Temperature-insensitive near-infrared method for determination of protein concentration during protein crystal growth

Optimal Operation of an Oscillatory Flow Crystallizer: Coupling Disturbance and Stability

In the process of industrial crystallization, it is always difficult to balance the secondary nucleation rate and metastable zone width (MSZW). Herein, we report an experimental and numerical study for the cooling crystallization of paracetamol in an oscillatory flow crystallizer (OFC), finding the optimal operating conditions for balancing the secondary nucleation rate and MSZW. The results show that the MSZW decreases with the increase of oscillation Reynolds number (Re _o). Compared to the traditional stirring system, the OFC has an MSZW three times larger than that of the stirring system under a similar power density of consumption. With the numerical simulation, the OFC can produce a stable space environment and instantaneous strong disturbance, which is conducive to the crystallization process. Above all, a high Re _o is favorable to produce a sufficient nucleation rate, which may inevitably constrict the MSZW to a certain degree. Then, the optimization strategy of the operating parameter (Re _o) in the OFC is proposed.

Selectivity and Sensitivity of Near-Infrared Spectroscopic Sensing of β-Hydroxybutyrate, Glucose, and Urea in Ternary Aqueous Solutions

The next-generation artificial pancreas is under development with the goal to enhance tight glycemic control for people with type 1 diabetes. Such technology requires the integration of a chemical sensing unit combined with an insulin infusion device controlled by an algorithm capable of autonomous operation. The potential of near-infrared spectroscopic sensing to serve as the chemical sensing unit is explored by demonstrating the ability to quantify multiple metabolic biomarkers from a single near-infrared spectrum. Independent measurements of β-hydroxy-butyrate, glucose, and urea are presented based on analysis of near-infrared spectra collected over the combination spectral range of 5000-4000 cm^-1 for a set of 50 ternary aqueous standard solutions. Spectra are characterized by a 1 μAU root-mean-square (RMS) noise for 100% lines with a resolution of 4 cm^-1 and an optical path length of 1 mm. Calibration models created by the net analyte signal (NAS) and the partial least squares (PLS) methods provide selective measurements for each analyte with standard errors of prediction in the upper micromolar concentration range. The NAS method is used to determine both the selectivity and sensitivity for each analyte and their values are consistent with these standard errors of prediction. The NAS method is also used to characterize the background spectral variance associated with instrumental and environmental variations associated with buffer spectra collected over a multiday period.

Three-level simultaneous component analysis for analyzing the near-infrared spectra of aqueous solutions under multiple perturbations

Quantitative analysis under various perturbations is a difficult problem because the analytical signal changes with different factors. In this work, three-level simultaneous component analysis (3-MSCA) was used for analyzing the near-infrared (NIR) spectra of aqueous solutions under different perturbations. The spectral data of aqueous proline solutions at different pH, concentration and temperature were measured, and a three-level model was built to describe the effects of the three perturbations on the spectra, respectively. The first level model describes the change of the spectra with pH, from which significant aggregation of proline was observed around the isoelectric point. The second and third level model show the spectral change with concentration and temperature, respectively, and the spectral feature has a very good linear relationship with the corresponding influencing factors. Therefore, the pH and concentration scores can be used as the calibration curve for quantitative analysis of the pH and the content of proline, and the temperature scores can be used to predict the temperature of the solutions. In addition, the structural change of water molecules under different conditions is obtained from the loadings. A decline of the bulk water was found with the increase of concentration, implying an ascending trend of the bonded water due to the interaction of proline and water. The dissociation of water clusters with the increase of temperature is also displayed.

Optimization of crystallization of biological macromolecules using dialysis combined with temperature control

A rational way to find the appropriate conditions to grow crystal samples for bio-crystallography is to determine the crystallization phase diagram, which allows precise control of the parameters affecting the crystal growth process. First, the nucleation is induced at supersaturated conditions close to the solubility boundary between the nucleation and metastable regions. Then, crystal growth is further achieved in the metastable zone - which is the optimal location for slow and ordered crystal expansion - by modulation of specific physical parameters. Recently, a prototype of an integrated apparatus for the rational optimization of crystal growth by mapping and manipulating temperature-precipitant-concentration phase diagrams has been constructed. Here, it is demonstrated that a thorough knowledge of the phase diagram is vital in any crystallization experiment. The relevance of the selection of the starting position and the kinetic pathway undertaken in controlling most of the final properties of the synthesized crystals is shown. The rational crystallization optimization strategies developed and presented here allow tailoring of crystal size and diffraction quality, significantly reducing the time, effort and amount of expensive protein material required for structure determination.

Quantitative determination by temperature dependent near-infrared spectra: a further study

Quantitative spectra-temperature relationship (QSTR) between near-infrared (NIR) spectra and temperature has been studied in our previous work (Talanta, 2010, 82, 1017-1021). In this study, applicability of the QSTR model for quantitative determination is further studied using the spectra of aqueous ethanol samples in the temperature range of 31-40°C and the concentration range of 1-99%. The results show that QSTR model can be built by using the spectra in a small temperature range and the quantitative analysis can be achieved by only two spectra at different temperatures. Moreover, calibration curves for different concentration ranges (1-5%, 20-70%, 95-99%, v/v) are investigated by using linear and nonlinear curve fitting, respectively. Both of the linear and nonlinear curves are found to be applicable within these concentration ranges. Therefore, the temperature dependent NIR spectra may provide a new way for quantitative determination and may have high potential in bio-fluids analysis or industrial practices.

Improved retroreflection method for measuring the refractive index of liquids

We propose a new method for measuring the refractive index of liquids with high precision; the method is based on use of the optical fiber end face. As an example, we investigated the refractive index of sugar solution under varying conditions tens of times. The results show that this method has the advantage of higher stability and repeatability. The concentration and the temperature-dependent refractive index of the sugar solution is also experimentally studied.

Net analyte signal-based simultaneous determination of dyes in environmental samples using moving window partial least squares regression with UV-vis spectroscopy

The multivariate calibration methods-moving window selection partial least squares regression (MWPLSR) and net analyte signal (NAS)-were employed for simultaneous determination of a mixture of C.I. Disperse Blue 183, C.I. Disperse Blue 79, C.I. Disperse Red 82, C.I. Disperse Red 65, C.I. Disperse Yellow 211 and C.I. Disperse Orange 25 by UV-vis spectrophotometry. The absorption spectra of the six disperse dyes were recorded between 320 and 680 nm. A modified changeable size moving window partial least squares (CSMWPLS) and searching combination moving window partial least squares (SCMWPLS) were proposed to search for an optimized spectral interval and an optimized combination of spectral regions from informative regions obtained by MWPLSR. Different wavelength regions were selected by taking into account different spectral parameters including the starting wavelength, the ending wavelength and wavelength interval. It was found that wavelength selection improved the performance of the corresponding net analyte signal-partial least squares (NAS-PLS) model, in terms of root mean square error (RMSE), compared with the results obtained using whole spectra or direct combination of informative regions for each dye. The importance of calibration design was also investigated by calculating the prediction and validation errors. The influence of using independent validation sets were emphasized. The proposed calibration method gave better results in combination and informative spectral regions for determination of the six disperse dyes without prior separation.

Near-infrared microspectroscopic analysis of rat skin tissue heterogeneity in relation to noninvasive glucose sensing

BACKGROUND

Noninvasive glucose measurements are possible by analysis of transmitted near-infrared light over the 4000- to 5000-cm(-1) spectral range. Such measurements are highly sensitive to the exact position of the fiber-optic interface on the surface of the skin sample. A critical question is the degree of heterogeneity of the major chemical components of the skin matrix in relation to the size of the fiber-optic probed used to collect noninvasive spectra. Microscopic spectral mapping is used to map the chemical distribution for a set of excised sections of rat skin.

METHOD

A Fourier transform near-infrared microspectrometer was used to collect transmission spectra from 16 tissue samples harvested from a set of four healthy Harlan-Sprague male rats. A reference point in the center of the tissue sample was probed regularly to track dehydration, changes in tissue composition, and changes in instrument performance. Amounts of the major skin constituents were determined by fitting microspectra to a set of six pure component absorbance spectra corresponding to water, type I collagen protein, keratin protein, fat, an offset term, and a slope term.

RESULTS

Microspectroscopy provides spectra with root mean square noise levels on 100% lines between 418 and 1475 microabsorbance units, which is sufficient for measuring the main chemical components of skin. The estimated spatial resolution of the microscope is 220 microm. The amounts of each tissue matrix component were determined for each 480 x 360-microm(2) location of a 4.8 x 3.6-mm(2) rectangular block of skin tissue. These spectra were used to generate two-dimensional distribution maps for each of the principal skin components.

CONCLUSIONS

Distribution of the chemical components of rat skin is significant relative to the dimensions of noninvasive glucose sensing. Chemical distribution maps reveal that variations in the chemical composition of the skin samples are on the same length scale as the fiber-optic probe used to collect noninvasive near-infrared spectra. Analysis of variance between tissue slices collected for one animal and analysis of variations between animals indicate that animal-to-animal variation for all four chemical components is significantly higher than variations between samples for a given animal. These findings justify the collection and interpretation of near-infrared microspectroscopic maps of human skin to establish chemical heterogeneity and its impact on noninvasive glucose sensing for the management of diabetes.

Tackling calibration problems of spectroscopic analysis in high-throughput experimentation

High-throughput experimentation and screening methods are changing work flows and creating new possibilities in biochemistry, organometallic chemistry, and catalysis. However, many high-throughput systems rely on off-line chromatography methods that shift the bottleneck to the analysis stage. On-line or at-line spectroscopic analysis is an attractive alternative. It is fast, noninvasive, and nondestructive and requires no sample handling. The disadvantage is that spectroscopic calibration is time-consuming and complex. Ideally, the calibration model should give reliable predictions while keeping the number of calibration samples to a minimum. In this paper, we employ the net analyte signal approach to build a calibration model for Fourier transform near-infrared measurements, using a minimum number of calibration samples based on blank samples. This approach fits very well to high-throughput setups. With this approach, we can reduce the number of calibration samples to the number of chemical components in the system. Thus, the question is no longer how many but which type of calibration samples should one include in the model to obtain reliable predictions. Various calibration models are tested using Monte Carlo simulations, and the results are compared with experimental data for palladium-catalyzed Heck cross-coupling.

Simple and robust near-infrared spectroscopic monitoring of indium-tin-oxide (ITO) etching solution using Teflon tubing

The ability to monitor etching solutions using a spectroscopy directly through existing Teflon lines in electronic industries is highly beneficial and offers many advantages. A monitoring method was developed using near-infrared (NIR) measurements with Teflon tubing as a sample container for the quantification of components in the indium-tin-oxide (ITO) etching solution composed of hydrochloric acid (HCl), acetic acid (CH3COOH) and water. Measurements were reproducible and it was possible to use the same calibration model for different Teflon tubings. Even though partial least squares (PLS) calibration performance was slightly degraded for Teflon cells when compared to quartz cells of the similar pathlength, the calibration data correlated well with reference data. The robustness of Teflon-based NIR measurement was evaluated by predicting the spectra of 10 independent samples that were collected using five different Teflon tubes. Although, two Teflon tubes were visually less transparent than the other three, there was no significant variation in the standard error of predictions (SEPs) among the five Teflon tubes. Calibration accuracy was successfully maintained and highly repeatable prediction results were achieved. This study verifies that a Teflon-based NIR measurement is reliable for the monitoring of etching solutions and it can be successfully integrated into on-line process monitoring.

Pure Component Selectivity Analysis of Multivariate Calibration Models from Near-Infrared Spectra

A novel procedure is proposed as a method to characterize the chemical basis of selectivity for multivariate calibration models. This procedure involves submitting pure component spectra of both the target analyte and suspected interferences to the calibration model in question. The resulting model output is analyzed and interpreted in terms of the relative contribution of each component to the predicted analyte concentration. The utility of this method is illustrated by an analysis of calibration models for glucose, sucrose, and maltose. Near-infrared spectra are collected over the 5000-4000-cm(-)(1) spectral range for a set of ternary mixtures of these sugars. Partial least-squares (PLS) calibration models are generated for each component, and these models provide selective responses for the targeted analytes with standard errors of prediction ranging from 0.2 to 0.7 mM over the concentration range of 0.5-50 mM. The concept of the proposed pure component selectivity analysis is illustrated with these models. Results indicate that the net analyte signal is solely responsible for the selectivity of each individual model. Despite strong spectral overlap for these simple carbohydrates, calibration models based on the PLS algorithm provide sufficient selectivity to distinguish these commonly used sugars. The proposed procedure demonstrates conclusively that no component of the sucrose or maltose spectrum contributes to the selective measurement of glucose. Analogous conclusions are possible for the sucrose and maltose calibration models.