scholarly journals A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant

Biology ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 272
Author(s):  
Edgar García-Fortea ◽  
Ana García-Pérez ◽  
Esther Gimeno-Páez ◽  
Alfredo Sánchez-Gimeno ◽  
Santiago Vilanova ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Throughput ◽  
Pollen Development ◽  
High Rate ◽  
Genotyping Platform ◽  
Enrichment Technology ◽  
Pure Lines ◽  
Single Primer

The development of double haploids (DHs) is a straightforward path for obtaining pure lines but has multiple bottlenecks. Among them is the determination of the optimal stage of pollen induction for androgenesis. In this work, we developed Microscan, a deep learning-based system for the detection and recognition of the stages of pollen development. In a first experiment, the algorithm was developed adapting the RetinaNet predictive model using microspores of different eggplant accessions as samples. A mean average precision of 86.30% was obtained. In a second experiment, the anther range to be cultivated in vitro was determined in three eggplant genotypes by applying the Microscan system. Subsequently, they were cultivated following two different androgenesis protocols (Cb and E6). The response was only observed in the anther size range predicted by Microscan, obtaining the best results with the E6 protocol. The plants obtained were characterized by flow cytometry and with the Single Primer Enrichment Technology high-throughput genotyping platform, obtaining a high rate of confirmed haploid and double haploid plants. Microscan has been revealed as a tool for the high-throughput efficient analysis of microspore samples, as it has been exemplified in eggplant by providing an increase in the yield of DHs production.

scholarly journals Single Primer Enrichment Technology (SPET) for High-Throughput Genotyping in Tomato and Eggplant Germplasm

2019 ◽  
Vol 10 ◽  
Author(s):  
Lorenzo Barchi ◽  
Alberto Acquadro ◽  
David Alonso ◽  
Giuseppe Aprea ◽  
Laura Bassolino ◽  
...  
Keyword(s):  
High Throughput ◽  
Enrichment Technology ◽  
Single Primer

scholarly journals High-throughput determination of the antigen specificities of T cell receptors in single cells

2018 ◽  
Author(s):  
Shu-Qi Zhang ◽  
Ke-Yue Ma ◽  
Alexandra A. Schonnesen ◽  
Mingliang Zhang ◽  
Chenfeng He ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
High Throughput ◽  
Single Cells ◽  
Cell Receptor ◽  
Cross Reactivity ◽  
Wild Type ◽  
Type Antigen

We present tetramer-associated T-cell receptor sequencing (TetTCR-Seq), a method to link T cell receptor (TCR) sequences to their cognate antigens in single cells at high throughput. Binding is determined using a library of DNA-barcoded antigen tetramers that is rapidly generated by in vitro transcription and translation. We applied TetTCR-Seq to identify patterns in TCR cross-reactivity with cancer neo-antigens and to rapidly isolate neo-antigen-specific TCRs with no cross-reactivity to the wild-type antigen.

A Fluorescence-Based High-Throughput Assay for the Identification of Anticancer Reagents Targeting Fructose-1,6-Bisphosphate Aldolase

2017 ◽  
Vol 23 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Eun Jeong Cho ◽  
Ashwini K. Devkota ◽  
Gabriel Stancu ◽  
Ramakrishna Edupunganti ◽  
Garth Powis ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Enzymatic Reaction ◽  
Current Method ◽  
High Rate ◽  
Assay Optimization ◽  
Wide Range ◽  
Probe Assay ◽  
Fructose 1,6 Bisphosphate

A high rate of glycolysis, which supplies energy and materials for anabolism, is observed in a wide range of tumor cells, making it a potential pathway to control cancer growth. ALDOA is a multifunctional enzyme in the glycolytic pathway and also promotes HIF-1α, which is of importance in hypoxic solid tumors. The current method for assaying ALDOA activity involves monitoring the consumption of NADH in vitro using absorbance or intrinsic fluorescence via a coupled enzymatic reaction. Here, we report the development of a homogeneous biochemical assay that can overcome limitations of current methods, in particular for the application of high-throughput drug screening. The assay utilizes the commercially available Elite NADH Assay Kit, which incorporates an enzymatic reaction to measure the level of NADH using a fluorescent probe. Assay optimization and validation are discussed. Its feasibility for high-throughput screening (HTS) was demonstrated by screening 65,000 compounds for the identification of small molecules that inhibit ALDOA. Through a validation screen and dose–response evaluation, four inhibitors with IC50 below 10 µM were identified. In conclusion, we demonstrate that a traditional ALDOA assay can be transformed readily into a fluorescence-based assay utilizing a commercial NADH detection kit that is rapid, sensitive, inexpensive, and HTS friendly.

scholarly journals A High-Throughput Method for Enzyme Kinetic Studies

2003 ◽  
Vol 8 (5) ◽  
pp. 544-554 ◽  
Author(s):  
Lakshmi D. Saraswat ◽  
Kimberley A. Caserta ◽  
Kathy Laws ◽  
Darren Wei ◽  
Simon S. Jones ◽  
...  
Keyword(s):  
Drug Metabolism ◽  
High Throughput ◽  
Kinetic Studies ◽  
Metabolic Stability ◽  
Metabolic Parameter ◽  
High Throughput Method ◽  
Multiple Samples ◽  
Parameter Values

A simple and flexible setup for conducting drug metabolism studies is described in this report. A heating block was designed for the Multimek liquid handler platform for incubation of multiple samples at 37 °C in a 96-well format. This setup enables the rapid performance of drug metabolism experiments on a large number of samples. In this report, the authors present the validation of the system by 1) showing reproducible and consistent determination of the in vitro half-life of midazolam in every well across the entire plate and 2) determination of metabolic parameter values of midazolam, testosterone, diclofenac, warfarin, and dextromethorphan and inhibition parameter values of quinidine and ketoconazole, all comparable to literature values. In addition, the authors demonstrate the application of the setup to determining the metabolic stability of a set of proprietary compounds, the inhibition of activity of cytochrome P450 (CYP) enzymes, and the conduct of a single combination experiment that can simultaneously determine the metabolic stability and CYP inhibition activity. Overall, the system represents a simple, high-throughput and useful tool for drug metabolism screening in drug discovery. ( Journal of Biomolecular Screening 2003:544-554)

scholarly journals Determination of the Time Course and Extent of Neurotoxicity at Defined Temperatures in Cultured Neurons Using a Modified Multiwell Plate Fluorescence Scanner

1997 ◽  
Vol 17 (4) ◽  
pp. 455-463 ◽  
Author(s):  
Rita Sattler ◽  
Milton P. Charlton ◽  
Mathias Hafner ◽  
Michael Tymianski
Keyword(s):  
High Throughput ◽  
Cortical Neurons ◽  
Time Course ◽  
Molecular Mechanisms ◽  
Neuronal Cultures ◽  
Lactate Dehydrogenase Release ◽  
Cultured Cortical Neurons ◽  
And Control

The cellular and molecular mechanisms of hypoxic/ischemic neurodegeneration are sensitive to numerous factors that modulate the time course and degree of neuronal death. Among such factors is hypothermia, which can dramatically protect neurons from injury. To examine and control for temperature-dependent effects, we developed a technique that provides for a high-throughput, accurate, and reproducible determination of the time course and degree of neurotoxicity in cultured cortical neurons at precisely defined temperatures. We used a fluorescence multiwell plate scanner, modified by us to permit the control of temperature, to perform serial quantitative measurements of propidium iodide (PI) fluorescence in cortical neuronal cultures exposed to excitotoxic insults. In validating this approach, we show that these time course measurements correlate highly with manual counts of PI-stained cells in the same cultures ( r = 0.958, p < 0.0001) and with lactate dehydrogenase release ( r = 0.964, p < 0.0001). This method represents an efficient approach to mechanistic and quantitative studies of cell death as well as a high-throughput technique for screening new neuroprotective therapies in vitro.

scholarly journals Performance of a deep learning based neural network in the selection of human blastocysts for implantation

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Charles L Bormann ◽  
Manoj Kumar Kanakasabapathy ◽  
Prudhvi Thirumalaraju ◽  
Raghav Gupta ◽  
Rohan Pooniwala ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Time Lapse ◽  
Vitro Fertilization ◽  
Clinical Patient ◽  
Static Images ◽  
Transfer Order ◽  
Selection Of

Deep learning in in vitro fertilization is currently being evaluated in the development of assistive tools for the determination of transfer order and implantation potential using time-lapse data collected through expensive imaging hardware. Assistive tools and algorithms that can work with static images, however, can help in improving the access to care by enabling their use with images acquired from traditional microscopes that are available to virtually all fertility centers. Here, we evaluated the use of a deep convolutional neural network (CNN), trained using single timepoint images of embryos collected at 113 hr post-insemination, in embryo selection amongst 97 clinical patient cohorts (742 embryos) and observed an accuracy of 90% in choosing the highest quality embryo available. Furthermore, a CNN trained to assess an embryo’s implantation potential directly using a set of 97 euploid embryos capable of implantation outperformed 15 trained embryologists (75.26% vs. 67.35%, p<0.0001) from five different fertility centers.

Lymph capillary pressure of rat intestinal villi during fluid absorption.

1979 ◽  
Vol 237 (3) ◽  
pp. E301 ◽  
Author(s):  
J S Lee
Keyword(s):  
Capillary Pressure ◽  
Fluid Pressure ◽  
High Rate ◽  
Tissue Fluid ◽  
Fluid Absorption ◽  
Tissue Space ◽  
Intestinal Preparation

A newly developed intestinal preparation is described for determining lymph capillary pressure (PL) in the villi in vivo and in vitro. Determination of PL provided an estimate of tissue fluid pressure in the villi. PL was related to the fluid absorption rate and increased by lymphatic obstruction. During fluid absorption from isotonic mucosal fluid, PL was 1.4 +/- 0.5 or 1.1 +/- 0.4 cmH2O determined in vivo or in vitro, respectively. Both pressures were essentially in the same range as that (0.7 +/- 0.3--1.3 +/- 0.5 cmH2O) in which the mucosal fluid was isotonic Na2SO4 solution or Na-free solutions from which little fluid absorption occurred. This range of pressures may be taken as the normal tissue fluid pressure in the villi. At a high rate of fluid absorption from hypotonic mucosal fluid, PL increased to 5.2 +/- 1.4 cmH2O and tissue fluid pressure was also similarly increased. It is concluded that the fluid absorptive process by the epithelium could not develop an appreciable hydrostatic pressure in the villus tissue space or in the lymphatics.

scholarly journals Development of a High-Throughput Biochemical Assay to Screen for Inhibitors of Aerobactin Synthetase IucA

2018 ◽  
Vol 23 (10) ◽  
pp. 1070-1082 ◽  
Author(s):  
Daniel C. Bailey ◽  
Brian P. Buckley ◽  
Mikhail V. Chernov ◽  
Andrew M. Gulick
Keyword(s):  
High Throughput ◽  
Pathogenic Bacteria ◽  
Enzyme Concentration ◽  
High Rate ◽  
Biochemical Assay ◽  
In Vivo Studies ◽  
Nutritional Immunity ◽  
Small Molecule Libraries

Acquiring sufficient quantities of iron to support survival is often a critical limitation for pathogenic bacteria. To meet this demand, bacteria have evolved unique strategies to scavenge iron and circumvent the nutritional immunity exerted by their hosts. One common strategy, which is often a key virulence factor for bacterial pathogens, involves the synthesis, secretion, and reuptake of iron chelators known as siderophores. In vitro and in vivo studies have demonstrated that the siderophore aerobactin is critical for virulence in the hypervirulent pathotype of Klebsiella pneumoniae (hvKP). Given the high rate of multidrug resistance in K. pneumoniae, and in light of the ever-increasing demand for novel Gram-negative therapeutic targets, we identified aerobactin production as a promising antivirulence target in hvKP. Herein, we describe the development of a high-throughput biochemical assay for identifying inhibitors of the aerobactin synthetase IucA. The assay was employed to screen ~110,000 compounds across several commercially available small-molecule libraries. IucA inhibitors with activity at micromolar concentrations were identified in our screening campaigns and confirmed using secondary orthogonal assays. However, the most potent compounds also exhibited some properties commonly observed with promiscuous/nonspecific inhibitors, including incubation time and target enzyme concentration dependence, as well as the potential to antagonize unrelated enzymes.

scholarly journals Deep Learning for High-Throughput Quantification of Oligodendrocyte Ensheathment at Single-Cell Resolution

2018 ◽  
Author(s):  
Yu Kang T Xu ◽  
Daryan Chitsaz ◽  
Robert A Brown ◽  
Qiao Ling Cui ◽  
Matthew A Dabarno ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
High Throughput ◽  
Heuristic Approach ◽  
The Neural Network ◽  
Automated Imaging ◽  
Parametric Analyses ◽  
Deep Learning Neural Network ◽  
High Level

AbstractHigh-throughput quantification of oligodendrocyte (OL) myelination is a significant challenge that, if addressed, would facilitate the development of therapeutics to promote myelin protection and repair. Here, we established a quantitative high-throughput method to asses OL ensheathment in-vitro, combining nanofiber culture devices and automated imaging with a heuristic approach that informed the development of a deep learning analytic algorithm. The heuristic approach was developed by modeling general characteristics of OL ensheathments, while the deep learning neural network employed a UNet architecture with enhanced capacity to associate ensheathed segments with individual OLs. Reliably extracting multiple morphological parameters from individual cells, without heuristic approximations, mimics the high-level decision-making capacity of human researchers and improves the validity of the neural network. Experimental validation demonstrated that the deep learning approach matched the accuracy of expert-human measurements of the length and number of myelin segments per cell. The combined use of automated imaging and analysis reduces tedious manual labor while eliminating variability. The capacity of this technology to perform multi-parametric analyses at the level of individual cells permits the detection of nuanced cellular differences to accelerate the discovery of new insight into OL physiology.

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