scholarly journals Extended live-cell barcoding approach for multiplexed mass cytometry

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Muharrem Muftuoglu ◽  
Li Li ◽  
Shaoheng Liang ◽  
Duncan Mak ◽  
Angelique J. Lin ◽  
...  
Keyword(s):  
Live Cell ◽  
Weak Signal ◽  
Mass Cytometry ◽  
Signal To Noise ◽  
Sample Processing ◽  
Experimental Conditions ◽  
Sample Pooling ◽  
Surface Staining ◽  
Signal Intensities ◽  
Antigenic Epitopes

AbstractSample barcoding is essential in mass cytometry analysis, since it can eliminate potential procedural variations, enhance throughput, and allow simultaneous sample processing and acquisition. Sample pooling after prior surface staining termed live-cell barcoding is more desirable than intracellular barcoding, where samples are pooled after fixation and permeabilization, since it does not depend on fixation-sensitive antigenic epitopes. In live-cell barcoding, the general approach uses two tags per sample out of a pool of antibodies paired with five palladium (Pd) isotopes in order to preserve appreciable signal-to-noise ratios and achieve higher yields after sample deconvolution. The number of samples that can be pooled in an experiment using live-cell barcoding is limited, due to weak signal intensities associated with Pd isotopes and the relatively low number of available tags. Here, we describe a novel barcoding technique utilizing 10 different tags, seven cadmium (Cd) tags and three Pd tags, with superior signal intensities that do not impinge on lanthanide detection, which enables enhanced pooling of samples with multiple experimental conditions and markedly enhances sample throughput.

scholarly journals Customizable live-cell imaging chambers for multimodal and multiplex fluorescence microscopy

2020 ◽  
Vol 98 (5) ◽  
pp. 612-623
Author(s):  
Adam Tepperman ◽  
David Jiao Zheng ◽  
Maria Abou Taka ◽  
Angela Vrieze ◽  
Austin Le Lam ◽  
...  
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Super Resolution ◽  
Live Cell ◽  
Imaging Modalities ◽  
Experimental Conditions ◽  
Microscopy Imaging ◽  
Glass Coverslip ◽  
Multiple Imaging ◽  
Microscopy Techniques

Using multiple imaging modalities while performing independent experiments in parallel can greatly enhance the throughput of microscopy-based research, but requires the provision of appropriate experimental conditions in a format that meets the optical requirements of the microscope. Although customized imaging chambers can meet these challenges, the difficulty of manufacturing custom chambers and the relatively high cost and design inflexibility of commercial chambers has limited the adoption of this approach. Herein, we demonstrate the use of 3D printing to produce inexpensive, customized, live-cell imaging chambers that are compatible with a range of imaging modalities, including super-resolution microscopy. In this approach, biocompatible plastics are used to print imaging chambers designed to meet the specific needs of an experiment, followed by adhesion of the printed chamber to a glass coverslip, producing a chamber that is impermeant to liquids and that supports the growth and imaging of cells over multiple days. This approach can also be used to produce moulds for casting microfluidic devices made of polydimethylsiloxane. The utility of these chambers is demonstrated using designs for multiplex microscopy, imaging under shear, chemotaxis, and general cellular imaging. Together, this approach represents an inexpensive yet highly customizable approach for producing imaging chambers that are compatible with modern microscopy techniques.

Development of Acrylamide-Based Rapid and Multicolor Fluorogenic Probes for High Signal-to-Noise Live Cell Imaging

2018 ◽  
Vol 30 (1) ◽  
pp. 184-191 ◽  
Author(s):  
Dasheng Zhang ◽  
Renmei Liu ◽  
Chunyan Bao ◽  
Chenxia Zhang ◽  
Lipeng Yang ◽  
...  
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
High Signal ◽  
Signal To Noise ◽  
Fluorogenic Probes

scholarly journals Comparative Performance of Catalytic Fenton Oxidation with Zero-Valent Iron (Fe(0)) in Comparison with Ferrous Sulphate for the Removal of Micropollutants

2019 ◽  
Vol 9 (11) ◽  
pp. 2181
Author(s):  
Anuradha Goswami ◽  
Jia-Qian Jiang
Keyword(s):  
Standard Deviation ◽  
Signal To Noise Ratio ◽  
Ferrous Sulphate ◽  
Fenton Oxidation ◽  
Zero Valent Iron ◽  
Fenton Process ◽  
Signal To Noise ◽  
Experimental Conditions ◽  
Comparative Performance ◽  
Sludge Production

This research aims to depict the comparative performance of micropollutants’ removal by FeSO4- and zero-valent iron (Fe(0))-catalytic Fenton oxidation and to explore the possibilities of minimising the sludge production from the process. The emerging micropollutants used for the study were gabapentin, sulfamethoxazole, diuron, terbutryn and terbuthylazine. The Taguchi method, which evaluates the signal-to-noise ratio instead of the standard deviation, was used to develop robust experimental conditions. Though both FeSO4- and Fe(0)-catalytic Fenton oxidation were able to completely degrade the stated micropollutants, the Fe(0)-catalytic Fenton process delivered better removal of dissolved organic carbon (DOC; 70%) than FeSO4 catalytic Fenton oxidation (45%). Fe(0)-catalytic Fenton oxidation facilitated heterogeneous treatment functions, which eliminated toxicity from contaminated solution and there was no recognisable sludge production.

scholarly journals Intelligent Data Analysis to Model and Understand Live Cell Time-lapse Sequences

2012 ◽  
Vol 51 (04) ◽  
pp. 332-340 ◽  
Author(s):  
A. Paterson ◽  
M. Ashtari ◽  
D. Ribé ◽  
G. Stenbeck ◽  
A. Tucker
Keyword(s):  
Data Analysis ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Time Lapse ◽  
Living Cells ◽  
Live Cell ◽  
Intelligent Data Analysis ◽  
Stable States ◽  
Experimental Conditions

SummaryBackground: One important aspect of cellular function, which is at the basis of tissue homeostasis, is the delivery of proteins to their correct destinations. Significant advances in live cell microscopy have allowed tracking of these pathways by following the dynamics of fluorescently labelled proteins in living cells.Objectives: This paper explores intelligent data analysis techniques to model the dynamic behavior of proteins in living cells as well as to classify different experimental conditions.Methods: We use a combination of decision tree classification and hidden Markov models. In particular, we introduce a novel approach to “align” hidden Markov models so that hidden states from different models can be cross-compared.Results: Our models capture the dynamics of two experimental conditions accurately with a stable hidden state for control data and multiple (less stable) states for the experimental data recapitulating the behaviour of particle trajectories within live cell time-lapse data.Conclusions: In addition to having successfully developed an automated framework for the classification of protein transport dynamics from live cell time-lapse data our model allows us to understand the dynamics of a complex trafficking pathway in living cells in culture.

The Design and Simulation of Cycled Amplifying Circuit

2013 ◽  
Vol 462-463 ◽  
pp. 632-635
Author(s):  
Na An ◽  
Cheng Long Gong ◽  
Weng Ming Su
Keyword(s):  
Adaptive Control ◽  
Error Compensation ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Detection Error ◽  
Signal To Noise ◽  
Analog Switch ◽  
Data Acquisition And Processing ◽  
Double Channel ◽  
Device Noise

There are many traditional methods to detect the weak signal(such as, locking -receive, synchronous cumulative and double channel de-noising) When the signal is very weak which easily submerged by the device noise,the error that measured by the above methods is too big. This paper mainly introduces the principle of a adaptive control faint signal cycle amplifier and through the method of error compensation to amplify signal cycled , which improve the signal-to-noise ratio and reduce the detection error. The structure of this system is simple and it cost low. besides,it convenient for use and debug. The circuit can also be applied to data acquisition and processing of weak signal and its significance is very widely .This paper designs a simulation circuit and analyzes sample-hold and analog switch.

Sample Presentation Considerations in Laser-Induced Breakdown Spectroscopy in Aqueous Solution

2007 ◽  
Vol 61 (9) ◽  
pp. 1021-1024 ◽  
Author(s):  
Xiao Fang ◽  
S. Rafi Ahmad
Keyword(s):  
Elemental Analysis ◽  
Aqueous Media ◽  
Water Jet ◽  
Laser Induced Breakdown Spectroscopy ◽  
Signal To Noise ◽  
Experimental Conditions ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Sample Presentation ◽  
Presentation Methods

Various sample presentation configurations for elemental analysis in aqueous media by laser-induced breakdown spectroscopy (LIBS) have been tested and analyzed. Direct and quantitative comparison between the two different sample presentation methods, plasma excitation within water bulk and on the surface in a water jet, has been carried out using the same LIBS system under the same experimental conditions. Temporal characteristics of light emitted from the plasma induced in both the water bulk and the jet surface containing calcium (Ca) were recorded and presented. Spectral data recorded under optimum detection gating conditions showed that the signal-to-noise ratio (S/N) for excitation in the water jet configuration is approximately 10 times higher than that in the bulk excitation, the actual values of enhancement being dependent on the element type. The typical spectra of aqueous samples containing sodium (Na), calcium (Ca), zinc (Zn), cadmium (Cd), and mercury (Hg) were detected and the signal-to-noise ratios were evaluated and compared for the sample presentation configurations under considerations. The results suggest that for better sensitivity of detection, a simple water jet sample presentation configuration could be designed and implemented for cost-effective commercial use of this technique for elemental analysis in a water environment.

scholarly journals On the application of frequency tagging

2020 ◽  
Author(s):  
Zoltan Derzsi
Keyword(s):  
Phase Noise ◽  
Detection Probability ◽  
Signal To Noise Ratio ◽  
Lower Probability ◽  
Weak Signal ◽  
Signal To Noise ◽  
Noise Component ◽  
Spectral Evaluation ◽  
Human Electrophysiology ◽  
Additional Phase

To detect a weak signal in human electrophysiology that is a response of a periodic external stimulus, spectral evaluation is mostly used. The recorded signal’s amplitude and phase noise components of the signal are statistically independent from each other, but both of them are decreasing the signal-to-noise ratio, which results in a lower probability of successful signal detection. Provided that the phase information of the stimuli is preserved, we found that a way to reject an additional phase noise component, which improves the detection probability considerably, by analysing the signal’s phase coherency instead of its spectrum.

scholarly journals Comparing current noise in biological and solid-state nanopores

2019 ◽  
Author(s):  
A. Fragasso ◽  
S. Schmid ◽  
C. Dekker
Keyword(s):  
Solid State ◽  
Single Molecule ◽  
Signal To Noise Ratio ◽  
Low Cost ◽  
Ionic Current ◽  
Low Noise ◽  
Signal To Noise ◽  
Experimental Conditions ◽  
High Frequencies ◽  
Noise Ratio

AbstractNanopores bear great potential as single-molecule tools for bioanalytical sensing and sequencing, due to their exceptional sensing capabilities, high-throughput, and low cost. The detection principle relies on detecting small differences in the ionic current as biomolecules traverse the nanopore. A major bottleneck for the further progress of this technology is the noise that is present in the ionic current recordings, because it limits the signal-to-noise ratio and thereby the effective time resolution of the experiment. Here, we review the main types of noise at low and high frequencies and discuss the underlying physics. Moreover, we compare biological and solid-state nanopores in terms of the signal-to-noise ratio (SNR), the important figure of merit, by measuring free translocations of a short ssDNA through a selected set of nanopores under typical experimental conditions. We find that SiNx solid-state nanopores provide the highest SNR, due to the large currents at which they can be operated and the relatively low noise at high frequencies. However, the real game-changer for many applications is a controlled slowdown of the translocation speed, which for MspA was shown to increase the SNR >160-fold. Finally, we discuss practical approaches for lowering the noise for optimal experimental performance and further development of the nanopore technology.

scholarly journals A Bayesian method for reducing bias in neural representational similarity analysis

2016 ◽  
Author(s):  
Ming Bo Cai ◽  
Nicolas W. Schuck ◽  
Jonathan Pillow ◽  
Yael Niv
Keyword(s):  
Neural Activity ◽  
Cognitive Task ◽  
Activity Patterns ◽  
Covariance Structure ◽  
Similarity Matrix ◽  
Imaging Data ◽  
Signal To Noise ◽  
Experimental Conditions ◽  
Sensory Stimuli ◽  
Neural Imaging

Abstract1In neuroscience, the similarity matrix of neural activity patterns in response to different sensory stimuli or under different cognitive states reflects the structure of neural representational space. Existing methods derive point estimations of neural activity patterns from noisy neural imaging data, and the similarity is calculated from these point estimations. We show that this approach translates structured noise from estimated patterns into spurious bias structure in the resulting similarity matrix, which is especially severe when signal-to-noise ratio is low and experimental conditions cannot be fully randomized in a cognitive task. We propose an alternative Bayesian framework for computing representational similarity in which we treat the covariance structure of neural activity patterns as a hyper-parameter in a generative model of the neural data, and directly estimate this covariance structure from imaging data while marginalizing over the unknown activity patterns. Converting the estimated covariance structure into a correlation matrix offers an unbiased estimate of neural representational similarity. Our method can also simultaneously estimate a signal-to-noise map that informs where the learned representational structure is supported more strongly, and the learned covariance matrix can be used as a structured prior to constrain Bayesian estimation of neural activity patterns.

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