Quantification of albumin in urine using preconcentration and near-infrared diffuse reflectance spectroscopy

Urinary albumin is an important diagnostic and prognostic marker for cardiorenal disease. Recent studies have shown that elevation of albumin excretion even in normal concentration range is associated with increased cardiorenal risk. Therefore, accurate measurement of urinary albumin in normal concentration range is necessary for clinical diagnosis. In this work, thiourea-functionalized silica nanoparticles are prepared and used for preconcentration of albumin in urine. The adsorbent with the analyte was then used for near-infrared diffuse reflectance spectroscopy measurement directly and partial least squares model was established for quantitative prediction. Forty samples were taken as calibration set for establishing PLS model and 17 samples were used for validation of the method. The correlation coefficient and the root mean squared error of cross validation is 0.9986 and 0.43, respectively. Residual predictive deviation value of the model is as high as 18.8. The recoveries of the 17 validation samples in the concentration range of 3.39-24.39 mg/L are between 95.9%-113.1%. Therefore, the method may provide a candidate method to quantify albumin excretion in urine.     

Determination of triglycerides in human serum by near-infrared diffuse reflectance spectroscopy using silver mirror as a substrate

Quantitative determination of serum triglycerides was achieved in diffuse reflectance mode using silver mirror as the substrate to enhance the spectral features.     

An approach by using near-infrared diffuse reflectance spectroscopy and resin adsorption for the determination of copper, cobalt and nickel ions in dilute solution

Near-infrared spectroscopy (NIRS) has been proved to be a powerful analytical tool and used in various fields, it is seldom, however, used in the analysis of metal ions in solutions. A method for quantitative determination of metal ions in solution is developed by using resin adsorption and near-infrared diffuse reflectance spectroscopy (NIRDRS). The method makes use of the resin adsorption for gathering the analytes from a dilute solution, and then NIRDRS of the adsorbate is measured. Because both the information of the metal ions and their interaction with the functional group of resin can be reflected in the spectrum, quantitative determination is achieved by using multivariate calibration technique. Taking copper (Cu²⁺), cobalt (Co²⁺) and nickel (Ni²⁺) as the analyzing targets and D401 resin as the adsorbent, partial least squares (PLS) model is built from the NIRDRS of the adsorbates. The results show that the concentrations that can be quantitatively detected are as low as 1.00, 1.98 and 1.00 mg L⁻¹ for Cu²⁺, Co²⁺ and Ni²⁺, respectively, and the coexistent ions do not influence the determination.     

Rapid determination of aluminum by UV-vis diffuse reflectance spectroscopy with application of suitable adsorbents

Diffuse reflectance spectroscopy (DRS) can be used as a rapid and sensitive method for the quantitative determination of low amounts of aluminum. In this analytical technique, the analyte in samples are extracted onto a solid sorbent matrix loaded with a colorimetric reagent and then quantified directly on the adsorbent surface. Alternatively, colored aluminum complexes formed in solution can also be immobilized onto adsorbent surface and be measured by DRS technique. Octadecyl silica disk, methyltrioctylammonium chloride–naphthalene and MCM-41 were examined as adsorbents. Eriochrome cyanine R and quinalizarin were used as coloring reagents. Optimal sorption conditions were found for each system of analyte–reagent–adsorbent. The concentration of analyte is determined using the appropriate form of the Kubelka–Munk function. We obtained for each of the aluminium–reagent–adsorbent system a calibration curve by plotting the absorbance versus the log 10²[Al³⁺] μg ml⁻¹. The linear dynamic range extends over two orders of magnitude within 0.01–15 μg ml⁻¹ with little differences in the range and in the correlation coefficients among the adsorbents. We consider that for a rapid determination of aluminum a spot-test-DRS combination with a detection limit of 1.0 × 10⁻² μg ml⁻¹ is the more facile and preferred technique.     

Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.     

Characterization of lead and lead leaching properties of lead glazed ceramics from the Solis Valley, Mexico, using inductively coupled plasma-mass spectrometry (ICP-MS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFT)

Ingestion of relatively small amounts of lead is now recognized to cause significant neurological and cognitive effects in humans. Large quantities may be fatal, yet lead poisoning, especially of children, is still a major public health concern in many parts of the world. In rural Mexican communities lead oxide (PbO) is added to ceramic glaze as a fluxing agent, lowering starting firing temperatures to 500 °C. The purpose of this study is to characterize the lead chemical forms in ceramic glazes from the Solis Valley, Mexico, to investigate lead leaching properties of these ceramics, and to demonstrate the applicability of lead isotope signatures as a means of tracing lead source origins. Ceramics were collected from the rural village of Santa Maria de Canchesda, State of Mexico, Mexico. Dried liquid glazes, post-fired glaze material, and pure PbO were analyzed by diffuse reflectance infrared Fourier transform spectroscopy (DRIFT). Results from DRIFT analysis indicate that PbO (1429 cm⁻¹ band) is the active form of lead found in liquid glazes and ceramics. Some shifting of 1429 cm⁻¹ PbO peak to lower wavenumbers occurs in post-fired ceramics, and this may be due to the formation of lead bisilicate during firing. Ceramics samples were leached in 0.02 M citric acid solution for 1 min, and leached lead concentrations were measured using inductively coupled plasma-mass spectrometry (ICP-MS). Lead concentrations in these leachates varied from 0.4-80.4 μg ml⁻¹, while the control pottery from the US leached only 0.1 μg ml⁻¹ lead. Elemental distributions on glaze surfaces were identified by laser ablation (LA)-ICP-MS. Nitric acid extracts of soils, teeth, and ceramic glazes were analyzed for lead isotope ratios (²⁰⁷Pb/²⁰⁶Pb vs. ²⁰⁸Pb/²⁰⁶Pb) using ICP-MS. Similarities of tooth and ceramic lead isotope ratios indicate that ceramics may be a substantial source of body lead burden in the Solis Valley. This study demonstrates the applicability of lead isotope ratios for lead source identification, and it identifies potential health risks from ceramic use induced lead toxicity within the Solis Valley.     

Determination of furosemide in pharmaceutical formulations by diffuse reflectance spectroscopy

In this report an analytical method to determine furosemide by using diffuse reflectance spectroscopy is presented. This study shows that this technique can give quantitative results using spot test analysis, particularly in the case of pharmaceuticals containing furosemide. The color spot test could be obtained by reaction between furosemide with p-dimethylaminocinnamaldehyde, in acid medium. This reaction produced a stable complex on filter paper after heating to 80 °C for 5 min. All reflectance measurements were carried out at 585 nm and the linear range was from 7.56×10⁻³ to 6.05×10⁻² mol l⁻¹, with a correlation coefficient of 0.999. The limit of detection was estimated to be 2.49×10⁻³ mol l⁻¹ (R.S.D.=1.7%) and the effect of common excipients on the reflectance measurements was evaluated. The method was applied to determine furosemide in commercial brands of pharmaceuticals. The results obtained by the proposed method were favorably compared with those of the official method, showing for the first time ever that quantitative spot test analysis by diffuse reflectance could be successfully used to determine furosemide in tablets.     

Testing of the Region of Murcia soils by near infrared diffuse reflectance spectroscopy and chemometrics

A partial least squares near infrared (PLS-NIR) method has been developed for the determination of several physicochemical parameters in soils from different locations of the Region of Murcia. The method was based on the proper chemometric treatment of diffuse reflectance spectra of soil samples. Reflectance spectra were scanned from samples stored in glass vials in the NIR region between 800 and 2600 nm, averaging 36 scans per spectrum at a resolution of 8 cm⁻¹. Models were built using reference data of 39 samples selected from a dendrogram obtained after hierarchical cluster analysis of NIR spectra of soils and prediction parameters were established from a validation set of 109 additional samples of the same area not considered to build the model. Organic matter, CaCO₃, pH, electrical conductivity (EC), together with several trace metals as Cr, Co, Ni, Cu, Zn, As, Se, Cd and Tl, were employed as characteristic parameters of the soils under study, and found results evidenced that PLS-NIR provides a valuable tool for screening purposes providing residual predictive deviations which ranged from 0.9 to 1.5 as a function of the considered parameter.     

Near-infrared diffuse reflectance spectroscopy with sample spots and chemometrics for fast determination of bovine serum albumin in micro-volume samples

Near-infrared diffuse reflectance spectroscopy(NIRDRS) has attracted more and more attention in analyzing the components in samples with complex matrices.However,to apply this technique to micro-analysis,there are still some obstacles to overcome such as the low sensitivity and spectral overlapping associated with this approach.A method for fast determination of bovine serum albumin (BSA) in micro-volume samples was studied using NIRDRS with sample spots and chemometric techniques.10μL of sample spotted on a filter paper substrate was used for the spectral measurements. Quantitative analysis was obtained by partial least squares(PLS) regression with signal processing and variable selection.The results show that the correlation coefficient(R) between the predicted and the reference concentration is 0.9897 and the recoveries are in the range of 87.4%-114.4%for the validation samples in the concentration range of 0.61-8.10 mg/mL.These results suggest that the method has the potential to quickly measure proteins in micro-volume solutions.     

Use of near-infrared reflectance spectroscopy in predicting nitrogen,phosphorus and calcium contents in heterogeneous woody plant species

Near-infrared reflectance spectroscopy was applied to determine nitrogen (N), phosphorus (P) and calcium (Ca) content in leaf samples of 18 woody species. A total of 183 samples from mountain, riparian and dry areas from the Central–Western Iberian Peninsula were collected for this purpose. The wide intervals of variation observed in nutrient concentrations (6.6–45.0 g kg^–1 for N, 0.24–2.97 g kg^–1 for P, and 1.00–20.06 g kg^–1 for Ca) were due to the great heterogeneity of the samples. To develop calibration equations, multiple linear regression, and partial least-squares regression (PLSR) were used. In both cases, three mathematical transformations of the data were applied: log1/R and first and second derivatives. The best calibration statistics were obtained using PLSR and derivative transformations (second derivative for N and first derivative for P and Ca). The following coefficients of multiple determination (R²) and standard errors of cross validation were obtained: 0.99 and 0.93 for N, 0.94 and 0.15 for P, and 0.95 and 0.88 for Ca. In the external validation the standard errors of prediction obtained were 0.76 (N), 0.11 (P) and 0.60 (Ca).     

Quantitative determination of acyclovir in plasma by near infrared spectroscopy

The aim of this study was to assess the feasibility of near infrared spectroscopy (NIRS) for analysis of acyclovir in plasma. This methodology was based on the direct measurement of the transmission spectra of liquid samples and a multivariate calibration model (partial least squares, PLS) to determine the acyclovir concentration in plasma sample. The PLS calibration set was built on using the spiked samples by mixing different amounts of acyclovir. Concentration of acyclovir in the plasma samples was calculated employing a 6-factors PLS calibration using the spectral information in the range of 6102-5450 cm^− 1. The root mean square errors of prediction (RMSEP) found was 1.21 for acyclovir. The developed PLS-NIRS procedure allows the determination of 120 samples/h does not require any sample pretreatment and avoids waste generation.     

Use of polyurethane foam and 3-hydroxy-7,8-benzo-1,2,3,4-tetrahydroquinoline for determination of nitrite by diffuse reflectance spectroscopy and colorimetry

Polyurethane foam (PUF) has been suggested as a solid polymeric reagent for determination of nitrite. The determination is based on the diazotization of end toluidine groups of PUF with nitrite in acidic medium followed by coupling of polymeric diazonium cation with 3-hydroxy-7,8-benzo-1,2,3,4-tetrahydroquinoline. The intensely colored polymeric azodye formed in this reaction can be used as a convenient analytic form for the determination of nitrite by diffuse reflectance spectroscopy (c _min = 0.7 ng mL⁻¹). The possibility of using a desktop scanner, digital camera, and computer data processing for the numerical evaluation of the color intensity of the polymeric azodye has been investigated. A scanner and digital camera can be used for determination of nitrite with the same sensitivity and reproducibility as with diffuse reflectance spectroscopy. The approach developed was applied for determination of nitrite in river water and human exhaled breath condensate.     

偏最小二乘-近红外漫反射光谱法测定西米替丁药片

研究了应用偏最小二乘法(PLS)同近红外漫反射光谱法结合,对西米替丁片剂药品进行无损非破坏定量分析,建立了最佳的数学校正模型。讨论了波长间隔和主成分数对PLS定量预测能力的影响,预测了未知样品。     

Nondestructive and rapid determination of nitrate in soil, dry deposits and aerosol samples using KBr-matrix with diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS)

This paper presents the development of a new, rapid and precise analytical method for submicrogram levels of nitrate (NO₃⁻) in environmental samples like soil, dry deposit samples, and coarse and fine aerosol particles. The determination of submicrogram levels of nitrate is based on the selection of a quantitative analytical peak at 1385 cm⁻¹ among the three observed vibrational peaks and preparing calibration curves using different known concentrations of nitrate by diffuse reflectance Fourier transform infra red spectrometric (DRIFTS) technique. Pre-weighed and ground infrared (IR) grade KBr was used as substrate over which remarkably wide range of known concentration of nitrate was sprayed and dried. The dried sample was analyzed by DRIFTS and absorbance was measured. Eight calibration curves for four different concentration ranges of nitrate for absorbance as well as peak area were prepared for samples containing lower and relatively higher values of nitrate. The relative standard deviation (n = 8) for the nitrate concentration ranges, 0.05-40, 0.05-1.5, 1.5-25, 5-40 μg/0.1 g KBr were in the range 1.6-2.3% for the above calibration curves. The limit of detection (LOD) of the method is 0.07 μg g⁻¹ NO₃⁻. The F- and t-tests were performed to check the analytical quality assurance test. The noteworthy feature of the reported method is the noninterference of any of the associated cations. The results were compared with that of ion-chromatographic method with high degree of acceptability. The method can be applied in wide concentration ranges. The method is reagent less, nondestructive, very fast, repeatable, and accurate and has high sample throughput value.     

Studying the uptake of aniline vapor by active alumina through in-line monitoring a differential adsorption bed with near-infrared diffuse reflectance spectroscopy

Through non-invasive monitoring the uptake of aniline vapor by active alumina in a differential adsorption bed (DAB) with near-infrared diffuse reflectance spectroscopy (NIR-DRS), we have studied several features of the adsorption, including isotherm, kinetics and the chemical state of aniline molecules in aniline-alumina system. What is perhaps more important, since the information above is obtained synchronously, the proposed methodology could provide information about the type of adsorption (chemical or physical adsorption), the change of chemical state of aniline in the system during the adsorption process, whether the chemical adsorption and physical adsorption took place simultaneously, the rate of the chemical and physical adsorption, and so on.     

Rapid qualitative and quantitative evaluation of deer antler (Cervus elaphus) using near-infrared reflectance spectroscopy

Near-infrared (NIR) spectroscopy has been applied for both the qualitative and quantitative evaluation of the velvet deer antler. The most important parameters of determining the quality of velvet antler are the habitat (the country of origin) and ash content. Conventionally, the habitat is determined by examining the appearance of samples (by human eye), which lacks objectivity. Ash content is measured by an ignition method (measurement ash residue), however, it is too slow (4–5 h) to be used for rapid at-site measurement. Velvet antlers from three different habitats (China, New Zealand, and Russia), albeit the same species of Cervus elaphus, were evaluated in this paper. Soft independence modeling of class analogies (SIMCA) and partial least squares (PLS) were used for classification of habitat and determination of ash content. The habitat was successfully identified with over 80% accuracy, and the ash content prediction result using PLS regression showed good correlation with the reference ignition method with a standard error of prediction (SEP) of 1.264%.     

Simultaneous determination of mercury, lead and cadmium ions in water using near-infrared spectroscopy with preconcentration by thiol-functionalized magnesium phyllosilicate clay

Analysis of metal ions in environment is of great importance for evaluating the risk of heavy metal to public health and ecological safety. A method for simultaneous determination of metal ions in water samples was developed by using adsorption preconcentration and near-infrared diffuse reflectance spectroscopy (NIRDRS). A high capacity adsorbent of thiol-functionalized magnesium phyllosilicate, named Mg-MTMS, was prepared by co-condensation for preconcentration of Hg²⁺, Pb²⁺ and Cd²⁺ in aqueous solutions. After adsorbing the analytes onto the adsorbent, NIRDRS was measured and PLS models were established for fast and simultaneous quantitative prediction. Because the interaction of the ions with the functional group of the adsorbent can be reflected in the spectra, the models built with the samples prepared by river water were proven to be efficient enough for precise prediction. The determination coefficients (R²) of the validation samples for the three ions were found as high as 0.9197, 0.9599 and 0.9861, respectively. Furthermore, because the high adsorption efficiency of Mg-MTMS, the detected concentrations are as low as milligrams per liter for the three ions, and the concentration can be further reduced. Therefore, the feasibility of quantitative analysis metal ions in river water by NIRDRS is proven and this may provide a new way for fast simultaneous determination of trace metals in environmental waters.     

Influence of data pre-processing on the quantitative determination of the ash content and lipids in roasted coffee by near infrared spectroscopy

In near-infrared (NIR) measurements, some physical features of the sample can be responsible for effects like light scattering, which lead to systematic variations unrelated to the studied responses. These errors can disturb the robustness and reliability of multivariate calibration models. Several mathematical treatments are usually applied to remove systematic noise in data, being the most common derivation, standard normal variate (SNV) and multiplicative scatter correction (MSC). New mathematical treatments, such as orthogonal signal correction (OSC) and direct orthogonal signal correction (DOSC), have been developed to minimize the variability unrelated to the response in spectral data. In this work, these two new pre-processing methods were applied to a set of roasted coffee NIR spectra. A separate calibration model was developed to quantify the ash content and lipids in roasted coffee samples by PLS regression. The results provided by these correction methods were compared to those obtained with the original data and the data corrected by derivation, SNV and MSC. For both responses, OSC and DOSC treatments gave PLS calibration models with improved prediction abilities (4.9 and 3.3% RMSEP with corrected data versus 7.1 and 8.3% RMSEP with original data, respectively).     

Selectivity for glucose,glucose-6-phosphate,and pyruvate in ternary mixtures from the multivariate analysis of near-infrared spectra

Near-infrared spectroscopy offers the potential for direct in situ analysis in complex biological systems. Chemical selectivity is a critical issue for such measurements given the extent of spectral overlap of overtone and combination spectra. In this work, the chemical basis of selectivity is investigated for a set of multivariate calibration models designed to quantify glucose, glucose-6-phosphate, and pyruvate independently in ternary mixtures. Near-infrared spectra are collected over the combination region (4,000–5,000 cm⁻¹) for a set of 60 standard solutions maintained at 37 °C. These standard solutions are composed of randomized concentrations (0.5–30 mM) of glucose, glucose-6-phosphate, and pyruvate. Individual calibration models are constructed for each solute by using the partial least-squares (PLS) algorithm with optimized spectral range and number of latent variables. The resulting standard errors are 0.90, 0.72, and 0.32 mM for glucose, glucose-6-phosphate, and pyruvate, respectively. A pure component selectivity analysis (PCSA) demonstrates selectivity for each solute in these ternary samples. The concentration of each solute is also predicted for each sample by using a set of net analyte signal (NAS) calibration models. A comparison of the PLS and NAS calibration vectors demonstrates the chemical basis of selectivity for these multivariate methods. Selectivity of each PLS and NAS calibration model originates from the unique spectral features associated with the targeted analyte. Overall, selectivity is demonstrated for each solute with an order of sensitivity of pyruvate > glucose-6-phosphate > glucose. Figure Combination near-infrared spectroscopy allows selective analytical measurements for glucose, glucose-6-phosphate, and pyruvate in ternary mixtures owing to the uniqueness of the individual absorption spectra for each solute     

Simultaneous determination of glycerol and clavulanic acid in an antibiotic bioprocess using attenuated total reflectance mid infrared spectroscopy

Attenuated total reflectance mid infrared (ATR-MIR) spectroscopy is a potential technique for the near real-time monitoring of filamentous bioprocesses. Here we investigate the utility of ATR-MIR to monitor and predict concentrations of glycerol and product (clavulanic acid) in a complex antibiotic bioprocess. Streptomyces clavuligerus exhibits filamentous growth, thus, as biomass accumulates the process fluid becomes much more viscous, and develops pronounced non-Newtonian behaviour. A multivariate statistical technique, partial least square (PLS) has been used to develop models for the key analytes over the time course of the bioprocess. These models were then validated externally using unseen samples, not used in the original modelling exercise. Despite the heterogeneous nature of the bioprocess and the resulting complexity of the spectra, the models developed had high correlation coefficient values and low prediction error values of 0.302 and 0.009 for glycerol and clavulanic acid, respectively. The findings extend the use of ATR-MIR in these difficult fluids which are typical of filamentous industrial bioprocesses, and demonstrate the practical utility of the technique in the measurement of a range of analyte types, including those present at relatively modest levels compared to the concentrations of biomass and major substrates.