Recent applications in derivative ultraviolet/visible absorption spectrophotometry: 2009–2011

Application of Odd-Order Derivatives in Fourier Transform Nuclear Magnetic Resonance Spectroscopy toward Quantitative Deconvolution

When Fourier transform (FT) spectrum peaks are overlapped, primary maxima of odd-order derivatives can be used to evaluate their independent intensities. We studied the feasibility of higher odd-order derivatives on Lorentzian peak shape and magnitude peak shape. Simulation studies for FT nuclear magnetic resonance (NMR) spectroscopy demonstrated good results toward quantitative deconvolution of overlapping FT spectrum peaks. Although it is not so desirable to deconvolute special line shapes such as Gaussian, Voigt, and Tsallis profiles, the odd-order derivatives exhibit a bright future compared to even-order derivatives. An application example of practical NMR spectroscopy with ethylbenzene isomers is presented. White Gaussian noises were added to the simulated spectra at two different signal-to-noise ratios (20 and 40). Kauppinen's denoising and smoothing algorithms can effectively remove interference of the noise and help to have good deconvoluting results using the odd-order derivatives. We compared features of our approach with popular deconvolution sharpening algorithms and conducted a comparison study with Kauppinen's Fourier self-deconvolution. Our approach has a better dynamic range of peak intensities and is not sensitive to the sampling rates. Other common deconvolution methods are also discussed briefly.

Continuous wavelet transform for solving the problem of minor components in quantitation of pharmaceuticals: a case study on the mixture of ibuprofen and phenylephrine with its degradation products

The presence of minor components represents a challenging problem in spectrophotometric analysis of pharmaceuticals. If one component has a low absorptivity or present in a low concentration compared to the other components, this will hinder its quantitation by spectrophotometric methods. Continuous Wavelet Transform (CWT) as a signal processing technique was utilized to figure out a solution to such a problem. A comparative study was established between traditional derivative spectrophotometry (Numerical Differentiation, ND) and CWT to indicate the advantages and limitations of each technique and possibility of solving the problem of minor components. A mixture of ibuprofen (IBU) and phenylephrine (PHE) with its degradation products forming a ternary mixture was used for comparing the two techniques. The two techniques were applied on raw spectral data and on ratio spectra data resulting in four methods, namely ND, CWT, Derivative Ratio-Zero Crossing (DRZC) and Continuous Wavelet Transform Ratio-Zero Crossing (CWTR-ZC) methods. By comparing the results in laboratory prepared mixtures, CWT technique showed advantages in analysis of mixtures with minor components than ND. The proposed methods were validated according to the ICH guideline Q2(R1), where their linearity was established with correlation coefficient ranging from 0.9995 to 0.9999. The linearity was in the range 3-40 μg/mL for PHE in all methods, while for IBU it was 20-180 and 30-180 μg/mL in CWT and ND methods, respectively. The CWT methods were applied for quantitative determination of the drugs in their dosage form showing the ability of the methods to quantitate minor components in pharmaceutical formulations.

Gaussian Decomposition vs. Semiclassical Quantum Simulation: Obtaining the High-Order Derivatives of a Spectrum in the Case of Photosynthetic Pigment Optical Properties Studying

In this paper, a procedure for obtaining undistorted high derivatives (up to the eighth order) of the optical absorption spectra of biomolecule pigments has been developed. To assess the effectiveness of the procedure, the theoretical spectra of bacteriochlorophyll a, chlorophyll a, spheroidene, and spheroidenone were simulated by fitting the experimental spectra using the differential evolution algorithm. The experimental spectra were also approximated using sets of Gaussians to calculate the model absorption spectra. Theoretical and model spectra can be differentiated without smoothing (high-frequency noise filtering) to obtain high derivatives. Superimposition of the noise track on the model spectra allows us to obtain test spectra similar to the experimental ones. Comparison of the high derivatives of the model spectra with those of the test spectra allows us to find the optimal parameters of the filter, the application of which leads to minimal differences between the high derivatives of the model and test spectra. For all four studied pigments, it was shown that smoothing the experimental spectra with optimal filters makes it possible to obtain the eighth derivatives of the experimental spectra, which were close to the eighth derivatives of their theoretical spectra.

Nitrite Quantification by Second Derivative Chemometric Models Mitigates Natural Organic Matter Interferences under Chloraminated Drinking Water Distribution System Conditions

Nitrite (NO2-) production in chloraminated drinking water distribution systems (CDWDSs) is among the first bulk water indicators of a nitrification event and is typically quantified using ion chromatography (IC) or colorimetric techniques. NO2- can also be quantified using chemometric models (CMs) formulated using molar absorptivity (Ɛ) and/or ultraviolet absorbance (UVA) spectra, but concerns exist regarding their accuracy and generalizability because of varying source water natural organic matter (NOM), monochloramine (NH2Cl), bromide (Br-), and other species in CDWDSs. We demonstrate that the impact of NOM was mitigated in the second derivative molar absorptivity (Ɛ″) and UVA spectra (UVA″) between 200-300 nm and developed a generalizable CM for NO2- quantification. The Ɛ″+UVA″ CM was calibrated with daily NO2- measurements by IC from five biofilm annular reactor (BAR) tests with feedwater from Fayetteville, Arkansas, USA (FAY1, n = 275) and validated with eight BAR tests (n = 376) with another Fayetteville water (FAY2) and two waters from Dallas, Texas, USA (DAL1 and DAL2). The Ɛ″+UVA″ CM used Ɛ″ for NO2-, nitrate (NO3-), Br-, and NH2Cl at wavelengths of 213-, 225-, 229- and 253 nm, had an adjusted R2 of 0.992 for FAY1 and 0.987 for the other waters, and had a method detection limit (MDL) of 0.050 mg·L-1-N. NO2- challenge samples with three reconstituted NOM types and Br- indicated the Ɛ″+UVA″ CM was generalizable at NOM concentrations like those in the BAR tests (≤ 2.5 mg·L-1-C). The Ɛ″+UVA″ CM accurately simulated NO2- in field tests from two CDWDSs undergoing nitrification, including one with NOM at 3.5 mg·L-1-C, illustrating a practical application of the CM for identifying biological ammonia oxidation.

Rapid Detection of Different Types of Soil Nitrogen Using Near-Infrared Hyperspectral Imaging

Rapid and accurate determination of soil nitrogen supply capacity by detecting nitrogen content plays an important role in guiding agricultural production activities. In this study, near-infrared hyperspectral imaging (NIR-HSI) combined with two spectral preprocessing algorithms, two characteristic wavelength selection algorithms and two machine learning algorithms were applied to determine the content of soil nitrogen. Two types of soils (laterite and loess, collected in 2020) and three types of nitrogen fertilizers, namely, ammonium bicarbonate (ammonium nitrogen, NH4-N), sodium nitrate (nitrate nitrogen, NO3-N) and urea (urea nitrogen, urea-N), were studied. The NIR characteristic peaks of three types of nitrogen were assigned and regression models were established. By comparing the model average performance indexes after 100 runs, the best model suitable for the detection of nitrogen in different types was obtained. For NH4-N, R2p = 0.92, RMSEP = 0.77% and RPD = 3.63; for NO3-N, R2p = 0.92, RMSEP = 0.74% and RPD = 4.17; for urea-N, R2p = 0.96, RMSEP = 0.57% and RPD = 5.24. It can therefore be concluded that HSI spectroscopy combined with multivariate models is suitable for the high-precision detection of various soil N in soils. This study provided a research basis for the development of precision agriculture in the future.

In vitro Fourier transform infrared spectroscopic study of the effect of glycerol on the uptake of beclomethasone dipropionate in living respiratory cells

The quantification of drug in living cells is of increasing interest in pharmaceutical research because of its importance in understanding drug efficacy and toxicity. Label-free in situ measurement methods are advantageous for their ability to obtain chemical and time profiles without the need of labelling or extraction steps. We have previously shown that Fourier transform infrared (FTIR) spectroscopy has the potential to quantify drug in situ within living cells at micromolar level when a simple solution of drug was added to the medium. The purpose of this study was to demonstrate that the approach can evaluate more complex systems such as the effect of membrane modification by a formulation on drug uptakes. The inhaled corticosteroid, beclomethasone dipropionate (BDP), in Calu-3 respiratory epithelial cells in the absence and presence of glycerol, an excipient in some inhaled medicines was used as the model system. The FTIR method was first validated for limit of detection (LOD) and quantification (LOQ) according to published guidelines and the LOQ was found to be ∼ 20 μM, good enough to quantify BDP in the living cell. The uptake of BDP by living Calu-3 cells was found to be reduced in the presence of glycerol as expected due to the stiffening of the cell membrane by the presence of glycerol in the formulation. This study demonstrates the valuable analytical capability of live-cell FTIR to study the effect of formulation on drug transport in lungs and to evaluate drug availability to intracellular targets. We conclude that FTIR has potential to contribute widely at the frontier of live-cell studies.

Development of an Optical Method to Monitor Nitrification in Drinking Water

Nitrification is a common issue observed in chloraminated drinking water distribution systems, resulting in the undesirable loss of monochloramine (NH₂Cl) residual. The decay of monochloramine releases ammonia (NH₃), which is converted to nitrite (NO₂^-) and nitrate (NO₃^-) through a biological oxidation process. During the course of monochloramine decay and the production of nitrite and nitrate, the spectral fingerprint is observed to change within the wavelength region sensitive to these species. In addition, chloraminated drinking water will contain natural organic matter (NOM), which also has a spectral fingerprint. To assess the nitrification status, the combined nitrate and nitrite absorbance fingerprint was isolated from the total spectra. A novel method is proposed here to isolate their spectra and estimate their combined concentration. The spectral fingerprint of pure monochloramine solution at different concentrations indicated that the absorbance difference between two concentrations at a specific wavelength can be related to other wavelengths by a linear function. It is assumed that the absorbance reduction in drinking water spectra due to monochloramine decay will follow a similar pattern as in ultrapure water. Based on this criteria, combined nitrate and nitrite spectra were isolated from the total spectrum. A machine learning model was developed using the support vector regression (SVR) algorithm to relate the spectral features of pure nitrate and nitrite with their concentrations. The model was used to predict the combined nitrate and nitrite concentration for a number of test samples. Out of these samples, the nitrified sample showed an increasing trend of combined nitrate and nitrite productions. The predicted values were matched with the observed concentrations, and the level of precision by the method was ± 0.01 mg-N L^-1. This method can be implemented in chloraminated distribution systems to monitor and manage nitrification.

Near-Infrared Optical Spectroscopy In Vivo Distinguishes Subjects with Alzheimer's Disease from Age-Matched Controls

Background:

Medical imaging methods such as PET and MRI aid clinical assessment of Alzheimer’s disease (AD). Less expensive, less technically demanding, and more widely deployable technologies are needed to expand objective screening for diagnosis, treatment, and research. We previously reported brain tissue near-infrared optical spectroscopy (NIR) in vitro indicating the potential to meet this need.

Objective:

To determine whether completely non-invasive, clinical, NIR in vivo can distinguish AD patients from age-matched controls and to show the potential of NIR as a clinical screen and monitor of therapeutic efficacy.

Methods:

NIR spectra were acquired in vivo. Three groups were studied: autopsy-confirmed AD, control and mild cognitive impairment (MCI). A feature selection approach using the first derivative of the intensity normalized spectra was used to discover spectral regions that best distinguished “AD-alone” (i.e., without other significant neuropathology) from controls. The approach was then applied to other autopsy-confirmed AD cases and to clinically diagnosed MCI cases.

Results:

Two regions about 860 and 895 nm completely separate AD patients from controls and differentiate MCI subjects according to the degree of impairment. The 895 nm feature is more important in separating MCI subjects from controls (ratio-of-weights: 1.3); the 860 nm feature is more important for distinguishing MCI from AD (ratio-of-weights: 8.2).

Conclusion:

These results form a proof of the concept that near-infrared spectroscopy can detect and classify diseased and normal human brain in vivo. A clinical trial is needed to determine whether the two features can track disease progression and monitor potential therapeutic interventions.

Paving the Way to Food Grade Analytical Chemistry: Use of a Natural Deep Eutectic Solvent to Determine Total Hydroxytyrosol and Tyrosol in Extra Virgin Olive Oils

Extra virgin olive oil (EVOO) is well known for containing relevant amounts of healthy phenolic compounds. The European Food Safety Authority (EFSA) allowed a health claim for labelling olive oils containing a minimum amount of hydroxytyrosol (OHTyr) and its derivatives, including tyrosol (Tyr). Therefore, harmonized and standardized analytical protocols are required in support of an effective application of the health claim. Acid hydrolysis performed after extraction and before chromatographic analysis has been shown to be a feasible approach. Nevertheless, other fast, green, and easy methods could be useful for on-site screening and monitoring applications. In the present research, a natural deep eutectic solvent (NADES) composed of lactic acid and glucose was used to perform a liquid/liquid extraction on EVOO samples, followed by UV-spectrophotometric analysis. The spectral features of the extracts were related with the content of total OHTyr and Tyr, determined by the acid hydrolysis method. The second derivative of spectra allowed focusing on three single wavelengths (i.e., 299 nm, 290 nm, and 282 nm) significantly related with total OHTyr, total Tyr, and their sum, respectively. In particular, the sum of OHTyr and Tyr could be determined with a root mean square error of prediction of 29.5 mg kg⁻¹, while the limits of quantitation and detection were respectively 11.8 and 4.9 mg kg⁻¹. The proposed method, therefore, represents an easy screening tool, with the use of a green, food-derived solvent, and could be considered as an attempt to pave the way for food grade analytical chemistry.

Simultaneous Determination of Metal Ions in Zinc Sulfate Solution Using UV-Vis Spectrometry and SPSE-XGBoost Method

Excessive discharge of heavy metal ions will aggravate environment pollution and threaten human health. Thus, it is of significance to real-time detect metal ions and control discharge in the metallurgical wastewater. We developed an accurate and rapid approach based on the singular perturbation spectrum estimator and extreme gradient boosting (SPSE-XGBoost) algorithms to simultaneously determine multi-metal ion concentrations by UV–vis spectrometry. In the approach, the spectral data is expanded by multi-order derivative preprocessing, and then, the sensitive feature bands in each spectrum are extracted by feature importance (VI score) ranking. Subsequently, the SPSE-XGBoost model are trained to combine multi-derivative features and to predict ion concentrations. The experimental results indicate that the developed “Expand-Extract-Combine” strategy can not only overcome problems of background noise and spectral overlapping but also mine the deeper spectrum information by integrating important features. Moreover, the SPSE-XGBoost strategy utilizes the selected feature subset instead of the full-spectrum for calculation, which effectively improves the computing speed. The comparisons of different data processing methods are conducted. It outcomes that the proposed strategy outperforms other routine methods and can profoundly determine the concentrations of zinc, copper, cobalt, and nickel with the lowest RMSEP. Therefore, our developed approach can be implemented as a promising mean for real-time and on-line determination of multi-metal ion concentrations in zinc hydrometallurgy.

Second derivative analysis of synthesized spectra for resolution and identification of overlapped absorption bands of amino acid residues in proteins: Bromelain and ficin spectra in the 240-320 nm range

We establish the origin and formation of peaks in UV absorption spectra of proteins by applying the second derivative analysis to (i) spectra of the native protein, (ii) to its model spectra "synthesized" as a sum of partial free amino acid spectra and (iii) to absorption spectra of the free amino acids. We show that the bromelain peaks at 248.2, 253.2, 258.4 and 264.2 nm are due to phenylalanine maxima; the predictable peak at 279.6 nm (which is almost coincident with the extremum of the zero-order spectrum at 279.4 nm) is mainly due to tyrosine maximum, while the peaks at 274.6 and 290.6 nm are due to tryptophan maximum; 268.0 nm peak to the superposition of tyrosine and phenylalanine maxima, and 283.4 nm peak to the superposition of tyrosine and tryptophan maxima. Similar results are obtained for ficin: the peaks at 248.4, 253.0 and 258.8 nm are formed by the phenylalanine maxima, the predictable peak at 264.4 nm accords with the corresponding bromelain 264.2 nm peak; the 279.4 nm peak almost coincides with the zero order spectrum peak (279.6 nm), but it is expressed stronger than that of bromelain due to a different ratio of tyrosine to tryptophan side groups. The peaks at 273.4 and 290.6 nm are associated with tryptophan, the 268.0 nm peak being mainly due to tyrosine (and fractionally to phenylalanine); and the 283.8 nm peak belongs to tyrosine and, to a greater extent, to tryptophan. We demonstrate that the amino acid residues of tryptophan, tyrosine and phenylalanine undergo correspondingly the largest, intermediate and the lowest positive (red) wavelength shift in the zero-order protein absorption spectrum with respect to the model (synthesized) spectrum. The difference appearing in the positions of the bromelain and ficin absorption band peaks is determined by superposition of relative contributions from amino acid residues. This superposition is resulted from (i) linear combination of amino acid residues spectra and (ii) their different (non-uniform) wavelength shifts as functions of microenvironment of these residues' chromophores. The proposed approach to the analysis of the protein absorption spectra with the help of "synthesized" spectra can be transferred to other objects studied in analytical and organic chemistry of high molecular compounds containing monomer units with various chromophores.

The impact of the order of derivative spectra on the performance of pattern recognition methods. Classification of medicinal plants according to the phylum

Data pre-processing is an important strategy in chemometrics and related fields because in many cases the transformation of data has a great effect on the performance of the method (model). However, a careful examination of the literature clearly points out that only very few systematic studies are dedicated to the effect of the derivative spectra on the performance of the pattern recognition methods. This comprehensive study compares the impact of the order of derivative spectra and other data pre-processing procedures (normalization and standardization) on the performance of cluster analysis, principal component analysis and discriminant analysis applied for characterization and classification of medicinal plants according to their phylum using UV spectra. The efficiency of the pre-processing methods was estimated by comparing the accuracy of classification and prediction measured by internal cross-validation. Derivatization method (1st order) resulted in the best classification (100%) of medicinal plants according to their phylum (Pteridophyte, Magnoliophyte and Spermatophyte) as compared to other pre-processing methods (normalized spectra-71.4%, standardized spectra-76.2% and original spectra-78.6%).

Analytical and pharmacological validation of the quantification of phenol red in a mouse model: An optimized method to evaluate expectorant drugs

INTRODUCTION

The evaluation of expectorant activity has been extensively studied in murine models, involving the secretion of phenol red in the trachea or bronchus to estimate the secretory capacity of lower airway mucosa. However, differences in the experimental protocols of several studies evidenced the need of to standardize the quantification of phenol red in the bronchoalveolar fluid (BALF).

METHODS

The analytical methodology for the quantification of phenol red in the BALF was optimized by investigation of pH influence, quantity of the alkali agent added and appropriate wavelength for quantification of phenol red by UV-VIS spectroscopy. Different phenol red suspensions (0.05, 0.5, 1.25, 2.5 and 5%) were prepared and administered intraperitoneally in mice at doses 5, 25, 50, 250 or 500 mg/kg.

RESULTS

It was shown that phenol red should be used at dose 500 mg/kg and intraperitoneal administration should be performed from a suspension at 1.25% (w/v). Furthermore, the alkalinizing agent of choice would be NaOH (0.1 M). The pharmacological validation of the analytical method showed that ambroxol (30, 60 or 120 mg/kg), guaifenesin (100 mg/kg), NH₄Cl (2000 mg/kg) or salbutamol (4 mg/kg) can be used as positive controls.

DISCUSSION

The phenol red quantification in the BALF is a rapid and low cost assay for the discovery of new expectorant drugs. Thus, it was proposed a standardization of the analytical and pharmacological methods to ensure the reliability of BALF processing and reproducibility of phenol red quantification for data analysis.

Mid-Infrared Tunable Laser-Based Broadband Fingerprint Absorption Spectroscopy for Trace Gas Sensing: A Review

The vast majority of gaseous chemical substances exhibit fundamental rovibrational absorption bands in the mid-infrared spectral region (2.5–25 μm), and the absorption of light by these fundamental bands provides a nearly universal means for their detection. A main feature of optical techniques is the non-intrusive in situ detection of trace gases. We reviewed primarily mid-infrared tunable laser-based broadband absorption spectroscopy for trace gas detection, focusing on 2008–2018. The scope of this paper is to discuss recent developments of system configuration, tunable lasers, detectors, broadband spectroscopic techniques, and their applications for sensitive, selective, and quantitative trace gas detection.

Chemometric simultaneous determination of Sofosbuvir and Ledipasvir in pharmaceutical dosage form

Partial least squares (PLS), different families of continuous wavelet transform (CWT), and first derivative spectrophotometry (DS) techniques were studied for quantification of Sofosbuvir (SFB) and Ledipasvir (LDV) simultaneously without separation step. The components were dissolved in Acetonitrile and the spectral behaviors were evaluated in the range of 200 to 400nm. The ultraviolet (UV) absorbance of LDV exhibits no interferences between 300 and 400nm and it was decided to predict the LDV amount through the classic spectrophotometry (CS) method in this spectral region as well. Data matrix of concentrations and calibrated models were developed, and then by applying a validation set the accuracy and precision of each model were studied. Actual concentrations versus predicted concentrations plotted and good correlation coefficients by each method resulted. Pharmaceutical dosage form was quantified by developed methods and the results were compared with the High Performance Liquid Chromatography (HPLC) reference method. Analysis Of Variance (ANOVA) in 95% confidence level showed no significant differences among methods.

UV Absorption Spectroscopy in Water-Filled Antiresonant Hollow Core Fibers for Pharmaceutical Detection

Due to a worldwide increased use of pharmaceuticals and, in particular, antibiotics, a growing number of these substance residues now contaminate natural water resources and drinking supplies. This triggers a considerable demand for low-cost, high-sensitivity methods for monitoring water quality. Since many biological substances exhibit strong and characteristic absorption features at wavelengths shorter than 300 nm, UV spectroscopy presents a suitable approach for the quantitative identification of such water-contaminating species. However, current UV spectroscopic devices often show limited light-matter interaction lengths, demand sophisticated and bulky experimental infrastructure which is not compatible with microfluidics, and leave large fractions of the sample analyte unused. Here, we introduce the concept of UV spectroscopy in liquid-filled anti-resonant hollow core fibers, with large core diameters and lengths of approximately 1 m, as a means to overcome such limitations. This extended light-matter interaction length principally improves the concentration detection limit by two orders of magnitude while using almost the entire sample volume-that is three orders of magnitude smaller compared to cuvette based approaches. By integrating the fibers into an optofluidic chip environment and operating within the lowest experimentally feasible transmission band, concentrations of the application-relevant pharmaceutical substances, sulfamethoxazole (SMX) and sodium salicylate (SS), were detectable down to 0.1 µM (26 ppb) and 0.4 µM (64 ppb), respectively, with the potential to reach significantly lower detection limits for further device integration.

Design of novel and modified dual optode membrane based on carbon dots for both ultratrace copper(ii) and cobalt(ii): derivative spectrophotometric and central composite design study

A selective, accurate and highly sensitive optical chemical sensor (optode) for the simultaneous determination of copper(ii) and cobalt(ii) without any prior separation or purification ion sensing was developed.

Highly effective adsorption of xanthene dyes (rhodamine B and erythrosine B) from aqueous solutions onto lemon citrus peel active carbon: characterization, resolving analysis, optimization and mechanistic studies

Erythrosine B (EB) and rhodamine B (RB) dyes that were selected as model of xanthene dyes for dye adsorption from aqueous solution, were removed effectively.

Direct DOC and nitrate determination in water using dual pathlength and second derivative UV spectrophotometry

UV spectrophotometry is largely used for water and wastewater quality monitoring. The measurement/estimation of specific and aggregate parameters such as nitrate and dissolved organic carbon (DOC) is possible with UV spectra exploitation, from 2 to multi wavelengths calibration. However, if nitrate determination from UV absorbance is known, major optical interferences linked to the presence of suspended solids, colloids or dissolved organic matter limit the relevance of UV measurement for DOC assessment. A new method based on UV spectrophotometric measurement of raw samples (without filtration) coupling a dual pathlength for spectra acquisition and the second derivative exploitation of the signal is proposed in this work. The determination of nitrate concentration is carried out from the second derivative of the absorbance at 226 nm corresponding at the inflexion point of nitrate signal decrease. A short optical pathlength can be used considering the strong absorption of nitrate ion around 210 nm. For DOC concentration determination the second derivative absorbance at 295 nm is proposed after nitrate correction. Organic matter absorbing slightly in the 270-330 nm window, a long optical pathlength must be selected in order to increase the sensitivity. The method was tested on several hundred of samples from small rivers of two agricultural watersheds located in Brittany, France, taken during dry and wet periods. The comparison between the proposed method and the standardised procedures for nitrate and DOC measurement gave a good adjustment for both parameters for ranges of 2-100 mg/L NO3 and 1-30 mg/L DOC.

A fully battery-powered inexpensive spectrophotometric system for high-sensitivity point-of-care analysis on a microfluidic chip

A cost-effective b[combining low line]a[combining low line]ttery-powered s[combining low line]pectrophotometric s[combining low line]ystem (BASS) was developed for quantitative point-of-care (POC) analysis on a microfluidic chip. By using methylene blue as a model analyte, we first compared the performance of the BASS with a commercial spectrophotometric system, and further applied the BASS for loop-mediated isothermal amplification (LAMP) detection and subsequent quantitative nucleic acid analysis which exhibited a comparable limit of detection to that of Nanodrop. Compared to the commercial spectrophotometric system, our spectrophotometric system is lower-cost, consumes less reagents, and has higher detection sensitivity. Most importantly, it does not rely on external power supplies. All these features make our spectrophotometric system highly suitable for a variety of POC analyses, such as field detection.

Continuous Wavelet Transform, a powerful alternative to Derivative Spectrophotometry in analysis of binary and ternary mixtures: A comparative study

A comparative study was established between two signal processing techniques showing the theoretical algorithm for each method and making a comparison between them to indicate the advantages and limitations. The methods under study are Numerical Differentiation (ND) and Continuous Wavelet Transform (CWT). These methods were studied as spectrophotometric resolution tools for simultaneous analysis of binary and ternary mixtures. To present the comparison, the two methods were applied for the resolution of Bisoprolol (BIS) and Hydrochlorothiazide (HCT) in their binary mixture and for the analysis of Amlodipine (AML), Aliskiren (ALI) and Hydrochlorothiazide (HCT) as an example for ternary mixtures. By comparing the results in laboratory prepared mixtures, it was proven that CWT technique is more efficient and advantageous in analysis of mixtures with severe overlapped spectra than ND. The CWT was applied for quantitative determination of the drugs in their pharmaceutical formulations and validated according to the ICH guidelines where accuracy, precision, repeatability and robustness were found to be within the acceptable limit.

Inter-laboratory verification of European pharmacopoeia monograph on derivative spectrophotometry method and its application for chitosan hydrochloride

Inter-laboratory verification of European pharmacopoeia (EP) monograph on derivative spectrophotometry (DS) method and its application for chitosan hydrochloride was carried out on two generation of instruments (earlier GBC Cintra 20 and current technology TS Evolution 300). Instruments operate with different versions of Savitzky-Golay algorithm and modes of generating digital derivative spectra. For resolution power parameter, defined as the amplitude ratio A/B in DS method EP monograph, comparable results were obtained only with algorithm's parameters smoothing points (SP) 7 and the 2nd degree polynomial and those provided corresponding data with other two modes on TS Evolution 300 Medium digital indirect and Medium digital direct. Using quoted algorithm's parameters, the differences in percentages between the amplitude ratio A/B averages, were within accepted criteria (±3%) for assay of drug product for method transfer. The deviation of 1.76% for the degree of deacetylation assessment of chitosan hydrochloride, determined on two instruments, (amplitude (1)D202; the 2nd degree polynomial and SP 9 in Savitzky-Golay algorithm), was acceptable, since it was within allowed criteria (±2%) for assay deviation of drug substance, for method transfer in pharmaceutical analyses.

Improved quantitative analysis of spectra using a new method of obtaining derivative spectra based on a singular perturbation technique

Spectroscopy is often applied when a rapid quantitative analysis is required, but one challenge is the translation of raw spectra into a final analysis. Derivative spectra are often used as a preliminary preprocessing step to resolve overlapping signals, enhance signal properties, and suppress unwanted spectral features that arise due to non-ideal instrument and sample properties. In this study, to improve quantitative analysis of near-infrared spectra, derivatives of noisy raw spectral data need to be estimated with high accuracy. A new spectral estimator based on singular perturbation technique, called the singular perturbation spectra estimator (SPSE), is presented, and the stability analysis of the estimator is given. Theoretical analysis and simulation experimental results confirm that the derivatives can be estimated with high accuracy using this estimator. Furthermore, the effectiveness of the estimator for processing noisy infrared spectra is evaluated using the analysis of beer spectra. The derivative spectra of the beer and the marzipan are used to build the calibration model using partial least squares (PLS) modeling. The results show that the PLS based on the new estimator can achieve better performance compared with the Savitzky-Golay algorithm and can serve as an alternative choice for quantitative analytical applications.

Transmission FTIR derivative spectroscopy for estimation of furosemide in raw material and tablet dosage form

A Fourier transform infrared derivative spectroscopy (FTIR-DS) method has been developed for determining furosemide (FUR) in pharmaceutical solid dosage form. The method involves the extraction of FUR from tablets with N,N-dimethylformamide by sonication and direct measurement in liquid phase mode using a reduced path length cell. In general, the spectra were measured in transmission mode and the equipment was configured to collect a spectrum at 4 cm⁻¹ resolution and a 13 s collection time (10 scans co-added). The spectra were collected between 1400 cm⁻¹ and 450 cm⁻¹. Derivative spectroscopy was used for data processing and quantitative measurement using the peak area of the second order spectrum of the major spectral band found at 1165 cm⁻¹ (SO₂ stretching of FUR) with baseline correction. The method fulfilled most validation requirements in the 2 mg/mL and 20 mg/mL range, with a 0.9998 coefficient of determination obtained by simple calibration model, and a general coefficient of variation <2%. The mean recovery for the proposed assay method resulted within the (100±3)% over the 80%–120% range of the target concentration. The results agree with a pharmacopoeial method and, therefore, could be considered interchangeable.

UV spectrophotometric simultaneous determination of paracetamol and ibuprofen in combined tablets by derivative and wavelet transforms

The application of first-order derivative and wavelet transforms to UV spectra and ratio spectra was proposed for the simultaneous determination of ibuprofen and paracetamol in their combined tablets. A new hybrid approach on the combined use of first-order derivative and wavelet transforms to spectra was also discussed. In this application, DWT (sym6 and haar), CWT (mexh), and FWT were optimized to give the highest spectral recoveries. Calibration graphs in the linear concentration ranges of ibuprofen (12–32 mg/L) and paracetamol (20–40 mg/L) were obtained by measuring the amplitudes of the transformed signals. Our proposed spectrophotometric methods were statistically compared to HPLC in terms of precision and accuracy.

UV spectrophotometric simultaneous determination of cefoperazone and sulbactam in pharmaceutical formulations by derivative, Fourier and wavelet transforms

Signal processing methods based on the use of derivative, Fourier and wavelet transforms were proposed for the spectrophotometric simultaneous determination of cefoperazone and sulbactam in powders for injection. These transforms were successfully applied to UV spectra and ratio spectra to find suitable working wavelengths. Wavelet signal processing was proved to have distinct advantages (i.e. higher peak intensity obtained, additional smooth function and scaling factor process eliminated) over derivative and Fourier transforms. Especially, a better resolution of spectral overlapping bands was obtained by the use of double signal transform in the sequences such as (i) spectra pre-processed by Fractional Wavelet Transform and subsequently subjected to Continuous Wavelet Transform or Discrete Wavelet Transform, and (ii) derivative - wavelet transforms combined. Calibration graphs for cefoperazone and sulbactam were recorded for the range 10-35 mg/L. Good accuracy and precision were reported for all proposed methods by analyzing synthetic mixtures of cefoperazone and sulbactam. Furthermore, these methods were statistically comparable to RP-HPLC.