Nonlinear least-squares fitting methods

Cancer Radiomic and Perfusion Imaging Automated Framework: Validation on Musculoskeletal Tumors

PURPOSE

Limitations from commercial software applications prevent the implementation of a robust and cost-efficient high-throughput cancer imaging radiomic feature extraction and perfusion analysis workflow. This study aimed to develop and validate a cancer research computational solution using open-source software for vendor- and sequence-neutral high-throughput image processing and feature extraction.

METHODS

The Cancer Radiomic and Perfusion Imaging (CARPI) automated framework is a Python-based software application that is vendor- and sequence-neutral. CARPI uses contour files generated using an application of the user's choice and performs automated radiomic feature extraction and perfusion analysis. This workflow solution was validated using two clinical data sets, one consisted of 40 pelvic chondrosarcomas and 42 sacral chordomas with a total of 82 patients, and a second data set consisted of 26 patients with undifferentiated pleomorphic sarcoma (UPS) imaged at multiple points during presurgical treatment.

RESULTS

Three hundred sixteen volumetric contour files were processed using CARPI. The application automatically extracted 107 radiomic features from multiple magnetic resonance imaging sequences and seven semiquantitative perfusion parameters from time-intensity curves. Statistically significant differences (P < .00047) were found in 18 of 107 radiomic features in chordoma versus chondrosarcoma, including six first-order and 12 high-order features. In UPS postradiation, the apparent diffusion coefficient mean increased 41% in good responders (P = .0017), while firstorder_10Percentile (P = .0312) was statistically significant between good and partial/nonresponders.

CONCLUSION

The CARPI processing of two clinical validation data sets confirmed the software application's ability to differentiate between different types of tumors and help predict patient response to treatment on the basis of radiomic features. Benchmark comparison with five similar open-source solutions demonstrated the advantages of CARPI in the automated perfusion feature extraction, relational database generation, and graphic report export features, although lacking a user-friendly graphical user interface and predictive model building.

Eggshell crack detection based on the transient impact analysis and cross-correlation method

To explore the transient impact process for cracked eggshell detection, an equivalent mechanical model was built based on a self-designed automatic excitation device. Through analysis of power spectrum from dynamic force signal, it was found that the impact speed affects only the impaction energy. In contrast, the material of the impact head and the weight of the excitation rod determine the energy and the cut-off frequency of the impaction. When the weight of impact tup is less than 6.62 g, the cut-off frequency of excitation impact can cover the egg's inherent frequency. Then, an optimized experiment system was designed to acquire the response acoustic signals. The cross-correlation analysis and Bayes classification methods were carried out to detect the cracked eggshell. In the conducted experiments, a crack detection level of 97% and a false rejection level of 1% were achieved. From the findings, it can be concluded that the proposed method will assist in optimizing the impact device and simplifying the classification algorithm for an online detection system.

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An equivalent mechanical model was built to analyze the transient impact process.

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The effective response signal which covers the inherent frequency of the egg was enhanced by the power spectrum analysis.

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The cross-correlation analysis method was proposed to distinguish the intact eggs and cracked eggs.

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In the conducted experiments, a crack detection level of 97% and a false rejection level of 1% were achieved.

Interactions of a Signal Transduction Protein Investigated by Fluorescence Stopped-Flow Kinetics

To understand cellular processes such as biochemical pathways and signaling networks, we need to understand binding and reaction rates of often competing reactions, their dependence on cellular concentrations of participating molecules, and the regulation of these rates through allostery, posttranslational modifications, or other mechanisms. To do so, we break these systems down into their elementary steps, which are almost invariably either unimolecular or bimolecular reactions that frequently occur on sub-second, often sub-millisecond, time scales. Rapid mixing techniques, which generally achieve mixing in less than 2 ms, are generally suitable for the study of such reactions. The application of these techniques to the study of enzyme mechanisms is described in several excellent texts (Cornish-Bowden, Fundamentals of enzyme kinetics, 1995; Gutfreund, Kinetics for the life sciences. Receptors, transmitters and catalysis, 1995); flow techniques are used to study individual steps by monitoring the approach to equilibrium (the pre-steady state) under single turnover conditions.The individual steps in complex biochemical reaction schemes determine how fast systems can respond to incoming signals and adapt to changed conditions [1, 2]. This chapter is concerned with in vitro techniques that have been developed to study fast reactions in solution, and we present the study of various interactions of calmodulin as an example. The kinetic information obtained with these techniques is indispensable for understanding the dynamics of biochemical processes and complements the static structural and thermodynamic information available from X-ray crystallography, NMR, and equilibrium binding studies.

A collection of programs for one-dimensional Ising analysis of linear repeat proteins with point substitutions

A collection of programs is presented to analyze the thermodynamics of folding of linear repeat proteins using a 1D Ising model to determine intrinsic folding and interfacial coupling free energies. Expressions for folding transitions are generated for a series of constructs with different repeat numbers and are globally fitted to transitions for these constructs. These programs are designed to analyze Ising parameters for capped homopolymeric consensus repeat constructs as well as heteropolymeric constructs that contain point substitutions, providing a rigorous framework for analysis of the effects of mutation on intrinsic and directional (i.e., N- vs. C-terminal) interfacial coupling free-energies. A bootstrap analysis is provided to estimate parameter uncertainty as well as correlations among fitted parameters. Rigorous statistical analysis is essential for interpreting fits using the complex models required for Ising analysis of repeat proteins, especially heteropolymeric repeat proteins. Programs described here are available at https://github.com/barricklab-at-jhu/Ising_programs.

Fast and Robust Quantification of Detergent Micellization Thermodynamics from Isothermal Titration Calorimetry

Detergents are widely used in modern in vitro biochemistry and biophysics, in particular to aid the characterization of integral membrane proteins. An important characteristic of these chemicals in aqueous solutions is the concentration above which their molecular monomers self-associate to form micelles, termed the critical micellar concentration (CMC). Micelles are supramolecular assemblies arranged with the hydrophobic portions oriented inward and the hydrophilic head groups positioned outward to interact with the aqueous solvent. Knowledge of the CMC is not only of practical relevance but also of theoretical interest because it provides thermodynamic insights. Isothermal titration calorimetry (ITC) is a powerful method to determine CMCs, as it furnishes additional information on the enthalpy and entropy of micellization. Here we describe our extension of previous methods to determine CMCs and other thermodynamic parameters from ITC demicellization curves. The new algorithm, incorporated into the stand-alone software package D/STAIN, analyzes ITC demicellization curves by taking advantage of state-of-the-art thermogram-integration techniques and automatically providing rigorous confidence intervals on the refined parameters. As a demonstration of the software's capabilities, we undertook ITC experiments to determine the respective CMCs of n-octyl β-d-glucopyranoside (OG), n-dodecyl β-d-maltopyranoside (DDM), and lauryldimethylamine N-oxide (LDAO). Motivated by the fact that in vitro membrane protein studies often require additives such as precipitants (e.g., polyethylene glycol (PEG)), we also carried out ITC demicellization studies in the presence of PEG3350, finding in all cases that PEG had significant effects on the thermodynamics of detergent micellization.

2b-RAD genotyping for population genomic studies of Chagas disease vectors: Rhodnius ecuadoriensis in Ecuador

BACKGROUND

Rhodnius ecuadoriensis is the main triatomine vector of Chagas disease, American trypanosomiasis, in Southern Ecuador and Northern Peru. Genomic approaches and next generation sequencing technologies have become powerful tools for investigating population diversity and structure which is a key consideration for vector control. Here we assess the effectiveness of three different 2b restriction site-associated DNA (2b-RAD) genotyping strategies in R. ecuadoriensis to provide sufficient genomic resolution to tease apart microevolutionary processes and undertake some pilot population genomic analyses.

METHODOLOGY/PRINCIPAL FINDINGS

The 2b-RAD protocol was carried out in-house at a non-specialized laboratory using 20 R. ecuadoriensis adults collected from the central coast and southern Andean region of Ecuador, from June 2006 to July 2013. 2b-RAD sequencing data was performed on an Illumina MiSeq instrument and analyzed with the STACKS de novo pipeline for loci assembly and Single Nucleotide Polymorphism (SNP) discovery. Preliminary population genomic analyses (global AMOVA and Bayesian clustering) were implemented. Our results showed that the 2b-RAD genotyping protocol is effective for R. ecuadoriensis and likely for other triatomine species. However, only BcgI and CspCI restriction enzymes provided a number of markers suitable for population genomic analysis at the read depth we generated. Our preliminary genomic analyses detected a signal of genetic structuring across the study area.

CONCLUSIONS/SIGNIFICANCE

Our findings suggest that 2b-RAD genotyping is both a cost effective and methodologically simple approach for generating high resolution genomic data for Chagas disease vectors with the power to distinguish between different vector populations at epidemiologically relevant scales. As such, 2b-RAD represents a powerful tool in the hands of medical entomologists with limited access to specialized molecular biological equipment.

Methane production enhancement from products of alkaline hydrogen peroxide pretreated sweet sorghum bagasse

Alkaline hydrogen peroxide (AHP) pretreatment was applied to improve methane production from sweet sorghum bagasse under mesophilic conditions.

Structural Insight into the 14-3-3 Protein-dependent Inhibition of Protein Kinase ASK1 (Apoptosis Signal-regulating kinase 1)

Apoptosis signal-regulating kinase 1 (ASK1, also known as MAP3K5), a member of the mitogen-activated protein kinase kinase kinase (MAP3K) family, regulates diverse physiological processes. The activity of ASK1 is triggered by various stress stimuli and is involved in the pathogenesis of cancer, neurodegeneration, inflammation, and diabetes. ASK1 forms a high molecular mass complex whose activity is, under non-stress conditions, suppressed through interaction with thioredoxin and the scaffolding protein 14-3-3. The 14-3-3 protein binds to the phosphorylated Ser-966 motif downstream of the ASK1 kinase domain. The role of 14-3-3 in the inhibition of ASK1 has yet to be elucidated. In this study we performed structural analysis of the complex between the ASK1 kinase domain phosphorylated at Ser-966 (pASK1-CD) and the 14-3-3ζ protein. Small angle x-ray scattering (SAXS) measurements and chemical cross-linking revealed that the pASK1-CD·14-3-3ζ complex is dynamic and conformationally heterogeneous. In addition, structural analysis coupled with the results of phosphorus NMR and time-resolved tryptophan fluorescence measurements suggest that 14-3-3ζ interacts with the kinase domain of ASK1 in close proximity to its active site, thus indicating this interaction might block its accessibility and/or affect its conformation.

On the acquisition and analysis of microscale thermophoresis data

A comprehensive understanding of the molecular mechanisms underpinning cellular functions is dependent on a detailed characterization of the energetics of macromolecular binding, often quantified by the equilibrium dissociation constant, KD. While many biophysical methods may be used to obtain KD, the focus of this report is a relatively new method called microscale thermophoresis (MST). In an MST experiment, a capillary tube filled with a solution containing a dye-labeled solute is illuminated with an infrared laser, rapidly creating a temperature gradient. Molecules will migrate along this gradient, causing changes in the observed fluorescence. Because the net migration of the labeled molecules will depend on their liganded state, a binding curve as a function of ligand concentration can be constructed from MST data and analyzed to determine KD. Herein, simulations demonstrate the limits of KD that can be measured in current instrumentation. They also show that binding kinetics is a major concern in planning and executing MST experiments. Additionally, studies of two protein-protein interactions illustrate challenges encountered in acquiring and analyzing MST data. Combined, these approaches indicate a set of best practices for performing and analyzing MST experiments. Software for rigorous data analysis is also introduced.

Density-dependent cooperative non-specific binding in solid-phase SELEX affinity selection

The non-specific binding of undesired ligands to a target is the primary factor limiting the enrichment of tight-binding ligands in affinity selection. Solution-phase non-specific affinity is determined by the free-energy of ligand binding to a single target. However, the solid-phase affinity might be higher if a ligand bound concurrently to multiple adjacent immobilized targets in a cooperative manner. Cooperativity could emerge in this case as a simple consequence of the relationship between the free energy of binding, localization entropy and the spatial distribution of the immobilized targets. We tested this hypothesis using a SELEX experimental design and found that non-specific RNA aptamer ligands can concurrently bind up to four bead-immobilized peptide targets, and that this can increase their effective binding affinity by two orders-of-magnitude. Binding curves were quantitatively explained by a new statistical mechanical model of density-dependent cooperative binding, which relates cooperative binding to both the target concentration and the target surface density on the immobilizing substrate. Target immobilization plays a key role in SELEX and other ligand enrichment methods, particularly in new multiplexed microfluidic purification devices, and these results have strong implications for optimizing their performance.

Confidence intervals for concentration and brightness from fluorescence fluctuation measurements

The theory of photon count histogram (PCH) analysis describes the distribution of fluorescence fluctuation amplitudes due to populations of fluorophores diffusing through a focused laser beam and provides a rigorous framework through which the brightnesses and concentrations of the fluorophores can be determined. In practice, however, the brightnesses and concentrations of only a few components can be identified. Brightnesses and concentrations are determined by a nonlinear least-squares fit of a theoretical model to the experimental PCH derived from a record of fluorescence intensity fluctuations. The χ(2) hypersurface in the neighborhood of the optimum parameter set can have varying degrees of curvature, due to the intrinsic curvature of the model, the specific parameter values of the system under study, and the relative noise in the data. Because of this varying curvature, parameters estimated from the least-squares analysis have varying degrees of uncertainty associated with them. There are several methods for assigning confidence intervals to the parameters, but these methods have different efficacies for PCH data. Here, we evaluate several approaches to confidence interval estimation for PCH data, including asymptotic standard error, likelihood joint-confidence region, likelihood confidence intervals, skew-corrected and accelerated bootstrap (BCa), and Monte Carlo residual resampling methods. We study these with a model two-dimensional membrane system for simplicity, but the principles are applicable as well to fluorophores diffusing in three-dimensional solution. Using simulated fluorescence fluctuation data, we find the BCa method to be particularly well-suited for estimating confidence intervals in PCH analysis, and several other methods to be less so. Using the BCa method and additional simulated fluctuation data, we find that confidence intervals can be reduced dramatically for a specific non-Gaussian beam profile.

Rapid mixing kinetic techniques

Almost all of the elementary steps in a biochemical reaction scheme are either unimolecular or bimolecular processes that frequently occur on sub-second, often sub-millisecond, time scales. The traditional approach in kinetic studies is to mix two or more reagents and monitor the changes in concentrations with time. Conventional spectrophotometers cannot generally be used to study reactions that are complete within less than about 20 s, as it takes that amount of time to manually mix the reagents and activate the instrument. Rapid mixing techniques, which generally achieve mixing in less than 2 ms, overcome this limitation. This chapter is concerned with the use of these techniques in the study of reactions which reach equilibrium; the application of these methods to the study of enzyme kinetics is described in several excellent texts (Cornish-Bowden, Fundamentals of enzyme kinetics. Portland Press, 1995; Gutfreund, Kinetics for the life sciences. Receptors, transmitters and catalysis. Cambridge University Press, 1995).There are various ways to monitor changes in concentration of reactants, intermediates and products after mixing, but the most common way is to use changes in optical signals (absorbance or fluorescence) which often accompany reactions. Although absorbance can sometimes be used, fluorescence is often preferred because of its greater sensitivity, particularly in monitoring conformational changes. Such methods are continuous with good time resolution but they seldom permit the direct determination of the concentrations of individual species. Alternatively, samples may be taken from the reaction volume, mixed with a chemical quenching agent to stop the reaction, and their contents assessed by techniques such as HPLC. These methods can directly determine the concentrations of different species, but are discontinuous and have a limited time resolution.

Protein-ligand interactions: fundamentals

Here are described the basic mechanisms governing the interactions between proteins and their natural or manmade ligands, together with the principles underlying their analysis. The consequences of these principles are detailed for the simplest case of one-to-one binding. The general features of experimental measurements of biomolecular interactions arise from properties of the molecules involved and, thus, are common to many methods of detection. Consequently, an understanding of these principles greatly simplifies adoption and comparison of experimental methods and provides the rationale underlying many common protocols. In seeking to understand and interpret the results of experiments or identify possible sources of error these fundamental ideas are a constant guide.

Simultaneous determination of equilibrium constants and enthalpy changes by titration calorimetry: Methods, instruments, and uncertainties

Calorimetric methods have been used to determine equilibrium constants since 1937, but no comprehensive review of the various calorimeters and methods has been done previously. This article reports methods for quantitative comparison of the capabilities of calorimeters for simultaneous determination of equilibrium constants and enthalpy changes, for determining optimal experimental conditions, and for assessing the effects of systematic and random errors on the accuracy and precision of equilibrium constants and enthalpy changes determined by this method.

Analysis of repeat-protein folding using nearest-neighbor statistical mechanical models

The linear "Ising" model, which has been around for nearly a century, treats the behavior of linear arrays of repetitive, interacting subunits. Linear "repeat-proteins" have only been described in the last decade or so, and their folding energies have only been characterized very recently. Owing to their repetitive structures, linear repeat-proteins are particularly well suited for analysis by the nearest-neighbor Ising formalism. After briefly describing the historical origins and applications of the Ising model to biopolymers, and introducing repeat protein structure, this chapter will focus on the application of the linear Ising model to repeat proteins. When applied to homopolymers, the model can be represented and applied in a fairly simplified form. When applied to heteropolymers, where differences in energies among individual subunits (i.e. repeats) must be included, some (but not all) of this simplicity is lost. Derivations of the linear Ising model for both homopolymer and heteropolymer repeat-proteins will be presented. With the increased complexity required for analysis of heteropolymeric repeat proteins, the ability to resolve different energy terms from experimental data can be compromised. Thus, a simple matrix approach will be developed to help inform on the degree to which different thermodynamic parameters can be extracted from a particular set of unfolding curves. Finally, we will describe the application of these models to analyze repeat-protein folding equilibria, focusing on simplified repeat proteins based on "consensus" sequence information.