The study aimed to develop a cost-effective and rapid approach for monitoring eleven crucial parameters that describe the health of cultivated Haplic Luvisol soils. To achieve this, the diffuse reflectance spectra in the NIR spectral region, between 1100 and 2500 nm, were registered, and partial least-squares (PLS) models to predict the concentrations of the critical parameters, including organic carbon, total nitrogen, the available soil nutrients (phosphorus, potassium and magnesium), the exchangeable cations (calcium, magnesium and potassium), the pH levels (determined in deionized water or KCl solution and hydrolytic acidity), were built. The validation results, which are expressed as RMSE and R2val that were obtained for validation the samples, demonstrate that the proposed approach is a reliable and efficient way to monitor the health of Haplic Luvisol soils. Specifically, excellent predictions were obtained for the total nitrogen, organic carbon and pH, which was determined in KCl solution with R2val values equal to 0.9696, 0.9573 and 0.9176, respectively. Additionally, very good PLS models were constructed to estimate the pH levels determined in deionized water, exchangeable magnesium, and po-tassium, which achieved R2val values of 0.8650, 0.8383, and 0.8329, respectively. For the remaining parameters, the corresponding R2val values were above 0.7294.

This study illustrates the successful application of near-infrared reflectance spectroscopy extended with chemometric modeling to profile Cd, Cu, Pb, Ni, Cr, Zn, Mn, and Fe in cultivated and fertilized Haplic Luvisol soils. The partial least-squares regression (PLSR) models were built to predict the elements present in the soil samples at very low contents. A total of 234 soil samples were investigated, and their reflectance spectra were recorded in the spectral range of 1100-2500 nm. The optimal spectral preprocessing was selected among 56 different scenarios considering the root mean squared error of prediction (RMSEP). The partial robust M-regression method (PRM) was used to handle the outlying samples. The most promising models were obtained for estimating the amount of Cu (using PRM) and Pb (using the classic PLS), leading to RMSEP expressed as a percentage of the response range, equal to 9.63% and 11.5%, respectively. The respective coefficients of determination for validation samples were equal to 0.86 and 0.58, respectively. Assuming similar variability of model residuals for the model and test set samples, coefficients of determination for validation samples were 0.94 and 0.89, respectively. Moreover, the favorable PLS models were also built for Zn, Mn, and Fe with coefficients of determinations equal to 0.87, 0.87, and 0.79.

Chemometric methods permit the construction of classifiers that effectively assist in monitoring safety, quality and authenticity of meat based on the near-infrared (NIR) spectral fingerprints. Discriminant techniques are often considered in multivariate quality control. However, when the authenticity of meat products is the primary concern, they often lead to an incorrect recognition of new samples. The performances of two class modeling techniques (CMT) in order to recognize meat sample species based on their NIR spectra was compared - a one-class classifier variant of the partial least squares method (OCPLS) and the soft independent modeling of class analogy (SIMCA). Based on obtained sensitivity and specificity values, OCPLS and SIMCA can be considered as an effective CMT for the classification of complex natural samples such as studied meat samples (with a relatively large variability). Moreover, particular attention was paid to the optimization and validation of a one-class classification model.

Plant medicines used by patients in self-treatment contain powerfully acting active substances which can be a source of adverse events including interactions with synthetic medicines. Usage of St. John's wort causes high risk of various complications. St. John's wort preparations shouldn't be combined with antidepressants without physician's consultation. Long-term intake of medicines which contain Hypericum perforatum extracts can be a reason of undesirable interactions with isoenzymes CYP3A4, CYP1A2, CYP2C9, CYP2C19 and P-glycoprotein (P-gp) for which St John's wort is a substrate. Compounds present in the St. John's wort, especially hyperforin, increase the activity of cytochrome P450 in the liver and intestinal mucosa as well as P-gp, which can accelerate their elimination from the body, decrease their concentrations and reduce the effect. Effective and safe phytotherapy requires a lot of knowledge about the properties and toxicity of preparations used and accurate monitoring of the consequences of their actions.

This paper presents and discusses the building of discriminant models from attenuated total reflectance (ATR)-FTIR and Raman spectra that were constructed to detect the presence of acetaminophen in over-the-counter pharmaceutical formulations. The datasets, containing 11 spectra of pure substances and 21 spectra of various formulations, were processed by partial least squares (PLS) discriminant analysis. The models found in the present study coped greatly with the discrimination, and their quality parameters were acceptable. A root mean square error of cross-validation was in the 0.14-0.35 range, while a root mean square error of prediction was in the 0.20-0.56 range. It was found that standard normal variate preprocessing had a negligible influence on the quality of ATR-FTIR; in the Raman case, it lowered the prediction error by 2. The influence of variable selection with the uninformative variable elimination by PLS method was studied, and no further model improvement was found.

The aim of this study was to determine whether antineoplastic cytostatic therapy induces changes in the oxidation or acetylation phe-notypes in patients with acute myeloblastic leukemia (AML). The investigations involved 22 patients with AML undergoing chemotherapy with daunorubicin, cytosine arabinoside, etoposide and mitoxantrone. The oxidation phenotype prior to therapy and after termination of induction was examined in all 22 patients and was examined in 10 patients after termination of the first consolidation cycle. The acetylation phenotype was examined prior to therapy and after termination of induction in 21 patients and after termination of the first remission consolidation cycle in 9 patients. The oxidation phenotype was determined by means of the method by Eichelbaum and Gross. The acetylation phenotype was determined using Varley’s modification of the Bratton-Marshall method. Anticancer therapy affected the oxidation phenotype, causing decreased activity of the cytochrome P450 isoenzyme CYP2D6. This decrease suggests that daunorubicin, cytosine arabinoside, etoposide and mitoxantrone may impair the metabolism of other active substances metabolized by this isoenzyme, which should be taken into consideration in planning the dosage scheme in individual patients and considering interactions between drugs. Evaluation of the effect of administered cytostatic drugs on acetylation phenotype revealed no statistically significant decrease in the rate of sulfadimidine acetylation.

The aim of this work was to propose a quick and cost-effective procedure, which could help to identify the types of fat (rapeseed, a mixture of rapeseed and soybean, and lard oils) added to feed used for raising pigs. For this purpose, liver samples were examined and their near-infrared reflectance spectra served as data for the construction of classic and robust soft independent modeling of class analogy (SIMCA) models. The results showed that the near-infrared reflectance spectra contained information sufficient to build good classification models that enabled three types of fat additions to be distinguished. The best classification results were obtained from robust SIMCA, indicating its superior performance in terms of high sensitivity and specificity in comparison with classic SIMCA. Specifically, robust models had sensitivities of 100% and specificities of 96.05%, 97.73% and 100%, for rapeseed, mixture of rapeseed and soybean, and lard enriched feed, respectively.

Near-infrared reflectance spectroscopy (NIRS) is often applied when a rapid quantification of major components in feed is required. This technique is preferred over the other analytical techniques due to the relatively few requirements concerning sample preparations, high efficiency and low costs of the analysis. In this study, NIRS was used to control the content of crude protein, fat and fibre in extracted rapeseed meal which was produced in the local industrial crushing plant. For modelling the NIR data, the partial least squares approach (PLS) was used. The satisfactory prediction errors were equal to 1.12, 0.13 and 0.45 (expressed in percentages referring to dry mass) for crude protein, fat and fibre content, respectively. To point out the key spectral regions which are important for modelling, uninformative variable elimination PLS, PLS with jackknife-based variable elimination, PLS with bootstrap-based variable elimination and the orthogonal partial least squares approach were compared for the data studied. They enabled an easier interpretation of the calibration models in terms of absorption bands and led to similar predictions for test samples compared to the initial models.

Citrus juices can interact with a number of medications. As little as 250 ml of grapefruit or orange juice can change the metabolism of drugs. Most drugs affected by citrus juices are known to be metabolized by CYP3A4. Recently, some studies have shown an in vitro inhibition of CYP2D6 metabolism by grapefruit juice. CYP2D6 enzyme is an important factor in the metabolism of 20-25% of clinically important drugs, such as antidepressants, neuroleptics, antiemetics, cardiologic drugs and opioids. The aim of our study was to investigate the effects of orange juice on human cytochrome CYP2D6 enzyme activity. The study involved twenty unrelated healthy volunteers. Ten of them received 250 ml (one glass) of orange juice daily for 5 days. Control group consisted of ten persons who received 250 ml (one glass) of tap water. The CYP2D6 phenotype was analyzed before and after 5 days of juice/water ingestion, using sparteine as a model drug. Sparteine and its metabolites were determined in urine by the method of Eichelbaum. Metabolic ratio (MR) was calculated as the ratio of amount of parent drug to the total amount of metabolites. Mean MR, measured after 5 days of drinking the juice, increased by only 7% in group receiving orange juice, and by 10% in control group receiving tap water. Our results suggest that orange juice has no significant influence on metabolism and excretion of CYP2D6-dependent drugs. So it is not necessary to advise patients against drinking orange juice at the same time when they take those drugs.

Citrus juices can interact with a number of medications. As little as 250 ml of grapefruit or orange juice can change the metabolism of drugs. Most drugs affected by citrus juices are known to be metabolized by CYP3A4. Recently, some studies have shown an in vitro inhibition of CYP2D6 metabolism by grapefruit juice. CYP2D6 enzyme is an important factor in the metabolism of 20–25% of clinically important drugs, such as antidepressants, neuroleptics, antiemetics, cardiologic drugs and opioids. The aim of our study was to investigate the effects of orange juice on human cytochrome CYP2D6 enzyme activity. The study involved twenty unrelated healthy volunteers. Ten of them received 250 ml (one glass) of orange juice daily for 5 days. Control group consisted of ten persons who received 250 ml (one glass) of tap water. The CYP2D6 phenotype was analyzed before and after 5 days of juice/water ingestion, using sparteine as a model drug. Sparteine and its metabolites were determined in urine by the method of Eichelbaum. Metabolic ratio (MR) was calculated as the ratio of amount of parent drug to the total amount of metabolites. Mean MR, measured after 5 days of drinking the juice, increased by only 7% in group receiving orange juice, and by 10% in control group receiving tap water. Our results suggest that orange juice has no significant influence on metabolism and excretion of CYP2D6-dependent drugs. So it is not necessary to advise patients against drinking orange juice at the same time when they take those drugs.

AIM:The relationship between genetically determined polymorphic oxidation and acetylation and susceptibility to some disease has aroused much interest. The aim of our study was to evaluate whether patients with Alzheimer's disease differ from healthy persons in their ability to oxidize sparteine and acetylate sulphadimidine as model substance.METHOD:Oxidation and acetylation phenotype were estimated in 20 patients with Alzheimer's disease. The control group consisted of 160 healthy volunteers for comparison of oxidation phenotype and 45 healthy subjects for comparison of acetylation phenotype.RESULTS:The phenotyping of oxidation revealed two distinct populations among 20 patients with Alzheimer's disease: 19 persons (95%) were extensive metabolizers (EMs) of sparteine and 1 person (5%) was a poor metabolizer (PMs). In 160 healthy persons, 146 persons (91.2%) were extensive metabolizers of sparteine and 14 persons (8.8%) were poor metabolizers. The difference between the frequency distribution of PMs and EMs in healthy persons and in patients with Alzheimer's disease was not statistically significant. The phenotyping of acetylation showed that among 20 patients with Alzheimer's disease 10 persons (50%) were rapid acetylators and 10 persons (50%) were slow acetylators. In 45 healthy subjects the phenotype of rapid acetylation was observed in 23 persons (5 1%) and slow acetylation in 22 persons (49%). Our study showed a lack of statistically significant differences between the percentage of rapid acetylators (51%) and of slow acetylators (49%) in the control group of healthy volunteers and in the group ofAlzheimer's disease.CONCLUSION:The results of our study may suggest that phenotypes of oxidation and acetylation are not associated with risk of the development of Alzheimer's disease.

INTRODUCTIONThe relationship between genetically determined polymorphic oxidation and acetylation and susceptibility to some disease was aroused much interest. The aim of our study was to evaluate whether patients with hyperthyreosis differ from healthy persons in their ability to oxidize sparteine and acetylate sulphadimidine as model drugs. Oxidation and acetylation were estimated in 48 patients with hiperthyreosis.MATERIAL AND METHODSThe control group consisted of 160 healthy volunteers for comparison of oxidation phenotype and 60 healthy volunteers for comparison of acetylation phenotype. The phenotyping of oxidation revealed two distinct populations among 40 patients with hyperthyreosis: 38 persons (95%) were extensive metabolizers (EM) of sparteine and 2 persons (5%) was poor metabolizers (PM). In 160 healthy persons (91.2%) were EM and 14 persons (8.8%) were PM. The difference between frequency distribution of PM and EM in healthy persons and in patients with hyperthyreosis was not statistically significant.RESULTSThe phenotyping of acetylation showed among 48 patients with hyperthyreosis 8 persons (13%) were rapid acetylators (RA) and 40 persons (87%) were slow acetylators (SA). In 60 healthy volunteers the phenotype of rapid acetylation was observed in 31 persons (51%) and slow acetylation in 29 persons (49%). Relative risk (odds ratio) of development of thyroid diseases was 5.34 times higher for SA in comparison to RA. The prevalence of SA among patients with hyperthyreosis in comparison to healthy volunteers was statistically significant (p < 0.0002).CONCLUSIONSThe results of our study may suggest that slow acetylation phenotype is associated with increased risk of the development of hyperthyreosis.