Digital image colorimetry for determination of ethanol in exhaled breath condensate.

Aim: This study aimed to develop a colorimetric approach for quantifying ethanol using smartphone image analysis. Method: This research presents a straightforward smartphone-based colorimetric sensor that efficiently measures ethanol levels in exhaled breath condensate (EBC) samples. The process involved changing the acidic dichromate color in an ethanolic solution, followed by image analysis. Results: The results showed that this method was able to estimate ethanol concentrations in the range of 300-1500 and 1600-8000 µg ml-1 in EBC. Conclusion: This study was a follow-up study on the previous work published for the determination of ethanol in EBC samples and highlights the potential benefits of using digital images and smartphone applications for ethanol determination in biological samples.

A smartphone digital image colorimetric method based on nanoparticles for determination of lamotrigine.

Aim: A colorimetric approach for quantification of lamotrigine using spectrophotometric and smartphone image analysis is described in this study. Methods: For full optimization and validation procedures, UV-visible spectroscopy was used, and image analysis was carried out with the help of an app (PhotoMetrix PRO®). Then, as a multivariate calibration method, parallel factor analysis was used for data analysis. Results: The results demonstrated the capacity of these methods to estimate lamotrigine concentrations in the range of 0.1-7.0 µg.ml-1 in exhaled breath condensate, indicating the value of using digital images and smartphone applications in combination with chemometric tools. Conclusion: The image analysis can be superior for its fast and reliable lamotrigine analysis in biological samples.

A colorimetric assay and MCR-ALS analysis of the peroxidase-like activity of poly (N-phenylglycine) functionalized with polyethylene glycol (PNPG-PEG) nanozyme for the determination of dopamine.

This report describes, for the first time, the coupling of UV-visible spectroscopy with multivariate curve resolution-alternative least-squares (MCR-ALS) algorithm to study peroxidase-like catalytic reaction of polyethylene glycol-functionalized poly (N-phenyl glycine) (PNPG-PEG) as an efficient and intrinsic peroxidase mimic activity (PMA) class of conducting organic polymer for selective detection of dopamine (DA) in the PNPG-PEG + TMB + H2O2 reaction system. PNPG-PEG was produced by means of a chemical route using ammonium persulphate (APS) as an oxidant agent of N-phenyl glycine monomer. The chemical composition, morphology, and thermal behavior of PNPG-PEG were examined by various instrumental techniques. PNPG-PEG exhibited significant peroxidase-mimic activity to catalyze the oxidation 3,3',5,5'- tetramethylbenzidine (TMB) substrate to oxidized TMB (oxTMB). The qualitative and quantitative determination of the oxidized TMB can easily be detected by the naked-eye and the recorded UV-vis absorbance spectra at 652 nm, respectively. Owing to the superior peroxidase-mimic activity of PNPG-PEG, the colorimetric detection of dopamine was successfully achieved at pH 4.0. Under optimal conditions, acceptable linear dependency was recorded in the concentration range of 5.1-125.0 µM, with a limit of detection (LOD) and limit of quantification (LOQ) equal to 4.6 µM and 13.8 µM (S/N = 3), respectively. Furthermore, this colorimetric assay was successfully used for quantitative analysis of dopamine in fetal bovine serum (FBS) and horse serum (HS) samples with recoveries in the range of 97-105% and 100-122%, respectively. After resolving the bilinear data matrix using MCR-ALS, three chemical components were found for different concentrations and pure spectral profiles. Based on the resolved profiles, the presence of free, slightly penetrated, and majorly penetrated TMB molecules entering the polymeric structure can be easily detected using MCR-ALS as an available statical method without any complex separation instruments. This peroxidase mimetic nanozyme as a visual, simple, low-cost, sensitive, and reproducible colorimetric platform can provide great potential applications in the monitoring and diagnosis of dopamine-related diseases.

Colorimetric assay for the detection of dopamine using bismuth ferrite oxide (Bi2Fe4O9) nanoparticles as an efficient peroxidase-mimic nanozyme.

This work describes the preparation of ternary bismuth ferrite oxide nanoparticles (Bi2Fe4O9 NPs) with an enzyme mimetic activity for dopamine (DA) qualitative and quantitative detection. Bi2Fe4O9 NPs were prepared using a facile, low cost, and one-pot hydrothermal treatment. The chemical composition, morphology, and optical properties of Bi2Fe4O9 nanozyme were characterized using different techniques such as Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction pattern (XRD), X-ray photoelectron spectroscopy (XPS), thermo-gravimetric analysis (TGA), dynamic light scattering (DLS), field-emission scanning electron microscopy (FESEM) imaging, FESEM-energy dispersive X-ray spectroscopy (EDS), UV-vis absorption, and fluorescence emission spectroscopy. Bi2Fe4O9 NPs were utilized to catalyze the oxidation of a typical chromogenic peroxidase substrate, 3,3',5,5'-tetramethylbenzidine (TMB), to form the blue-colored oxidized product (oxTMB), in the presence of hydrogen peroxide (H2O2). All reactions occurred in acetate buffer solution (pH 3.5) to generate hydroxyl radicals (•OH) and the kinetics were followed by UV-vis absorbance at 654 nm. The steady-state kinetic parameters were obtained from the Michaelis-Menten equation and exhibited a good catalytic efficiency of Bi2Fe4O9 NPs as enzyme mimetics. Michaelis-Menten constant (Km) values were estimated as 0.07 and 0.73 mM for TMB and H2O2, respectively. The presented method is efficient, rapid, cost-effective, and sensitive for the colorimetric detection of dopamine with a linear range (LR) from 0.15 to 50 µM and a detection limit (LOD) of 51 nM. The proposed colorimetric sensor was successfully applied for the detection of different concentrations of dopamine in spiked fetal bovine serum (FBS) and horse serum (HS) samples. It is anticipated that Bi2Fe4O9 nanozyme holds great potential in biomedical analysis and diagnostic applications of dopamine-related diseases.

Metabolomics approach to study in vivo toxicity of graphene oxide nanosheets.

Although graphene oxide (GO) nanosheets are widely used in different fields, the mechanism of their toxicity remains relatively unknown. NMR-based metabolomics was used to study in vivo time and dose-dependent toxicity of GO nanosheets in mice. Sixty serum samples from mice in four different time intervals including 24 and 72 h and 7 and 21 days after injection of 0-, 1-, and 10-mg/kg b.w. were analyzed based on 1 HNMR spectra of each sample and multivariate methods. In comparison with the control group, 12 changed metabolites were identified in GO nanosheet-treated mice groups. These metabolites are involved in steroid hormone biosynthesis and steroid biosynthesis pathways. It was seen that the time factor is more important than the dose factor and the groups were separated in a time direction, completely. We found that GO nanosheets has toxicity and can affect steroidal hormones. However, this study shows that after 21 days, the treated groups regardless of their GO nanosheet dose are very close to the control group. This means that in one step exposure to GO nanosheets, their toxicity diminished after 21 days.

A facile and high-sensitive bio-sensing of the V617F mutation in JAK2 gene by GSH-CdTe-QDs FRET-based sensor.

This study aimed to directly detect the V617F point mutation of the Janus kinase 2 (JAK2) gene in the target DNA using a FRET-based biosensor. The water-soluble GSH-CdTe-QDs were synthesized by a one-step process, then GSH-QD conjugated to the termini amino-modified oligonucleotides target via carboxylic groups on the QD surface. The prepared QDs-DNA biosensor was applied in the quantitative and rapid detection of V617F mutation with a detection limit of 3 × 10-9 mol L-1 based on the FRET mechanism. In other words, detecting the V617F mutation by bio-sensing technology would be much simpler, cheaper, time-saving, highly sensitive, and more convenient than molecular diagnostic tools. Furthermore, the nano-biosensor was applied to detect the V617F mutation in clinical samples compared to the common ARMS-PCR (Amplification Refractory Mutation System-Polymerase Chain Reaction) standard method. The results revealed that the GSH-capped biosensors would be effective for V617F mutation detection in samples distinguished with satisfactory analytical outcomes. Therefore, the designed fluorescence nanoprobe is suitable for the specific detection of V617F mutation of the JAK2 gene in clinical samples.

Inulin-Coated Iron Oxide Nanoparticles: A Theranostic Platform for Contrast-Enhanced MR Imaging of Acute Hepatic Failure.

The present study introduces a superparamagnetic nanocomposite, Fe-Si-In, as a T2 magnetic resonance imaging (MRI) contrast agent with a core of iron oxide nanoparticles and a nonporous silica inner shell/carboxymethyl inulin outer shell. Due to its core/shell properties, the structure characterization, biocompatibility, and performance in MRI, as well as its potential as a drug delivery system, were thoroughly evaluated. The results have shown that the synthesized nanocomposite possesses excellent biocompatibility and acceptable magnetization (Ms = 20 emu g-1). It also has the potential to be a nanocarrier for drug delivery purposes, as evidenced by the results of curcumin administration studies. The developed nanocomposite has shown excellent performance in MRI, while the in vitro relaxivity measurements reveal a stronger T2 relaxivity (r2 = 223.2 ms) compared to the commercial samples available in the market. Furthermore, the in vivo MRI studies demonstrate an excellent contrast between injured livers and normal ones in rats which again upholds the high performance of Fe-Si-In in MRI diagnostics.

PVP Surface-protected silica coated iron oxide nanoparticles for MR imaging application.

This paper proposed an engineered mesoporous silica-coated Fe3O4 nanoparticle, PVPMSFe, prepared by a sol-gel/surface-protected etching mechanism as an MRI T2 contrast agent. To this end, the structural characterization of the nanocomposite was performed by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) method, VSM, thermogravimetric analysis (TGA), TEM, FESEM, and energy-dispersive X-ray scanning electron microscopy (EDS). The findings show that the synthesized nanocomposite has a mesoporous structure with an average particle size of 11.8 nm and excellent magnetization properties. The biocompatibility of PVPMSFe was investigated by MTT assay and hemolysis assay of red blood cells and the results indicate that PVPMSFe has favorable biocompatibility. Besides, the effect of PVPMSFe was assessed with MRI relaxivity measurement (T2 signal). Regarding the in vitro MRI relaxivity measurements outputs (r2=144.4), PVPMSFe can attenuate the T2 signal of MRI, perfectly which makes it an efficient T2 contrast agent.

PARAFAC study of L-cys@CdTe QDs interaction to BSA, cytochrome c and trypsin: An approach through electrostatic and covalent bonds.

Utilizing fluorescence spectroscopy, non-covalent and covalent interactions of L-cys@CdTe quantum dots to bovine serum albumin (BSA), cytochrome c and trypsin were investigated. L-cys@CdTe QDs with the emission maximum at 530 nm and an average diameter of 2.6 nm were synthesized in the aqueous medium. Formaldehyde, N-(3-dimethylaminopropyl)-N-ethylcarbodiimide hydrochloride (EDC) with N-hydroxysuccinimide (NHS), and glutaraldehyde was applied as cross-linkers. In the case of both electrostatic and covalent strategies PARAFAC, as a powerful multi-way chemometrics technique, was utilized to analyze fluorescence excitation-emission (EEM) spectra. For non-covalent and covalent bonding, two and three significant components composed the PARAFAC models. Resolved EEM shows that in the presence of formaldehyde, a new component with an emission peak similar to BSA was obtained. Using EDC-NHS cross-linker, the fluorescence peak of the newly formed component was in a distinct wavelength with similar emission intensity, compared to L-cys@CdTe QDs and BSA. Employing glutaraldehyde, a distinguished component was easily detected at emission wavelengths higher than that of L-cys@CdTe QDs and proteins. It was concluded that the choice of cross-linker is a critical step to create different emission spectra when dealing with nano-bio-conjugations. This study shows that glutaraldehyde cross-linker leads to increase sensitivity, selectivity, and accuracy of protein analysis.

NMR-based plasma metabolic profiling in patients with unstable angina.

OBJECTIVES: Unstable angina (UA) is a form of the acute coronary syndrome (ACS) that affects more than a third of the population before age 70. Due to the limitations of diagnostic tests, appropriate identification of UA is difficult. In this study, we proceeded to investigate metabolite profiling in UA patients compared with controls to determine potential candidate biomarkers. MATERIALS AND METHODS: Ninety-four plasma samples from UA and 32 samples from controls were analyzed based on 1H NMR spectroscopy. The raw data were processed, analyzed, and subjected to partial least squares-discrimination analysis (PLS-DA), a supervised classification method with a good separation of control and UA patients was observed. The most important variables (VIP) ≥1 were selected and submitted to MetaboAnalyst pathway enrichment to identify the most important ones. RESULTS: We identified 17 disturbed metabolites in UA patients in comparison with the controls. These metabolites are involved in various biochemical pathways such as steroid hormone biosynthesis, aminoacyl-tRNA biosynthesis, and lysine degradation. Some of the metabolites were deoxycorticosterone, 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, and 2-methoxyestrone. In order to determine test applicability in diagnosing UA, a diagnostic model was further created using the receiver operator characteristic (ROC) curve. The areas under the curve (AUC), sensitivity, specificity, and precision were 0.87, 90%, 65%, and 91%, respectively, for diagnosing of UA. CONCLUSION: These metabolites could not only be useful for the diagnosis of UA patients but also provide more information for further deciphering of the biological processes of UA.

Effects of green synthesis of sulfur nanoparticles from Cinnamomum zeylanicum barks on physiological and biochemical factors of Lettuce (Lactuca sativa).

In this study, the effect of green synthesized sulfur nanoparticle (SNP) at different concentration (0, 0.01, 0.1, 1 and 10 mg/ml) on some physiological, phytochemical and biochemical traits of lettuce plants was investigated. For the first time, SNP were green synthesized using Cinnamomum zeylanicum barks extract. Our results indicated that the treatment of lettuce plants with 1 mg/ml of SNP improved the growth and photosynthetic parameters of lettuce plants than related control. Some other physiological parameters such as proline, glycine betaine and soluble sugars levels along with some phytochemical parameters like anthocyanin, total phenol, flavonoids and tannin contents were enhanced after treatment of the plants with same concentration of SNP. On the other hand, specific activity of antioxidant enzymes (catalase, ascorbate peroxidase and polyphenol oxidase) and stress markers level, MDA and H2O2 were reduced in the same treated lettuce plants. However, a concentration of 10 mg/ml of SNP exhibited toxicity on lettuce plants with inducing oxidative stress markers (H2O2 and MDA) and consequently reducing plant growth and biomass. This oxidative stress tend to diminish some physiological, phytochemical and biochemical parameters in treated lettuce plants. Overall, it can be concluded that the green synthesis SNP at an optimal concentration of 1 mg/ml improved physiological parameters in the lettuce plants making them potent to tolerate stressful conditions. However, higher concentration of SNP (10 mg/ml) indicated toxic effects on all of the physiological parameters.

Metabolomics in early detection and prognosis of acute coronary syndrome.

Acute coronary syndrome (ACS) is one of the most dangerous types of coronary heart disease (CHD) and contributes to significant mortality and morbidity worldwide. Outcomes in these patients remain a challenge despite improvements in diagnosis and treatment. Risk stratification continues to be problematic and the identification of novel predictors is crucial for improved outcomes. As such, there is a strong need for the development of novel analytical methods as well as the characterization of better predictive and prognostic biomarkers to enable more personalized treatment. Metabolite profile analysis may greatly assist in interpreting altered pathway dynamics, especially when combined with other 'omics' technologies such as transcriptomics and proteomics. In this review, we describe ACS pathophysiology and recent advances in the role of metabolomics in the diagnosis and the molecular pathogenesis of ACS. We briefly describe key technologies used in metabolomics research and statistical approaches for data reduction and pathway analysis and discuss their application to CHD.

Optimization of Olive Oil-Based Nanoemulsion Preparation for Intravenous Drug Delivery.

A seven-factor Box-Behnken design was used for the optimized development of an olive oil-based nanoemulsion (NE) intended for intravenous drug delivery. The independent variables of olive oil concentration, tween 80 concentration, span 80 concentration, rate of adding of oil in aqueous phase, homogenization speed, homogenization time, and preparation temperature, were used as inputs of the factorial design. The response variables were mean droplet diameter, zeta potential (ZP), and polydispersity index (PDI). A quadratic, linear and 2FI model was established to predict the responses based on the multivariate model developed. The obtained experimental responses were in good agreement with predicted values from expert design, showing residual standard error (RSE) less than 10 %. TEM revealed that the optimized nanoemulsions were almost spherical with mean diameter about 40 nm. The developed formulation showed only about 4.6% of hemolysis and was safe for intravenous delivery. As well, the other in vitro characterization of the optimal nanoemulsion such as viscosity, percent transmittance, physical stability, and solubility study revealed it to be promising as an intravenous drug delivery system.

The assessment of metabolite alteration induced by -OH functionalized multi-walled carbon nanotubes in mice using NMR-based metabonomics.

Introduction: There is a fundamental need to characterize multiwalled carbon nanotubes (MWCNTs) toxicity to guarantee their safe application. Functionalized MWCNTs have recently attracted special interest in order to enhance biocompatibility. The aim of the current work was to study the underlying toxicity mechanism of the -OH-functionalized MWCNTs (MWCNTs-OH), using the powerful NMR-based metabonomics technique. Methods: Following intraperitoneal single-injection of mice with 3 doses of MWCNTs-OH and one control, samples were collected at four time points during 22-days for NMR, biochemistry, and histopathology analysis. Metabolome profiling and pathway analysis were implemented by chemometrics tools and metabolome databases. Results: Based on the 1H-NMR data, metabolic perturbation induced by MWCNTs-OH were characterized by altered levels of steroid hormones, including elevated androgens, estrogens, corticosterone, and aldosterone. Moreover, increased L-lysine, aminoadipate, taurine and taurocholic acid and decreased biotin were observed in the high-dose group (1 mg.kg-1 B.W.) compared to the control. The findings also indicated that steroid hormone biosynthesis, lysine biosynthesis, and biotin metabolism are the most affected pathways by MWCNTs-OH. Conclusion: These pathways can reflect perturbation of energy, amino acids, and fat metabolism, as well as oxidative stress. The data obtained by biochemistry, metabonomics, and histopathology were in good agreement, proving that MWCNTs-OH was excreted within 24 h, through the biliary pathway.

Apigenin inhibits growth of the Plasmodium berghei and disrupts some metabolic pathways in mice.

Due to the challenges in the control, prevention, and eradication of parasitic diseases like malaria, there is an urgent need to discover new therapeutic agents. Plant-derived medicines may open new ways in the field of antiplasmodial therapy. This study is aimed to investigate the toxicity and in vivo antiplasmodial activity of apigenin, a dietary flavonoid. Apigenin cytotoxicity was investigated on Huh7 cell line, brine shrimp (Artemia salina) larva, and human red blood cells. In vivo toxicity of apigenin was assessed by metabolomics approaches. Apigenin exhibited significant suppression of parasitemia in a dose-dependent manner; it suppressed Plasmodium berghei growth by 69.74%, 50.3%, and 49.23% at concentrations of 70, 35, and 15 mg/kg/day, respectively. The IC50 value for apigenin after 24 hr exposure to Huh7 cells was 225 µg/ml. Apigenin did not show noticeable toxicity on A. salina and also on the membrane integrity of red blood cells. After 24 hr exposure of mice to apigenin, alterations were seen in the metabolism of glucocorticoids and mineralocorticoids, bile acid metabolism (alternative pathway), sulfur metabolism, bile acid metabolism, metabolism of estrogens and androgens, cholesterol catabolism, and biosynthesis of cholesterol. These findings indicate that apigenin has potential in vivo antiplasmodial activity against P. berghei infected mice with high selectivity against malaria, but it can disrupt some metabolic pathways in mice.

Synthesis, characterization and in vivo evaluation of cadmium telluride quantum dots toxicity in mice by toxicometabolomics approach.

Quantum dots (QDs) have widespread application in many fields such as medicine and electronics. The need for understanding the potentially harmful side effects of these materials becomes clear. In this study, the toxicity of cadmium telluride quantum dots (CdTe-QDs) and bulk Cd2+ has been investigated and compared by applying metabolomics methods. The datasets were 1H-NMR data from mice plasma which had been taken from four groups of mice in different time intervals. Then, the data were analyzed by applying chemometrics methods and the metabolites were found from Human Metabolome Database (HMDB). The results showed the significant change in the level of some metabolites especially estrogenic steroids in different groups with different amounts of received Cd. The findings also indicated that steroid hormone biosynthesis, lysine biosynthesis and taurine and hypotaurine metabolism are the most affected pathways by CdTe-QDs especially in estrogenic steroids. The over-representation analysis indicated that endoplasmic reticulum, gonads, and hepatocytes are most affected. Since the pattern of metabolite alteration of CdTe-QDs with equivalent Cd2+ was similar to those of CdCl2, it was postulated that beside Cd2+ effects, the toxicity of CdTe-QDs is associated with other factors.

Lipidomics Unravels the Role of Leaf Lipids in Thyme Plant Response to Drought Stress.

Thymus is one of the best known genera within the Labiatae (Lamiaceae) family, with more than 200 species and many medicinal and culinary uses. The effects of prolonged drought on lipid profile were investigated in tolerant and sensitive thyme plants (Thymus serpyllum L. and Thymus vulgaris L., respectively). Non-targeted non-polar metabolite profiling was carried out using Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry with one-month-old plants exposed to drought stress, and their morpho-physiological parameters were also evaluated. Tolerant and sensitive plants exhibited clearly different responses at a physiological level. In addition, different trends for a number of non-polar metabolites were observed when comparing stressed and control samples, for both sensitive and tolerant plants. Sensitive plants showed the highest decrease (55%) in main lipid components such as galactolipids and phospholipids. In tolerant plants, the level of lipids involved in signaling increased, while intensities of those induced by stress (e.g., oxylipins) dramatically decreased (50-60%), in particular with respect to metabolites with m/z values of 519.3331, 521.3488, and 581.3709. Partial least square discriminant analysis separated all the samples into four groups: tolerant watered, tolerant stressed, sensitive watered and sensitive stressed. The combination of lipid profiling and physiological parameters represented a promising tool for investigating the mechanisms of plant response to drought stress at non-polar metabolome level.

Mechanism, decomposition pathway and new evidence for self-healing of manganese oxides as efficient water oxidizing catalysts: new insights.

The electrochemical water-oxidation reaction usually requires a catalyst to reduce the overpotential and Earth-abundant catalysts, like MnO2, are attracting much attention. Here we use chemometric analysis, EPR and UV-Vis spectroscopies to track Mn(II) and MnO4(-) byproducts to the reaction of a MnO2 film in the presence of cerium(IV) ammonium nitrate. Permanganate ion is involved in at least two key reactions: it may oxidize water to O2 or can combine with Mn(II) to remake MnO2 solid. We propose mechanisms for water oxidation and present a self-healing process for this reaction.

Applying constraints on model-based methods: estimation of rate constants in a second order consecutive reaction.

This paper describes estimation of reaction rate constants and pure ultraviolet/visible (UV-vis) spectra of the component involved in a second order consecutive reaction between Ortho-Amino benzoeic acid (o-ABA) and Diazoniom ions (DIAZO), with one intermediate. In the described system, o-ABA was not absorbing in the visible region of interest and thus, closure rank deficiency problem did not exist. Concentration profiles were determined by solving differential equations of the corresponding kinetic model. In that sense, three types of model-based procedures were applied to estimate the rate constants of the kinetic system, according to Levenberg/Marquardt (NGL/M) algorithm. Original data-based, Score-based and concentration-based objective functions were included in these nonlinear fitting procedures. Results showed that when there is error in initial concentrations, accuracy of estimated rate constants strongly depends on the type of applied objective function in fitting procedure. Moreover, flexibility in application of different constraints and optimization of the initial concentrations estimation during the fitting procedure were investigated. Results showed a considerable decrease in ambiguity of obtained parameters by applying appropriate constraints and adjustable initial concentrations of reagents.

Application of chemometrics methods with kinetic constraints for estimation of rate constants of second order consecutive reactions.

To determine the rate constants for the second order consecutive reactions of the form U + V -(k1)--> W -(k2)--> P, a number of chemometrics and hard modeling-based methods are described. The absorption spectroscopic data from the reaction were utilized for performing the analysis. Concentrations and extinctions of components were comparable, and all of them were absorbing species. The number of steps in the reaction was less than the number of absorbing species, which resulted in a rank-deficient response matrix. This can cause difficulties for some of the methods described in the literature. The standard MATLAB functions were used for determining the solutions of the differential equations as well as for finding the optimal rate constants to describe the kinetic profiles. The available knowledge about the system determines the approaches described in this paper. The knowledge includes the spectra of reactants and products, the initial concentrations, and the exact kinetics. Some of this information is sometimes not available or is hard to estimate. Multiple linear regression for fitting the kinetic parameters to the obtained concentration profiles, rank augmentation using multiple batch runs, a mixed spectral approach which treats the reaction using a pseudo species concept, and principal components regression are the four groups of methods discussed in this study. In one of the simulated datasets the spectra are quite different, and in the other one the spectra of one reactant and of the product share a high degree of overlap. Instrumental noise, sampling error are the sources of error considered. Our aim was the investigation of the relative merits of each method.