging accompanied by the high throughput that stems from their catalytic imaging mechanism. As the industry maps the evolution of lithographic technology to the 20 nm regime, it is appropriate to review the factors that control the performance of CA resists, and examine whether the traditional evolutionary path of materials refinement will provide materials capable of supporting device manufacturing at those dimensions. The impacts of image blur, line-edge roughness and shot noise on the ability to image CA resists at nanoscale dimensions will be discussed.

Clinical and laboratory applications of slide-based cytometry with the LSC, SFM, and the iCYTE imaging cytometer instruments

NASA Astrophysics Data System (ADS)

Bocsi, Jozsef; Luther, Ed; Mittag, Anja; Jensen, Ingo; Sack, Ulrich; Lenz, Dominik; Trezl, Lajos; Varga, Viktor S.; Molnar, Beea; Tarnok, Attila

2004-06-01

Background: Slide based cytometry (SBC) is a technology for the rapid stoichiometric analysis of cells fixed to surfaces. Its applications are highly versatile and ranges from the clinics to high throughput drug discovery. SBC is realized in different instruments such as the Laser Scanning Cytometer (LSC) and Scanning Fluorescent Microscope (SFM) and the novel inverted microscope based iCyte image cytometer (Compucyte Corp.). Methods: Fluorochrome labeled specimens were immobilized on microscopic slides. They were placed on a conventional fluorescence microscope and analyzed by photomultiplayers or digital camera. Data comparable to flow cytometry were generated. In addition, each individual event could be visualized. Applications: The major advantage of instruments is the combination of two features: a) the minimal sample volume needed, and b) the connection of fluorescence data and morphological information. Rare cells were detected, frequency of apoptosis by myricetin formaldehyde and H2O2 mixtures was determined;. Conclusion: LSC, SFM and the novel iCyte have a wide spectrum of applicability in SBC and can be introduced as a standard technology for multiple settings. In addition, the iCyte and SFM instrument is suited for high throughput screening by automation and may be in future adapted to telepathology due to their high quality images. (This study was supported by the IZKF-Leipzig, Germany and T 034245 OTKA, Hungary)

Polymer-Based Dense Fluidic Networks for High Throughput Screening with Ultrasensitive Fluorescence Detection

PubMed Central

Okagbare, Paul I.; Soper, Steven A.

2011-01-01

Microfluidics represents a viable platform for performing High Throughput Screening (HTS) due to its ability to automate fluid handling and generate fluidic networks with high number densities over small footprints appropriate for the simultaneous optical interrogation of many screening assays. While most HTS campaigns depend on fluorescence, readers typically use point detection and serially address the assay results significantly lowering throughput or detection sensitivity due to a low duty cycle. To address this challenge, we present here the fabrication of a high density microfluidic network packed into the imaging area of a large field-of-view (FoV) ultrasensitive fluorescence detection system. The fluidic channels were 1, 5 or 10 μm (width), 1 μm (depth) with a pitch of 1–10 μm and each fluidic processor was individually addressable. The fluidic chip was produced from a molding tool using hot embossing and thermal fusion bonding to enclose the fluidic channels. A 40X microscope objective (numerical aperture = 0.75) created a FoV of 200 μm, providing the ability to interrogate ~25 channels using the current fluidic configuration. An ultrasensitive fluorescence detection system with a large FoV was used to transduce fluorescence signals simultaneously from each fluidic processor onto the active area of an electron multiplying charge-coupled device (EMCCD). The utility of these multichannel networks for HTS was demonstrated by carrying out the high throughput monitoring of the activity of an enzyme, APE1, used as a model screening assay. PMID:20872611

Fast assembling of neuron fragments in serial 3D sections.

PubMed

Chen, Hanbo; Iascone, Daniel Maxim; da Costa, Nuno Maçarico; Lein, Ed S; Liu, Tianming; Peng, Hanchuan

2017-09-01

Reconstructing neurons from 3D image-stacks of serial sections of thick brain tissue is very time-consuming and often becomes a bottleneck in high-throughput brain mapping projects. We developed NeuronStitcher, a software suite for stitching non-overlapping neuron fragments reconstructed in serial 3D image sections. With its efficient algorithm and user-friendly interface, NeuronStitcher has been used successfully to reconstruct very large and complex human and mouse neurons.

Recent advances in MRI technology: Implications for image quality and patient safety

PubMed Central

Sobol, Wlad T.

2012-01-01

Recent advances in MRI technology are presented, with emphasis on how this new technology impacts clinical operations (better image quality, faster exam times, and improved throughput). In addition, implications for patient safety are discussed with emphasis on the risk of patient injury due to either high local specific absorption rate (SAR) or large cumulative energy doses delivered during long exam times. Patient comfort issues are examined as well. PMID:23961024

A Crowdsourcing Evaluation of the NIH Chemical Probes

PubMed Central

Oprea, Tudor I.; Bologa, Cristian G.; Boyer, Scott; Curpan, Ramona F.; Glen, Robert C.; Hopkins, Andrew L.; Lipinski, Christopher A.; Marshall, Garland R.; Martin, Yvonne C.; Ostopovici-Halip, Liliana; Rishton, Gilbert; Ursu, Oleg; Vaz, Roy J.; Waller, Chris; Waldmann, Herbert; Sklar, Larry A.

2013-01-01

Between 2004 and 2008, the NIH molecular libraries and imaging initiative (MLI) pilot phase funded ten high-throughput Screening Centers, resulting in the deposition of 691 assays into PubChem and the nomination of 64 chemical probes. We crowdsourced the MLI output to 11 experts, who expressed medium or high levels of confidence in 48 of these 64 probes. PMID:19536101

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web.

PubMed

Taylor, Stephen; Noble, Roger

2014-09-15

Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. © The Author 2014. Published by Oxford University Press.

Vortex coronagraphs for the Habitable Exoplanet Imaging Mission concept: theoretical performance and telescope requirements

NASA Astrophysics Data System (ADS)

Ruane, Garreth; Mawet, Dimitri; Mennesson, Bertrand; Jewell, Jeffrey; Shaklan, Stuart

2018-01-01

The Habitable Exoplanet Imaging Mission concept requires an optical coronagraph that provides deep starlight suppression over a broad spectral bandwidth, high throughput for point sources at small angular separation, and insensitivity to temporally varying, low-order aberrations. Vortex coronagraphs are a promising solution that performs optimally on off-axis, monolithic telescopes and may also be designed for segmented telescopes with minor losses in performance. We describe the key advantages of vortex coronagraphs on off-axis telescopes such as (1) unwanted diffraction due to aberrations is passively rejected in several low-order Zernike modes relaxing the wavefront stability requirements for imaging Earth-like planets from <10 to >100 pm rms, (2) stars with angular diameters >0.1 λ / D may be sufficiently suppressed, (3) the absolute planet throughput is >10 % , even for unfavorable telescope architectures, and (4) broadband solutions (Δλ / λ > 0.1) are readily available for both monolithic and segmented apertures. The latter make use of grayscale apodizers in an upstream pupil plane to provide suppression of diffracted light from amplitude discontinuities in the telescope pupil without inducing additional stroke on the deformable mirrors. We set wavefront stability requirements on the telescope, based on a stellar irradiance threshold set at an angular separation of 3 ± 0.5λ / D from the star, and discuss how some requirements may be relaxed by trading robustness to aberrations for planet throughput.

Goodman High Throughput Spectrograph | SOAR

Science.gov Websites

SPARTAN Near-IR Camera Ohio State Infrared Imager/Spectrograph (OSIRIS) - NO LONGER AVAILABLE SOAR 320-850 nm wavelength range. The paper describing the instrument is Clemens et al. (2004) Applying for IRAF. Publishing results based on Goodman data?: ADS link to 2004 SPIE Goodman Spectrograph paper

RootScan: Software for high-throughput analysis of root anatomical traits

USDA-ARS?s Scientific Manuscript database

RootScan is a program for semi-automated image analysis of anatomical phenes in root cross-sections. RootScan uses pixel value thresholds to separate the cross-section from its background and to visually dissect it into tissue regions. Area measurements and object counts are performed within various...

The X-ray astronomy satellite ASCA

NASA Technical Reports Server (NTRS)

Tanaka, Yasuo; Inoue, Hajime; Holt, Stephen S.

1994-01-01

Advanced Satellite for Cosmology and Astrophysics (ASCA) is a high-throughput X-ray astronomy observatory which is capable of simultaneous imaging and spectroscopic observations over a wide energy range 0.5-10 keV. The scientific capabilities of ASCA and some aspects related to its operation and observations are briefly described.

A high brightness probe of polymer nanoparticles for biological imaging

NASA Astrophysics Data System (ADS)

Zhou, Sirong; Zhu, Jiarong; Li, Yaping; Feng, Liheng

2018-03-01

Conjugated polymer nanoparticles (CPNs) with high brightness in long wavelength region were prepared by the nano-precipitation method. Based on fluorescence resonance energy transfer (FRET) mechanism, the high brightness property of the CPNs was realized by four different emission polymers. Dynamic light scattering (DLS) and scanning electron microscopy (SEM) displayed that the CPNs possessed a spherical structure and an average diameter of 75 nm. Analysis assays showed that the CPNs had excellent biocompatibility, good photostability and low cytotoxicity. The CPNs were bio-modified with a cell penetrating peptide (Tat, a targeted element) through covalent link. Based on the entire wave fluorescence emission, the functionalized CPNs1-4 can meet multichannel and high throughput assays in cell and organ imaging. The contribution of the work lies in not only providing a new way to obtain a high brightness imaging probe in long wavelength region, but also using targeted cell and organ imaging.

Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh I.; Keymeulen, Didier; Kimesh, Matthew A.

2012-01-01

Modern hyperspectral imaging systems are able to acquire far more data than can be downlinked from a spacecraft. Onboard data compression helps to alleviate this problem, but requires a system capable of power efficiency and high throughput. Software solutions have limited throughput performance and are power-hungry. Dedicated hardware solutions can provide both high throughput and power efficiency, while taking the load off of the main processor. Thus a hardware compression system was developed. The implementation uses a field-programmable gate array (FPGA). The implementation is based on the fast lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral-Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which achieves excellent compression performance and has low complexity. This algorithm performs predictive compression using an adaptive filtering method, and uses adaptive Golomb coding. The implementation also packetizes the coded data. The FL algorithm is well suited for implementation in hardware. In the FPGA implementation, one sample is compressed every clock cycle, which makes for a fast and practical realtime solution for space applications. Benefits of this implementation are: 1) The underlying algorithm achieves a combination of low complexity and compression effectiveness that exceeds that of techniques currently in use. 2) The algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. 3) Hardware acceleration provides a throughput improvement of 10 to 100 times vs. the software implementation. A prototype of the compressor is available in software, but it runs at a speed that does not meet spacecraft requirements. The hardware implementation targets the Xilinx Virtex IV FPGAs, and makes the use of this compressor practical for Earth satellites as well as beyond-Earth missions with hyperspectral instruments.

Nile Red Detection of Bacterial Hydrocarbons and Ketones in a High-Throughput Format

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinzon, NM; Aukema, KG; Gralnick, JA

A method for use in high-throughput screening of bacteria for the production of long-chain hydrocarbons and ketones by monitoring fluorescent light emission in the presence of Nile red is described. Nile red has previously been used to screen for polyhydroxybutyrate (PHB) and fatty acid esters, but this is the first report of screening for recombinant bacteria making hydrocarbons or ketones. The microtiter plate assay was evaluated using wild-type and recombinant strains of Shewanella oneidensis and Escherichia coli expressing the enzyme OleA, previously shown to initiate hydrocarbon biosynthesis. The strains expressing exogenous Stenotrophomonas maltophilia oleA, with increased levels of ketone productionmore » as determined by gas chromatography-mass spectrometry, were distinguished with Nile red fluorescence. Confocal microscopy images of S. oneidensis oleA-expressing strains stained with Nile red were consistent with a membrane localization of the ketones. This differed from Nile red staining of bacterial PHB or algal lipid droplets that showed intracellular inclusion bodies. These results demonstrated the applicability of Nile red in a high-throughput technique for the detection of bacterial hydrocarbons and ketones. IMPORTANCE In recent years, there has been renewed interest in advanced biofuel sources such as bacterial hydrocarbon production. Previous studies used solvent extraction of bacterial cultures followed by gas chromatography-mass spectrometry (GC-MS) to detect and quantify ketones and hydrocarbons (Beller HR, Goh EB, Keasling JD, Appl. Environ. Microbiol. 76: 1212-1223, 2010; Sukovich DJ, Seffernick JL, Richman JE, Gralnick JA, Wackett LP, Appl. Environ. Microbiol. 76: 3850-3862, 2010). While these analyses are powerful and accurate, their labor-intensive nature makes them intractable to high-throughput screening; therefore, methods for rapid identification of bacterial strains that are overproducing hydrocarbons are needed. The use of high-throughput evaluation of bacterial and algal hydrophobic molecule production via Nile red fluorescence from lipids and esters was extended in this study to include hydrocarbons and ketones. This work demonstrated accurate, high-throughput detection of high-level bacterial long-chain ketone and hydrocarbon production by screening for increased fluorescence of the hydrophobic dye Nile red.« less

High-Throughput Mechanobiology Screening Platform Using Micro- and Nanotopography.

PubMed

Hu, Junqiang; Gondarenko, Alexander A; Dang, Alex P; Bashour, Keenan T; O'Connor, Roddy S; Lee, Sunwoo; Liapis, Anastasia; Ghassemi, Saba; Milone, Michael C; Sheetz, Michael P; Dustin, Michael L; Kam, Lance C; Hone, James C

2016-04-13

We herein demonstrate the first 96-well plate platform to screen effects of micro- and nanotopographies on cell growth and proliferation. Existing high-throughput platforms test a limited number of factors and are not fully compatible with multiple types of testing and assays. This platform is compatible with high-throughput liquid handling, high-resolution imaging, and all multiwell plate-based instrumentation. We use the platform to screen for topographies and drug-topography combinations that have short- and long-term effects on T cell activation and proliferation. We coated nanofabricated "trench-grid" surfaces with anti-CD3 and anti-CD28 antibodies to activate T cells and assayed for interleukin 2 (IL-2) cytokine production. IL-2 secretion was enhanced at 200 nm trench width and >2.3 μm grating pitch; however, the secretion was suppressed at 100 nm width and <0.5 μm pitch. The enhancement on 200 nm grid trench was further amplified with the addition of blebbistatin to reduce contractility. The 200 nm grid pattern was found to triple the number of T cells in long-term expansion, a result with direct clinical applicability in adoptive immunotherapy.

High-Throughput Synthesis and Structure of Zeolite ZSM-43 with Two-Directional 8-Ring Channels.

PubMed

Willhammar, Tom; Su, Jie; Yun, Yifeng; Zou, Xiaodong; Afeworki, Mobae; Weston, Simon C; Vroman, Hilda B; Lonergan, William W; Strohmaier, Karl G

2017-08-07

The aluminosilicate zeolite ZSM-43 (where ZSM = Zeolite Socony Mobil) was first synthesized more than 3 decades ago, but its chemical structure remained unsolved because of its poor crystallinity and small crystal size. Here we present optimization of the ZSM-43 synthesis using a high-throughput approach and subsequent structure determination by the combination of electron crystallographic methods and powder X-ray diffraction. The synthesis required the use of a combination of both inorganic (Cs + and K + ) and organic (choline) structure-directing agents. High-throughput synthesis enabled a screening of the synthesis conditions, which made it possible to optimize the synthesis, despite its complexity, in order to obtain a material with significantly improved crystallinity. When both rotation electron diffraction and high-resolution transmission electron microscopy imaging techniques are applied, the structure of ZSM-43 could be determined. The structure of ZSM-43 is a new zeolite framework type and possesses a unique two-dimensional channel system limited by 8-ring channels. ZSM-43 is stable upon calcination, and sorption measurements show that the material is suitable for adsorption of carbon dioxide as well as methane.

Directed molecular evolution to design advanced red fluorescent proteins.

PubMed

Subach, Fedor V; Piatkevich, Kiryl D; Verkhusha, Vladislav V

2011-11-29

Fluorescent proteins have become indispensable imaging tools for biomedical research. Continuing progress in fluorescence imaging, however, requires probes with additional colors and properties optimized for emerging techniques. Here we summarize strategies for development of red-shifted fluorescent proteins. We discuss possibilities for knowledge-based rational design based on the photochemistry of fluorescent proteins and the position of the chromophore in protein structure. We consider advances in library design by mutagenesis, protein expression systems and instrumentation for high-throughput screening that should yield improved fluorescent proteins for advanced imaging applications.

Miniaturized microscope for high throughput screening of tumor spheroids in microfluidic devices

NASA Astrophysics Data System (ADS)

Uranga, Javier; Rodríguez-Pena, Alejandro; Gahigiro, Desiré; Ortiz-de-Solorzano, Carlos

2018-02-01

High-throughput in vitro screening of highly physiological three-dimensional cell cultures (3D-HTS) is rapidly gaining importance in preclinical studies, to study the effect of the microenvironment in tumor development, and to evaluate the efficacy of new anticancer drugs. Furthermore, it could also be envisioned the use of 3D-HTS systems in personalized anti-cancer treatment planning, based on tumor organoids or spheroids grown from tumor biopsies or isolated tumor circulating cells. Most commercial, multi-well plate based 3D-HTS systems are large, expensive, and are based on the use of multi-well plates that hardly provide a physiological environment and require the use of large amounts of biological material and reagents. In this paper we present a novel, miniaturized inverted microscope (hereinafter miniscospe), made up of low-cost, mass producible parts, that can be used to monitor the growth of living tumor cell spheroids within customized three-dimensional microfluidic platforms. Our 3D-HTS miniscope combines phase contrast imaging based on oblique back illumination technique with traditional widefield epi-fluorescence imaging, implemented using miniaturized electro-optical parts and gradient-index refraction lenses. This small (3x6x2cm), lightweight device can effectively image overtime the growth of (>200) tumor spheroids in a controlled and reproducible environment. Our miniscope can be used to acquire time-lapse images of cellular living spheroids over the course of several hours and captures their growth before and after drug treatment, to evaluate the effectiveness of the drug.

An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

PubMed

Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

2016-01-01

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

Diffusion tensor imaging using multiple coils for mouse brain connectomics.

PubMed

Nouls, John C; Badea, Alexandra; Anderson, Robert B J; Cofer, Gary P; Allan Johnson, G

2018-06-01

The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal-to-noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil-dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two-coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade-offs between imaging throughput and connectivity matrix integrity, studies may seek to clarify how measurement variability, post-processing techniques and biological variability impact mouse brain connectomics. Copyright © 2018 John Wiley & Sons, Ltd.

Toward a Low-Cost System for High-Throughput Image-Based Phenotyping of Root System Architecture

NASA Astrophysics Data System (ADS)

Davis, T. W.; Schneider, D. J.; Cheng, H.; Shaw, N.; Kochian, L. V.; Shaff, J. E.

2015-12-01

Root system architecture is being studied more closely for improved nutrient acquisition, stress tolerance and carbon sequestration by relating the genetic material that corresponds to preferential physical features. This information can help direct plant breeders in addressing the growing concerns regarding the global demand on crops and fossil fuels. To help support this incentive comes a need to make high-throughput image-based phenotyping of plant roots, at the individual plant scale, simpler and more affordable. Our goal is to create an affordable and portable product for simple image collection, processing and management that will extend root phenotyping to institutions with limited funding (e.g., in developing countries). Thus, a new integrated system has been developed using the Raspberry Pi single-board computer. Similar to other 3D-based imaging platforms, the system utilizes a stationary camera to photograph a rotating crop root system (e.g., rice, maize or sorghum) that is suspended either in a gel or on a mesh (for hydroponics). In contrast, the new design takes advantage of powerful open-source hardware and software to reduce the system costs, simplify the imaging process, and manage the large datasets produced by the high-resolution photographs. A newly designed graphical user interface (GUI) unifies the system controls (e.g., adjusting camera and motor settings and orchestrating the motor motion with image capture), making it easier to accommodate a variety of experiments. During each imaging session, integral metadata necessary for reproducing experiment results are collected (e.g., plant type and age, growing conditions and treatments, camera settings) using hierarchical data format files. These metadata are searchable within the GUI and can be selected and extracted for further analysis. The GUI also supports an image previewer that performs limited image processing (e.g., thresholding and cropping). Root skeletonization, 3D reconstruction and trait calculation (e.g., rooting depth, rooting angle, total volume of roots) is being developed in conjunction with this project.

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

PubMed

Perez-Sanz, Fernando; Navarro, Pedro J; Egea-Cortines, Marcos

2017-11-01

The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. © The Author 2017. Published by Oxford University Press.

Precise diagnosis in different scenarios using photoacoustic and fluorescence imaging with dual-modality nanoparticles

NASA Astrophysics Data System (ADS)

Peng, Dong; Du, Yang; Shi, Yiwen; Mao, Duo; Jia, Xiaohua; Li, Hui; Zhu, Yukun; Wang, Kun; Tian, Jie

2016-07-01

Photoacoustic imaging and fluorescence molecular imaging are emerging as important research tools for biomedical studies. Photoacoustic imaging offers both strong optical absorption contrast and high ultrasonic resolution, and fluorescence molecular imaging provides excellent superficial resolution, high sensitivity, high throughput, and the ability for real-time imaging. Therefore, combining the imaging information of both modalities can provide comprehensive in vivo physiological and pathological information. However, currently there are limited probes available that can realize both fluorescence and photoacoustic imaging, and advanced biomedical applications for applying this dual-modality imaging approach remain underexplored. In this study, we developed a dual-modality photoacoustic-fluorescence imaging nanoprobe, ICG-loaded Au@SiO2, which was uniquely designed, consisting of gold nanorod cores and indocyanine green with silica shell spacer layers to overcome fluorophore quenching. This nanoprobe was examined by both PAI and FMI for in vivo imaging on tumor and ischemia mouse models. Our results demonstrated that the nanoparticles can specifically accumulate at the tumor and ischemic areas and be detected by both imaging modalities. Moreover, this dual-modality imaging strategy exhibited superior advantages for a precise diagnosis in different scenarios. The new nanoprobe with the dual-modality imaging approach holds great potential for diagnosis and stage classification of tumor and ischemia related diseases.Photoacoustic imaging and fluorescence molecular imaging are emerging as important research tools for biomedical studies. Photoacoustic imaging offers both strong optical absorption contrast and high ultrasonic resolution, and fluorescence molecular imaging provides excellent superficial resolution, high sensitivity, high throughput, and the ability for real-time imaging. Therefore, combining the imaging information of both modalities can provide comprehensive in vivo physiological and pathological information. However, currently there are limited probes available that can realize both fluorescence and photoacoustic imaging, and advanced biomedical applications for applying this dual-modality imaging approach remain underexplored. In this study, we developed a dual-modality photoacoustic-fluorescence imaging nanoprobe, ICG-loaded Au@SiO2, which was uniquely designed, consisting of gold nanorod cores and indocyanine green with silica shell spacer layers to overcome fluorophore quenching. This nanoprobe was examined by both PAI and FMI for in vivo imaging on tumor and ischemia mouse models. Our results demonstrated that the nanoparticles can specifically accumulate at the tumor and ischemic areas and be detected by both imaging modalities. Moreover, this dual-modality imaging strategy exhibited superior advantages for a precise diagnosis in different scenarios. The new nanoprobe with the dual-modality imaging approach holds great potential for diagnosis and stage classification of tumor and ischemia related diseases. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03809c

ChiMS: Open-source instrument control software platform on LabVIEW for imaging/depth profiling mass spectrometers.

PubMed

Cui, Yang; Hanley, Luke

2015-06-01

ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science.

ChiMS: Open-source instrument control software platform on LabVIEW for imaging/depth profiling mass spectrometers

PubMed Central

Cui, Yang; Hanley, Luke

2015-01-01

ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science. PMID:26133872

ChiMS: Open-source instrument control software platform on LabVIEW for imaging/depth profiling mass spectrometers

NASA Astrophysics Data System (ADS)

Cui, Yang; Hanley, Luke

2015-06-01

ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science.

Analyzing microtomography data with Python and the scikit-image library.

PubMed

Gouillart, Emmanuelle; Nunez-Iglesias, Juan; van der Walt, Stéfan

2017-01-01

The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.

Advanced phenotyping and phenotype data analysis for the study of plant growth and development.

PubMed

Rahaman, Md Matiur; Chen, Dijun; Gillani, Zeeshan; Klukas, Christian; Chen, Ming

2015-01-01

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis.

Applying Zeeman Doppler imaging to solar spectra

NASA Astrophysics Data System (ADS)

Hussain, G. A. J.; Saar, S. H.; Collier Cameron, A.

2004-03-01

A new generation of spectro-polarimeters with high throughput (e.g. CFHT/ESPADONS and LBT/PEPSI) is becoming available. This opportunity can be exploited using Zeeman Doppler imaging (ZDI), a technique that inverts time-series of Stokes V spectra to map stellar surface magnetic fields (Semel 1989). ZDI is assisted by ``Least squares deconvolution'' (LSD), which sums up the signal from 1000's of photospheric lines to produce a mean deconvolved profile with higher S:N (Donati & Collier Cameron 1997).

Neural network control of focal position during time-lapse microscopy of cells.

PubMed

Wei, Ling; Roberts, Elijah

2018-05-09

Live-cell microscopy is quickly becoming an indispensable technique for studying the dynamics of cellular processes. Maintaining the specimen in focus during image acquisition is crucial for high-throughput applications, especially for long experiments or when a large sample is being continuously scanned. Automated focus control methods are often expensive, imperfect, or ill-adapted to a specific application and are a bottleneck for widespread adoption of high-throughput, live-cell imaging. Here, we demonstrate a neural network approach for automatically maintaining focus during bright-field microscopy. Z-stacks of yeast cells growing in a microfluidic device were collected and used to train a convolutional neural network to classify images according to their z-position. We studied the effect on prediction accuracy of the various hyperparameters of the neural network, including downsampling, batch size, and z-bin resolution. The network was able to predict the z-position of an image with ±1 μm accuracy, outperforming human annotators. Finally, we used our neural network to control microscope focus in real-time during a 24 hour growth experiment. The method robustly maintained the correct focal position compensating for 40 μm of focal drift and was insensitive to changes in the field of view. About ~100 annotated z-stacks were required to train the network making our method quite practical for custom autofocus applications.

Rapid, low dose X-ray diffractive imaging of the malaria parasite Plasmodium falciparum.

PubMed

Jones, Michael W M; Dearnley, Megan K; van Riessen, Grant A; Abbey, Brian; Putkunz, Corey T; Junker, Mark D; Vine, David J; McNulty, Ian; Nugent, Keith A; Peele, Andrew G; Tilley, Leann

2014-08-01

Phase-diverse X-ray coherent diffractive imaging (CDI) provides a route to high sensitivity and spatial resolution with moderate radiation dose. It also provides a robust solution to the well-known phase-problem, making on-line image reconstruction feasible. Here we apply phase-diverse CDI to a cellular sample, obtaining images of an erythrocyte infected by the sexual stage of the malaria parasite, Plasmodium falciparum, with a radiation dose significantly lower than the lowest dose previously reported for cellular imaging using CDI. The high sensitivity and resolution allow key biological features to be identified within intact cells, providing complementary information to optical and electron microscopy. This high throughput method could be used for fast tomographic imaging, or to generate multiple replicates in two-dimensions of hydrated biological systems without freezing or fixing. This work demonstrates that phase-diverse CDI is a valuable complementary imaging method for the biological sciences and ready for immediate application. © 2013 Elsevier B.V. All rights reserved.

Intelligent Interfaces for Mining Large-Scale RNAi-HCS Image Databases

PubMed Central

Lin, Chen; Mak, Wayne; Hong, Pengyu; Sepp, Katharine; Perrimon, Norbert

2010-01-01

Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques. PMID:21278820

LittleQuickWarp: an ultrafast image warping tool.

PubMed

Qu, Lei; Peng, Hanchuan

2015-02-01

Warping images into a standard coordinate space is critical for many image computing related tasks. However, for multi-dimensional and high-resolution images, an accurate warping operation itself is often very expensive in terms of computer memory and computational time. For high-throughput image analysis studies such as brain mapping projects, it is desirable to have high performance image warping tools that are compatible with common image analysis pipelines. In this article, we present LittleQuickWarp, a swift and memory efficient tool that boosts 3D image warping performance dramatically and at the same time has high warping quality similar to the widely used thin plate spline (TPS) warping. Compared to the TPS, LittleQuickWarp can improve the warping speed 2-5 times and reduce the memory consumption 6-20 times. We have implemented LittleQuickWarp as an Open Source plug-in program on top of the Vaa3D system (http://vaa3d.org). The source code and a brief tutorial can be found in the Vaa3D plugin source code repository. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of Novel Compounds Inhibiting Chikungunya Virus-Induced Cell Death by High Throughput Screening of a Kinase Inhibitor Library

PubMed Central

Gomes, Rafael G. B.; da Silva, Camila T.; Taniguchi, Juliana B.; No, Joo Hwan; Lombardot, Benoit; Schwartz, Olivier; Hansen, Michael A. E.; Freitas-Junior, Lucio H.

2013-01-01

Chikungunya virus (CHIKV) is a mosquito-borne arthrogenic alphavirus that causes acute febrile illness in humans accompanied by joint pains and in many cases, persistent arthralgia lasting weeks to years. The re-emergence of CHIKV has resulted in numerous outbreaks in the eastern hemisphere, and threatens to expand in the foreseeable future. Unfortunately, no effective treatment is currently available. The present study reports the use of resazurin in a cell-based high-throughput assay, and an image-based high-content assay to identify and characterize inhibitors of CHIKV-infection in vitro. CHIKV is a highly cytopathic virus that rapidly kills infected cells. Thus, cell viability of HuH-7 cells infected with CHIKV in the presence of compounds was determined by measuring metabolic reduction of resazurin to identify inhibitors of CHIKV-associated cell death. A kinase inhibitor library of 4,000 compounds was screened against CHIKV infection of HuH-7 cells using the resazurin reduction assay, and the cell toxicity was also measured in non-infected cells. Seventy-two compounds showing ≥50% inhibition property against CHIKV at 10 µM were selected as primary hits. Four compounds having a benzofuran core scaffold (CND0335, CND0364, CND0366 and CND0415), one pyrrolopyridine (CND0545) and one thiazol-carboxamide (CND3514) inhibited CHIKV-associated cell death in a dose-dependent manner, with EC50 values between 2.2 µM and 7.1 µM. Based on image analysis, these 6 hit compounds did not inhibit CHIKV replication in the host cell. However, CHIKV-infected cells manifested less prominent apoptotic blebs typical of CHIKV cytopathic effect compared with the control infection. Moreover, treatment with these compounds reduced viral titers in the medium of CHIKV-infected cells by up to 100-fold. In conclusion, this cell-based high-throughput screening assay using resazurin, combined with the image-based high content assay approach identified compounds against CHIKV having a novel antiviral activity - inhibition of virus-induced CPE - likely by targeting kinases involved in apoptosis. PMID:24205414

GiA Roots: software for the high throughput analysis of plant root system architecture.

PubMed

Galkovskyi, Taras; Mileyko, Yuriy; Bucksch, Alexander; Moore, Brad; Symonova, Olga; Price, Charles A; Topp, Christopher N; Iyer-Pascuzzi, Anjali S; Zurek, Paul R; Fang, Suqin; Harer, John; Benfey, Philip N; Weitz, Joshua S

2012-07-26

Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks. We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be extended to estimate novel phenotypes specified by the end-user. We demonstrate the use of GiA Roots on a set of 2393 images of rice roots representing 12 genotypes from the species Oryza sativa. We validate trait measurements against prior analyses of this image set that demonstrated that RSA traits are likely heritable and associated with genotypic differences. Moreover, we demonstrate that GiA Roots is extensible and an end-user can add functionality so that GiA Roots can estimate novel RSA traits. In summary, we show that the software can function as an efficient tool as part of a workflow to move from large numbers of root images to downstream analysis.

Quantification of diffusion tensor imaging in normal white matter maturation of early childhood using an automated processing pipeline.

PubMed

Loh, K B; Ramli, N; Tan, L K; Roziah, M; Rahmat, K; Ariffin, H

2012-07-01

The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.

High-speed atomic force microscopy and peak force tapping control

NASA Astrophysics Data System (ADS)

Hu, Shuiqing; Mininni, Lars; Hu, Yan; Erina, Natalia; Kindt, Johannes; Su, Chanmin

2012-03-01

ITRS Roadmap requires defect size measurement below 10 nanometers and challenging classifications for both blank and patterned wafers and masks. Atomic force microscope (AFM) is capable of providing metrology measurement in 3D at sub-nanometer accuracy but has long suffered from drawbacks in throughput and limitation of slow topography imaging without chemical information. This presentation focus on two disruptive technology developments, namely high speed AFM and quantitative nanomechanical mapping, which enables high throughput measurement with capability of identifying components through concurrent physical property imaging. The high speed AFM technology has allowed the imaging speed increase by 10-100 times without loss of the data quality. Such improvement enables the speed of defect review on a wafer to increase from a few defects per hour to nearly 100 defects an hour, approaching the requirements of ITRS Roadmap. Another technology development, Peak Force Tapping, substantially simplified the close loop system response, leading to self-optimization of most challenging samples groups to generate expert quality data. More importantly, AFM also simultaneously provides a series of mechanical property maps with a nanometer spatial resolution during defect review. These nanomechanical maps (including elastic modulus, hardness, and surface adhesion) provide complementary information for elemental analysis, differentiate defect materials by their physical properties, and assist defect classification beyond topographic measurements. This paper will explain the key enabling technologies, namely high speed tip-scanning AFM using innovative flexure design and control algorithm. Another critical element is AFM control using Peak Force Tapping, in which the instantaneous tip-sample interaction force is measured and used to derive a full suite of physical properties at each imaging pixel. We will provide examples of defect review data on different wafers and media disks. The similar AFM-based defect review capacity was also applied to EUV masks.

Fluorescence lifetime imaging system with nm-resolution and single-molecule sensitivity

NASA Astrophysics Data System (ADS)

Wahl, Michael; Rahn, Hans-Juergen; Ortmann, Uwe; Erdmann, Rainer; Boehmer, Martin; Enderlein, Joerg

2002-03-01

Fluorescence lifetime measurement of organic fluorophores is a powerful tool for distinguishing molecules of interest from background or other species. This is of interest in sensitive analysis and Single Molecule Detection (SMD). A demand in many applications is to provide 2-D imaging together with lifetime information. The method of choice is then Time-Correlated Single Photon Counting (TCSPC). We have devloped a compact system on a single PC board that can perform TCSPC at high throughput, while synchronously driving a piezo scanner holding the immobilized sample. The system allows count rates up to 3 MHz and a resolution down to 30 ps. An overall Instrument Response Function down to 300ps is achieved with inexpensive detectors and diode lasers. The board is designed for the PCI bus, permitting high throughput without loss of counts. It is reconfigurable to operate in different modes. The Time-Tagged Time-Resolved (TTTR) mode permits the recording of all photon events with a real-time tag allowing data analysis with unlimited flexibility. We use the Time-Tag clock for an external piezo scanner that moves the sample. As the clock source is common for scanning and tagging, the individual photons can be matched to pixels. Demonstrating the capablities of the system we studied single molecule solutions. Lifetime imaging can be performed at high resolution with as few as 100 photons per pixel.

Shot-noise limited throughput of soft x-ray ptychography for nanometrology applications

NASA Astrophysics Data System (ADS)

Koek, Wouter; Florijn, Bastiaan; Bäumer, Stefan; Kruidhof, Rik; Sadeghian, Hamed

2018-03-01

Due to its potential for high resolution and three-dimensional imaging, soft x-ray ptychography has received interest for nanometrology applications. We have analyzed the measurement time per unit area when using soft x-ray ptychography for various nanometrology applications including mask inspection and wafer inspection, and are thus able to predict (order of magnitude) throughput figures. Here we show that for a typical measurement system, using a typical sampling strategy, and when aiming for 10-15 nm resolution, it is expected that a wafer-based topology (2.5D) measurement takes approximately 4 minutes per μm2 , and a full three-dimensional measurement takes roughly 6 hours per μm2 . Due to their much higher reflectivity EUV masks can be measured considerably faster; a measurement speed of 0.1 seconds per μm2 is expected. However, such speeds do not allow for full wafer or mask inspection at industrially relevant throughput.

Automated imaging system for single molecules

DOEpatents

Schwartz, David Charles; Runnheim, Rodney; Forrest, Daniel

2012-09-18

There is provided a high throughput automated single molecule image collection and processing system that requires minimal initial user input. The unique features embodied in the present disclosure allow automated collection and initial processing of optical images of single molecules and their assemblies. Correct focus may be automatically maintained while images are collected. Uneven illumination in fluorescence microscopy is accounted for, and an overall robust imaging operation is provided yielding individual images prepared for further processing in external systems. Embodiments described herein are useful in studies of any macromolecules such as DNA, RNA, peptides and proteins. The automated image collection and processing system and method of same may be implemented and deployed over a computer network, and may be ergonomically optimized to facilitate user interaction.

Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

PubMed

Lee, Jia-Ying Joey; Miller, James Alastair; Basu, Sreetama; Kee, Ting-Zhen Vanessa; Loo, Lit-Hsin

2018-06-01

Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence to build an in vitro pulmonotoxicity assay by automatically comparing and selecting human lung-cell lines and their associated quantitative phenotypic features most predictive of in vivo pulmonotoxicity. This approach is called "High-throughput In vitro Phenotypic Profiling for Toxicity Prediction" (HIPPTox). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). In comparison, the predictivity of a standard cell-viability assay on the same set of chemicals is much lower (77.1% balanced accuracy, 84.6% sensitivity, and 69.5% specificity). We also used the assay to evaluate 17 additional test chemicals with unknown/unclear human pulmonotoxicity, and experimentally confirmed that many of the pulmonotoxic reference and predicted-positive test chemicals induce DNA strand breaks and/or activation of the DNA-damage response (DDR) pathway. Therefore, HIPPTox helps us to uncover these common modes-of-action of pulmonotoxic chemicals. HIPPTox may also be applied to other cell types or models, and accelerate the development of predictive in vitro assays for other cell-type- or organ-specific toxicities.

High-Throughput Quantification of GFP-LC3+ Dots by Automated Fluorescence Microscopy.

PubMed

Bravo-San Pedro, J M; Pietrocola, F; Sica, V; Izzo, V; Sauvat, A; Kepp, O; Maiuri, M C; Kroemer, G; Galluzzi, L

2017-01-01

Macroautophagy is a specific variant of autophagy that involves a dedicated double-membraned organelle commonly known as autophagosome. Various methods have been developed to quantify the size of the autophagosomal compartment, which is an indirect indicator of macroautophagic responses, based on the peculiar ability of microtubule-associated protein 1 light chain 3 beta (MAP1LC3B; best known as LC3) to accumulate in forming autophagosomes upon maturation. One particularly convenient method to monitor the accumulation of mature LC3 within autophagosomes relies on a green fluorescent protein (GFP)-tagged variant of this protein and fluorescence microscopy. In physiological conditions, cells transfected temporarily or stably with a GFP-LC3-encoding construct exhibit a diffuse green fluorescence over the cytoplasm and nucleus. Conversely, in response to macroautophagy-promoting stimuli, the GFP-LC3 signal becomes punctate and often (but not always) predominantly cytoplasmic. The accumulation of GFP-LC3 in cytoplasmic dots, however, also ensues the blockage of any of the steps that ensure the degradation of mature autophagosomes, calling for the implementation of strategies that accurately discriminate between an increase in autophagic flux and an arrest in autophagic degradation. Various cell lines have been engineered to stably express GFP-LC3, which-combined with the appropriate controls of flux, high-throughput imaging stations, and automated image analysis-offer a relatively straightforward tool to screen large chemical or biological libraries for inducers or inhibitors of autophagy. Here, we describe a simple and robust method for the high-throughput quantification of GFP-LC3 + dots by automated fluorescence microscopy. © 2017 Elsevier Inc. All rights reserved.

An Ecometric Study of Recent Microfossils using High-throughput Imaging

NASA Astrophysics Data System (ADS)

Elder, L. E.; Hull, P. M.; Hsiang, A. Y.; Kahanamoku, S.

2016-02-01

The era of Big Data has ushered in the potential to collect population level information in a manageable time frame. Taxon-free morphological trait analysis, referred to as ecometrics, can be used to examine and compare ecological dynamics between communities with entirely different species compositions. Until recently population level studies of morphology were difficult because of the time intensive task of collecting measurements. To overcome this, we implemented advances in imaging technology and created software to automate measurements. This high-throughput set of methods collects assemblage-scale data, with methods tuned to foraminiferal samples (e.g., light objects on a dark background). Methods include serial focused dark-field microscopy, custom software (Automorph) to batch process images, extract 2D and 3D shape parameters and frames, and implement landmark-free geometric morphometric analyses. Informatics pipelines were created to store, catalog and share images through the Yale Peabody Museum(YPM; peabody.yale.edu). We openly share software and images to enhance future data discovery. In less than a year we have generated over 25TB of high resolution semi 3D images for this initial study. Here, we take the first step towards developing ecometric approaches for open ocean microfossil communities with a calibration study of community shape in recent sediments. We will present an overview of the `shape' of modern planktonic foraminiferal communities from 25 Atlantic core top samples (23 sites in the North and Equatorial Atlantic; 2 sites in the South Atlantic). In total, more than 100,000 microfossils and fragments were imaged from these sites' sediment cores, an unprecedented morphometric sample set. Correlates of community shape, including diversity, temperature, and latitude, will be discussed. These methods have also been applied to images of limpets and fish teeth to date, and have the potential to be used on modern taxa to extract meaningful information on community responses to changing climate.

Digital One Disc One Compound Method for High Throughput Discovery of Prostate Cancer Targeting Ligands

DTIC Science & Technology

2016-12-01

near-infrared imaging to evaluate in vivo the tumor targeting properties of the prostate cancer ligands on xenograft models, from which in vivo...2007). (13) Rosca, E.V., Gillies, R.J. & Caplan, M.R. Glioblastoma targeting via integrins is concentration dependent. Biotechnol Bioeng 104, 408

High-throughput behavioral screening method for detecting auditory response defects in zebrafish.

PubMed

Bang, Pascal I; Yelick, Pamela C; Malicki, Jarema J; Sewell, William F

2002-08-30

We have developed an automated, high-throughput behavioral screening method for detecting hearing defects in zebrafish. Our assay monitors a rapid escape reflex in response to a loud sound. With this approach, 36 adult zebrafish, restrained in visually isolated compartments, can be simultaneously assessed for responsiveness to near-field 400 Hz sinusoidal tone bursts. Automated, objective determinations of responses are achieved with a computer program that obtains images at precise times relative to the acoustic stimulus. Images taken with a CCD video camera before and after stimulus presentation are subtracted to reveal a response to the sound. Up to 108 fish can be screened per hour. Over 6500 fish were tested to validate the reliability of the assay. We found that 1% of these animals displayed hearing deficits. The phenotypes of non-responders were further assessed with radiological analysis for defects in the gross morphology of the auditory system. Nearly all of those showed abnormalities in conductive elements of the auditory system: the swim bladder or Weberian ossicles. Copyright 2002 Elsevier Science B.V.

Performances of multiprocessor multidisk architectures for continuous media storage

NASA Astrophysics Data System (ADS)

Gennart, Benoit A.; Messerli, Vincent; Hersch, Roger D.

1996-03-01

Multimedia interfaces increase the need for large image databases, capable of storing and reading streams of data with strict synchronicity and isochronicity requirements. In order to fulfill these requirements, we consider a parallel image server architecture which relies on arrays of intelligent disk nodes, each disk node being composed of one processor and one or more disks. This contribution analyzes through bottleneck performance evaluation and simulation the behavior of two multi-processor multi-disk architectures: a point-to-point architecture and a shared-bus architecture similar to current multiprocessor workstation architectures. We compare the two architectures on the basis of two multimedia algorithms: the compute-bound frame resizing by resampling and the data-bound disk-to-client stream transfer. The results suggest that the shared bus is a potential bottleneck despite its very high hardware throughput (400Mbytes/s) and that an architecture with addressable local memories located closely to their respective processors could partially remove this bottleneck. The point- to-point architecture is scalable and able to sustain high throughputs for simultaneous compute- bound and data-bound operations.

Unsupervised automated high throughput phenotyping of RNAi time-lapse movies.

PubMed

Failmezger, Henrik; Fröhlich, Holger; Tresch, Achim

2013-10-04

Gene perturbation experiments in combination with fluorescence time-lapse cell imaging are a powerful tool in reverse genetics. High content applications require tools for the automated processing of the large amounts of data. These tools include in general several image processing steps, the extraction of morphological descriptors, and the grouping of cells into phenotype classes according to their descriptors. This phenotyping can be applied in a supervised or an unsupervised manner. Unsupervised methods are suitable for the discovery of formerly unknown phenotypes, which are expected to occur in high-throughput RNAi time-lapse screens. We developed an unsupervised phenotyping approach based on Hidden Markov Models (HMMs) with multivariate Gaussian emissions for the detection of knockdown-specific phenotypes in RNAi time-lapse movies. The automated detection of abnormal cell morphologies allows us to assign a phenotypic fingerprint to each gene knockdown. By applying our method to the Mitocheck database, we show that a phenotypic fingerprint is indicative of a gene's function. Our fully unsupervised HMM-based phenotyping is able to automatically identify cell morphologies that are specific for a certain knockdown. Beyond the identification of genes whose knockdown affects cell morphology, phenotypic fingerprints can be used to find modules of functionally related genes.

Tissue vascularization through 3D printing: Will technology bring us flow?

PubMed

Paulsen, S J; Miller, J S

2015-05-01

Though in vivo models provide the most physiologically relevant environment for studying tissue function, in vitro studies provide researchers with explicit control over experimental conditions and the potential to develop high throughput testing methods. In recent years, advancements in developmental biology research and imaging techniques have significantly improved our understanding of the processes involved in vascular development. However, the task of recreating the complex, multi-scale vasculature seen in in vivo systems remains elusive. 3D bioprinting offers a potential method to generate controlled vascular networks with hierarchical structure approaching that of in vivo networks. Bioprinting is an interdisciplinary field that relies on advances in 3D printing technology along with advances in imaging and computational modeling, which allow researchers to monitor cellular function and to better understand cellular environment within the printed tissue. As bioprinting technologies improve with regards to resolution, printing speed, available materials, and automation, 3D printing could be used to generate highly controlled vascularized tissues in a high throughput manner for use in regenerative medicine and the development of in vitro tissue models for research in developmental biology and vascular diseases. © 2015 Wiley Periodicals, Inc.

High-throughput microsphiltration to assess red blood cell deformability and screen for malaria transmission-blocking drugs.

PubMed

Duez, Julien; Carucci, Mario; Garcia-Barbazan, Irene; Corral, Matias; Perez, Oscar; Presa, Jesus Luis; Henry, Benoit; Roussel, Camille; Ndour, Papa Alioune; Rosa, Noemi Bahamontes; Sanz, Laura; Gamo, Francisco-Javier; Buffet, Pierre

2018-06-01

The mechanical retention of rigid erythrocytes in the spleen is central in major hematological diseases such as hereditary spherocytosis, sickle-cell disease and malaria. Here, we describe the use of microsphiltration (microsphere filtration) to assess erythrocyte deformability in hundreds to thousands of samples in parallel, by filtering them through microsphere layers in 384-well plates adapted for the discovery of compounds that stiffen Plasmodium falciparum gametocytes, with the aim of interrupting malaria transmission. Compound-exposed gametocytes are loaded into microsphiltration plates, filtered and then transferred to imaging plates for analysis. High-content imaging detects viable gametocytes upstream and downstream from filters and quantifies spleen-like retention. This screening assay takes 3-4 d. Unlike currently available methods used to assess red blood cell (RBC) deformability, microsphiltration enables high-throughput pharmacological screening (tens of thousands of compounds tested in a matter of months) and involves a cell mechanical challenge that induces a physiologically relevant dumbbell-shape deformation. It therefore directly assesses the ability of RBCs to cross inter-endothelial splenic slits in vivo. This protocol has potential applications in quality control for transfusion and in determination of phenotypic markers of erythrocytes in hematological diseases.

Multi-shot PROPELLER for high-field preclinical MRI

PubMed Central

Pandit, Prachi; Qi, Yi; Story, Jennifer; King, Kevin F.; Johnson, G. Allan

2012-01-01

With the development of numerous mouse models of cancer, there is a tremendous need for an appropriate imaging technique to study the disease evolution. High-field T2-weighted imaging using PROPELLER MRI meets this need. The 2-shot PROPELLER technique presented here, provides (a) high spatial resolution, (b) high contrast resolution, and (c) rapid and non-invasive imaging, which enables high-throughput, longitudinal studies in free-breathing mice. Unique data collection and reconstruction makes this method robust against motion artifacts. The 2-shot modification introduced here, retains more high-frequency information and provides higher SNR than conventional single-shot PROPELLER, making this sequence feasible at high-fields, where signal loss is rapid. Results are shown in a liver metastases model to demonstrate the utility of this technique in one of the more challenging regions of the mouse, which is the abdomen. PMID:20572138

Multishot PROPELLER for high-field preclinical MRI.

PubMed

Pandit, Prachi; Qi, Yi; Story, Jennifer; King, Kevin F; Johnson, G Allan

2010-07-01

With the development of numerous mouse models of cancer, there is a tremendous need for an appropriate imaging technique to study the disease evolution. High-field T(2)-weighted imaging using PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI meets this need. The two-shot PROPELLER technique presented here provides (a) high spatial resolution, (b) high contrast resolution, and (c) rapid and noninvasive imaging, which enables high-throughput, longitudinal studies in free-breathing mice. Unique data collection and reconstruction makes this method robust against motion artifacts. The two-shot modification introduced here retains more high-frequency information and provides higher signal-to-noise ratio than conventional single-shot PROPELLER, making this sequence feasible at high fields, where signal loss is rapid. Results are shown in a liver metastases model to demonstrate the utility of this technique in one of the more challenging regions of the mouse, which is the abdomen. (c) 2010 Wiley-Liss, Inc.

OPTICAL PROCESSING OF INFORMATION: Multistage optoelectronic two-dimensional image switches

NASA Astrophysics Data System (ADS)

Fedorov, V. B.

1994-06-01

The implementation principles and the feasibility of construction of high-throughput multistage optoelectronic switches, capable of transmitting data in the form of two-dimensional images along interconnected pairs of optical channels, are considered. Different ways of realising compact switches are proposed. They are based on the use of polarisation-sensitive elements, arrays of modulators of the plane of polarisation of light, arrays of objectives, and free-space optics. Optical systems of such switches can theoretically ensure that the resolution and optical losses in two-dimensional image transmission are limited only by diffraction. Estimates are obtained of the main maximum-performance parameters of the proposed optoelectronic image switches.

Phase imaging of mechanical properties of live cells (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wax, Adam

2017-02-01

The mechanisms by which cells respond to mechanical stimuli are essential for cell function yet not well understood. Many rheological tools have been developed to characterize cellular viscoelastic properties but these typically require direct mechanical contact, limiting their throughput. We have developed a new approach for characterizing the organization of subcellular structures using a label free, noncontact, single-shot phase imaging method that correlates to measured cellular mechanical stiffness. The new analysis approach measures refractive index variance and relates it to disorder strength. These measurements are compared to cellular stiffness, measured using the same imaging tool to visualize nanoscale responses to flow shear stimulus. The utility of the technique is shown by comparing shear stiffness and phase disorder strength across five cellular populations with varying mechanical properties. An inverse relationship between disorder strength and shear stiffness is shown, suggesting that cell mechanical properties can be assessed in a format amenable to high throughput studies using this novel, non-contact technique. Further studies will be presented which include examination of mechanical stiffness in early carcinogenic events and investigation of the role of specific cellular structural proteins in mechanotransduction.

Real-time image processing for label-free enrichment of Actinobacteria cultivated in picolitre droplets.

PubMed

Zang, Emerson; Brandes, Susanne; Tovar, Miguel; Martin, Karin; Mech, Franziska; Horbert, Peter; Henkel, Thomas; Figge, Marc Thilo; Roth, Martin

2013-09-21

The majority of today's antimicrobial therapeutics is derived from secondary metabolites produced by Actinobacteria. While it is generally assumed that less than 1% of Actinobacteria species from soil habitats have been cultivated so far, classic screening approaches fail to supply new substances, often due to limited throughput and frequent rediscovery of already known strains. To overcome these restrictions, we implement high-throughput cultivation of soil-derived Actinobacteria in microfluidic pL-droplets by generating more than 600,000 pure cultures per hour from a spore suspension that can subsequently be incubated for days to weeks. Moreover, we introduce triggered imaging with real-time image-based droplet classification as a novel universal method for pL-droplet sorting. Growth-dependent droplet sorting at frequencies above 100 Hz is performed for label-free enrichment and extraction of microcultures. The combination of both cultivation of Actinobacteria in pL-droplets and real-time detection of growing Actinobacteria has great potential in screening for yet unknown species as well as their undiscovered natural products.

Fuzzy Logic-based expert system for evaluating cake quality of freeze-dried formulations.

PubMed

Trnka, Hjalte; Wu, Jian X; Van De Weert, Marco; Grohganz, Holger; Rantanen, Jukka

2013-12-01

Freeze-drying of peptide and protein-based pharmaceuticals is an increasingly important field of research. The diverse nature of these compounds, limited understanding of excipient functionality, and difficult-to-analyze quality attributes together with the increasing importance of the biosimilarity concept complicate the development phase of safe and cost-effective drug products. To streamline the development phase and to make high-throughput formulation screening possible, efficient solutions for analyzing critical quality attributes such as cake quality with minimal material consumption are needed. The aim of this study was to develop a fuzzy logic system based on image analysis (IA) for analyzing cake quality. Freeze-dried samples with different visual quality attributes were prepared in well plates. Imaging solutions together with image analytical routines were developed for extracting critical visual features such as the degree of cake collapse, glassiness, and color uniformity. On the basis of the IA outputs, a fuzzy logic system for analysis of these freeze-dried cakes was constructed. After this development phase, the system was tested with a new screening well plate. The developed fuzzy logic-based system was found to give comparable quality scores with visual evaluation, making high-throughput classification of cake quality possible. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

High-throughput flow alignment of barcoded hydrogel microparticles†

PubMed Central

Chapin, Stephen C.; Pregibon, Daniel C.

2010-01-01

Suspension (particle-based) arrays offer several advantages over conventional planar arrays in the detection and quantification of biomolecules, including the use of smaller sample volumes, more favorable probe-target binding kinetics, and rapid probe-set modification. We present a microfluidic system for the rapid alignment of multifunctional hydrogel microparticles designed to bear one or several biomolecule probe regions, as well as a graphical code to identify the embedded probes. Using high-speed imaging, we have developed and optimized a flow-through system that (1) allows for a high particle throughput, (2) ensures proper particle alignment for decoding and target quantification, and (3) can be reliably operated continuously without clogging. A tapered channel flanked by side focusing streams is used to orient the flexible, tablet-shaped particles into a well-ordered flow in the center of the channel. The effects of channel geometry, particle geometry, particle composition, particle loading density, and barcode design are explored to determine the best combination for eventual use in biological assays. Particles in the optimized system move at velocities of ~50 cm s−1 and with throughputs of ~40 particles s−1. Simple physical models and CFD simulations have been used to investigate flow behavior in the device. PMID:19823726

Experimental Study of an Advanced Concept of Moderate-resolution Holographic Spectrographs

NASA Astrophysics Data System (ADS)

Muslimov, Eduard; Valyavin, Gennady; Fabrika, Sergei; Musaev, Faig; Galazutdinov, Gazinur; Pavlycheva, Nadezhda; Emelianov, Eduard

2018-07-01

We present the results of an experimental study of an advanced moderate-resolution spectrograph based on a cascade of narrow-band holographic gratings. The main goal of the project is to achieve a moderately high spectral resolution with R up to 5000 simultaneously in the 4300–6800 Å visible spectral range on a single standard CCD, together with an increased throughput. The experimental study consisted of (1) resolution and image quality tests performed using the solar spectrum, and (2) a total throughput test performed for a number of wavelengths using a calibrated lab monochromator. The measured spectral resolving power reaches values over R > 4000 while the experimental throughput is as high as 55%, which agrees well with the modeling results. Comparing the obtained characteristics of the spectrograph under consideration with the best existing spectrographs, we conclude that the used concept can be considered as a very competitive and cheap alternative to the existing spectrographs of the given class. We propose several astrophysical applications for the instrument and discuss the prospect of creating its full-scale version.

PREVAIL: IBM's e-beam technology for next generation lithography

NASA Astrophysics Data System (ADS)

Pfeiffer, Hans C.

2000-07-01

PREVAIL - Projection Reduction Exposure with Variable Axis Immersion Lenses represents the high throughput e-beam projection approach to NGL which IBM is pursuing in cooperation with Nikon Corporation as alliance partner. This paper discusses the challenges and accomplishments of the PREVAIL project. The supreme challenge facing all e-beam lithography approaches has been and still is throughput. Since the throughput of e-beam projection systems is severely limited by the available optical field size, the key to success is the ability to overcome this limitation. The PREVAIL technique overcomes field-limiting off-axis aberrations through the use of variable axis lenses, which electronically shift the optical axis simultaneously with the deflected beam so that the beam effectively remains on axis. The resist images obtained with the Proof-of-Concept (POC) system demonstrate that PREVAIL effectively eliminates off- axis aberrations affecting both resolution and placement accuracy of pixels. As part of the POC system a high emittance gun has been developed to provide uniform illumination of the patterned subfield and to fill the large numerical aperture projection optics designed to significantly reduce beam blur caused by Coulomb interaction.

Precision production: enabling deterministic throughput for precision aspheres with MRF

NASA Astrophysics Data System (ADS)

Maloney, Chris; Entezarian, Navid; Dumas, Paul

2017-10-01

Aspherical lenses offer advantages over spherical optics by improving image quality or reducing the number of elements necessary in an optical system. Aspheres are no longer being used exclusively by high-end optical systems but are now replacing spherical optics in many applications. The need for a method of production-manufacturing of precision aspheres has emerged and is part of the reason that the optics industry is shifting away from artisan-based techniques towards more deterministic methods. Not only does Magnetorheological Finishing (MRF) empower deterministic figure correction for the most demanding aspheres but it also enables deterministic and efficient throughput for series production of aspheres. The Q-flex MRF platform is designed to support batch production in a simple and user friendly manner. Thorlabs routinely utilizes the advancements of this platform and has provided results from using MRF to finish a batch of aspheres as a case study. We have developed an analysis notebook to evaluate necessary specifications for implementing quality control metrics. MRF brings confidence to optical manufacturing by ensuring high throughput for batch processing of aspheres.

Ultra-high throughput real-time instruments for capturing fast signals and rare events

NASA Astrophysics Data System (ADS)

Buckley, Brandon Walter

Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and processing. The act of time-stretching effectively boosts the performance of the back-end electronics and digital signal processors. The slowed down signals reach the back-end electronics with reduced bandwidth, and are therefore less affected by high-frequency roll-off and distortion. Time-stretching also increases the effective sampling rate of analog-to-digital converters and reduces aperture jitter, thereby improving resolution. Finally, the instantaneous throughputs of digital signal processors are enhanced by the stretch factor to otherwise unattainable speeds. Leveraging these unique capabilities, TiSER becomes the ideal tool for capturing high-speed signals and characterizing rare phenomena. For this thesis, I have developed techniques to improve the spectral efficiency, bandwidth, and resolution of TiSER using polarization multiplexing, all-optical modulation, and coherent dispersive Fourier transformation. To reduce the latency and improve the data handling capacity, I have also designed and implemented a real-time digital signal processing electronic backend, achieving 1.5 tera-bit per second instantaneous processing throughput. Finally, I will present results from experiments highlighting TiSER's impact in real-world applications. Confocal fluorescence microscopy is the most widely used method for unveiling the molecular composition of biological specimens. However, the weak optical emission of fluorescent probes and the tradeoff between imaging speed and sensitivity is problematic for acquiring blur-free images of fast phenomena and cells flowing at high speed. Here I introduce a new fluorescence imaging modality, which leverages techniques from wireless communication to reach record pixel and frame rates. Termed Fluorescence Imaging using Radio-frequency tagged Emission (FIRE), this new imaging modality is capable of resolving never before seen dynamics in living cells - such as action potentials in neurons and metabolic waves in astrocytes - as well as performing high-content image assays of cells and particles in high-speed flow.

Review of high fidelity imaging spectrometer design for remote sensing

NASA Astrophysics Data System (ADS)

Mouroulis, Pantazis; Green, Robert O.

2018-04-01

We review the design and assessment techniques that underlie a number of successfully deployed space and airborne imaging spectrometers that have been demonstrated to achieve demanding specifications in terms of throughput and response uniformity. The principles are illustrated with telescope designs as well as spectrometer examples from the Offner and Dyson families. We also show how the design space can be extended with the use of freeform surfaces and provide additional design examples with grating as well as prism dispersive elements.

Computational efficient segmentation of cell nuclei in 2D and 3D fluorescent micrographs

NASA Astrophysics Data System (ADS)

De Vylder, Jonas; Philips, Wilfried

2011-02-01

This paper proposes a new segmentation technique developed for the segmentation of cell nuclei in both 2D and 3D fluorescent micrographs. The proposed method can deal with both blurred edges as with touching nuclei. Using a dual scan line algorithm its both memory as computational efficient, making it interesting for the analysis of images coming from high throughput systems or the analysis of 3D microscopic images. Experiments show good results, i.e. recall of over 0.98.

Optimizing ultrafast wide field-of-view illumination for high-throughput multi-photon imaging and screening of mutant fluorescent proteins

NASA Astrophysics Data System (ADS)

Stoltzfus, Caleb; Mikhailov, Alexandr; Rebane, Aleksander

2017-02-01

Fluorescence induced by 1wo-photon absorption (2PA) and three-photon absorption (3PA) is becoming an increasingly important tool for deep-tissue microscopy, especially in conjunction with genetically-encoded functional probes such as fluorescent proteins (FPs). Unfortunately, the efficacy of the multi-photon excitation of FPs is notoriously low, and because relations between a biological fluorophore's nonlinear-optical properties and its molecular structure are inherently complex, there are no practical avenues available that would allow boosting the performance of current FPs. Here we describe a novel method, where we apply directed evolution to optimize the 2PA properties of EGFP. Key to the success of this approach consists in high-throughput screening of mutants that would allow selection of variants with promising 2PA and 3PA properties in a broad near-IR excitation range of wavelength. For this purpose, we construct and test a wide field-of-view (FOV), femtosecond imaging system that we then use to quantify the multi-photon excited fluorescence in the 550- 1600 nm range of tens of thousands of E. coli colonies expressing randomly mutated FPs in a standard 10 cm diameter Petri dish configuration. We present a quantitative analysis of different factors that are currently limiting the maximum throughput of the femtosecond multi-photon screening techniques and also report on quantitative measurement of absolute 2PA and 3PA cross sections spectra.

(abstract) A High Throughput 3-D Inner Product Processor

NASA Technical Reports Server (NTRS)

Daud, Tuan

1996-01-01

A particularily challenging image processing application is the real time scene acquisition and object discrimination. It requires spatio-temporal recognition of point and resolved objects at high speeds with parallel processing algorithms. Neural network paradigms provide fine grain parallism and, when implemented in hardware, offer orders of magnitude speed up. However, neural networks implemented on a VLSI chip are planer architectures capable of efficient processing of linear vector signals rather than 2-D images. Therefore, for processing of images, a 3-D stack of neural-net ICs receiving planar inputs and consuming minimal power are required. Details of the circuits with chip architectures will be described with need to develop ultralow-power electronics. Further, use of the architecture in a system for high-speed processing will be illustrated.

Applications of Molecular Imaging

PubMed Central

Galbán, Craig; Galbán, Stefanie; Van Dort, Marcian; Luker, Gary D.; Bhojani, Mahaveer S.; Rehemtualla, Alnawaz; Ross, Brian D.

2015-01-01

Today molecular imaging technologies play a central role in clinical oncology. The use of imaging techniques in early cancer detection, treatment response and new therapy development is steadily growing and has already significantly impacted clinical management of cancer. In this chapter we will overview three different molecular imaging technologies used for the understanding of disease biomarkers, drug development, or monitoring therapeutic outcome. They are (1) optical imaging (bioluminescence and fluorescence imaging) (2) magnetic resonance imaging (MRI), and (3) nuclear imaging (e.g, single photon emission computed tomography (SPECT) and positron emission tomography (PET)). We will review the use of molecular reporters of biological processes (e.g. apoptosis and protein kinase activity) for high throughput drug screening and new cancer therapies, diffusion MRI as a biomarker for early treatment response and PET and SPECT radioligands in oncology. PMID:21075334

Radiomics: Extracting more information from medical images using advanced feature analysis

PubMed Central

Lambin, Philippe; Rios-Velazquez, Emmanuel; Leijenaar, Ralph; Carvalho, Sara; van Stiphout, Ruud G.P.M.; Granton, Patrick; Zegers, Catharina M.L.; Gillies, Robert; Boellard, Ronald; Dekker, André; Aerts, Hugo J.W.L.

2015-01-01

Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics – the high-throughput extraction of large amounts of image features from radiographic images – addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory. PMID:22257792

Numerical techniques for high-throughput reflectance interference biosensing

NASA Astrophysics Data System (ADS)

Sevenler, Derin; Ünlü, M. Selim

2016-06-01

We have developed a robust and rapid computational method for processing the raw spectral data collected from thin film optical interference biosensors. We have applied this method to Interference Reflectance Imaging Sensor (IRIS) measurements and observed a 10,000 fold improvement in processing time, unlocking a variety of clinical and scientific applications. Interference biosensors have advantages over similar technologies in certain applications, for example highly multiplexed measurements of molecular kinetics. However, processing raw IRIS data into useful measurements has been prohibitively time consuming for high-throughput studies. Here we describe the implementation of a lookup table (LUT) technique that provides accurate results in far less time than naive methods. We also discuss an additional benefit that the LUT method can be used with a wider range of interference layer thickness and experimental configurations that are incompatible with methods that require fitting the spectral response.

High Content Screening of a Kinase-Focused Library Reveals Compounds Broadly-Active against Dengue Viruses

PubMed Central

Li, Xiaolan; Milan Bonotto, Rafaela; No, Joo Hwan; Kim, Keum Hyun; Baek, Sungmin; Kim, Hee Young; Windisch, Marc Peter; Pamplona Mosimann, Ana Luiza; de Borba, Luana; Liuzzi, Michel; Hansen, Michael Adsetts Edberg; Nunes Duarte dos Santos, Claudia; Freitas-Junior, Lucio Holanda

2013-01-01

Dengue virus is a mosquito-borne flavivirus that has a large impact in global health. It is considered as one of the medically important arboviruses, and developing a preventive or therapeutic solution remains a top priority in the medical and scientific community. Drug discovery programs for potential dengue antivirals have increased dramatically over the last decade, largely in part to the introduction of high-throughput assays. In this study, we have developed an image-based dengue high-throughput/high-content assay (HT/HCA) using an innovative computer vision approach to screen a kinase-focused library for anti-dengue compounds. Using this dengue HT/HCA, we identified a group of compounds with a 4-(1-aminoethyl)-N-methylthiazol-2-amine as a common core structure that inhibits dengue viral infection in a human liver-derived cell line (Huh-7.5 cells). Compounds CND1201, CND1203 and CND1243 exhibited strong antiviral activities against all four dengue serotypes. Plaque reduction and time-of-addition assays suggests that these compounds interfere with the late stage of viral infection cycle. These findings demonstrate that our image-based dengue HT/HCA is a reliable tool that can be used to screen various chemical libraries for potential dengue antiviral candidates. PMID:23437413

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

Molecular and Cellular Quantitative Microscopy: theoretical investigations, technological developments and applications to neurobiology

NASA Astrophysics Data System (ADS)

Esposito, Alessandro

2006-05-01

This PhD project aims at the development and evaluation of microscopy techniques for the quantitative detection of molecular interactions and cellular features. The primarily investigated techniques are Fαrster Resonance Energy Transfer imaging and Fluorescence Lifetime Imaging Microscopy. These techniques have the capability to quantitatively probe the biochemical environment of fluorophores. An automated microscope capable of unsupervised operation has been developed that enables the investigation of molecular and cellular properties at high throughput levels and the analysis of cellular heterogeneity. State-of-the-art Förster Resonance Energy Transfer imaging, Fluorescence Lifetime Imaging Microscopy, Confocal Laser Scanning Microscopy and the newly developed tools have been combined with cellular and molecular biology techniques for the investigation of protein-protein interactions, oligomerization and post-translational modifications of α-Synuclein and Tau, two proteins involved in Parkinson’s and Alzheimer’s disease, respectively. The high inter-disciplinarity of this project required the merging of the expertise of both the Molecular Biophysics Group at the Debye Institute - Utrecht University and the Cell Biophysics Group at the European Neuroscience Institute - Gαttingen University. This project was conducted also with the support and the collaboration of the Center for the Molecular Physiology of the Brain (Göttingen), particularly with the groups associated with the Molecular Quantitative Microscopy and Parkinson’s Disease and Aggregopathies areas. This work demonstrates that molecular and cellular quantitative microscopy can be used in combination with high-throughput screening as a powerful tool for the investigation of the molecular mechanisms of complex biological phenomena like those occurring in neurodegenerative diseases.

CellAnimation: an open source MATLAB framework for microscopy assays.

PubMed

Georgescu, Walter; Wikswo, John P; Quaranta, Vito

2012-01-01

Advances in microscopy technology have led to the creation of high-throughput microscopes that are capable of generating several hundred gigabytes of images in a few days. Analyzing such wealth of data manually is nearly impossible and requires an automated approach. There are at present a number of open-source and commercial software packages that allow the user to apply algorithms of different degrees of sophistication to the images and extract desired metrics. However, the types of metrics that can be extracted are severely limited by the specific image processing algorithms that the application implements, and by the expertise of the user. In most commercial software, code unavailability prevents implementation by the end user of newly developed algorithms better suited for a particular type of imaging assay. While it is possible to implement new algorithms in open-source software, rewiring an image processing application requires a high degree of expertise. To obviate these limitations, we have developed an open-source high-throughput application that allows implementation of different biological assays such as cell tracking or ancestry recording, through the use of small, relatively simple image processing modules connected into sophisticated imaging pipelines. By connecting modules, non-expert users can apply the particular combination of well-established and novel algorithms developed by us and others that are best suited for each individual assay type. In addition, our data exploration and visualization modules make it easy to discover or select specific cell phenotypes from a heterogeneous population. CellAnimation is distributed under the Creative Commons Attribution-NonCommercial 3.0 Unported license (http://creativecommons.org/licenses/by-nc/3.0/). CellAnimationsource code and documentation may be downloaded from www.vanderbilt.edu/viibre/software/documents/CellAnimation.zip. Sample data are available at www.vanderbilt.edu/viibre/software/documents/movies.zip. walter.georgescu@vanderbilt.edu Supplementary data available at Bioinformatics online.

Sparse models for correlative and integrative analysis of imaging and genetic data

PubMed Central

Lin, Dongdong; Cao, Hongbao; Calhoun, Vince D.

2014-01-01

The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis. PMID:25218561

Design of a dataway processor for a parallel image signal processing system

NASA Astrophysics Data System (ADS)

Nomura, Mitsuru; Fujii, Tetsuro; Ono, Sadayasu

1995-04-01

Recently, demands for high-speed signal processing have been increasing especially in the field of image data compression, computer graphics, and medical imaging. To achieve sufficient power for real-time image processing, we have been developing parallel signal-processing systems. This paper describes a communication processor called 'dataway processor' designed for a new scalable parallel signal-processing system. The processor has six high-speed communication links (Dataways), a data-packet routing controller, a RISC CORE, and a DMA controller. Each communication link operates at 8-bit parallel in a full duplex mode at 50 MHz. Moreover, data routing, DMA, and CORE operations are processed in parallel. Therefore, sufficient throughput is available for high-speed digital video signals. The processor is designed in a top- down fashion using a CAD system called 'PARTHENON.' The hardware is fabricated using 0.5-micrometers CMOS technology, and its hardware is about 200 K gates.

High-speed laser microsurgery of alert fruit flies for fluorescence imaging of neural activity

PubMed Central

Sinha, Supriyo; Liang, Liang; Ho, Eric T. W.; Urbanek, Karel E.; Luo, Liqun; Baer, Thomas M.; Schnitzer, Mark J.

2013-01-01

Intravital microscopy is a key means of monitoring cellular function in live organisms, but surgical preparation of a live animal for microscopy often is time-consuming, requires considerable skill, and limits experimental throughput. Here we introduce a spatially precise (<1-µm edge precision), high-speed (<1 s), largely automated, and economical protocol for microsurgical preparation of live animals for optical imaging. Using a 193-nm pulsed excimer laser and the fruit fly as a model, we created observation windows (12- to 350-µm diameters) in the exoskeleton. Through these windows we used two-photon microscopy to image odor-evoked Ca2+ signaling in projection neuron dendrites of the antennal lobe and Kenyon cells of the mushroom body. The impact of a laser-cut window on fly health appears to be substantially less than that of conventional manual dissection, for our imaging durations of up to 18 h were ∼5–20 times longer than prior in vivo microscopy studies of hand-dissected flies. This improvement will facilitate studies of numerous questions in neuroscience, such as those regarding neuronal plasticity or learning and memory. As a control, we used phototaxis as an exemplary complex behavior in flies and found that laser microsurgery is sufficiently gentle to leave it intact. To demonstrate that our techniques are applicable to other species, we created microsurgical openings in nematodes, ants, and the mouse cranium. In conjunction with emerging robotic methods for handling and mounting flies or other small organisms, our rapid, precisely controllable, and highly repeatable microsurgical techniques should enable automated, high-throughput preparation of live animals for optical experimentation. PMID:24167298

Hierarchical classification strategy for Phenotype extraction from epidermal growth factor receptor endocytosis screening.

PubMed

Cao, Lu; Graauw, Marjo de; Yan, Kuan; Winkel, Leah; Verbeek, Fons J

2016-05-03

Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system. In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated. The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes.

Maximizing the quantitative accuracy and reproducibility of Förster resonance energy transfer measurement for screening by high throughput widefield microscopy

PubMed Central

Schaufele, Fred

2013-01-01

Förster resonance energy transfer (FRET) between fluorescent proteins (FPs) provides insights into the proximities and orientations of FPs as surrogates of the biochemical interactions and structures of the factors to which the FPs are genetically fused. As powerful as FRET methods are, technical issues have impeded their broad adoption in the biologic sciences. One hurdle to accurate and reproducible FRET microscopy measurement stems from variable fluorescence backgrounds both within a field and between different fields. Those variations introduce errors into the precise quantification of fluorescence levels on which the quantitative accuracy of FRET measurement is highly dependent. This measurement error is particularly problematic for screening campaigns since minimal well-to-well variation is necessary to faithfully identify wells with altered values. High content screening depends also upon maximizing the numbers of cells imaged, which is best achieved by low magnification high throughput microscopy. But, low magnification introduces flat-field correction issues that degrade the accuracy of background correction to cause poor reproducibility in FRET measurement. For live cell imaging, fluorescence of cell culture media in the fluorescence collection channels for the FPs commonly used for FRET analysis is a high source of background error. These signal-to-noise problems are compounded by the desire to express proteins at biologically meaningful levels that may only be marginally above the strong fluorescence background. Here, techniques are presented that correct for background fluctuations. Accurate calculation of FRET is realized even from images in which a non-flat background is 10-fold higher than the signal. PMID:23927839

Non-destructive Determination of Shikimic Acid Concentration in Transgenic Maize Exhibiting Glyphosate Tolerance Using Chlorophyll Fluorescence and Hyperspectral Imaging

PubMed Central

Feng, Xuping; Yu, Chenliang; Chen, Yue; Peng, Jiyun; Ye, Lanhan; Shen, Tingting; Wen, Haiyong; He, Yong

2018-01-01

The development of transgenic glyphosate-tolerant crops has revolutionized weed control in crops in many regions of the world. The early, non-destructive identification of superior plant phenotypes is an important stage in plant breeding programs. Here, glyphosate-tolerant transgenic maize and its parental wild-type control were studied at 2, 4, 6, and 8 days after glyphosate treatment. Visible and near-infrared hyperspectral imaging and chlorophyll fluorescence imaging techniques were applied to monitor the performance of plants. In our research, transgenic maize, which was highly tolerant to glyphosate, was phenotyped using these high-throughput non-destructive methods to validate low levels of shikimic acid accumulation and high photochemical efficiency of photosystem II as reflected by maximum quantum yield and non-photochemical quenching in response to glyphosate. For hyperspectral imaging analysis, the combination of spectroscopy and chemometric methods was used to predict shikimic acid concentration. Our results indicated that a partial least-squares regression model, built on optimal wavelengths, effectively predicted shikimic acid concentrations, with a coefficient of determination value of 0.79 for the calibration set, and 0.82 for the prediction set. Moreover, shikimic acid concentration estimates from hyperspectral images were visualized on the prediction maps by spectral features, which could help in developing a simple multispectral imaging instrument for non-destructive phenotyping. Specific physiological effects of glyphosate affected the photochemical processes of maize, which induced substantial changes in chlorophyll fluorescence characteristics. A new data-driven method, combining mean fluorescence parameters and featuring a screening approach, provided a satisfactory relationship between fluorescence parameters and shikimic acid content. The glyphosate-tolerant transgenic plants can be identified with the developed discrimination model established on important wavelengths or sensitive fluorescence parameters 6 days after glyphosate treatment. The overall results indicated that both hyperspectral imaging and chlorophyll fluorescence imaging techniques could provide useful tools for stress phenotyping in maize breeding programs and could enable the detection and evaluation of superior genotypes, such as glyphosate tolerance, with a non-destructive high-throughput technique. PMID:29686693

Non-destructive Determination of Shikimic Acid Concentration in Transgenic Maize Exhibiting Glyphosate Tolerance Using Chlorophyll Fluorescence and Hyperspectral Imaging.

PubMed

Feng, Xuping; Yu, Chenliang; Chen, Yue; Peng, Jiyun; Ye, Lanhan; Shen, Tingting; Wen, Haiyong; He, Yong

2018-01-01

The development of transgenic glyphosate-tolerant crops has revolutionized weed control in crops in many regions of the world. The early, non-destructive identification of superior plant phenotypes is an important stage in plant breeding programs. Here, glyphosate-tolerant transgenic maize and its parental wild-type control were studied at 2, 4, 6, and 8 days after glyphosate treatment. Visible and near-infrared hyperspectral imaging and chlorophyll fluorescence imaging techniques were applied to monitor the performance of plants. In our research, transgenic maize, which was highly tolerant to glyphosate, was phenotyped using these high-throughput non-destructive methods to validate low levels of shikimic acid accumulation and high photochemical efficiency of photosystem II as reflected by maximum quantum yield and non-photochemical quenching in response to glyphosate. For hyperspectral imaging analysis, the combination of spectroscopy and chemometric methods was used to predict shikimic acid concentration. Our results indicated that a partial least-squares regression model, built on optimal wavelengths, effectively predicted shikimic acid concentrations, with a coefficient of determination value of 0.79 for the calibration set, and 0.82 for the prediction set. Moreover, shikimic acid concentration estimates from hyperspectral images were visualized on the prediction maps by spectral features, which could help in developing a simple multispectral imaging instrument for non-destructive phenotyping. Specific physiological effects of glyphosate affected the photochemical processes of maize, which induced substantial changes in chlorophyll fluorescence characteristics. A new data-driven method, combining mean fluorescence parameters and featuring a screening approach, provided a satisfactory relationship between fluorescence parameters and shikimic acid content. The glyphosate-tolerant transgenic plants can be identified with the developed discrimination model established on important wavelengths or sensitive fluorescence parameters 6 days after glyphosate treatment. The overall results indicated that both hyperspectral imaging and chlorophyll fluorescence imaging techniques could provide useful tools for stress phenotyping in maize breeding programs and could enable the detection and evaluation of superior genotypes, such as glyphosate tolerance, with a non-destructive high-throughput technique.

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

DOE PAGES

Ozturk, Hande; Yan, Hanfei; He, Yan; ...

2018-05-09

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ozturk, Hande; Yan, Hanfei; He, Yan

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

Low-Cost, High-Throughput 3D Pulmonary Imager Using Hyperpolarized Contrast Agents and Low-Field MRI

DTIC Science & Technology

2016-10-01

COMMUNITIES OF INTEREST? ................................................. 8 4. IMPACT...publicize the work performed and also for their exposure to biomedical science. How were the results disseminated to communities of interest? Nothing...biomedical community , expanding the utility of HP methods as a new tool for probing fundamental biomedical questions. Acknowledgments The authors thank

"First generation" automated DNA sequencing technology.

PubMed

Slatko, Barton E; Kieleczawa, Jan; Ju, Jingyue; Gardner, Andrew F; Hendrickson, Cynthia L; Ausubel, Frederick M

2011-10-01

Beginning in the 1980s, automation of DNA sequencing has greatly increased throughput, reduced costs, and enabled large projects to be completed more easily. The development of automation technology paralleled the development of other aspects of DNA sequencing: better enzymes and chemistry, separation and imaging technology, sequencing protocols, robotics, and computational advancements (including base-calling algorithms with quality scores, database developments, and sequence analysis programs). Despite the emergence of high-throughput sequencing platforms, automated Sanger sequencing technology remains useful for many applications. This unit provides background and a description of the "First-Generation" automated DNA sequencing technology. It also includes protocols for using the current Applied Biosystems (ABI) automated DNA sequencing machines. © 2011 by John Wiley & Sons, Inc.

Digital micromirror device-based laser-illumination Fourier ptychographic microscopy

PubMed Central

Kuang, Cuifang; Ma, Ye; Zhou, Renjie; Lee, Justin; Barbastathis, George; Dasari, Ramachandra R.; Yaqoob, Zahid; So, Peter T. C.

2015-01-01

We report a novel approach to Fourier ptychographic microscopy (FPM) by using a digital micromirror device (DMD) and a coherent laser source (532 nm) for generating spatially modulated sample illumination. Previously demonstrated FPM systems are all based on partially-coherent illumination, which offers limited throughput due to insufficient brightness. Our FPM employs a high power coherent laser source to enable shot-noise limited high-speed imaging. For the first time, a digital micromirror device (DMD), imaged onto the back focal plane of the illumination objective, is used to generate spatially modulated sample illumination field for ptychography. By coding the on/off states of the micromirrors, the illumination plane wave angle can be varied at speeds more than 4 kHz. A set of intensity images, resulting from different oblique illuminations, are used to numerically reconstruct one high-resolution image without obvious laser speckle. Experiments were conducted using a USAF resolution target and a fiber sample, demonstrating high-resolution imaging capability of our system. We envision that our approach, if combined with a coded-aperture compressive-sensing algorithm, will further improve the imaging speed in DMD-based FPM systems. PMID:26480361

Digital micromirror device-based laser-illumination Fourier ptychographic microscopy.

PubMed

Kuang, Cuifang; Ma, Ye; Zhou, Renjie; Lee, Justin; Barbastathis, George; Dasari, Ramachandra R; Yaqoob, Zahid; So, Peter T C

2015-10-19

We report a novel approach to Fourier ptychographic microscopy (FPM) by using a digital micromirror device (DMD) and a coherent laser source (532 nm) for generating spatially modulated sample illumination. Previously demonstrated FPM systems are all based on partially-coherent illumination, which offers limited throughput due to insufficient brightness. Our FPM employs a high power coherent laser source to enable shot-noise limited high-speed imaging. For the first time, a digital micromirror device (DMD), imaged onto the back focal plane of the illumination objective, is used to generate spatially modulated sample illumination field for ptychography. By coding the on/off states of the micromirrors, the illumination plane wave angle can be varied at speeds more than 4 kHz. A set of intensity images, resulting from different oblique illuminations, are used to numerically reconstruct one high-resolution image without obvious laser speckle. Experiments were conducted using a USAF resolution target and a fiber sample, demonstrating high-resolution imaging capability of our system. We envision that our approach, if combined with a coded-aperture compressive-sensing algorithm, will further improve the imaging speed in DMD-based FPM systems.

Low-Cost High-Precision PIAA Optics for High Contrast Imaging with Exo-Planet Coronagraphs

NASA Technical Reports Server (NTRS)

Balasubramanian, Kunjithapatham; Shaklan, Stuart B.; Pueyo, Laurent; Wilson, Daniel W.; Guyon, Olivier

2010-01-01

PIAA optics for high contrast imaging present challenges in manufacturing and testing due to their large surface departures from aspheric profiles at the aperture edges. With smaller form factors and consequent smaller surface deformations (<50 microns), fabrication of these mirrors with diamond turning followed by electron beam lithographic techniques becomes feasible. Though such a design reduces the system throughput to approx.50%, it still provides good performance down to 2 lambda/D inner working angle. With new achromatic focal plane mask designs, the system performance can be further improved. We report on the design, expected performance, fabrication challenges, and initial assessment of such novel PIAA optics.

Resolution and throughput optimized intraoperative spectrally encoded coherence tomography and reflectometry (iSECTR) for multimodal imaging during ophthalmic microsurgery

NASA Astrophysics Data System (ADS)

Malone, Joseph D.; El-Haddad, Mohamed T.; Leeburg, Kelsey C.; Terrones, Benjamin D.; Tao, Yuankai K.

2018-02-01

Limited visualization of semi-transparent structures in the eye remains a critical barrier to improving clinical outcomes and developing novel surgical techniques. While increases in imaging speed has enabled intraoperative optical coherence tomography (iOCT) imaging of surgical dynamics, several critical barriers to clinical adoption remain. Specifically, these include (1) static field-of-views (FOVs) requiring manual instrument-tracking; (2) high frame-rates require sparse sampling, which limits FOV; and (3) small iOCT FOV also limits the ability to co-register data with surgical microscopy. We previously addressed these limitations in image-guided ophthalmic microsurgery by developing microscope-integrated multimodal intraoperative swept-source spectrally encoded scanning laser ophthalmoscopy and optical coherence tomography. Complementary en face images enabled orientation and coregistration with the widefield surgical microscope view while OCT imaging enabled depth-resolved visualization of surgical instrument positions relative to anatomic structures-of-interest. In addition, we demonstrated novel integrated segmentation overlays for augmented-reality surgical guidance. Unfortunately, our previous system lacked the resolution and optical throughput for in vivo retinal imaging and necessitated removal of cornea and lens. These limitations were predominately a result of optical aberrations from imaging through a shared surgical microscope objective lens, which was modeled as a paraxial surface. Here, we present an optimized intraoperative spectrally encoded coherence tomography and reflectometry (iSECTR) system. We use a novel lens characterization method to develop an accurate model of surgical microscope objective performance and balance out inherent aberrations using iSECTR relay optics. Using this system, we demonstrate in vivo multimodal ophthalmic imaging through a surgical microscope

[Methods of high-throughput plant phenotyping for large-scale breeding and genetic experiments].

PubMed

Afonnikov, D A; Genaev, M A; Doroshkov, A V; Komyshev, E G; Pshenichnikova, T A

2016-07-01

Phenomics is a field of science at the junction of biology and informatics which solves the problems of rapid, accurate estimation of the plant phenotype; it was rapidly developed because of the need to analyze phenotypic characteristics in large scale genetic and breeding experiments in plants. It is based on using the methods of computer image analysis and integration of biological data. Owing to automation, new approaches make it possible to considerably accelerate the process of estimating the characteristics of a phenotype, to increase its accuracy, and to remove a subjectivism (inherent to humans). The main technologies of high-throughput plant phenotyping in both controlled and field conditions, their advantages and disadvantages, and also the prospects of their use for the efficient solution of problems of plant genetics and breeding are presented in the review.

Development of a High-Content Orthopoxvirus Infectivity and Neutralization Assays

PubMed Central

Gates, Irina; Olson, Victoria; Smith, Scott; Patel, Nishi; Damon, Inger; Karem, Kevin

2015-01-01

Currently, a number of assays measure Orthopoxvirus neutralization with serum from individuals, vaccinated against smallpox. In addition to the traditional plaque reduction neutralization test (PRNT), newer higher throughput assays are based on neutralization of recombinant vaccinia virus, expressing reporter genes such as β-galactosidase or green fluorescent protein. These methods could not be used to evaluate neutralization of variola virus, since genetic manipulations of this virus are prohibited by international agreements. Currently, PRNT is the assay of choice to measure neutralization of variola virus. However, PRNT assays are time consuming, labor intensive, and require considerable volume of serum sample for testing. Here, we describe the development of a high-throughput, cell-based imaging assay that can be used to measure neutralization, and characterize replication kinetics of various Orthopoxviruses, including variola, vaccinia, monkeypox, and cowpox. PMID:26426117

Quantitative secondary electron imaging for work function extraction at atomic level and layer identification of graphene

PubMed Central

Zhou, Yangbo; Fox, Daniel S; Maguire, Pierce; O’Connell, Robert; Masters, Robert; Rodenburg, Cornelia; Wu, Hanchun; Dapor, Maurizio; Chen, Ying; Zhang, Hongzhou

2016-01-01

Two-dimensional (2D) materials usually have a layer-dependent work function, which require fast and accurate detection for the evaluation of their device performance. A detection technique with high throughput and high spatial resolution has not yet been explored. Using a scanning electron microscope, we have developed and implemented a quantitative analytical technique which allows effective extraction of the work function of graphene. This technique uses the secondary electron contrast and has nanometre-resolved layer information. The measurement of few-layer graphene flakes shows the variation of work function between graphene layers with a precision of less than 10 meV. It is expected that this technique will prove extremely useful for researchers in a broad range of fields due to its revolutionary throughput and accuracy. PMID:26878907

Visualization of small lesions in rat cartilage by means of laboratory-based x-ray phase contrast imaging

NASA Astrophysics Data System (ADS)

Marenzana, Massimo; Hagen, Charlotte K.; Das Neves Borges, Patricia; Endrizzi, Marco; Szafraniec, Magdalena B.; Ignatyev, Konstantin; Olivo, Alessandro

2012-12-01

Being able to quantitatively assess articular cartilage in three-dimensions (3D) in small rodent animal models, with a simple laboratory set-up, would prove extremely important for the development of pre-clinical research focusing on cartilage pathologies such as osteoarthritis (OA). These models are becoming essential tools for the development of new drugs for OA, a disease affecting up to 1/3 of the population older than 50 years for which there is no cure except prosthetic surgery. However, due to limitations in imaging technology, high-throughput 3D structural imaging has not been achievable in small rodent models, thereby limiting their translational potential and their efficiency as research tools. We show that a simple laboratory system based on coded-aperture x-ray phase contrast imaging (CAXPCi) can correctly visualize the cartilage layer in slices of an excised rat tibia imaged both in air and in saline solution. Moreover, we show that small, surgically induced lesions are also correctly detected by the CAXPCi system, and we support this finding with histopathology examination. Following these successful proof-of-concept results in rat cartilage, we expect that an upgrade of the system to higher resolutions (currently underway) will enable extending the method to the imaging of mouse cartilage as well. From a technological standpoint, by showing the capability of the system to detect cartilage also in water, we demonstrate phase sensitivity comparable to other lab-based phase methods (e.g. grating interferometry). In conclusion, CAXPCi holds a strong potential for being adopted as a routine laboratory tool for non-destructive, high throughput assessment of 3D structural changes in murine articular cartilage, with a possible impact in the field similar to the revolution that conventional microCT brought into bone research.

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

NIR hyperspectral compressive imager based on a modified Fabry–Perot resonator

NASA Astrophysics Data System (ADS)

Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Stern, Adrian

2018-04-01

The acquisition of hyperspectral (HS) image datacubes with available 2D sensor arrays involves a time consuming scanning process. In the last decade, several compressive sensing (CS) techniques were proposed to reduce the HS acquisition time. In this paper, we present a method for near-infrared (NIR) HS imaging which relies on our rapid CS resonator spectroscopy technique. Within the framework of CS, and by using a modified Fabry–Perot resonator, a sequence of spectrally modulated images is used to recover NIR HS datacubes. Owing to the innovative CS design, we demonstrate the ability to reconstruct NIR HS images with hundreds of spectral bands from an order of magnitude fewer measurements, i.e. with a compression ratio of about 10:1. This high compression ratio, together with the high optical throughput of the system, facilitates fast acquisition of large HS datacubes.

Architecture for a PACS primary diagnosis workstation

NASA Astrophysics Data System (ADS)

Shastri, Kaushal; Moran, Byron

1990-08-01

A major factor in determining the overall utility of a medical Picture Archiving and Communications (PACS) system is the functionality of the diagnostic workstation. Meyer-Ebrecht and Wendler [1] have proposed a modular picture computer architecture with high throughput and Perry et.al [2] have defined performance requirements for radiology workstations. In order to be clinically useful, a primary diagnosis workstation must not only provide functions of current viewing systems (e.g. mechanical alternators [3,4]) such as acceptable image quality, simultaneous viewing of multiple images, and rapid switching of image banks; but must also provide a diagnostic advantage over the current systems. This includes window-level functions on any image, simultaneous display of multi-modality images, rapid image manipulation, image processing, dynamic image display (cine), electronic image archival, hardcopy generation, image acquisition, network support, and an easy user interface. Implementation of such a workstation requires an underlying hardware architecture which provides high speed image transfer channels, local storage facilities, and image processing functions. This paper describes the hardware architecture of the Siemens Diagnostic Reporting Console (DRC) which meets these requirements.

A Near-Optimal Distributed QoS Constrained Routing Algorithm for Multichannel Wireless Sensor Networks

PubMed Central

Lin, Frank Yeong-Sung; Hsiao, Chiu-Han; Yen, Hong-Hsu; Hsieh, Yu-Jen

2013-01-01

One of the important applications in Wireless Sensor Networks (WSNs) is video surveillance that includes the tasks of video data processing and transmission. Processing and transmission of image and video data in WSNs has attracted a lot of attention in recent years. This is known as Wireless Visual Sensor Networks (WVSNs). WVSNs are distributed intelligent systems for collecting image or video data with unique performance, complexity, and quality of service challenges. WVSNs consist of a large number of battery-powered and resource constrained camera nodes. End-to-end delay is a very important Quality of Service (QoS) metric for video surveillance application in WVSNs. How to meet the stringent delay QoS in resource constrained WVSNs is a challenging issue that requires novel distributed and collaborative routing strategies. This paper proposes a Near-Optimal Distributed QoS Constrained (NODQC) routing algorithm to achieve an end-to-end route with lower delay and higher throughput. A Lagrangian Relaxation (LR)-based routing metric that considers the “system perspective” and “user perspective” is proposed to determine the near-optimal routing paths that satisfy end-to-end delay constraints with high system throughput. The empirical results show that the NODQC routing algorithm outperforms others in terms of higher system throughput with lower average end-to-end delay and delay jitter. In this paper, for the first time, the algorithm shows how to meet the delay QoS and at the same time how to achieve higher system throughput in stringently resource constrained WVSNs.

Use of Optical Imaging Technology in the Validation of a New, Rapid, Cost-Effective Drug Screen as Part of a Tiered In Vivo Screening Paradigm for Development of Drugs To Treat Cutaneous Leishmaniasis

PubMed Central

Parriot, Sandi; Hudson, Thomas H.; Lang, Thierry; Ngundam, Franklyn; Leed, Susan; Sena, Jenell; Harris, Michael; O'Neil, Michael; Sciotti, Richard; Read, Lisa; Lecoeur, Herve; Grogl, Max

2017-01-01

ABSTRACT In any drug discovery and development effort, a reduction in the time of the lead optimization cycle is critical to decrease the time to license and reduce costs. In addition, ethical guidelines call for the more ethical use of animals to minimize the number of animals used and decrease their suffering. Therefore, any effort to develop drugs to treat cutaneous leishmaniasis requires multiple tiers of in vivo testing that start with higher-throughput efficacy assessments and progress to lower-throughput models with the most clinical relevance. Here, we describe the validation of a high-throughput, first-tier, noninvasive model of lesion suppression that uses an in vivo optical imaging technology for the initial screening of compounds. A strong correlation between luciferase activity and the parasite load at up to 18 days postinfection was found. This correlation allows the direct assessment of the effects of drug treatment on parasite burden. We demonstrate that there is a strong correlation between drug efficacy measured on day 18 postinfection and the suppression of lesion size by day 60 postinfection, which allows us to reach an accurate conclusion on drug efficacy in only 18 days. Compounds demonstrating a significant reduction in the bioluminescence signal compared to that in control animals can be tested in lower-throughput, more definitive tests of lesion cure in BALB/c mice and Golden Syrian hamsters (GSH) using Old World and New World parasites. PMID:28137819

High count-rate study of two TES x-ray microcalorimeters with different transition temperatures

NASA Astrophysics Data System (ADS)

Lee, Sang-Jun; Adams, Joseph S.; Bandler, Simon R.; Betancourt-Martinez, Gabriele L.; Chervenak, James A.; Eckart, Megan E.; Finkbeiner, Fred M.; Kelley, Richard L.; Kilbourne, Caroline A.; Porter, Frederick S.; Sadleir, John E.; Smith, Stephen J.; Wassell, Edward J.

2017-10-01

We have developed transition-edge sensor (TES) microcalorimeter arrays with high count-rate capability and high energy resolution to carry out x-ray imaging spectroscopy observations of various astronomical sources and the Sun. We have studied the dependence of the energy resolution and throughput (fraction of processed pulses) on the count rate for such microcalorimeters with two different transition temperatures (T c). Devices with both transition temperatures were fabricated within a single microcalorimeter array directly on top of a solid substrate where the thermal conductance of the microcalorimeter is dependent upon the thermal boundary resistance between the TES sensor and the dielectric substrate beneath. Because the thermal boundary resistance is highly temperature dependent, the two types of device with different T cs had very different thermal decay times, approximately one order of magnitude different. In our earlier report, we achieved energy resolutions of 1.6 and 2.3 eV at 6 keV from lower and higher T c devices, respectively, using a standard analysis method based on optimal filtering in the low flux limit. We have now measured the same devices at elevated x-ray fluxes ranging from 50 Hz to 1000 Hz per pixel. In the high flux limit, however, the standard optimal filtering scheme nearly breaks down because of x-ray pile-up. To achieve the highest possible energy resolution for a fixed throughput, we have developed an analysis scheme based on the so-called event grade method. Using the new analysis scheme, we achieved 5.0 eV FWHM with 96% throughput for 6 keV x-rays of 1025 Hz per pixel with the higher T c (faster) device, and 5.8 eV FWHM with 97% throughput with the lower T c (slower) device at 722 Hz.

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas.

PubMed

Kinoshita, Manabu; Sakai, Mio; Arita, Hideyuki; Shofuda, Tomoko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki; Nakanishi, Katsuyuki; Kanemura, Yonehiro

2016-01-01

Reports have suggested that tumor textures presented on T2-weighted images correlate with the genetic status of glioma. Therefore, development of an image analyzing framework that is capable of objective and high throughput image texture analysis for large scale image data collection is needed. The current study aimed to address the development of such a framework by introducing two novel parameters for image textures on T2-weighted images, i.e., Shannon entropy and Prewitt filtering. Twenty-two WHO grade 2 and 28 grade 3 glioma patients were collected whose pre-surgical MRI and IDH1 mutation status were available. Heterogeneous lesions showed statistically higher Shannon entropy than homogenous lesions (p = 0.006) and ROC curve analysis proved that Shannon entropy on T2WI was a reliable indicator for discrimination of homogenous and heterogeneous lesions (p = 0.015, AUC = 0.73). Lesions with well-defined borders exhibited statistically higher Edge mean and Edge median values using Prewitt filtering than those with vague lesion borders (p = 0.0003 and p = 0.0005 respectively). ROC curve analysis also proved that both Edge mean and median values were promising indicators for discrimination of lesions with vague and well defined borders and both Edge mean and median values performed in a comparable manner (p = 0.0002, AUC = 0.81 and p < 0.0001, AUC = 0.83, respectively). Finally, IDH1 wild type gliomas showed statistically lower Shannon entropy on T2WI than IDH1 mutated gliomas (p = 0.007) but no difference was observed between IDH1 wild type and mutated gliomas in Edge median values using Prewitt filtering. The current study introduced two image metrics that reflect lesion texture described on T2WI. These two metrics were validated by readings of a neuro-radiologist who was blinded to the results. This observation will facilitate further use of this technique in future large scale image analysis of glioma.

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web

PubMed Central

Taylor, Stephen; Noble, Roger

2014-01-01

Motivation: Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Availability and implementation: Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. Contact:  stephen.taylor@imm.ox.ac.uk and roger@coritsu.com PMID:24849578

Cell-free measurements of brightness of fluorescently labeled antibodies

PubMed Central

Zhou, Haiying; Tourkakis, George; Shi, Dennis; Kim, David M.; Zhang, Hairong; Du, Tommy; Eades, William C.; Berezin, Mikhail Y.

2017-01-01

Validation of imaging contrast agents, such as fluorescently labeled imaging antibodies, has been recognized as a critical challenge in clinical and preclinical studies. As the number of applications for imaging antibodies grows, these materials are increasingly being subjected to careful scrutiny. Antibody fluorescent brightness is one of the key parameters that is of critical importance. Direct measurements of the brightness with common spectroscopy methods are challenging, because the fluorescent properties of the imaging antibodies are highly sensitive to the methods of conjugation, degree of labeling, and contamination with free dyes. Traditional methods rely on cell-based assays that lack reproducibility and accuracy. In this manuscript, we present a novel and general approach for measuring the brightness using antibody-avid polystyrene beads and flow cytometry. As compared to a cell-based method, the described technique is rapid, quantitative, and highly reproducible. The proposed method requires less than ten microgram of sample and is applicable for optimizing synthetic conjugation procedures, testing commercial imaging antibodies, and performing high-throughput validation of conjugation procedures. PMID:28150730

Cluster secondary ion mass spectrometry microscope mode mass spectrometry imaging.

PubMed

Kiss, András; Smith, Donald F; Jungmann, Julia H; Heeren, Ron M A

2013-12-30

Microscope mode imaging for secondary ion mass spectrometry is a technique with the promise of simultaneous high spatial resolution and high-speed imaging of biomolecules from complex surfaces. Technological developments such as new position-sensitive detectors, in combination with polyatomic primary ion sources, are required to exploit the full potential of microscope mode mass spectrometry imaging, i.e. to efficiently push the limits of ultra-high spatial resolution, sample throughput and sensitivity. In this work, a C60 primary source was combined with a commercial mass microscope for microscope mode secondary ion mass spectrometry imaging. The detector setup is a pixelated detector from the Medipix/Timepix family with high-voltage post-acceleration capabilities. The system's mass spectral and imaging performance is tested with various benchmark samples and thin tissue sections. The high secondary ion yield (with respect to 'traditional' monatomic primary ion sources) of the C60 primary ion source and the increased sensitivity of the high voltage detector setup improve microscope mode secondary ion mass spectrometry imaging. The analysis time and the signal-to-noise ratio are improved compared with other microscope mode imaging systems, all at high spatial resolution. We have demonstrated the unique capabilities of a C60 ion microscope with a Timepix detector for high spatial resolution microscope mode secondary ion mass spectrometry imaging. Copyright © 2013 John Wiley & Sons, Ltd.

A Fabry-Perot interferometric imaging spectrometer in LWIR

NASA Astrophysics Data System (ADS)

Zhang, Fang; Gao, Jiaobo; Wang, Nan; Wu, Jianghui; Meng, Hemin; Zhang, Lei; Gao, Shan

2017-02-01

With applications ranging from the desktop to remote sensing, the long wave infrared (LWIR) interferometric spectral imaging system is always with huge volume and large weight. In order to miniaturize and light the instrument, a new method of LWIR spectral imaging system based on a variable gap Fabry-Perot (FP) interferometer is researched. With the system working principle analyzed, theoretically, it is researched that how to make certain the primary parameter, such as, wedge angle of interferometric cavity, f-number of the imaging lens and the relationship between the wedge angle and the modulation of the interferogram. A prototype is developed and a good experimental result of a uniform radiation source, a monochromatic source, is obtained. The research shows that besides high throughput and high spectral resolution, the advantage of miniaturization is also simultaneously achieved in this method.

Displacement of particles in microfluidics by laser-generated tandem bubbles

NASA Astrophysics Data System (ADS)

Lautz, Jaclyn; Sankin, Georgy; Yuan, Fang; Zhong, Pei

2010-11-01

The dynamic interaction between laser-generated tandem bubble and individual polystyrene particles of 2 and 10 μm in diameter is studied in a microfluidic channel (25 μm height) by high-speed imaging and particle image velocimetry. The asymmetric collapse of the tandem bubble produces a pair of microjets and associated long-lasting vortices that can propel a single particle to a maximum velocity of 1.4 m/s in 30 μs after the bubble collapse with a resultant directional displacement up to 60 μm in 150 μs. This method may be useful for high-throughput cell sorting in microfluidic devices.

3D-resolved fluorescence and phosphorescence lifetime imaging using temporal focusing wide-field two-photon excitation

PubMed Central

Choi, Heejin; Tzeranis, Dimitrios S.; Cha, Jae Won; Clémenceau, Philippe; de Jong, Sander J. G.; van Geest, Lambertus K.; Moon, Joong Ho; Yannas, Ioannis V.; So, Peter T. C.

2012-01-01

Fluorescence and phosphorescence lifetime imaging are powerful techniques for studying intracellular protein interactions and for diagnosing tissue pathophysiology. While lifetime-resolved microscopy has long been in the repertoire of the biophotonics community, current implementations fall short in terms of simultaneously providing 3D resolution, high throughput, and good tissue penetration. This report describes a new highly efficient lifetime-resolved imaging method that combines temporal focusing wide-field multiphoton excitation and simultaneous acquisition of lifetime information in frequency domain using a nanosecond gated imager from a 3D-resolved plane. This approach is scalable allowing fast volumetric imaging limited only by the available laser peak power. The accuracy and performance of the proposed method is demonstrated in several imaging studies important for understanding peripheral nerve regeneration processes. Most importantly, the parallelism of this approach may enhance the imaging speed of long lifetime processes such as phosphorescence by several orders of magnitude. PMID:23187477

Delta-Doping at Wafer Level for High Throughput, High Yield Fabrication of Silicon Imaging Arrays

NASA Technical Reports Server (NTRS)

Hoenk, Michael E. (Inventor); Nikzad, Shoulch (Inventor); Jones, Todd J. (Inventor); Greer, Frank (Inventor); Carver, Alexander G. (Inventor)

2014-01-01

Systems and methods for producing high quantum efficiency silicon devices. A silicon MBE has a preparation chamber that provides for cleaning silicon surfaces using an oxygen plasma to remove impurities and a gaseous (dry) NH3 + NF3 room temperature oxide removal process that leaves the silicon surface hydrogen terminated. Silicon wafers up to 8 inches in diameter have devices that can be fabricated using the cleaning procedures and MBE processing, including delta doping.

Advanced phenotyping and phenotype data analysis for the study of plant growth and development

PubMed Central

Rahaman, Md. Matiur; Chen, Dijun; Gillani, Zeeshan; Klukas, Christian; Chen, Ming

2015-01-01

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis. PMID:26322060

Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform

NASA Astrophysics Data System (ADS)

Mohd Asaari, Mohd Shahrimie; Mishra, Puneet; Mertens, Stien; Dhondt, Stijn; Inzé, Dirk; Wuyts, Nathalie; Scheunders, Paul

2018-04-01

The potential of close-range hyperspectral imaging (HSI) as a tool for detecting early drought stress responses in plants grown in a high-throughput plant phenotyping platform (HTPPP) was explored. Reflectance spectra from leaves in close-range imaging are highly influenced by plant geometry and its specific alignment towards the imaging system. This induces high uninformative variability in the recorded signals, whereas the spectral signature informing on plant biological traits remains undisclosed. A linear reflectance model that describes the effect of the distance and orientation of each pixel of a plant with respect to the imaging system was applied. By solving this model for the linear coefficients, the spectra were corrected for the uninformative illumination effects. This approach, however, was constrained by the requirement of a reference spectrum, which was difficult to obtain. As an alternative, the standard normal variate (SNV) normalisation method was applied to reduce this uninformative variability. Once the envisioned illumination effects were eliminated, the remaining differences in plant spectra were assumed to be related to changes in plant traits. To distinguish the stress-related phenomena from regular growth dynamics, a spectral analysis procedure was developed based on clustering, a supervised band selection, and a direct calculation of a spectral similarity measure against a reference. To test the significance of the discrimination between healthy and stressed plants, a statistical test was conducted using a one-way analysis of variance (ANOVA) technique. The proposed analysis techniques was validated with HSI data of maize plants (Zea mays L.) acquired in a HTPPP for early detection of drought stress in maize plant. Results showed that the pre-processing of reflectance spectra with the SNV effectively reduces the variability due to the expected illumination effects. The proposed spectral analysis method on the normalized spectra successfully detected drought stress from the third day of drought induction, confirming the potential of HSI for drought stress detection studies and further supporting its adoption in HTPPP.

In vivo monitoring of cellular energy metabolism using SoNar, a highly responsive sensor for NAD(+)/NADH redox state.

PubMed

Zhao, Yuzheng; Wang, Aoxue; Zou, Yejun; Su, Ni; Loscalzo, Joseph; Yang, Yi

2016-08-01

NADH and its oxidized form NAD(+) have a central role in energy metabolism, and their concentrations are often considered to be among the most important readouts of metabolic state. Here, we present a detailed protocol to image and monitor NAD(+)/NADH redox state in living cells and in vivo using a highly responsive, genetically encoded fluorescent sensor known as SoNar (sensor of NAD(H) redox). The chimeric SoNar protein was initially developed by inserting circularly permuted yellow fluorescent protein (cpYFP) into the NADH-binding domain of Rex protein from Thermus aquaticus (T-Rex). It functions by binding to either NAD(+) or NADH, thus inducing protein conformational changes that affect its fluorescent properties. We first describe steps for how to establish SoNar-expressing cells, and then discuss how to use the system to quantify the intracellular redox state. This approach is sensitive, accurate, simple and able to report subtle perturbations of various pathways of energy metabolism in real time. We also detail the application of SoNar to high-throughput chemical screening of candidate compounds targeting cell metabolism in a microplate-reader-based assay, along with in vivo fluorescence imaging of tumor xenografts expressing SoNar in mice. Typically, the approximate time frame for fluorescence imaging of SoNar is 30 min for living cells and 60 min for living mice. For high-throughput chemical screening in a 384-well-plate assay, the whole procedure generally takes no longer than 60 min to assess the effects of 380 compounds on cell metabolism.

Automating fruit fly Drosophila embryo injection for high throughput transgenic studies

NASA Astrophysics Data System (ADS)

Cornell, E.; Fisher, W. W.; Nordmeyer, R.; Yegian, D.; Dong, M.; Biggin, M. D.; Celniker, S. E.; Jin, J.

2008-01-01

To decipher and manipulate the 14 000 identified Drosophila genes, there is a need to inject a large number of embryos with transgenes. We have developed an automated instrument for high throughput injection of Drosophila embryos. It was built on an inverted microscope, equipped with a motorized xy stage, autofocus, a charge coupled device camera, and an injection needle mounted on a high speed vertical stage. A novel, micromachined embryo alignment device was developed to facilitate the arrangement of a large number of eggs. The control system included intelligent and dynamic imaging and analysis software and an embryo injection algorithm imitating a human operator. Once the injection needle and embryo slide are loaded, the software automatically images and characterizes each embryo and subsequently injects DNA into all suitable embryos. The ability to program needle flushing and monitor needle status after each injection ensures reliable delivery of biomaterials. Using this instrument, we performed a set of transformation injection experiments. The robot achieved injection speeds and transformation efficiencies comparable to those of a skilled human injector. Because it can be programed to allow injection at various locations in the embryo, such as the anterior pole or along the dorsal or ventral axes, this system is also suitable for injection of general biochemicals, including drugs and RNAi.

Fly-scan ptychography

DOE PAGES

Huang, Xiaojing; Lauer, Kenneth; Clark, Jesse N.; ...

2015-03-13

We report an experimental ptychography measurement performed in fly-scan mode. With a visible-light laser source, we demonstrate a 5-fold reduction of data acquisition time. By including multiple mutually incoherent modes into the incident illumination, high quality images were successfully reconstructed from blurry diffraction patterns. Thus, this approach significantly increases the throughput of ptychography, especially for three-dimensional applications and the visualization of dynamic systems.

Deep Learning in Label-free Cell Classification

PubMed Central

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-01-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells. PMID:26975219

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-03-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

A transmission imaging spectrograph and microfabricated channel system for DNA analysis.

PubMed

Simpson, J W; Ruiz-Martinez, M C; Mulhern, G T; Berka, J; Latimer, D R; Ball, J A; Rothberg, J M; Went, G T

2000-01-01

In this paper we present the development of a DNA analysis system using a microfabricated channel device and a novel transmission imaging spectrograph which can be efficiently incorporated into a high throughput genomics facility for both sizing and sequencing of DNA fragments. The device contains 48 channels etched on a glass substrate. The channels are sealed with a flat glass plate which also provides a series of apertures for sample loading and contact with buffer reservoirs. Samples can be easily loaded in volumes up to 640 nL without band broadening because of an efficient electrokinetic stacking at the electrophoresis channel entrance. The system uses a dual laser excitation source and a highly sensitive charge-coupled device (CCD) detector allowing for simultaneous detection of many fluorescent dyes. The sieving matrices for the separation of single-stranded DNA fragments are polymerized in situ in denaturing buffer systems. Examples of separation of single-stranded DNA fragments up to 500 bases in length are shown, including accurate sizing of GeneCalling fragments, and sequencing samples prepared with a reduced amount of dye terminators. An increase in sample throughput has been achieved by color multiplexing.

Functional approach to high-throughput plant growth analysis

PubMed Central

2013-01-01

Method Taking advantage of the current rapid development in imaging systems and computer vision algorithms, we present HPGA, a high-throughput phenotyping platform for plant growth modeling and functional analysis, which produces better understanding of energy distribution in regards of the balance between growth and defense. HPGA has two components, PAE (Plant Area Estimation) and GMA (Growth Modeling and Analysis). In PAE, by taking the complex leaf overlap problem into consideration, the area of every plant is measured from top-view images in four steps. Given the abundant measurements obtained with PAE, in the second module GMA, a nonlinear growth model is applied to generate growth curves, followed by functional data analysis. Results Experimental results on model plant Arabidopsis thaliana show that, compared to an existing approach, HPGA reduces the error rate of measuring plant area by half. The application of HPGA on the cfq mutant plants under fluctuating light reveals the correlation between low photosynthetic rates and small plant area (compared to wild type), which raises a hypothesis that knocking out cfq changes the sensitivity of the energy distribution under fluctuating light conditions to repress leaf growth. Availability HPGA is available at http://www.msu.edu/~jinchen/HPGA. PMID:24565437

Functional screening assays with neurons generated from pluripotent stem cell-derived neural stem cells.

PubMed

Efthymiou, Anastasia; Shaltouki, Atossa; Steiner, Joseph P; Jha, Balendu; Heman-Ackah, Sabrina M; Swistowski, Andrzej; Zeng, Xianmin; Rao, Mahendra S; Malik, Nasir

2014-01-01

Rapid and effective drug discovery for neurodegenerative disease is currently impeded by an inability to source primary neural cells for high-throughput and phenotypic screens. This limitation can be addressed through the use of pluripotent stem cells (PSCs), which can be derived from patient-specific samples and differentiated to neural cells for use in identifying novel compounds for the treatment of neurodegenerative diseases. We have developed an efficient protocol to culture pure populations of neurons, as confirmed by gene expression analysis, in the 96-well format necessary for screens. These differentiated neurons were subjected to viability assays to illustrate their potential in future high-throughput screens. We have also shown that organelles such as nuclei and mitochondria could be live-labeled and visualized through fluorescence, suggesting that we should be able to monitor subcellular phenotypic changes. Neurons derived from a green fluorescent protein-expressing reporter line of PSCs were live-imaged to assess markers of neuronal maturation such as neurite length and co-cultured with astrocytes to demonstrate further maturation. These studies confirm that PSC-derived neurons can be used effectively in viability and functional assays and pave the way for high-throughput screens on neurons derived from patients with neurodegenerative disorders.

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

Strategic and Operational Plan for Integrating Transcriptomics ...

EPA Pesticide Factsheets

Plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT; the details are in the attached slide presentation presentation on plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT, given at the OECD meeting on June 23, 2016

High-Throughput Experimental Approach Capabilities | Materials Science |

Science.gov Websites

NREL High-Throughput Experimental Approach Capabilities High-Throughput Experimental Approach by yellow and is for materials in the upper right sector. NREL's high-throughput experimental ,Te) and oxysulfide sputtering Combi-5: Nitrides and oxynitride sputtering We also have several non

Flexible Measurement of Bioluminescent Reporters Using an Automated Longitudinal Luciferase Imaging Gas- and Temperature-optimized Recorder (ALLIGATOR).

PubMed

Crosby, Priya; Hoyle, Nathaniel P; O'Neill, John S

2017-12-13

Luciferase-based reporters of cellular gene expression are in widespread use for both longitudinal and end-point assays of biological activity. In circadian rhythms research, for example, clock gene fusions with firefly luciferase give rise to robust rhythms in cellular bioluminescence that persist over many days. Technical limitations associated with photomultiplier tubes (PMT) or conventional microscopy-based methods for bioluminescence quantification have typically demanded that cells and tissues be maintained under quite non-physiological conditions during recording, with a trade-off between sensitivity and throughput. Here, we report a refinement of prior methods that allows long-term bioluminescence imaging with high sensitivity and throughput which supports a broad range of culture conditions, including variable gas and humidity control, and that accepts many different tissue culture plates and dishes. This automated longitudinal luciferase imaging gas- and temperature-optimized recorder (ALLIGATOR) also allows the observation of spatial variations in luciferase expression across a cell monolayer or tissue, which cannot readily be observed by traditional methods. We highlight how the ALLIGATOR provides vastly increased flexibility for the detection of luciferase activity when compared with existing methods.

Application of polarization in high speed, high contrast inspection

NASA Astrophysics Data System (ADS)

Novak, Matthew J.

2017-08-01

Industrial optical inspection often requires high speed and high throughput of materials. Engineers use a variety of techniques to handle these inspection needs. Some examples include line scan cameras, high speed multi-spectral and laser-based systems. High-volume manufacturing presents different challenges for inspection engineers. For example, manufacturers produce some components in quantities of millions per month, per week or even per day. Quality control of so many parts requires creativity to achieve the measurement needs. At times, traditional vision systems lack the contrast to provide the data required. In this paper, we show how dynamic polarization imaging captures high contrast images. These images are useful for engineers to perform inspection tasks in some cases where optical contrast is low. We will cover basic theory of polarization. We show how to exploit polarization as a contrast enhancement technique. We also show results of modeling for a polarization inspection application. Specifically, we explore polarization techniques for inspection of adhesives on glass.

A robust, high-throughput method for computing maize ear, cob, and kernel attributes automatically from images.

PubMed

Miller, Nathan D; Haase, Nicholas J; Lee, Jonghyun; Kaeppler, Shawn M; de Leon, Natalia; Spalding, Edgar P

2017-01-01

Grain yield of the maize plant depends on the sizes, shapes, and numbers of ears and the kernels they bear. An automated pipeline that can measure these components of yield from easily-obtained digital images is needed to advance our understanding of this globally important crop. Here we present three custom algorithms designed to compute such yield components automatically from digital images acquired by a low-cost platform. One algorithm determines the average space each kernel occupies along the cob axis using a sliding-window Fourier transform analysis of image intensity features. A second counts individual kernels removed from ears, including those in clusters. A third measures each kernel's major and minor axis after a Bayesian analysis of contour points identifies the kernel tip. Dimensionless ear and kernel shape traits that may interrelate yield components are measured by principal components analysis of contour point sets. Increased objectivity and speed compared to typical manual methods are achieved without loss of accuracy as evidenced by high correlations with ground truth measurements and simulated data. Millimeter-scale differences among ear, cob, and kernel traits that ranged more than 2.5-fold across a diverse group of inbred maize lines were resolved. This system for measuring maize ear, cob, and kernel attributes is being used by multiple research groups as an automated Web service running on community high-throughput computing and distributed data storage infrastructure. Users may create their own workflow using the source code that is staged for download on a public repository. © 2016 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

WIYN bench upgrade: a revitalized spectrograph

NASA Astrophysics Data System (ADS)

Bershady, M.; Barden, S.; Blanche, P.-A.; Blanco, D.; Corson, C.; Crawford, S.; Glaspey, J.; Habraken, S.; Jacoby, G.; Keyes, J.; Knezek, P.; Lemaire, P.; Liang, M.; McDougall, E.; Poczulp, G.; Sawyer, D.; Westfall, K.; Willmarth, D.

2008-07-01

We describe the redesign and upgrade of the versatile fiber-fed Bench Spectrograph on the WIYN 3.5m telescope. The spectrograph is fed by either the Hydra multi-object positioner or integral-field units (IFUs) at two other ports, and can be configured with an adjustable camera-collimator angle to use low-order and echelle gratings. The upgrade, including a new collimator, charge-coupled device (CCD) and modern controller, and volume-phase holographic gratings (VPHG), has high performance-to-cost ratio by combining new technology with a system reconfiguration that optimizes throughput while utilizing as much of the existing instrument as possible. A faster, all-refractive collimator enhances throughput by 60%, nearly eliminates the slit-function due to vignetting, and improves image quality to maintain instrumental resolution. Two VPH gratings deliver twice the diffraction efficiency of existing surface-relief gratings: A 740 l/mm grating (float-glass and post-polished) used in 1st and 2nd-order, and a large 3300 l/mm grating (spectral resolution comparable to the R2 echelle). The combination of collimator, high-quantum efficiency (QE) CCD, and VPH gratings yields throughput gain-factors of up to 3.5.

Out-of-focal plane imaging by leakage radiation microscopy

NASA Astrophysics Data System (ADS)

Zhu, Liangfu; Zhang, Douguo; Wang, Ruxue; Wen, Xiaolei; Wang, Pei; Ming, Hai; Badugu, Ramachandram; Lakowicz, Joseph R.

2017-09-01

Leakage radiation microscopy (LRM) is used to investigate the optical properties of surfaces. The front-focal plane (FFP) image with LRM reveals the structural features on the surfaces. A back-focal plane (BFP) image with LRM reveals the angular distribution of the radiation. Herein, we experimentally demonstrate that the out-of-focal plane (OFP) images present a link between the FFP and BFP images and provide optical information that cannot be resolved by either FFP or BFP images. The OFP image provides a link between the spatial location of the emission and the angular distribution from the same location, and thus information about the film’s discontinuity, nonuniformity or variable thickness can be uncovered. The use of OFP imaging will extend the scope and applications of the LRM and coupled emission imaging, which are powerful tools in nanophotonics and high throughput fluorescence screening.

Quantitative Image Restoration in Bright Field Optical Microscopy.

PubMed

Gutiérrez-Medina, Braulio; Sánchez Miranda, Manuel de Jesús

2017-11-07

Bright field (BF) optical microscopy is regarded as a poor method to observe unstained biological samples due to intrinsic low image contrast. We introduce quantitative image restoration in bright field (QRBF), a digital image processing method that restores out-of-focus BF images of unstained cells. Our procedure is based on deconvolution, using a point spread function modeled from theory. By comparing with reference images of bacteria observed in fluorescence, we show that QRBF faithfully recovers shape and enables quantify size of individual cells, even from a single input image. We applied QRBF in a high-throughput image cytometer to assess shape changes in Escherichia coli during hyperosmotic shock, finding size heterogeneity. We demonstrate that QRBF is also applicable to eukaryotic cells (yeast). Altogether, digital restoration emerges as a straightforward alternative to methods designed to generate contrast in BF imaging for quantitative analysis. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Using Imaging Methods to Interrogate Radiation-Induced Cell Signaling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shankaran, Harish; Weber, Thomas J.; Freiin von Neubeck, Claere H.

2012-04-01

There is increasing emphasis on the use of systems biology approaches to define radiation induced responses in cells and tissues. Such approaches frequently rely on global screening using various high throughput 'omics' platforms. Although these methods are ideal for obtaining an unbiased overview of cellular responses, they often cannot reflect the inherent heterogeneity of the system or provide detailed spatial information. Additionally, performing such studies with multiple sampling time points can be prohibitively expensive. Imaging provides a complementary method with high spatial and temporal resolution capable of following the dynamics of signaling processes. In this review, we utilize specific examplesmore » to illustrate how imaging approaches have furthered our understanding of radiation induced cellular signaling. Particular emphasis is placed on protein co-localization, and oscillatory and transient signaling dynamics.« less

Detecting crop population growth using chlorophyll fluorescence imaging.

PubMed

Wang, Heng; Qian, Xiangjie; Zhang, Lan; Xu, Sailong; Li, Haifeng; Xia, Xiaojian; Dai, Liankui; Xu, Liang; Yu, Jingquan; Liu, Xu

2017-12-10

For both field and greenhouse crops, it is challenging to evaluate their growth information on a large area over a long time. In this work, we developed a chlorophyll fluorescence imaging-based system for crop population growth information detection. Modular design was used to make the system provide high-intensity uniform illumination. This system can perform modulated chlorophyll fluorescence induction kinetics measurement and chlorophyll fluorescence parameter imaging over a large area of up to 45  cm×34  cm. The system can provide different lighting intensity by modulating the duty cycle of its control signal. Results of continuous monitoring of cucumbers in nitrogen deficiency show the system can reduce the judge error of crop physiological status and improve monitoring efficiency. Meanwhile, the system is promising in high throughput application scenarios.

The Wide Field Imager for Athena

NASA Astrophysics Data System (ADS)

Rau, A.; Nandra, K.; Meidinger, N.; Plattner, M.

2017-10-01

The Wide Field Imager (WFI) is one of the two scientific instruments of Athena, ESA's next large X-ray Observatory with launch in 2028. The instrument will provide two defining capabilities to the mission sensitive wide-field imaging spectroscopy and excellent high-count rate performance. It will do so with the use of two separate detectors systems, the Large Detector Array (LDA) optimized for its field of view (40'×40') with a 100 fold survey speed increase compared to existing X-ray missions, and the Fast Detector (FD) tweaked for high throughput and low pile-up for point sources as bright as the Crab. In my talk I will present the key performance parameters of the instrument and their links to the scientific goals of Athena and summarize the status of the ongoing development activities.

Optical designs of reflection and refraction collection optics for a JT-60SA core Thomson scattering system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tojo, H.; Hatae, T.; Hamano, T.

2013-09-15

Collection optics for core measurements in a JT-60SA Thomson scattering system were designed. The collection optics will be installed in a limited space and have a wide field of view and wide wavelength range. Two types of the optics are therefore suggested: refraction and reflection types. The reflection system, with a large primary mirror, avoids large chromatic aberrations. Because the size limit of the primary mirror and vignetting due to the secondary mirror affect the total collection throughput, conditions that provide the high throughput are found through an optimization. A refraction system with four lenses forming an Ernostar system ismore » also employed. The use of high-refractive-index glass materials enhances the freedom of the lens curvatures, resulting in suppression of the spherical and coma aberration. Moreover, sufficient throughput can be achieved, even with smaller lenses than that of a previous design given in [H. Tojo, T. Hatae, T. Sakuma, T. Hamano, K. Itami, Y. Aida, S. Suitoh, and D. Fujie, Rev. Sci. Instrum. 81, 10D539 (2010)]. The optical resolutions of the reflection and refraction systems are both sufficient for understanding the spatial structures in plasma. In particular, the spot sizes at the image of the optics are evaluated as ∼0.3 mm and ∼0.4 mm, respectively. The throughput for the two systems, including the pupil size and transmissivity, are also compared. The results show that good measurement accuracy (<10%) even at high electron temperatures (<30 keV) can be expected in the refraction system.« less

Optical designs of reflection and refraction collection optics for a JT-60SA core Thomson scattering system.

PubMed

Tojo, H; Hatae, T; Hamano, T; Sakuma, T; Itami, K

2013-09-01

Collection optics for core measurements in a JT-60SA Thomson scattering system were designed. The collection optics will be installed in a limited space and have a wide field of view and wide wavelength range. Two types of the optics are therefore suggested: refraction and reflection types. The reflection system, with a large primary mirror, avoids large chromatic aberrations. Because the size limit of the primary mirror and vignetting due to the secondary mirror affect the total collection throughput, conditions that provide the high throughput are found through an optimization. A refraction system with four lenses forming an Ernostar system is also employed. The use of high-refractive-index glass materials enhances the freedom of the lens curvatures, resulting in suppression of the spherical and coma aberration. Moreover, sufficient throughput can be achieved, even with smaller lenses than that of a previous design given in [H. Tojo, T. Hatae, T. Sakuma, T. Hamano, K. Itami, Y. Aida, S. Suitoh, and D. Fujie, Rev. Sci. Instrum. 81, 10D539 (2010)]. The optical resolutions of the reflection and refraction systems are both sufficient for understanding the spatial structures in plasma. In particular, the spot sizes at the image of the optics are evaluated as ~0.3 mm and ~0.4 mm, respectively. The throughput for the two systems, including the pupil size and transmissivity, are also compared. The results show that good measurement accuracy (<10%) even at high electron temperatures (<30 keV) can be expected in the refraction system.

Deep learning massively accelerates super-resolution localization microscopy.

PubMed

Ouyang, Wei; Aristov, Andrey; Lelek, Mickaël; Hao, Xian; Zimmer, Christophe

2018-06-01

The speed of super-resolution microscopy methods based on single-molecule localization, for example, PALM and STORM, is limited by the need to record many thousands of frames with a small number of observed molecules in each. Here, we present ANNA-PALM, a computational strategy that uses artificial neural networks to reconstruct super-resolution views from sparse, rapidly acquired localization images and/or widefield images. Simulations and experimental imaging of microtubules, nuclear pores, and mitochondria show that high-quality, super-resolution images can be reconstructed from up to two orders of magnitude fewer frames than usually needed, without compromising spatial resolution. Super-resolution reconstructions are even possible from widefield images alone, though adding localization data improves image quality. We demonstrate super-resolution imaging of >1,000 fields of view containing >1,000 cells in ∼3 h, yielding an image spanning spatial scales from ∼20 nm to ∼2 mm. The drastic reduction in acquisition time and sample irradiation afforded by ANNA-PALM enables faster and gentler high-throughput and live-cell super-resolution imaging.

Intracellular Detection of Viral Transcription and Replication Using RNA FISH

DTIC Science & Technology

2016-05-26

sequence and how it can be rapidly performed to minimize time spent in high containment. We have adapted existing protocols for mRNA detection with...We and others have been expanded this technique to use in virus-infected tissue sections, high -throughput imaging, and for flow-cytometry based...free water. Add 1 gram of dextran sulfate and mix for 10 minutes at room temperature . Aliquot and store the hybridization buffer at 4ºC. Wash

A high-throughput technique for determining grain boundary character non-destructively in microstructures with through-thickness grains

DOE PAGES

Seita, Matteo; Volpi, Marco; Patala, Srikanth; ...

2016-06-24

Grain boundaries (GBs) govern many properties of polycrystalline materials. However, because of their structural variability, our knowledge of GB constitutive relations is still very limited. We present a novel method to characterise the complete crystallography of individual GBs non-destructively, with high-throughput, and using commercially available tools. This method combines electron diffraction, optical reflectance and numerical image analysis to determine all five crystallographic parameters of numerous GBs in samples with through-thickness grains. We demonstrate the technique by measuring the crystallographic character of about 1,000 individual GBs in aluminum in a single run. Our method enables cost- and time-effective assembly of crystallography–propertymore » databases for thousands of individual GBs. Furthermore, such databases are essential for identifying GB constitutive relations and for predicting GB-related behaviours of polycrystalline solids.« less

Separation and Concentration without Clogging Using a High-Throughput Tunable Filter

NASA Astrophysics Data System (ADS)

Mossige, E. J.; Jensen, A.; Mielnik, M. M.

2018-05-01

We present a detailed experimental study of a hydrodynamic filtration microchip and show how chip performance can be tuned and clogging avoided by adjusting the flow rates. We demonstrate concentration and separation of microspheres at throughputs as high as 29 ml /min and with 96% pureness. Results of streakline visualizations show that the thickness of a tunable filtration layer dictates the cutoff size and that two different concentration mechanisms exist. Particles larger than pores are concentrated by low-velocity rolling over the filtration pillars, while particles smaller than pores are concentrated by lateral drift across the filtration layer. Results of microscopic particle image velocimetry and particle-tracking velocimetry show that the degree of lateral migration can be quantified by the slip velocity between the particle and the surrounding fluid. Finally, by utilizing differences in inertia and separation mode, we demonstrate size-based separation of particles in a mixture.

P-TRAP: a Panicle TRAit Phenotyping tool.

PubMed

A L-Tam, Faroq; Adam, Helene; Anjos, António dos; Lorieux, Mathias; Larmande, Pierre; Ghesquière, Alain; Jouannic, Stefan; Shahbazkia, Hamid Reza

2013-08-29

In crops, inflorescence complexity and the shape and size of the seed are among the most important characters that influence yield. For example, rice panicles vary considerably in the number and order of branches, elongation of the axis, and the shape and size of the seed. Manual low-throughput phenotyping methods are time consuming, and the results are unreliable. However, high-throughput image analysis of the qualitative and quantitative traits of rice panicles is essential for understanding the diversity of the panicle as well as for breeding programs. This paper presents P-TRAP software (Panicle TRAit Phenotyping), a free open source application for high-throughput measurements of panicle architecture and seed-related traits. The software is written in Java and can be used with different platforms (the user-friendly Graphical User Interface (GUI) uses Netbeans Platform 7.3). The application offers three main tools: a tool for the analysis of panicle structure, a spikelet/grain counting tool, and a tool for the analysis of seed shape. The three tools can be used independently or simultaneously for analysis of the same image. Results are then reported in the Extensible Markup Language (XML) and Comma Separated Values (CSV) file formats. Images of rice panicles were used to evaluate the efficiency and robustness of the software. Compared to data obtained by manual processing, P-TRAP produced reliable results in a much shorter time. In addition, manual processing is not repeatable because dry panicles are vulnerable to damage. The software is very useful, practical and collects much more data than human operators. P-TRAP is a new open source software that automatically recognizes the structure of a panicle and the seeds on the panicle in numeric images. The software processes and quantifies several traits related to panicle structure, detects and counts the grains, and measures their shape parameters. In short, P-TRAP offers both efficient results and a user-friendly environment for experiments. The experimental results showed very good accuracy compared to field operator, expert verification and well-known academic methods.

P-TRAP: a Panicle Trait Phenotyping tool

PubMed Central

2013-01-01

Background In crops, inflorescence complexity and the shape and size of the seed are among the most important characters that influence yield. For example, rice panicles vary considerably in the number and order of branches, elongation of the axis, and the shape and size of the seed. Manual low-throughput phenotyping methods are time consuming, and the results are unreliable. However, high-throughput image analysis of the qualitative and quantitative traits of rice panicles is essential for understanding the diversity of the panicle as well as for breeding programs. Results This paper presents P-TRAP software (Panicle TRAit Phenotyping), a free open source application for high-throughput measurements of panicle architecture and seed-related traits. The software is written in Java and can be used with different platforms (the user-friendly Graphical User Interface (GUI) uses Netbeans Platform 7.3). The application offers three main tools: a tool for the analysis of panicle structure, a spikelet/grain counting tool, and a tool for the analysis of seed shape. The three tools can be used independently or simultaneously for analysis of the same image. Results are then reported in the Extensible Markup Language (XML) and Comma Separated Values (CSV) file formats. Images of rice panicles were used to evaluate the efficiency and robustness of the software. Compared to data obtained by manual processing, P-TRAP produced reliable results in a much shorter time. In addition, manual processing is not repeatable because dry panicles are vulnerable to damage. The software is very useful, practical and collects much more data than human operators. Conclusions P-TRAP is a new open source software that automatically recognizes the structure of a panicle and the seeds on the panicle in numeric images. The software processes and quantifies several traits related to panicle structure, detects and counts the grains, and measures their shape parameters. In short, P-TRAP offers both efficient results and a user-friendly environment for experiments. The experimental results showed very good accuracy compared to field operator, expert verification and well-known academic methods. PMID:23987653

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection.

PubMed

Cruz-Roa, Angel; Gilmore, Hannah; Basavanhally, Ajay; Feldman, Michael; Ganesan, Shridar; Shih, Natalie; Tomaszewski, John; Madabhushi, Anant; González, Fabio

2018-01-01

Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200 × 200 pixels). Only recently, Fully convolutional networks (FCN) are able to deal with larger image sizes (500 × 500 pixels) for semantic segmentation. Hence, the direct application of CNNs to WSI is not computationally feasible because for a WSI, a CNN would require billions or trillions of parameters. To alleviate this issue, this paper presents a novel method, High-throughput Adaptive Sampling for whole-slide Histopathology Image analysis (HASHI), which involves: i) a new efficient adaptive sampling method based on probability gradient and quasi-Monte Carlo sampling, and, ii) a powerful representation learning classifier based on CNNs. We applied HASHI to automated detection of invasive breast cancer on WSI. HASHI was trained and validated using three different data cohorts involving near 500 cases and then independently tested on 195 studies from The Cancer Genome Atlas. The results show that (1) the adaptive sampling method is an effective strategy to deal with WSI without compromising prediction accuracy by obtaining comparative results of a dense sampling (∼6 million of samples in 24 hours) with far fewer samples (∼2,000 samples in 1 minute), and (2) on an independent test dataset, HASHI is effective and robust to data from multiple sites, scanners, and platforms, achieving an average Dice coefficient of 76%.

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection

PubMed Central

Gilmore, Hannah; Basavanhally, Ajay; Feldman, Michael; Ganesan, Shridar; Shih, Natalie; Tomaszewski, John; Madabhushi, Anant; González, Fabio

2018-01-01

Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200 × 200 pixels). Only recently, Fully convolutional networks (FCN) are able to deal with larger image sizes (500 × 500 pixels) for semantic segmentation. Hence, the direct application of CNNs to WSI is not computationally feasible because for a WSI, a CNN would require billions or trillions of parameters. To alleviate this issue, this paper presents a novel method, High-throughput Adaptive Sampling for whole-slide Histopathology Image analysis (HASHI), which involves: i) a new efficient adaptive sampling method based on probability gradient and quasi-Monte Carlo sampling, and, ii) a powerful representation learning classifier based on CNNs. We applied HASHI to automated detection of invasive breast cancer on WSI. HASHI was trained and validated using three different data cohorts involving near 500 cases and then independently tested on 195 studies from The Cancer Genome Atlas. The results show that (1) the adaptive sampling method is an effective strategy to deal with WSI without compromising prediction accuracy by obtaining comparative results of a dense sampling (∼6 million of samples in 24 hours) with far fewer samples (∼2,000 samples in 1 minute), and (2) on an independent test dataset, HASHI is effective and robust to data from multiple sites, scanners, and platforms, achieving an average Dice coefficient of 76%. PMID:29795581

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

An acquisition system for CMOS imagers with a genuine 10 Gbit/s bandwidth

NASA Astrophysics Data System (ADS)

Guérin, C.; Mahroug, J.; Tromeur, W.; Houles, J.; Calabria, P.; Barbier, R.

2012-12-01

This paper presents a high data throughput acquisition system for pixel detector readout such as CMOS imagers. This CMOS acquisition board offers a genuine 10 Gbit/s bandwidth to the workstation and can provide an on-line and continuous high frame rate imaging capability. On-line processing can be implemented either on the Data Acquisition Board or on the multi-cores workstation depending on the complexity of the algorithms. The different parts composing the acquisition board have been designed to be used first with a single-photon detector called LUSIPHER (800×800 pixels), developed in our laboratory for scientific applications ranging from nano-photonics to adaptive optics. The architecture of the acquisition board is presented and the performances achieved by the produced boards are described. The future developments (hardware and software) concerning the on-line implementation of algorithms dedicated to single-photon imaging are tackled.

A compact LWIR imaging spectrometer with a variable gap Fabry-Perot interferometer

NASA Astrophysics Data System (ADS)

Zhang, Fang; Gao, Jiaobo; Wang, Nan; Zhao, Yujie; Zhang, Lei; Gao, Shan

2017-02-01

Fourier transform spectroscopy is a widely employed method for obtaining spectra, with applications ranging from the desktop to remote sensing. The long wave infrared (LWIR) interferometric spectral imaging system is always with huge volume and large weight. In order to miniaturize and light the instrument, a new method of LWIR spectral imaging system based on a variable gap Fabry-Perot (FP) interferometer is researched. With the system working principle analyzed, theoretically, it is researched that how to make certain the primary parameter, such as, the reflectivity of the two interferometric cavity surfaces, field of view (FOV) and f-number of the imaging lens. A prototype is developed and a good experimental result of CO2 laser is obtained. The research shows that besides high throughput and high spectral resolution, the advantage of miniaturization is also simultaneously achieved in this method.

High throughput, parallel imaging and biomarker quantification of human spermatozoa by ImageStream flow cytometry.

PubMed

Buckman, Clayton; George, Thaddeus C; Friend, Sherree; Sutovsky, Miriam; Miranda-Vizuete, Antonio; Ozanon, Christophe; Morrissey, Phil; Sutovsky, Peter

2009-12-01

Spermatid specific thioredoxin-3 protein (SPTRX-3) accumulates in the superfluous cytoplasm of defective human spermatozoa. Novel ImageStream technology combining flow cytometry with cell imaging was used for parallel quantification and visualization of SPTRX-3 protein in defective spermatozoa of five men from infertile couples. The majority of the SPTRX-3 containing cells were overwhelmingly spermatozoa with a variety of morphological defects, detectable in the ImageStream recorded images. Quantitative parameters of relative SPTRX-3 induced fluorescence measured by ImageStream correlated closely with conventional flow cytometric measurements of the same sample set and reflected the results of clinical semen evaluation. Image Stream quantification of SPTRX-3 combines and surpasses the informative value of both conventional flow cytometry and light microscopic semen evaluation. The observed patterns of the retention of SPTRX-3 in the sperm samples from infertility patients support the view that SPTRX3 is a biomarker of male infertility.

Time-Domain Microfluidic Fluorescence Lifetime Flow Cytometry for High-Throughput Förster Resonance Energy Transfer Screening

PubMed Central

Nedbal, Jakub; Visitkul, Viput; Ortiz-Zapater, Elena; Weitsman, Gregory; Chana, Prabhjoat; Matthews, Daniel R; Ng, Tony; Ameer-Beg, Simon M

2015-01-01

Sensing ion or ligand concentrations, physico-chemical conditions, and molecular dimerization or conformation change is possible by assays involving fluorescent lifetime imaging. The inherent low throughput of imaging impedes rigorous statistical data analysis on large cell numbers. We address this limitation by developing a fluorescence lifetime-measuring flow cytometer for fast fluorescence lifetime quantification in living or fixed cell populations. The instrument combines a time-correlated single photon counting epifluorescent microscope with microfluidics cell-handling system. The associated computer software performs burst integrated fluorescence lifetime analysis to assign fluorescence lifetime, intensity, and burst duration to each passing cell. The maximum safe throughput of the instrument reaches 3,000 particles per minute. Living cells expressing spectroscopic rulers of varying peptide lengths were distinguishable by Förster resonant energy transfer measured by donor fluorescence lifetime. An epidermal growth factor (EGF)-stimulation assay demonstrated the technique's capacity to selectively quantify EGF receptor phosphorylation in cells, which was impossible by measuring sensitized emission on a standard flow cytometer. Dual-color fluorescence lifetime detection and cell-specific chemical environment sensing were exemplified using di-4-ANEPPDHQ, a lipophilic environmentally sensitive dye that exhibits changes in its fluorescence lifetime as a function of membrane lipid order. To our knowledge, this instrument opens new applications in flow cytometry which were unavailable due to technological limitations of previously reported fluorescent lifetime flow cytometers. The presented technique is sensitive to lifetimes of most popular fluorophores in the 0.5–5 ns range including fluorescent proteins and is capable of detecting multi-exponential fluorescence lifetime decays. This instrument vastly enhances the throughput of experiments involving fluorescence lifetime measurements, thereby providing statistically significant quantitative data for analysis of large cell populations. © 2014 International Society for Advancement of Cytometry PMID:25523156

Spectroscopic imaging system for high-throughput viability assessment of ovarian spheroids or microdissected tumor tissues (MDTs) in a microfluidic chip

NASA Astrophysics Data System (ADS)

St-Georges-Robillard, A.; Masse, M.; Kendall-Dupont, J.; Strupler, M.; Patra, B.; Jermyn, M.; Mes-Masson, A.-M.; Leblond, F.; Gervais, T.

2016-02-01

There is a growing effort in the biomicrosystems community to develop a personalized treatment response assay for cancer patients using primary cells, patient-derived spheroids, or live tissues on-chip. Recently, our group has developed a technique to cut tumors in 350 μm diameter microtissues and keep them alive on-chip, enabling multiplexed in vitro drug assays on primary tumor tissue. Two-photon microscopy, confocal microscopy and flow cytometry are the current standard to assay tissue chemosensitivity on-chip. While these techniques provide microscopic and molecular information, they are not adapted for high-throughput analysis of microtissues. We present a spectroscopic imaging system that allows rapid quantitative measurements of multiple fluorescent viability markers simultaneously by using a liquid crystal tunable filter to record fluorescence and transmittance spectra. As a proof of concept, 24 spheroids composed of ovarian cancer cell line OV90 were formed in a microfluidic chip, stained with two live cell markers (CellTrackerTM Green and Orange), and imaged. Fluorescence images acquired were normalized to the acquisition time and gain of the camera, dark noise was removed, spectral calibration was applied, and spatial uniformity was corrected. Spectral un-mixing was applied to separate each fluorophore's contribution. We have demonstrated that rapid and simultaneous viability measurements on multiple spheroids can be achieved, which will have a significant impact on the prediction of a tumor's response to multiple treatment options. This technique may be applied as well in drug discovery to assess the potential of a drug candidate directly on human primary tissue.

Androgen Receptor Functional Analyses by High Throughput Imaging: Determination of Ligand, Cell Cycle, and Mutation-Specific Effects

PubMed Central

Szafran, Adam T.; Szwarc, Maria; Marcelli, Marco; Mancini, Michael A.

2008-01-01

Background Understanding how androgen receptor (AR) function is modulated by exposure to steroids, growth factors or small molecules can have important mechanistic implications for AR-related disease therapies (e.g., prostate cancer, androgen insensitivity syndrome, AIS), and in the analysis of environmental endocrine disruptors. Methodology/Principal Findings We report the development of a high throughput (HT) image-based assay that quantifies AR subcellular and subnuclear distribution, and transcriptional reporter gene activity on a cell-by-cell basis. Furthermore, simultaneous analysis of DNA content allowed determination of cell cycle position and permitted the analysis of cell cycle dependent changes in AR function in unsynchronized cell populations. Assay quality for EC50 coefficients of variation were 5–24%, with Z' values reaching 0.91. This was achieved by the selective analysis of cells expressing physiological levels of AR, important because minor over-expression resulted in elevated nuclear speckling and decreased transcriptional reporter gene activity. A small screen of AR-binding ligands, including known agonists, antagonists, and endocrine disruptors, demonstrated that nuclear translocation and nuclear “speckling” were linked with transcriptional output, and specific ligands were noted to differentially affect measurements for wild type versus mutant AR, suggesting differing mechanisms of action. HT imaging of patient-derived AIS mutations demonstrated a proof-of-principle personalized medicine approach to rapidly identify ligands capable of restoring multiple AR functions. Conclusions/Significance HT imaging-based multiplex screening will provide a rapid, systems-level analysis of compounds/RNAi that may differentially affect wild type AR or clinically relevant AR mutations. PMID:18978937

Automated profiling of individual cell-cell interactions from high-throughput time-lapse imaging microscopy in nanowell grids (TIMING).

PubMed

Merouane, Amine; Rey-Villamizar, Nicolas; Lu, Yanbin; Liadi, Ivan; Romain, Gabrielle; Lu, Jennifer; Singh, Harjeet; Cooper, Laurence J N; Varadarajan, Navin; Roysam, Badrinath

2015-10-01

There is a need for effective automated methods for profiling dynamic cell-cell interactions with single-cell resolution from high-throughput time-lapse imaging data, especially, the interactions between immune effector cells and tumor cells in adoptive immunotherapy. Fluorescently labeled human T cells, natural killer cells (NK), and various target cells (NALM6, K562, EL4) were co-incubated on polydimethylsiloxane arrays of sub-nanoliter wells (nanowells), and imaged using multi-channel time-lapse microscopy. The proposed cell segmentation and tracking algorithms account for cell variability and exploit the nanowell confinement property to increase the yield of correctly analyzed nanowells from 45% (existing algorithms) to 98% for wells containing one effector and a single target, enabling automated quantification of cell locations, morphologies, movements, interactions, and deaths without the need for manual proofreading. Automated analysis of recordings from 12 different experiments demonstrated automated nanowell delineation accuracy >99%, automated cell segmentation accuracy >95%, and automated cell tracking accuracy of 90%, with default parameters, despite variations in illumination, staining, imaging noise, cell morphology, and cell clustering. An example analysis revealed that NK cells efficiently discriminate between live and dead targets by altering the duration of conjugation. The data also demonstrated that cytotoxic cells display higher motility than non-killers, both before and during contact. broysam@central.uh.edu or nvaradar@central.uh.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

High Throughput Plasma Water Treatment

NASA Astrophysics Data System (ADS)

Mujovic, Selman; Foster, John

2016-10-01

The troublesome emergence of new classes of micro-pollutants, such as pharmaceuticals and endocrine disruptors, poses challenges for conventional water treatment systems. In an effort to address these contaminants and to support water reuse in drought stricken regions, new technologies must be introduced. The interaction of water with plasma rapidly mineralizes organics by inducing advanced oxidation in addition to other chemical, physical and radiative processes. The primary barrier to the implementation of plasma-based water treatment is process volume scale up. In this work, we investigate a potentially scalable, high throughput plasma water reactor that utilizes a packed bed dielectric barrier-like geometry to maximize the plasma-water interface. Here, the water serves as the dielectric medium. High-speed imaging and emission spectroscopy are used to characterize the reactor discharges. Changes in methylene blue concentration and basic water parameters are mapped as a function of plasma treatment time. Experimental results are compared to electrostatic and plasma chemistry computations, which will provide insight into the reactor's operation so that efficiency can be assessed. Supported by NSF (CBET 1336375).

Using high-throughput barcode sequencing to efficiently map connectomes

PubMed Central

Peikon, Ian D.; Kebschull, Justus M.; Vagin, Vasily V.; Ravens, Diana I.; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R.; Bressan, Dario

2017-01-01

Abstract The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision—a ‘connectome’—is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence—an RNA ‘barcode’—which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. PMID:28449067

Cell classification using big data analytics plus time stretch imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jalali, Bahram; Chen, Claire L.; Mahjoubfar, Ata

2016-09-01

We show that blood cells can be classified with high accuracy and high throughput by combining machine learning with time stretch quantitative phase imaging. Our diagnostic system captures quantitative phase images in a flow microscope at millions of frames per second and extracts multiple biophysical features from individual cells including morphological characteristics, light absorption and scattering parameters, and protein concentration. These parameters form a hyperdimensional feature space in which supervised learning and cell classification is performed. We show binary classification of T-cells against colon cancer cells, as well classification of algae cell strains with high and low lipid content. The label-free screening averts the negative impact of staining reagents on cellular viability or cell signaling. The combination of time stretch machine vision and learning offers unprecedented cell analysis capabilities for cancer diagnostics, drug development and liquid biopsy for personalized genomics.

Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

Hyperspectral Imaging and Spectroscopy of Fluorescently Coupled Acyl-CoA: Cholesterol Acyltransferase in Insect Cells

NASA Technical Reports Server (NTRS)

Malak, H.; Mahtani, H.; Herman, P.; Vecer, J.; Lu, X.; Chang, T. Y.; Richmond, Robert C.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

A high-performance hyperspectral imaging module with high throughput of light suitable for low-intensity fluorescence microscopic imaging and subsequent analysis, including single-pixel-defined emission spectroscopy, was tested on Sf21 insect cells expressing green fluorescence associated with recombinant green fluorescent protein linked or not with the membrane protein acyl-CoA:cholesterol acyltransferase. The imager utilized the phenomenon of optical activity as a new technique providing information over a spectral range of 220-1400 nm, and was inserted between the microscope and an 8-bit CCD video-rate camera. The resulting fluorescence image did not introduce observable image aberrations. The images provided parallel acquisition of well resolved concurrent spatial and spectral information such that fluorescence associated with green fluorescent protein alone was demonstrated to be diffuse within the Sf21 insect cell, and that green fluorescence associated with the membrane protein was shown to be specifically concentrated within regions of the cell cytoplasm. Emission spectra analyzed from different regions of the fluorescence image showed blue shift specific for the regions of concentration associated with the membrane protein.

Camera array based light field microscopy

PubMed Central

Lin, Xing; Wu, Jiamin; Zheng, Guoan; Dai, Qionghai

2015-01-01

This paper proposes a novel approach for high-resolution light field microscopy imaging by using a camera array. In this approach, we apply a two-stage relay system for expanding the aperture plane of the microscope into the size of an imaging lens array, and utilize a sensor array for acquiring different sub-apertures images formed by corresponding imaging lenses. By combining the rectified and synchronized images from 5 × 5 viewpoints with our prototype system, we successfully recovered color light field videos for various fast-moving microscopic specimens with a spatial resolution of 0.79 megapixels at 30 frames per second, corresponding to an unprecedented data throughput of 562.5 MB/s for light field microscopy. We also demonstrated the use of the reported platform for different applications, including post-capture refocusing, phase reconstruction, 3D imaging, and optical metrology. PMID:26417490

Helium Ion Beam Microscopy for Copper Grain Identification in BEOL Structures

NASA Astrophysics Data System (ADS)

van den Boom, Ruud J. J.; Parvaneh, Hamed; Voci, Dave; Huynh, Chuong; Stern, Lewis; Dunn, Kathleen A.; Lifshin, Eric

2009-09-01

Grain size determination in advanced metallization structures requires a technique with resolution ˜2 nm, with a high signal-to-noise ratio and high orientation-dependant contrast for unambiguous identification of grain boundaries. Ideally, such a technique would also be capable of high-throughput and rapid time-to-knowledge. The Helium Ion Microscope (HIM) offers one possibility for achieving these aims in a single platform. This article compares the performance of the HIM with Focused Ion Beam, Scanning Electron and Transmission Electron Microscopes, in terms of achievable image resolution and contrast, using plan-view and cross-sectional imaging of electroplated samples. Although the HIM is capable of sub-nanometer beam diameter, the low signal-to-noise ratio in the images necessitates signal averaging, which degrades the measured image resolution to 6-8 nm. Strategies for improving S/N are discussed in light of the trade-off between beam current and probe size, accelerating voltage, and dwell time.

Whole Organism High-Content Screening by Label-Free, Image-Based Bayesian Classification for Parasitic Diseases

PubMed Central

Paveley, Ross A.; Mansour, Nuha R.; Hallyburton, Irene; Bleicher, Leo S.; Benn, Alex E.; Mikic, Ivana; Guidi, Alessandra; Gilbert, Ian H.; Hopkins, Andrew L.; Bickle, Quentin D.

2012-01-01

Sole reliance on one drug, Praziquantel, for treatment and control of schistosomiasis raises concerns about development of widespread resistance, prompting renewed interest in the discovery of new anthelmintics. To discover new leads we designed an automated label-free, high content-based, high throughput screen (HTS) to assess drug-induced effects on in vitro cultured larvae (schistosomula) using bright-field imaging. Automatic image analysis and Bayesian prediction models define morphological damage, hit/non-hit prediction and larval phenotype characterization. Motility was also assessed from time-lapse images. In screening a 10,041 compound library the HTS correctly detected 99.8% of the hits scored visually. A proportion of these larval hits were also active in an adult worm ex-vivo screen and are the subject of ongoing studies. The method allows, for the first time, screening of large compound collections against schistosomes and the methods are adaptable to other whole organism and cell-based screening by morphology and motility phenotyping. PMID:22860151

The Phase-Induced Amplitude Apodization Coronagraph (PIAAC): A High Performance Coronagraph for Exoplanet Imaging

NASA Astrophysics Data System (ADS)

Guyon, O.; Pluzhnik, E.; Martinache, F.; Ridgway, S.; Galicher, R.

2004-12-01

Using 2 aspheric mirrors, it is possible to achromatically apodize a telescope beam without losing light (Phase-Induced Amplitude Apodization, PIAA). We propose a coronagraph concept using this technique: the telescope pupil is first apodized to yield a high contrast focal plane image, on which an occulting mask is placed. The exit pupil is then de-apodized to regain a large field of view. We show that the PIAAC combines all the qualities needed for efficient exoplanet imaging: full throughput, small inner working angle (1.2 l/d), high angular resolution (l/d), low sensitivity to tip-tilt, and large field of view (more than 200 l/d in diameter). We conclude that PIAAC is well adapted for exoplanet imaging with a 4m to 6m space telescope (TPF mission). This work was carried out under JPL contract numbers 1254445 and 1257767 for Development of Technologies for the Terrestrial Planet Finder Mission, with the support and hospitality of the National Astronomical Observatory of Japan.

High-throughput analysis of sub-visible mAb aggregate particles using automated fluorescence microscopy imaging.

PubMed

Paul, Albert Jesuran; Bickel, Fabian; Röhm, Martina; Hospach, Lisa; Halder, Bettina; Rettich, Nina; Handrick, René; Herold, Eva Maria; Kiefer, Hans; Hesse, Friedemann

2017-07-01

Aggregation of therapeutic proteins is a major concern as aggregates lower the yield and can impact the efficacy of the drug as well as the patient's safety. It can occur in all production stages; thus, it is essential to perform a detailed analysis for protein aggregates. Several methods such as size exclusion high-performance liquid chromatography (SE-HPLC), light scattering, turbidity, light obscuration, and microscopy-based approaches are used to analyze aggregates. None of these methods allows determination of all types of higher molecular weight (HMW) species due to a limited size range. Furthermore, quantification and specification of different HMW species are often not possible. Moreover, automation is a perspective challenge coming up with automated robotic laboratory systems. Hence, there is a need for a fast, high-throughput-compatible method, which can detect a broad size range and enable quantification and classification. We describe a novel approach for the detection of aggregates in the size range 1 to 1000 μm combining fluorescent dyes for protein aggregate labelling and automated fluorescence microscope imaging (aFMI). After appropriate selection of the dye and method optimization, our method enabled us to detect various types of HMW species of monoclonal antibodies (mAbs). Using 10 μmol L -1 4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonate (Bis-ANS) in combination with aFMI allowed the analysis of mAb aggregates induced by different stresses occurring during downstream processing, storage, and administration. Validation of our results was performed by SE-HPLC, UV-Vis spectroscopy, and dynamic light scattering. With this new approach, we could not only reliably detect different HMW species but also quantify and classify them in an automated approach. Our method achieves high-throughput requirements and the selection of various fluorescent dyes enables a broad range of applications.

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-06-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-04-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

Fluorescence lifetime microscopy with a time- and space-resolved single-photon counting detector

PubMed Central

Michalet, X.; Siegmund, O.H.W.; Vallerga, J.V.; Jelinsky, P.; Pinaud, F. F.; Millaud, J.E.; Weiss, S.

2017-01-01

We have recently developed a wide-field photon-counting detector (the H33D detector) having high-temporal and high-spatial resolutions and capable of recording up to 500,000 photons per sec. Its temporal performance has been previously characterized using solutions of fluorescent materials with different lifetimes, and its spatial resolution using sub-diffraction objects (beads and quantum dots). Here we show its application to fluorescence lifetime imaging of live cells and compare its performance to a scanning confocal TCSPC approach. With the expected improvements in photocathode sensitivity and increase in detector throughput, this technology appears as a promising alternative to the current lifetime imaging solutions. PMID:29449756

High-content profiling of cell responsiveness to graded substrates based on combinyatorially variant polymers.

PubMed

Liu, Er; Treiser, Matthew D; Patel, Hiral; Sung, Hak-Joon; Roskov, Kristen E; Kohn, Joachim; Becker, Matthew L; Moghe, Prabhas V

2009-08-01

We have developed a novel approach combining high information and high throughput analysis to characterize cell adhesive responses to biomaterial substrates possessing gradients in surface topography. These gradients were fabricated by subjecting thin film blends of tyrosine-derived polycarbonates, i.e. poly(DTE carbonate) and poly(DTO carbonate) to a gradient temperature annealing protocol. Saos-2 cells engineered with a green fluorescent protein (GFP) reporter for farnesylation (GFP-f) were cultured on the gradient substrates to assess the effects of nanoscale surface topology and roughness that arise during the phase separation process on cell attachment and adhesion strength. The high throughput imaging approach allowed us to rapidly identify the "global" and "high content" structure-property relationships between cell adhesion and biomaterial properties such as polymer chemistry and topography. This study found that cell attachment and spreading increased monotonically with DTE content and were significantly elevated at the position with intermediate regions corresponding to the highest "gradient" of surface roughness, while GFP-f farnesylation intensity descriptors were sensitively altered by surface roughness, even in cells with comparable levels of spreading.

Eddy current-shielded x-space relaxometer for sensitive magnetic nanoparticle characterization

PubMed Central

Bauer, L. M.; Hensley, D. W.; Zheng, B.; Tay, Z. W.; Goodwill, P. W.; Griswold, M. A.; Conolly, S. M.

2016-01-01

The development of magnetic particle imaging (MPI) has created a need for optimized magnetic nanoparticles. Magnetic particle relaxometry is an excellent tool for characterizing potential tracers for MPI. In this paper, we describe the design and construction of a high-throughput tabletop relaxometer that is able to make sensitive measurements of MPI tracers without the need for a dedicated shield room. PMID:27250472

Eddy current-shielded x-space relaxometer for sensitive magnetic nanoparticle characterization.

PubMed

Bauer, L M; Hensley, D W; Zheng, B; Tay, Z W; Goodwill, P W; Griswold, M A; Conolly, S M

2016-05-01

The development of magnetic particle imaging (MPI) has created a need for optimized magnetic nanoparticles. Magnetic particle relaxometry is an excellent tool for characterizing potential tracers for MPI. In this paper, we describe the design and construction of a high-throughput tabletop relaxometer that is able to make sensitive measurements of MPI tracers without the need for a dedicated shield room.

Low Cost, High-Throughput 3D Pulmonary Imager Using Hyperpolarized Contrast Agents and Low Field MRI

DTIC Science & Technology

2016-10-01

HAS THE PROJECT PROVIDED? ..... 7 HOW WERE THE RESULTS DISSEMINATED TO COMMUNITIES OF INTEREST? ................................................. 8...the results disseminated to communities of interest? Nothing to Report 4. IMPACT What was the impact on the development of the principal...the broader biomedical community , expanding the utility of HP methods as a new tool for probing fundamental biomedical questions. Acknowledgments The

Improved Resolution Optical Time Stretch Imaging Based on High Efficiency In-Fiber Diffraction.

PubMed

Wang, Guoqing; Yan, Zhijun; Yang, Lei; Zhang, Lin; Wang, Chao

2018-01-12

Most overlooked challenges in ultrafast optical time stretch imaging (OTSI) are sacrificed spatial resolution and higher optical loss. These challenges are originated from optical diffraction devices used in OTSI, which encode image into spectra of ultrashort optical pulses. Conventional free-space diffraction gratings, as widely used in existing OTSI systems, suffer from several inherent drawbacks: limited diffraction efficiency in a non-Littrow configuration due to inherent zeroth-order reflection, high coupling loss between free-space gratings and optical fibers, bulky footprint, and more importantly, sacrificed imaging resolution due to non-full-aperture illumination for individual wavelengths. Here we report resolution-improved and diffraction-efficient OTSI using in-fiber diffraction for the first time to our knowledge. The key to overcome the existing challenges is a 45° tilted fiber grating (TFG), which serves as a compact in-fiber diffraction device offering improved diffraction efficiency (up to 97%), inherent compatibility with optical fibers, and improved imaging resolution owning to almost full-aperture illumination for all illumination wavelengths. 50 million frames per second imaging of fast moving object at 46 m/s with improved imaging resolution has been demonstrated. This conceptually new in-fiber diffraction design opens the way towards cost-effective, compact and high-resolution OTSI systems for image-based high-throughput detection and measurement.

Quantitative volumetric imaging of normal, neoplastic and hyperplastic mouse prostate using ultrasound.

PubMed

Singh, Shalini; Pan, Chunliu; Wood, Ronald; Yeh, Chiuan-Ren; Yeh, Shuyuan; Sha, Kai; Krolewski, John J; Nastiuk, Kent L

2015-09-21

Genetically engineered mouse models are essential to the investigation of the molecular mechanisms underlying human prostate pathology and the effects of therapy on the diseased prostate. Serial in vivo volumetric imaging expands the scope and accuracy of experimental investigations of models of normal prostate physiology, benign prostatic hyperplasia and prostate cancer, which are otherwise limited by the anatomy of the mouse prostate. Moreover, accurate imaging of hyperplastic and tumorigenic prostates is now recognized as essential to rigorous pre-clinical trials of new therapies. Bioluminescent imaging has been widely used to determine prostate tumor size, but is semi-quantitative at best. Magnetic resonance imaging can determine prostate volume very accurately, but is expensive and has low throughput. We therefore sought to develop and implement a high throughput, low cost, and accurate serial imaging protocol for the mouse prostate. We developed a high frequency ultrasound imaging technique employing 3D reconstruction that allows rapid and precise assessment of mouse prostate volume. Wild-type mouse prostates were examined (n = 4) for reproducible baseline imaging, and treatment effects on volume were compared, and blinded data analyzed for intra- and inter-operator assessments of reproducibility by correlation and for Bland-Altman analysis. Examples of benign prostatic hyperplasia mouse model prostate (n = 2) and mouse prostate implantation of orthotopic human prostate cancer tumor and its growth (n =  ) are also demonstrated. Serial measurement volume of the mouse prostate revealed that high frequency ultrasound was very precise. Following endocrine manipulation, regression and regrowth of the prostate could be monitored with very low intra- and interobserver variability. This technique was also valuable to monitor the development of prostate growth in a model of benign prostatic hyperplasia. Additionally, we demonstrate accurate ultrasound image-guided implantation of orthotopic tumor xenografts and monitoring of subsequent tumor growth from ~10 to ~750 mm(3) volume. High frequency ultrasound imaging allows precise determination of normal, neoplastic and hyperplastic mouse prostate. Low cost and small image size allows incorporation of this imaging modality inside clean animal facilities, and thereby imaging of immunocompromised models. 3D reconstruction for volume determination is easily mastered, and both small and large relative changes in volume are accurately visualized. Ultrasound imaging does not rely on penetration of exogenous imaging agents, and so may therefore better measure poorly vascularized or necrotic diseased tissue, relative to bioluminescent imaging (IVIS). Our method is precise and reproducible with very low inter- and intra-observer variability. Because it is non-invasive, mouse models of prostatic disease states can be imaged serially, reducing inter-animal variability, and enhancing the power to detect small volume changes following therapeutic intervention.

Small angle X-ray scattering as a high-throughput method to classify antimicrobial modes of action.

PubMed

von Gundlach, A R; Garamus, V M; Gorniak, T; Davies, H A; Reischl, M; Mikut, R; Hilpert, K; Rosenhahn, A

2016-05-01

Multi-drug resistant bacteria are currently undermining our health care system worldwide. While novel antimicrobial drugs, such as antimicrobial peptides, are urgently needed, identification of new modes of action is money and time consuming, and in addition current approaches are not available in a high throughput manner. Here we explore how small angle X-ray scattering (SAXS) as high throughput method can contribute to classify the mode of action for novel antimicrobials and therefore supports fast decision making in drug development. Using data bases for natural occurring antimicrobial peptides or predicting novel artificial peptides, many candidates can be discovered that will kill a selected target bacterium. However, in order to narrow down the selection it is important to know if these peptides follow all the same mode of action. In addition, the mode of action should be different from conventional antibiotics, in consequence peptide candidates can be developed further into drugs against multi-drug resistant bacteria. Here we used one short antimicrobial peptide with unknown mode of action and compared the ultrastructural changes of Escherichia coli cells after treatment with the peptide to cells treated with classic antibiotics. The key finding is that SAXS as a structure sensitive tool provides a rapid feedback on drug induced ultrastructural alterations in whole E. coli cells. We could demonstrate that ultrastructural changes depend on the used antibiotics and their specific mode of action. This is demonstrated using several well characterized antimicrobial compounds and the analysis of resulting SAXS curves by principal component analysis. To understand the result of the PCA analysis, the data is correlated with TEM images. In contrast to real space imaging techniques, SAXS allows to obtain nanoscale information averaged over approximately one million cells. The measurement takes only seconds, while conventional tests to identify a mode of action require days or weeks per single substance. The antimicrobial peptide showed a different mode of action as all tested antibiotics including polymyxin B and is therefore a good candidate for further drug development. We envision SAXS to become a useful tool within the high-throughput screening pipeline of modern drug discovery. This article is part of a Special Issue entitled: Antimicrobial peptides edited by Karl Lohner and Kai Hilpert. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of a Whole Slide Imaging System on Smartphones and Evaluation With Frozen Section Samples

PubMed Central

Jiang, Liren

2017-01-01

Background The aim was to develop scalable Whole Slide Imaging (sWSI), a WSI system based on mainstream smartphones coupled with regular optical microscopes. This ultra-low-cost solution should offer diagnostic-ready imaging quality on par with standalone scanners, supporting both oil and dry objective lenses of different magnifications, and reasonably high throughput. These performance metrics should be evaluated by expert pathologists and match those of high-end scanners. Objective The aim was to develop scalable Whole Slide Imaging (sWSI), a whole slide imaging system based on smartphones coupled with optical microscopes. This ultra-low-cost solution should offer diagnostic-ready imaging quality on par with standalone scanners, supporting both oil and dry object lens of different magnification. All performance metrics should be evaluated by expert pathologists and match those of high-end scanners. Methods In the sWSI design, the digitization process is split asynchronously between light-weight clients on smartphones and powerful cloud servers. The client apps automatically capture FoVs at up to 12-megapixel resolution and process them in real-time to track the operation of users, then give instant feedback of guidance. The servers first restitch each pair of FoVs, then automatically correct the unknown nonlinear distortion introduced by the lens of the smartphone on the fly, based on pair-wise stitching, before finally combining all FoVs into one gigapixel VS for each scan. These VSs can be viewed using Internet browsers anywhere. In the evaluation experiment, 100 frozen section slides from patients randomly selected among in-patients of the participating hospital were scanned by both a high-end Leica scanner and sWSI. All VSs were examined by senior pathologists whose diagnoses were compared against those made using optical microscopy as ground truth to evaluate the image quality. Results The sWSI system is developed for both Android and iPhone smartphones and is currently being offered to the public. The image quality is reliable and throughput is approximately 1 FoV per second, yielding a 15-by-15 mm slide under 20X object lens in approximately 30-35 minutes, with little training required for the operator. The expected cost for setup is approximately US $100 and scanning each slide costs between US $1 and $10, making sWSI highly cost-effective for infrequent or low-throughput usage. In the clinical evaluation of sample-wise diagnostic reliability, average accuracy scores achieved by sWSI-scan-based diagnoses were as follows: 0.78 for breast, 0.88 for uterine corpus, 0.68 for thyroid, and 0.50 for lung samples. The respective low-sensitivity rates were 0.05, 0.05, 0.13, and 0.25 while the respective low-specificity rates were 0.18, 0.08, 0.20, and 0.25. The participating pathologists agreed that the overall quality of sWSI was generally on par with that produced by high-end scanners, and did not affect diagnosis in most cases. Pathologists confirmed that sWSI is reliable enough for standard diagnoses of most tissue categories, while it can be used for quick screening of difficult cases. Conclusions As an ultra-low-cost alternative to whole slide scanners, diagnosis-ready VS quality and robustness for commercial usage is achieved in the sWSI solution. Operated on main-stream smartphones installed on normal optical microscopes, sWSI readily offers affordable and reliable WSI to resource-limited or infrequent clinical users. PMID:28916508

Systems cell biology of the mitotic spindle.

PubMed

Saleem, Ramsey A; Aitchison, John D

2010-01-11

Cell division depends critically on the temporally controlled assembly of mitotic spindles, which are responsible for the distribution of duplicated chromosomes to each of the two daughter cells. To gain insight into the process, Vizeacoumar et al., in this issue (Vizeacoumar et al. 2010. J. Cell Biol. doi:10.1083/jcb.200909013), have combined systems genetics with high-throughput and high-content imaging to comprehensively identify and classify novel components that contribute to the morphology and function of the mitotic spindle.

Multiprocessor Z-Buffer Architecture for High-Speed, High Complexity Computer Image Generation.

DTIC Science & Technology

1983-12-01

Oversampling 50 17. "Poking Through" Effects 51 18. Sampling Paths 52 19. Triangle Variables 54 20. Intelligent Tiling Algorithm 61 21. Tiler Functional Blocks...64 * 22. HSD Interface 65 23. Tiling Machine Setup 67 24. Tiling Machine 68 25. Tile Accumulate 69 26. A lx$ Sorting Machine 77 27. A 2x8 Sorting...Delay 227 87. Effect of Triangle Size on Tiler Throughput Rates 229 88. Tiling Machine Setup Stage Performance for Oversample Mode 234 89. Tiling

Quantitative Developments of Biomolecular Databases, Measurement Methodology, and Comprehensive Transport Models for Bioanalytical Microfluidics

DTIC Science & Technology

2006-10-01

Gibbs, E. M., Fletterick, R. J., Day, Y. S. N., Myszka, D. G., and Rath, V. L. (2002) “Structure-activity analysis of the purine-binding site of human ...Rich, R. L., Day, Y. S. N., Morton, T. A., and Myszka, D. G., (2001) “High- resolution and high-throughput protocols for measuring drug/ human serum...entire text) 1. Attard, P., Images of nanobubbles on hydrophobic surfaces and their interactions. Phys. Rev. Lett., 2001. 87. 2. Ottino, J.M

Visual Exploration of Genetic Association with Voxel-based Imaging Phenotypes in an MCI/AD Study

PubMed Central

Kim, Sungeun; Shen, Li; Saykin, Andrew J.; West, John D.

2010-01-01

Neuroimaging genomics is a new transdisciplinary research field, which aims to examine genetic effects on brain via integrated analyses of high throughput neuroimaging and genomic data. We report our recent work on (1) developing an imaging genomic browsing system that allows for whole genome and entire brain analyses based on visual exploration and (2) applying the system to the imaging genomic analysis of an existing MCI/AD cohort. Voxel-based morphometry is used to define imaging phenotypes. ANCOVA is employed to evaluate the effect of the interaction of genotypes and diagnosis in relation to imaging phenotypes while controlling for relevant covariates. Encouraging experimental results suggest that the proposed system has substantial potential for enabling discovery of imaging genomic associations through visual evaluation and for localizing candidate imaging regions and genomic regions for refined statistical modeling. PMID:19963597

Efficient geometric rectification techniques for spectral analysis algorithm

NASA Technical Reports Server (NTRS)

Chang, C. Y.; Pang, S. S.; Curlander, J. C.

1992-01-01

The spectral analysis algorithm is a viable technique for processing synthetic aperture radar (SAR) data in near real time throughput rates by trading the image resolution. One major challenge of the spectral analysis algorithm is that the output image, often referred to as the range-Doppler image, is represented in the iso-range and iso-Doppler lines, a curved grid format. This phenomenon is known to be the fanshape effect. Therefore, resampling is required to convert the range-Doppler image into a rectangular grid format before the individual images can be overlaid together to form seamless multi-look strip imagery. An efficient algorithm for geometric rectification of the range-Doppler image is presented. The proposed algorithm, realized in two one-dimensional resampling steps, takes into consideration the fanshape phenomenon of the range-Doppler image as well as the high squint angle and updates of the cross-track and along-track Doppler parameters. No ground reference points are required.

Enabling inspection solutions for future mask technologies through the development of massively parallel E-Beam inspection

NASA Astrophysics Data System (ADS)

Malloy, Matt; Thiel, Brad; Bunday, Benjamin D.; Wurm, Stefan; Jindal, Vibhu; Mukhtar, Maseeh; Quoi, Kathy; Kemen, Thomas; Zeidler, Dirk; Eberle, Anna Lena; Garbowski, Tomasz; Dellemann, Gregor; Peters, Jan Hendrik

2015-09-01

The new device architectures and materials being introduced for sub-10nm manufacturing, combined with the complexity of multiple patterning and the need for improved hotspot detection strategies, have pushed current wafer inspection technologies to their limits. In parallel, gaps in mask inspection capability are growing as new generations of mask technologies are developed to support these sub-10nm wafer manufacturing requirements. In particular, the challenges associated with nanoimprint and extreme ultraviolet (EUV) mask inspection require new strategies that enable fast inspection at high sensitivity. The tradeoffs between sensitivity and throughput for optical and e-beam inspection are well understood. Optical inspection offers the highest throughput and is the current workhorse of the industry for both wafer and mask inspection. E-beam inspection offers the highest sensitivity but has historically lacked the throughput required for widespread adoption in the manufacturing environment. It is unlikely that continued incremental improvements to either technology will meet tomorrow's requirements, and therefore a new inspection technology approach is required; one that combines the high-throughput performance of optical with the high-sensitivity capabilities of e-beam inspection. To support the industry in meeting these challenges SUNY Poly SEMATECH has evaluated disruptive technologies that can meet the requirements for high volume manufacturing (HVM), for both the wafer fab [1] and the mask shop. Highspeed massively parallel e-beam defect inspection has been identified as the leading candidate for addressing the key gaps limiting today's patterned defect inspection techniques. As of late 2014 SUNY Poly SEMATECH completed a review, system analysis, and proof of concept evaluation of multiple e-beam technologies for defect inspection. A champion approach has been identified based on a multibeam technology from Carl Zeiss. This paper includes a discussion on the need for high-speed e-beam inspection and then provides initial imaging results from EUV masks and wafers from 61 and 91 beam demonstration systems. Progress towards high resolution and consistent intentional defect arrays (IDA) is also shown.

Fast globally optimal segmentation of cells in fluorescence microscopy images.

PubMed

Bergeest, Jan-Philip; Rohr, Karl

2011-01-01

Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.

Combining high-throughput MALDI-TOF mass spectrometry and isoelectric focusing gel electrophoresis for virtual 2D gel-based proteomics.

PubMed

Lohnes, Karen; Quebbemann, Neil R; Liu, Kate; Kobzeff, Fred; Loo, Joseph A; Ogorzalek Loo, Rachel R

2016-07-15

The virtual two-dimensional gel electrophoresis/mass spectrometry (virtual 2D gel/MS) technology combines the premier, high-resolution capabilities of 2D gel electrophoresis with the sensitivity and high mass accuracy of mass spectrometry (MS). Intact proteins separated by isoelectric focusing (IEF) gel electrophoresis are imaged from immobilized pH gradient (IPG) polyacrylamide gels (the first dimension of classic 2D-PAGE) by matrix-assisted laser desorption/ionization (MALDI) MS. Obtaining accurate intact masses from sub-picomole-level proteins embedded in 2D-PAGE gels or in IPG strips is desirable to elucidate how the protein of one spot identified as protein 'A' on a 2D gel differs from the protein of another spot identified as the same protein, whenever tryptic peptide maps fail to resolve the issue. This task, however, has been extremely challenging. Virtual 2D gel/MS provides access to these intact masses. Modifications to our matrix deposition procedure improve the reliability with which IPG gels can be prepared; the new procedure is described. Development of this MALDI MS imaging (MSI) method for high-throughput MS with integrated 'top-down' MS to elucidate protein isoforms from complex biological samples is described and it is demonstrated that a 4-cm IPG gel segment can now be imaged in approximately 5min. Gel-wide chemical and enzymatic methods with further interrogation by MALDI MS/MS provide identifications, sequence-related information, and post-translational/transcriptional modification information. The MSI-based virtual 2D gel/MS platform may potentially link the benefits of 'top-down' and 'bottom-up' proteomics. Copyright © 2016 Elsevier Inc. All rights reserved.

Snapshot imaging Fraunhofer line discriminator for detection of plant fluorescence

NASA Astrophysics Data System (ADS)

Gupta Roy, S.; Kudenov, M. W.

2015-05-01

Non-invasive quantification of plant health is traditionally accomplished using reflectance based metrics, such as the normalized difference vegetative index (NDVI). However, measuring plant fluorescence (both active and passive) to determine photochemistry of plants has gained importance. Due to better cost efficiency, lower power requirements, and simpler scanning synchronization, detecting passive fluorescence is preferred over active fluorescence. In this paper, we propose a high speed imaging approach for measuring passive plant fluorescence, within the hydrogen alpha Fraunhofer line at ~656 nm, using a Snapshot Imaging Fraunhofer Line Discriminator (SIFOLD). For the first time, the advantage of snapshot imaging for high throughput Fraunhofer Line Discrimination (FLD) is cultivated by our system, which is based on a multiple-image Fourier transform spectrometer and a spatial heterodyne interferometer (SHI). The SHI is a Sagnac interferometer, which is dispersion compensated using blazed diffraction gratings. We present data and techniques for calibrating the SIFOLD to any particular wavelength. This technique can be applied to quantify plant fluorescence at low cost and reduced complexity of data collection.

The National Institutes of Health Clinical Center Digital Imaging Network, Picture Archival and Communication System, and Radiology Information System.

PubMed

Goldszal, A F; Brown, G K; McDonald, H J; Vucich, J J; Staab, E V

2001-06-01

In this work, we describe the digital imaging network (DIN), picture archival and communication system (PACS), and radiology information system (RIS) currently being implemented at the Clinical Center, National Institutes of Health (NIH). These systems are presently in clinical operation. The DIN is a redundant meshed network designed to address gigabit density and expected high bandwidth requirements for image transfer and server aggregation. The PACS projected workload is 5.0 TB of new imaging data per year. Its architecture consists of a central, high-throughput Digital Imaging and Communications in Medicine (DICOM) data repository and distributed redundant array of inexpensive disks (RAID) servers employing fiber-channel technology for immediate delivery of imaging data. On demand distribution of images and reports to clinicians and researchers is accomplished via a clustered web server. The RIS follows a client-server model and provides tools to order exams, schedule resources, retrieve and review results, and generate management reports. The RIS-hospital information system (HIS) interfaces include admissions, discharges, and transfers (ATDs)/demographics, orders, appointment notifications, doctors update, and results.

Thermal Neutron Radiography using a High-flux Compact Neutron Generator

NASA Astrophysics Data System (ADS)

Taylor, Michael; Sengbusch, Evan; Seyfert, Chris; Moll, Eli; Radel, Ross

A novel neutron imaging system has been designed and constructed by Phoenix Nuclear Labs to investigate specimens when conventional X-ray imaging will not suffice. A first-generation electronic neutron generator is actively being used by the United States Army and is coupled with activation films for neutron radiography to inspect munitions and other critical defence and aerospace components. A second-generation system has been designed to increase the total neutron output from an upgraded gaseous deuterium target to 5×1011 DD n/s, generating higher neutron flux at the imaging plane and dramatically reducing interrogation time, while maintaining high spatial resolution and low geometric unsharpness. A description of the neutron generator and imaging system, including the beamline, target and detector platform, is given in this paper. State of the art neutron moderators, collimators and imaging detector components are also discussed in the context of increasing specimen throughput and optimizing image quality. Neutron radiographs captured with the neutron radiography system will be further compared against simulated images using the MCNP nuclear simulation code.

Micro-computed tomography imaging and analysis in developmental biology and toxicology.

PubMed

Wise, L David; Winkelmann, Christopher T; Dogdas, Belma; Bagchi, Ansuman

2013-06-01

Micro-computed tomography (micro-CT) is a high resolution imaging technique that has expanded and strengthened in use since it was last reviewed in this journal in 2004. The technology has expanded to include more detailed analysis of bone, as well as soft tissues, by use of various contrast agents. It is increasingly applied to questions in developmental biology and developmental toxicology. Relatively high-throughput protocols now provide a powerful and efficient means to evaluate embryos and fetuses subjected to genetic manipulations or chemical exposures. This review provides an overview of the technology, including scanning, reconstruction, visualization, segmentation, and analysis of micro-CT generated images. This is followed by a review of more recent applications of the technology in some common laboratory species that highlight the diverse issues that can be addressed. Copyright © 2013 Wiley Periodicals, Inc.

Noninvasive characterization of the fission yeast cell cycle by monitoring dry mass with digital holographic microscopy.

PubMed

Rappaz, Benjamin; Cano, Elena; Colomb, Tristan; Kühn, Jonas; Depeursinge, Christian; Simanis, Viesturs; Magistretti, Pierre J; Marquet, Pierre

2009-01-01

Digital holography microscopy (DHM) is an optical technique which provides phase images yielding quantitative information about cell structure and cellular dynamics. Furthermore, the quantitative phase images allow the derivation of other parameters, including dry mass production, density, and spatial distribution. We have applied DHM to study the dry mass production rate and the dry mass surface density in wild-type and mutant fission yeast cells. Our study demonstrates the applicability of DHM as a tool for label-free quantitative analysis of the cell cycle and opens the possibility for its use in high-throughput screening.

Studying post-etching silicon crystal defects on 300mm wafer by automatic defect review AFM

NASA Astrophysics Data System (ADS)

Zandiatashbar, Ardavan; Taylor, Patrick A.; Kim, Byong; Yoo, Young-kook; Lee, Keibock; Jo, Ahjin; Lee, Ju Suk; Cho, Sang-Joon; Park, Sang-il

2016-03-01

Single crystal silicon wafers are the fundamental elements of semiconductor manufacturing industry. The wafers produced by Czochralski (CZ) process are very high quality single crystalline materials with known defects that are formed during the crystal growth or modified by further processing. While defects can be unfavorable for yield for some manufactured electrical devices, a group of defects like oxide precipitates can have both positive and negative impacts on the final device. The spatial distribution of these defects may be found by scattering techniques. However, due to limitations of scattering (i.e. light wavelength), many crystal defects are either poorly classified or not detected. Therefore a high throughput and accurate characterization of their shape and dimension is essential for reviewing the defects and proper classification. While scanning electron microscopy (SEM) can provide high resolution twodimensional images, atomic force microscopy (AFM) is essential for obtaining three-dimensional information of the defects of interest (DOI) as it is known to provide the highest vertical resolution among all techniques [1]. However AFM's low throughput, limited tip life, and laborious efforts for locating the DOI have been the limitations of this technique for defect review for 300 mm wafers. To address these limitations of AFM, automatic defect review AFM has been introduced recently [2], and is utilized in this work for studying DOI on 300 mm silicon wafer. In this work, we carefully etched a 300 mm silicon wafer with a gaseous acid in a reducing atmosphere at a temperature and for a sufficient duration to decorate and grow the crystal defects to a size capable of being detected as light scattering defects [3]. The etched defects form a shallow structure and their distribution and relative size are inspected by laser light scattering (LLS). However, several groups of defects couldn't be properly sized by the LLS due to the very shallow depth and low light scattering. Likewise, SEM cannot be used effectively for post-inspection defect review and classification of these very shallow types of defects. To verify and obtain accurate shape and three-dimensional information of those defects, automatic defect review AFM (ADR AFM) is utilized for accurate locating and imaging of DOI. In ADR AFM, non-contact mode imaging is used for non-destructive characterization and preserving tip sharpness for data repeatability and reproducibility. Locating DOI and imaging are performed automatically with a throughput of many defects per hour. Topography images of DOI has been collected and compared with SEM images. The ADR AFM has been shown as a non-destructive metrology tool for defect review and obtaining three-dimensional topography information.

A Fully Automated Microfluidic Femtosecond Laser Axotomy Platform for Nerve Regeneration Studies in C. elegans

PubMed Central

Gokce, Sertan Kutal; Guo, Samuel X.; Ghorashian, Navid; Everett, W. Neil; Jarrell, Travis; Kottek, Aubri; Bovik, Alan C.; Ben-Yakar, Adela

2014-01-01

Femtosecond laser nanosurgery has been widely accepted as an axonal injury model, enabling nerve regeneration studies in the small model organism, Caenorhabditis elegans. To overcome the time limitations of manual worm handling techniques, automation and new immobilization technologies must be adopted to improve throughput in these studies. While new microfluidic immobilization techniques have been developed that promise to reduce the time required for axotomies, there is a need for automated procedures to minimize the required amount of human intervention and accelerate the axotomy processes crucial for high-throughput. Here, we report a fully automated microfluidic platform for performing laser axotomies of fluorescently tagged neurons in living Caenorhabditis elegans. The presented automation process reduces the time required to perform axotomies within individual worms to ∼17 s/worm, at least one order of magnitude faster than manual approaches. The full automation is achieved with a unique chip design and an operation sequence that is fully computer controlled and synchronized with efficient and accurate image processing algorithms. The microfluidic device includes a T-shaped architecture and three-dimensional microfluidic interconnects to serially transport, position, and immobilize worms. The image processing algorithms can identify and precisely position axons targeted for ablation. There were no statistically significant differences observed in reconnection probabilities between axotomies carried out with the automated system and those performed manually with anesthetics. The overall success rate of automated axotomies was 67.4±3.2% of the cases (236/350) at an average processing rate of 17.0±2.4 s. This fully automated platform establishes a promising methodology for prospective genome-wide screening of nerve regeneration in C. elegans in a truly high-throughput manner. PMID:25470130

International Ultraviolet Explorer Final Archive

NASA Technical Reports Server (NTRS)

1997-01-01

CSC processed IUE images through the Final Archive Data Processing System. Raw images were obtained from both NDADS and the IUEGTC optical disk platters for processing on the Alpha cluster, and from the IUEGTC optical disk platters for DECstation processing. Input parameters were obtained from the IUE database. Backup tapes of data to send to VILSPA were routinely made on the Alpha cluster. IPC handled more than 263 requests for priority NEWSIPS processing during the contract. Staff members also answered various questions and requests for information and sent copies of IUE documents to requesters. CSC implemented new processing capabilities into the NEWSIPS processing systems as they became available. In addition, steps were taken to improve efficiency and throughput whenever possible. The node TORTE was reconfigured as the I/O server for Alpha processing in May. The number of Alpha nodes used for the NEWSIPS processing queue was increased to a maximum of six in measured fashion in order to understand the dependence of throughput on the number of nodes and to be able to recognize when a point of diminishing returns was reached. With Project approval, generation of the VD FITS files was dropped in July. This action not only saved processing time but, even more significantly, also reduced the archive storage media requirements, and the time required to perform the archiving, drastically. The throughput of images verified through CDIVS and processed through NEWSIPS for the contract period is summarized below. The number of images of a given dispersion type and camera that were processed in any given month reflects several factors, including the availability of the required NEWSIPS software system, the availability of the corresponding required calibrations (e.g., the LWR high-dispersion ripple correction and absolute calibration), and the occurrence of reprocessing efforts such as that conducted to incorporate the updated SWP sensitivity-degradation correction in May.

CMOS Image Sensors for High Speed Applications.

PubMed

El-Desouki, Munir; Deen, M Jamal; Fang, Qiyin; Liu, Louis; Tse, Frances; Armstrong, David

2009-01-01

Recent advances in deep submicron CMOS technologies and improved pixel designs have enabled CMOS-based imagers to surpass charge-coupled devices (CCD) imaging technology for mainstream applications. The parallel outputs that CMOS imagers can offer, in addition to complete camera-on-a-chip solutions due to being fabricated in standard CMOS technologies, result in compelling advantages in speed and system throughput. Since there is a practical limit on the minimum pixel size (4∼5 μm) due to limitations in the optics, CMOS technology scaling can allow for an increased number of transistors to be integrated into the pixel to improve both detection and signal processing. Such smart pixels truly show the potential of CMOS technology for imaging applications allowing CMOS imagers to achieve the image quality and global shuttering performance necessary to meet the demands of ultrahigh-speed applications. In this paper, a review of CMOS-based high-speed imager design is presented and the various implementations that target ultrahigh-speed imaging are described. This work also discusses the design, layout and simulation results of an ultrahigh acquisition rate CMOS active-pixel sensor imager that can take 8 frames at a rate of more than a billion frames per second (fps).

High Throughput PBTK: Open-Source Data and Tools for ...

EPA Pesticide Factsheets

Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy

High-throughput label-free screening of euglena gracilis with optofluidic time-stretch quantitative phase microscopy

NASA Astrophysics Data System (ADS)

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Yaxiaer, Yalikun; Kobayashi, Hirofumi; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-02-01

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, microalgal biofuel is expected to play a key role in reducing the detrimental effects of global warming since microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid contents and fail to characterize a diverse population of microalgal cells with single-cell resolution in a noninvasive and interference-free manner. Here we demonstrate high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy. In particular, we use Euglena gracilis - an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement) within lipid droplets. Our optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch phase-contrast microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase contents of every single cell at a high throughput of 10,000 cells/s. We characterize heterogeneous populations of E. gracilis cells under two different culture conditions to evaluate their lipid production efficiency. Our method holds promise as an effective analytical tool for microalgaebased biofuel production.

A 181 GOPS AKAZE Accelerator Employing Discrete-Time Cellular Neural Networks for Real-Time Feature Extraction.

PubMed

Jiang, Guangli; Liu, Leibo; Zhu, Wenping; Yin, Shouyi; Wei, Shaojun

2015-09-04

This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network) that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures.

Cargo identification algorithms facilitating unmanned/unattended inspection at high throughput portals

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2007-10-01

A simple model is presented of a possible inspection regimen applied to each leg of a cargo containers' journey between its point of origin and destination. Several candidate modalities are proposed to be used at multiple remote locations to act as a pre-screen inspection as the target approaches a perimeter and as the primary inspection modality at the portal. Information from multiple data sets are fused to optimize the costs and performance of a network of such inspection systems. A series of image processing algorithms are presented that automatically process X-ray images of containerized cargo. The goal of this processing is to locate the container in a real time stream of traffic traversing a portal without impeding the flow of commerce. Such processing may facilitate the inclusion of unmanned/unattended inspection systems in such a network. Several samples of the processing applied to data collected from deployed systems are included. Simulated data from a notional cargo inspection system with multiple sensor modalities and advanced data fusion algorithms are also included to show the potential increased detection and throughput performance of such a configuration.

Automatic pelvis segmentation from x-ray images of a mouse model

NASA Astrophysics Data System (ADS)

Al Okashi, Omar M.; Du, Hongbo; Al-Assam, Hisham

2017-05-01

The automatic detection and quantification of skeletal structures has a variety of different applications for biological research. Accurate segmentation of the pelvis from X-ray images of mice in a high-throughput project such as the Mouse Genomes Project not only saves time and cost but also helps achieving an unbiased quantitative analysis within the phenotyping pipeline. This paper proposes an automatic solution for pelvis segmentation based on structural and orientation properties of the pelvis in X-ray images. The solution consists of three stages including pre-processing image to extract pelvis area, initial pelvis mask preparation and final pelvis segmentation. Experimental results on a set of 100 X-ray images showed consistent performance of the algorithm. The automated solution overcomes the weaknesses of a manual annotation procedure where intra- and inter-observer variations cannot be avoided.

High-throughput screening of high Monascus pigment-producing strain based on digital image processing.

PubMed

Xia, Meng-lei; Wang, Lan; Yang, Zhi-xia; Chen, Hong-zhang

2016-04-01

This work proposed a new method which applied image processing and support vector machine (SVM) for screening of mold strains. Taking Monascus as example, morphological characteristics of Monascus colony were quantified by image processing. And the association between the characteristics and pigment production capability was determined by SVM. On this basis, a highly automated screening strategy was achieved. The accuracy of the proposed strategy is 80.6 %, which is compatible with the existing methods (81.1 % for microplate and 85.4 % for flask). Meanwhile, the screening of 500 colonies only takes 20-30 min, which is the highest rate among all published results. By applying this automated method, 13 strains with high-predicted production were obtained and the best one produced as 2.8-fold (226 U/mL) of pigment and 1.9-fold (51 mg/L) of lovastatin compared with the parent strain. The current study provides us with an effective and promising method for strain improvement.

A Low-Power High-Speed Smart Sensor Design for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi

1997-01-01

A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.

Nonlinear Optical Characterization of Membrane Protein Microcrystals and Nanocrystals.

PubMed

Newman, Justin A; Simpson, Garth J

2016-01-01

Nonlinear optical methods such as second harmonic generation (SHG) and two-photon excited UV fluorescence (TPE-UVF) imaging are promising approaches to address bottlenecks in the membrane protein structure determination pipeline. The general principles of SHG and TPE-UVF are discussed here along with instrument design considerations. Comparisons to conventional methods in high throughput crystallization condition screening and crystal quality assessment prior to X-ray diffraction are also discussed.

A Functional High-Throughput Assay of Myelination in Vitro

DTIC Science & Technology

2014-07-01

iPS cells derived from human astrocytes. These cell lines will serve as an excellent source of human cells from which our model systems may be...image the 3D rat dorsal root ganglion ( DRG ) cultures with sufficiently low background as to detect electrically-evoked depolarization events, as...stimulation and recording system specifically for this purpose. Further, we found that the limitations inherent in optimizing speed and FOV may

High-throughput optofluidic profiling of Euglena gracilis with morphological and chemical specificity

NASA Astrophysics Data System (ADS)

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Jiang, Yiyue; Ozeki, Yasuyuki; Goda, Keisuke

2016-11-01

The world is faced with environmental problems and the energy crisis due to the combustion and depletion of fossil fuels. The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate a high-throughput optofluidic Euglena gracilis profiler which consists of an optical time-stretch microscope and a fluorescence analyzer on top of an inertial-focusing microfluidic device that can detect fluorescence from lipid droplets in their cell body and provide images of E. gracilis cells simultaneously at a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method provides a promise for evaluating the efficiency of lipid-inducing techniques for biofuel production, which is also applicable for identifying biomedical samples such as blood cells and cancer cells.

Deep Learning in Label-free Cell Classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

From astronomy and telecommunications to biomedicine

NASA Astrophysics Data System (ADS)

Behr, Bradford B.; Baker, Scott A.; Bismilla, Yusuf; Cenko, Andrew T.; DesRoches, Brandon; Hajian, Arsen R.; Meade, Jeffrey T.; Nitkowski, Arthur; Preston, Kyle J.; Schmidt, Bradley S.; Sherwood-Droz, Nicolás.; Slaa, Jared

2015-03-01

Photonics is an inherently interdisciplinary endeavor, as technologies and techniques invented or developed in one scientific field are often found to be applicable to other fields or disciplines. We present two case studies in which optical spectroscopy technologies originating from stellar astrophysics and optical telecommunications multiplexing have been successfully adapted for biomedical applications. The first case involves a design concept called the High Throughput Virtual Slit, or HTVS, which provides high spectral resolution without the throughput inefficiency typically associated with a narrow spectrometer slit. HTVS-enhanced spectrometers have been found to significantly improve the sensitivity and speed of fiber-fed Raman analysis systems, and the method is now being adapted for hyperspectral imaging for medical and biological sensing. The second example of technology transfer into biomedicine centers on integrated optics, in which optical waveguides are fabricated on to silicon substrates in a substantially similar fashion as integrated circuits in computer chips. We describe an architecture referred to as OCTANE which implements a small and robust "spectrometer-on-a-chip" which is optimized for optical coherence tomography (OCT). OCTANE-based OCT systems deliver three-dimensional imaging resolution at the micron scale with greater stability and lower cost than equivalent conventional OCT approaches. Both HTVS and OCTANE enable higher precision and improved reliability under environmental conditions that are typically found in a clinical or laboratory setting.

Deep Learning in Label-free Cell Classification

DOE PAGES

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; ...

2016-03-15

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

A scalable diffraction-based scanning 3D colour video display as demonstrated by using tiled gratings and a vertical diffuser.

PubMed

Jia, Jia; Chen, Jhensi; Yao, Jun; Chu, Daping

2017-03-17

A high quality 3D display requires a high amount of optical information throughput, which needs an appropriate mechanism to distribute information in space uniformly and efficiently. This study proposes a front-viewing system which is capable of managing the required amount of information efficiently from a high bandwidth source and projecting 3D images with a decent size and a large viewing angle at video rate in full colour. It employs variable gratings to support a high bandwidth distribution. This concept is scalable and the system can be made compact in size. A horizontal parallax only (HPO) proof-of-concept system is demonstrated by projecting holographic images from a digital micro mirror device (DMD) through rotational tiled gratings before they are realised on a vertical diffuser for front-viewing.