scholarly journals Automatic detection of adult cardiomyocyte for high throughput measurements of calcium and contractility

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256713
Author(s):  
L. Cao ◽  
E. Manders ◽  
M. Helmes
Keyword(s):  
High Throughput ◽  
Gold Standard ◽  
Automatic Detection ◽  
Field Of View ◽  
Cell Boundary ◽  
Edge Information ◽  
Statistical Reliability ◽  
Adult Cardiomyocytes

Simultaneous calcium and contractility measurements on isolated adult cardiomyocytes have been the gold standard for the last decades to study cardiac (patho)physiology. However, the throughput of this system is low which limits the number of compounds that can be tested per animal. We developed instrumentation and software that can automatically find adult cardiomyocytes. Cells are detected based on the cell boundary using a Sobel-filter to find the edge information in the field of view. Separately, we detected motion by calculating the variance of intensity for each pixel in the frame through time. Additionally, it detects the best region for calcium and contractility measurements. A sensitivity of 0.66 ± 0.08 and a precision of 0.82 ± 0.03 was reached using our cell finding algorithm. The percentage of cells that were found and had good contractility measurements was 90 ± 10%. In addition, the average time between 2 cardiomyocyte calcium and contractility measurements decreased from 93.5 ± 80.2 to 15.6 ± 8.0 seconds using our software and microscope. This drastically increases throughput and provides a higher statistical reliability when performing adult cardiomyocyte functional experiments.

High-throughput and uniform large field-of-view multichannel fluorescence microscopy with super-thin dichroism for a dPCR gene chip

2020 ◽  
Vol 59 (34) ◽  
pp. 10768
Author(s):  
Francis Yaw Otuboah ◽  
Jihong Zheng ◽  
Cheng Chen ◽  
Zicheng Wang ◽  
Xinjun Wan ◽  
...  
Keyword(s):  
Fluorescence Microscopy ◽  
High Throughput ◽  
Gene Chip ◽  
Field Of View ◽  
Large Field

scholarly journals Surrogate-assisted feature extraction for high-throughput phenotyping

2016 ◽  
Vol 24 (e1) ◽  
pp. e143-e149 ◽  
Author(s):  
Sheng Yu ◽  
Abhishek Chakrabortty ◽  
Katherine P Liao ◽  
Tianrun Cai ◽  
Ashwin N Ananthakrishnan ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Language Processing ◽  
High Throughput ◽  
Gold Standard ◽  
Characteristic Curve ◽  
Feature Selection Method ◽  
International Classification Of Diseases ◽  
Silver Standard ◽  
Automated Feature Extraction ◽  
High Throughput Phenotyping

Objective: Phenotyping algorithms are capable of accurately identifying patients with specific phenotypes from within electronic medical records systems. However, developing phenotyping algorithms in a scalable way remains a challenge due to the extensive human resources required. This paper introduces a high-throughput unsupervised feature selection method, which improves the robustness and scalability of electronic medical record phenotyping without compromising its accuracy. Methods: The proposed Surrogate-Assisted Feature Extraction (SAFE) method selects candidate features from a pool of comprehensive medical concepts found in publicly available knowledge sources. The target phenotype’s International Classification of Diseases, Ninth Revision and natural language processing counts, acting as noisy surrogates to the gold-standard labels, are used to create silver-standard labels. Candidate features highly predictive of the silver-standard labels are selected as the final features. Results: Algorithms were trained to identify patients with coronary artery disease, rheumatoid arthritis, Crohn’s disease, and ulcerative colitis using various numbers of labels to compare the performance of features selected by SAFE, a previously published automated feature extraction for phenotyping procedure, and domain experts. The out-of-sample area under the receiver operating characteristic curve and F-score from SAFE algorithms were remarkably higher than those from the other two, especially at small label sizes. Conclusion: SAFE advances high-throughput phenotyping methods by automatically selecting a succinct set of informative features for algorithm training, which in turn reduces overfitting and the needed number of gold-standard labels. SAFE also potentially identifies important features missed by automated feature extraction for phenotyping or experts.

scholarly journals Computational Prediction of Bacteriophage Host Ranges

2022 ◽  
Vol 10 (1) ◽  
pp. 149
Author(s):  
Cyril J. Versoza ◽  
Susanne P. Pfeifer
Keyword(s):  
Antibiotic Resistance ◽  
Host Range ◽  
High Throughput ◽  
Gold Standard ◽  
Computational Prediction ◽  
Bioinformatic Tools ◽  
Key Factor

Increased antibiotic resistance has prompted the development of bacteriophage agents for a multitude of applications in agriculture, biotechnology, and medicine. A key factor in the choice of agents for these applications is the host range of a bacteriophage, i.e., the bacterial genera, species, and strains a bacteriophage is able to infect. Although experimental explorations of host ranges remain the gold standard, such investigations are inherently limited to a small number of viruses and bacteria amendable to cultivation. Here, we review recently developed bioinformatic tools that offer a promising and high-throughput alternative by computationally predicting the putative host ranges of bacteriophages, including those challenging to grow in laboratory environments.

scholarly journals Is PXRD the gold standard in high throughput experiments?

2007 ◽  
Vol 63 (a1) ◽  
pp. s53-s53
Author(s):  
C. Gilmore ◽  
G. Barr ◽  
G. Cunningham ◽  
C. Frampton
Keyword(s):  
High Throughput ◽  
Gold Standard ◽  
High Throughput Experiments

scholarly journals Apoptosis assessment in high-content and high-throughput screening assays

BioTechniques ◽  
2021 ◽  
Vol 70 (6) ◽  
pp. 309-318
Author(s):  
Céline Rens ◽  
Tirosh Shapira ◽  
Sandra Peña-Diaz ◽  
Joseph D Chao ◽  
Tom Pfeifer ◽  
...  
Keyword(s):  
High Throughput ◽  
Gold Standard ◽  
High Throughput Screening ◽  
High Content Screening ◽  
Terminal Deoxynucleotidyl Transferase ◽  
Hoechst 33342 ◽  
Monitoring Method ◽  
Multiple Cell ◽  
Screening Assays ◽  
Intracellular Infections

Here the authors describe the development of AUTOptosis, an economical and rapid apoptosis monitoring method suitable for high-content and high-throughput screening assays. AUTOptosis is based on the quantification of nuclei intensity via staining with Hoechst 33342. First, the authors calibrated the method using standard apoptosis inducers in multiple cell lines. Next, the authors validated the applicability of this approach to high-content screening using a small library of compounds and compared it with the terminal deoxynucleotidyl transferase dUTP nick end labeling gold standard. Finally, the authors demonstrated the specificity of the method by using AUTOposis to detect apoptosis triggered by Mycobacterium tuberculosis intracellular infections.

scholarly journals High-throughput characterisation of bull semen motility using differential dynamic microscopy

2018 ◽  
Author(s):  
Alys Jepson ◽  
Jochen Arlt ◽  
Jonathan Statham ◽  
Mark Spilman ◽  
Katie Burton ◽  
...  
Keyword(s):  
High Throughput ◽  
Oscillation Amplitude ◽  
Field Of View ◽  
Large Field ◽  
Laboratory Measurements ◽  
Spermatozoa Motility ◽  
Bull Semen ◽  
The Mean ◽  
On Farm ◽  
Low Cell Density

AbstractWe report a high-throughput technique for characterising the motility of spermatozoa using differential dynamic microscopy. A large field of view movie (~ 10mm2) records thousands of cells (e.g. ≈ 5000 cells even at a low cell density of 20 × 106 cells/ml) at once and yields averaged measurements of the mean (υ) and standard deviation (σ) of the swimming speed, a head oscillation amplitude (A0) and frequency (f0), and the fraction of motile spermatozoa (α). Interestingly, the measurement of α relies on the swimming spermatozoa enhancing the motion of the non-swimming population. We demonstrate the ease and rapidity of our method by performing on-farm characterisation of bull spermatozoa motility, and validate the technique by comparing laboratory measurements with tracking. Our results confirm the long-standing theoretical prediction that for swimming spermatozoa.

scholarly journals HIGH THROUGHPUT SYSTEM FOR PLANT HEIGHT AND HYPERSPECTRAL MEASUREMENT

2018 ◽  
Vol XLII-3 ◽  
pp. 2365-2369
Author(s):  
H. Zhao ◽  
L. Xu ◽  
H. Jiang ◽  
S. Shi ◽  
D. Chen
Keyword(s):  
Physicochemical Properties ◽  
High Throughput ◽  
Stereo Vision ◽  
Three Dimensional ◽  
Working Hours ◽  
Field Of View ◽  
Geometrical Characteristics ◽  
Dimensional Measurement ◽  
Three Dimensional Measurement ◽  
3D Information

Hyperspectral and three-dimensional measurement can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. And narrow field of view (FOV) extends the working hours in farms. Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information.

Lensless On-Chip Fluorescent Imaging Over an Ultra Wide Field-of-View

2010 ◽  
Author(s):  
Ahmet F. Coskun ◽  
Ting-Wei Su ◽  
Aydogan Ozcan
Keyword(s):  
High Throughput ◽  
Imaging Modality ◽  
Scattered Light ◽  
Fluorescent Imaging ◽  
Field Of View ◽  
Fluorescent Detection ◽  
Fluorescent Light ◽  
Wide Field ◽  
Excitation Light ◽  
Wide Field Of View

We introduce a lensless high-throughput fluorescent detection modality that can simultaneously image micro-objects and labeled cells over an ultra-wide field-of-view (FOV) of ∼8cm2 without the use of any lenses, thin-film filters and mechanical scanners. This lensfree platform utilizes total-internal-reflection (TIR) to block the excitation light, and an inexpensive absorption filter to remove the weakly scattered light that does not obey TIR. The emitted fluorescent light from the objects is then detected on the same chip without the use of any lenses. A digital deconvolution algorithm is used to resolve overlapping fluorescent spots, enabling a resolution of ∼40–50 μm over the entire field-of-view. Such an ultra wide field-of-view lensfree fluorescent imaging modality might be very valuable for high-throughput screening applications as well as quantification of rare cells such as circulating tumor cells using ultra-large microfluidic devices.

High-Throughput Cell Imaging, Counting and Characterization on a Chip

2008 ◽  
Author(s):  
Ting-Wei Su ◽  
Sungkyu Seo ◽  
Anthony Erlinger ◽  
Aydogan Ozcan
Keyword(s):  
Health Care Providers ◽  
High Throughput ◽  
Point Of Care ◽  
Cell Types ◽  
Field Of View ◽  
Cell Counting ◽  
Care Providers ◽  
Counting Approach ◽  
On Chip

We introduce a lensfree on chip imaging platform that enables high-throughput monitoring, counting, and identification of several different microscopic objects such as different cell types within a heterogeneous solution. This imaging platform can in principle be miniaturized to a hand-held device that can be used by minimally trained health care providers at the point-of-care to measure the cell count of e.g., red blood cells from whole blood samples with a counting speed of >100,000 cells/sec. This novel optical imaging platform can also be merged with microfluidic systems to be able to rapidly monitor and count hundreds of thousand of cells within a field-of-view (FOV) of ∼10 cm2 in vitro. The immediate impact of this lensfree on chip cell counting approach is its improved speed, significantly larger field-of-view and simplified design that permits considerable miniaturization of the entire cell counting device.

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