scholarly journals Single molecule tracking and analysis framework including theory-predicted parameter settings

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Timo Kuhn ◽  
Johannes Hettich ◽  
Rubina Davtyan ◽  
J. Christof M. Gebhardt
Keyword(s):  
Single Molecule ◽  
Spatial Information ◽  
Reaction Rates ◽  
Data Sets ◽  
Analysis Framework ◽  
Tracking Errors ◽  
Experimental Conditions ◽  
Single Molecule Tracking ◽  
External Software ◽  
User Friendly

AbstractImaging, tracking and analyzing individual biomolecules in living systems is a powerful technology to obtain quantitative kinetic and spatial information such as reaction rates, diffusion coefficients and localization maps. Common tracking tools often operate on single movies and require additional manual steps to analyze whole data sets or to compare different experimental conditions. We report a fast and comprehensive single molecule tracking and analysis framework (TrackIt) to simultaneously process several multi-movie data sets. A user-friendly GUI offers convenient tracking visualization, multiple state-of-the-art analysis procedures, display of results, and data im- and export at different levels to utilize external software tools. We applied our framework to quantify dissociation rates of a transcription factor in the nucleus and found that tracking errors, similar to fluorophore photobleaching, have to be considered for reliable analysis. Accordingly, we developed an algorithm, which accounts for both tracking losses and suggests optimized tracking parameters when evaluating reaction rates. Our versatile and extensible framework facilitates quantitative analysis of single molecule experiments at different experimental conditions.

scholarly journals Single molecule tracking and analysis framework including theory-predicted parameter settings

2020 ◽  
Author(s):  
Timo Kuhn ◽  
Johannes Hettich ◽  
J. Christof M. Gebhardt
Keyword(s):  
Single Molecule ◽  
Spatial Information ◽  
Reaction Rates ◽  
Data Sets ◽  
Analysis Framework ◽  
Tracking Errors ◽  
Experimental Conditions ◽  
Single Molecule Tracking ◽  
External Software ◽  
User Friendly

AbstractImaging, tracking and analyzing individual biomolecules in living systems is a powerful technology to obtain quantitative kinetic and spatial information such as reaction rates, diffusion coefficients and localization maps. Common tracking tools often operate on single movies and require additional manual steps to analyze whole data sets or to compare different experimental conditions. We report a fast and comprehensive single molecule tracking and analysis framework (TrackIt) to simultaneously process several multi-movie data sets. A user-friendly GUI offers convenient tracking visualization, multiple state-of-the-art analysis procedures, display of results, and data im- and export at different levels to utilize external software tools. We applied our framework to quantify dissociation rates of a transcription factor in the nucleus and found that tracking errors, similar to fluorophore photobleaching, have to be considered for reliable analysis. Accordingly, we developed an algorithm, which accounts for both tracking losses and suggests optimized tracking parameters when evaluating reaction rates. Our versatile and extensible framework facilitates quantitative analysis of single molecule experiments at different experimental conditions.

scholarly journals Computational Design of Sensitized Combustion Chemistry Experiments

2021 ◽  
Vol 7 ◽  
Author(s):  
Cody Ising ◽  
Pedro Rodriguez ◽  
Daniel Lopez ◽  
Jeffrey Santner
Keyword(s):  
Shock Tube ◽  
Initial Conditions ◽  
Computational Design ◽  
Reaction Rates ◽  
Oxidation Reactions ◽  
Combustion Chemistry ◽  
Experimental Conditions ◽  
As Species ◽  
User Friendly

In combustion chemistry experiments, reaction rates are often extracted from complex experiments using detailed models. To aid in this process, experiments are performed such that measurable quantities, such as species concentrations, flame speed, and ignition delay, are sensitive to reaction rates of interest. In this work, a systematic method for determining such sensitized experimental conditions is demonstrated. An open-source python script was created using the Cantera module to simulate thousands of 0D and hundreds of 1D combustion chemistry experiments in parallel across a broad, user-defined range of mixture conditions. The results of the simulation are post-processed to normalize and compare sensitivity values among reactions and across initial conditions for time-varying and steady-state simulations, in order to determine the “most useful” experimental conditions. This software can be utilized by researchers as a fast, user-friendly screening tool to determine the thermodynamic and mixture parameters for an experimental campaign. We demonstrate this software through two case studies comparing results of the 0D script against a shock tube experiment and results of the 1D script against a spherical flame experiment. In the shock tube case study we present mixture conditions compared to those used in the literature to study H + O2 (+M)→HO2(+M). In the flame case study, we present mixture conditions compared to those in the literature to study formyl radical (HCO) decomposition and oxidation reactions. The systematically determined experimental conditions identified in the present work are similar to the conditions chosen in the literature.

scholarly journals Laplacian Regularized Spatial-Aware Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery

2018 ◽  
Vol 11 (1) ◽  
pp. 29 ◽  
Author(s):  
Xinwei Jiang ◽  
Xin Song ◽  
Yongshan Zhang ◽  
Junjun Jiang ◽  
Junbin Gao ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Spatial Information ◽  
Feature Reduction ◽  
Collaborative Representation ◽  
Data Sets ◽  
Analysis Framework ◽  
Spatial Constraint ◽  
Spatial Constraints ◽  
Low Dimensional ◽  
Laplacian Regularization

Dimensionality Reduction (DR) models are of significance to extract low-dimensional features for Hyperspectral Images (HSIs) data analysis where there exist lots of noisy and redundant spectral features. Among many DR techniques, the Graph-Embedding Discriminant Analysis framework has demonstrated its effectiveness for HSI feature reduction. Based on this framework, many representation based models are developed to learn the similarity graphs, but most of these methods ignore the spatial information, resulting in unsatisfactory performance of DR models. In this paper, we firstly propose a novel supervised DR algorithm termed Spatial-aware Collaborative Graph for Discriminant Analysis (SaCGDA) by introducing a simple but efficient spatial constraint into Collaborative Graph-based Discriminate Analysis (CGDA) which is inspired by recently developed Spatial-aware Collaborative Representation (SaCR). In order to make the representation of samples on the data manifold smoother, i.e., similar pixels share similar representations, we further add the spectral Laplacian regularization and propose the Laplacian regularized SaCGDA (LapSaCGDA), where the two spectral and spatial constraints can exploit the intrinsic geometric structures embedded in HSIs efficiently. Experiments on three HSIs data sets verify that the proposed SaCGDA and LapSaCGDA outperform other state-of-the-art methods.

scholarly journals MORF: An online tool for exploring microbial cell responses using multi-omics analysis

2020 ◽  
Vol 2 (7A) ◽  
Author(s):  
Vicki Springthorpe ◽  
Rosalyn Leaman ◽  
Despoina Sifouna ◽  
Joyce Bennett ◽  
Gavin Thomas
Keyword(s):  
Data Sets ◽  
Full Potential ◽  
Experimental Conditions ◽  
Statistical Knowledge ◽  
Analysis Tools ◽  
Omics Analysis ◽  
Differential Gene ◽  
Reducing Costs ◽  
Tools And Techniques ◽  
User Friendly

With continuing improvements and reducing costs of high-throughput technologies, microbiologists are increasingly collecting multi-omics datasets. However, the tools and techniques used to analyse these kinds of data are often highly specialised and require bioinformatics, statistics and often coding experience. Many studies also tend to report on a single aspect of the data whilst overlooking other potentially interesting phenomena. Consequently, many of these multi-omics data sets are not being used to their full potential. MORF was created as a solution to these problems by providing access to multi-omics datasets through an online interface which presents the data in a user-friendly and accessible way. No coding experience or specialist statistical knowledge is required, and users are free to explore the data using interactive graphics and simple analysis tools. Here we demonstrate MORF using multi-omics datasets from two experiments using bacteria in industrial fermentation processes. First, Escherichia coli engineered to produce styrene, a valuable chemical used in the manufacture of polymers, and secondly a Clostridium which produces the biofuel butanol. A key outcome was the identification of targets believed to be involved in responding to membrane stress, which we identified using MORF’s differential gene and protein analysis tools. Work is underway to further characterise and engineer these targets to improve product yields. In conclusion, MORF provides a framework for omics analysis that can be applied to any organism or set of experimental conditions, and will help researchers and collaborators to make the most of their data.

scholarly journals Systematic Assessment of Freely-Diffusing Single-Molecule Fluorescence Detection using Brownian Motion Simulations

2019 ◽  
Author(s):  
Dolev Hagai ◽  
Eitan Lerner
Keyword(s):  
Brownian Motion ◽  
Fluorescence Detection ◽  
Single Molecule ◽  
Spatial Information ◽  
Three Dimensional ◽  
Single Molecule Fluorescence ◽  
Experimental Conditions ◽  
Systematic Assessment ◽  
Detection Volume ◽  
Burst Analysis

Single-molecule fluorescence detection (SMFD) experiments are useful in distinguishing between sub-populations of molecular species in measurements of heterogeneous samples. One of the experimental platforms for SMFD is based on a confocal microscope setup, where molecules in the solution randomly traverse an effective detection volume, formed by a tightly focused laser beam. The non-uniformity of the excitation profile and the random nature of Brownian motion, produce fluctuating fluorescence signals. For these signals to be distinguished from the background, single-molecule fluorescence burst analysis is frequently used. Yet, the relation between the results of burst analyses and the underlying spatial information of the diffusing molecules is still obscure and requires systematic assessment. In this work we performed three-dimensional Brownian motion simulations of SMFD, and tested the positions from which the molecules emitted photons that were detected and passed the burst analysis criteria for different values of burst analysis parameters. The results of this work verify which of the burst analysis parameters and experimental conditions influence both the position of molecules in space when fluorescence is detected and taken into account, and whether these bursts of photons arise purely from single molecules, or not entirely.

scholarly journals Resolving Cytosolic Diffusive States in Bacteria by Single-Molecule Tracking

2018 ◽  
Author(s):  
J. Rocha ◽  
J. Corbitt ◽  
T. Yan ◽  
C. Richardson ◽  
A. Gahlmann
Keyword(s):  
Data Analysis ◽  
Single Molecule ◽  
Time Window ◽  
Analysis Framework ◽  
Cellular Functions ◽  
Single Molecule Tracking ◽  
State Switching ◽  
Single Protein ◽  
Simplifying Assumptions ◽  
Analytical Approaches

AbstractThe trajectory of a single protein in the cytosol of a living cell contains information about its molecular interactions in its native environment. However, it has remained challenging to accurately resolve and characterize the diffusive states that can manifest in the cytosol using analytical approaches based on simplifying assumptions. Here, we show that multiple intracellular diffusive states can be successfully resolved if sufficient single-molecule trajectory information is available to generate well-sampled distributions of experimental measurements and if experimental biases are taken into account during data analysis. To address the inherent experimental biases in camera-based and MINFLUX-based single-molecule tracking, we use an empirical data analysis framework based on Monte Carlo simulations of confined Brownian motion. This framework is general and adaptable to arbitrary cell geometries and data acquisition parameters employed in 2D or 3D single-molecule tracking. We show that, in addition to determining the diffusion coefficients and populations of prevalent diffusive states, the timescales of diffusive state switching can be determined by stepwise increasing the time window of averaging over subsequent single-molecule displacements. Time-averaged diffusion (TAD) analysis of single-molecule tracking data may thus provide quantitative insights into binding and unbinding reactions among rapidly diffusing molecules that are integral for cellular functions.

SEM analysis of the change in the reaction rates with deposit structures in the copper-iron cementation system

1978 ◽  
Vol 36 (1) ◽  
pp. 456-457
Author(s):  
V. Annamalai ◽  
L.E. Murr
Keyword(s):  
Structural Characteristics ◽  
Secondary Electron Emission ◽  
Copper Deposit ◽  
Reaction Rates ◽  
Sem Analysis ◽  
Experimental Conditions ◽  
Major Drawback ◽  
Emission Mode ◽  
Scrap Iron ◽  
Image Position

Economical recovery of copper metal from leach liquors has been carried out by the simple process of cementing copper onto a suitable substrate metal, such as scrap-iron, since the 16th century. The process has, however, a major drawback of consuming more iron than stoichiometrically needed by the reaction.Therefore, many research groups started looking into the process more closely. Though it is accepted that the structural characteristics of the resultant copper deposit cause changes in reaction rates for various experimental conditions, not many systems have been systematically investigated. This paper examines the deposit structures and the kinetic data, and explains the correlations between them.A simple cementation cell along with rotating discs of pure iron (99.9%) were employed in this study to obtain the kinetic results The resultant copper deposits were studied in a Hitachi Perkin-Elmer HHS-2R scanning electron microscope operated at 25kV in the secondary electron emission mode.

Evaluation of Acoustic Analyses of Voice in Nonoptimized Conditions

2020 ◽  
Vol 63 (12) ◽  
pp. 3991-3999
Author(s):  
Benjamin van der Woerd ◽  
Min Wu ◽  
Vijay Parsa ◽  
Philip C. Doyle ◽  
Kevin Fung
Keyword(s):  
Repeated Measures ◽  
Voice Quality ◽  
Data Sets ◽  
Acoustic Measurements ◽  
Sample Collection ◽  
Experimental Conditions ◽  
Environment Analysis ◽  
Acoustic Measures ◽  
Recording Conditions ◽  
Cepstral Peak Prominence

Objectives This study aimed to evaluate the fidelity and accuracy of a smartphone microphone and recording environment on acoustic measurements of voice. Method A prospective cohort proof-of-concept study. Two sets of prerecorded samples (a) sustained vowels (/a/) and (b) Rainbow Passage sentence were played for recording via the internal iPhone microphone and the Blue Yeti USB microphone in two recording environments: a sound-treated booth and quiet office setting. Recordings were presented using a calibrated mannequin speaker with a fixed signal intensity (69 dBA), at a fixed distance (15 in.). Each set of recordings (iPhone—audio booth, Blue Yeti—audio booth, iPhone—office, and Blue Yeti—office), was time-windowed to ensure the same signal was evaluated for each condition. Acoustic measures of voice including fundamental frequency ( f o ), jitter, shimmer, harmonic-to-noise ratio (HNR), and cepstral peak prominence (CPP), were generated using a widely used analysis program (Praat Version 6.0.50). The data gathered were compared using a repeated measures analysis of variance. Two separate data sets were used. The set of vowel samples included both pathologic ( n = 10) and normal ( n = 10), male ( n = 5) and female ( n = 15) speakers. The set of sentence stimuli ranged in perceived voice quality from normal to severely disordered with an equal number of male ( n = 12) and female ( n = 12) speakers evaluated. Results The vowel analyses indicated that the jitter, shimmer, HNR, and CPP were significantly different based on microphone choice and shimmer, HNR, and CPP were significantly different based on the recording environment. Analysis of sentences revealed a statistically significant impact of recording environment and microphone type on HNR and CPP. While statistically significant, the differences across the experimental conditions for a subset of the acoustic measures (viz., jitter and CPP) have shown differences that fell within their respective normative ranges. Conclusions Both microphone and recording setting resulted in significant differences across several acoustic measurements. However, a subset of the acoustic measures that were statistically significant across the recording conditions showed small overall differences that are unlikely to have clinical significance in interpretation. For these acoustic measures, the present data suggest that, although a sound-treated setting is ideal for voice sample collection, a smartphone microphone can capture acceptable recordings for acoustic signal analysis.

A Reinvestigation of the Deceptively Simple Reaction of Toluene with ●OH, and the Fate of the Benzyl Radical. I. a Combined Thermodynamic and Kinetic Study on the Competition Between ●OH Addition and Hydrogen Abstraction Reactions.

2019 ◽  
Author(s):  
Zoi Salta ◽  
Agnie M. Kosmas ◽  
Marc E. Segovia ◽  
Martina Kieninger ◽  
Oscar Ventura ◽  
...  
Keyword(s):  
Density Functional ◽  
Room Temperature ◽  
Hydrogen Abstraction ◽  
Reaction Rates ◽  
Composite Model ◽  
Alternative Mechanism ◽  
Radical Intermediate ◽  
Experimental Conditions ◽  
Methyl Group ◽  
Benzyl Radical

This work reports density functional and composite model chemistry calculations performed on the reactions of toluene with the hydroxyl radical. Both experimentally observed H-abstraction from the methyl group and possible additions to the phenyl ring were investigated. Reaction enthalpies and heights of the barriers suggest that H-abstraction is more favorable than ●OH addition to the ring. The calculated reaction rates at room temperature and the radical-intermediate product fractions support this view. This is somehow contradictory with the fact that, under most experimental conditions, cresols are observed in a larger concentration than benzaldehyde. Since the accepted mechanism for benzaldehyde formation involves H-abstraction, a contradiction arises that begs for an explanation. In this first part of our work we give the evidences that support the preference of hydrogen abstraction over ●OH addition and suggest an alternative mechanism which shows that cresols can actually arise also from the former reaction and not only from the latter.

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