Application of fuzzy algorithms in conjunction with H-NMR spectroscopy to differentiate alcoholic beverages.

Background: Recent statistics from the European Commission indicate that wine is one of the commodities most commonly subject to food fraud. In this context, the development of reliable classification models to differentiate alcoholic beverages requires, besides sensitive analytical tools, the use of the most suitable data-processing methods like those based on advanced statistical tools or artificial intelligence.

Results: The present study aims to establish a new, innovative approach for the differentiation of alcoholic beverages (wines and fruit distillates), which is able to increase the discrimination rate of the models that have been developed.

Multivariate color scale image analysis - Thin layer chromatography for comprehensive evaluation of complex samples fingerprint.

A chemometric evaluation of the information provided by different color scale fingerprints in thin layer chromatographic analysis of complex samples is proposed for the correct classification of a set of medicinal plant extracts. The fingerprints of the samples were acquired on HPTLC Silica gel 60 F and HPTLC Silica gel 60 plates using multiple levels of visualization under UV light. Images processing on red (R), green (G), blue (B) and respectively grey (K) color scale selection was used in order to evaluate the complete chromatographic profile of the extracts.

Fuzzy characterization and classification of bacteria species detected at single-cell level by surface-enhanced Raman scattering.

Advanced chemometric methods, such as fuzzy c-means, a semi-supervised clustering method, and fuzzy linear discriminant analysis (FLDA), a new robust supervised classification method in combination with principal component analysis (PCA), namely PCA-FLDA, have been successfully applied for characterization and classification of bacterial species detected at single-cell level by surface-enhanced Raman scattering (SERS) spectroscopy. SERS spectra of three species (S. aureus, E.

Fuzzy Divisive Hierarchical Associative-Clustering Applied to Different Varieties of White Wines According to Their Multi-Elemental Profiles.

Wine data are usually characterized by high variability, in terms of compounds and concentration ranges. Chemometric methods can be efficiently used to extract and exploit the meaningful information contained in such data. Therefore, the fuzzy divisive hierarchical associative-clustering (FDHAC) method was efficiently applied in this study, for the classification of several varieties of Romanian white wines, using the elemental profile (concentrations of 30 elements analyzed by ICP-MS).

Finding specific peaks (markers) using fuzzy divisive hierarchical associative-clustering based on the chromatographic profiles of medicinal plant extracts obtained at various detection wavelengths.

Advanced chemometric methods, such as fuzzy c-means (FCM), a fuzzy divisive hierarchical clustering algorithm (FDHC), and fuzzy divisive hierarchical associative-clustering (FDHAC), which offer the excellent possibility to associate each fuzzy partition of samples with a fuzzy set of characteristics (features), have been successfully applied in this study. FDHAC, a method that utilizes specific regions of chromatographic fingerprints or specific peaks as a fuzzy set of characteristics, was effectively applied to the characterization and classification of medicinal plant extracts according to their antioxidant capacities, using their chromatographic profiles monitored at 242, 260, 280, 320, 340, and 380 nm via HPLC with a multistep isocratic and gradient elution system and diode array detection (HPLC-DAD). What is quite new is the partitioning of the chromatographic retention time ranges and peaks (markers) and their association with different plant extract samples with high, moderate or low antioxidant capacity.

Fuzzy partitioning of clinical data for DMT2 patients.

The present study represents an original approach to data interpretation of clinical data for patients with diagnosis diabetes mellitus type 2 (DMT2) using fuzzy clustering as a tool for intelligent data analysis. Fuzzy clustering is often used in classification and interpretation of medical data (including in medical diagnosis studies) but in this study it is applied with a different goal: to separate a group of 100 patients with DMT2 from a control group of healthy volunteers and, further, to reveal three different patterns of similarity between the patients. Each pattern is described by specific descriptors (variables), which ensure pattern interpretation by appearance of underling disease to DMT2.

Comprehensive evaluation of radical scavenging, reducing power and chelating capacity of free proteinogenic amino acids using spectroscopic assays and multivariate exploratory techniques.

Among others, amino acids can inhibit oxidative processes through multiple pathways including inactivation of reactive oxygen species, scavenging free radicals, chelation of pro-oxidative transition metals, as well as reduction of hydroperoxides. Moreover, they can be a major target for oxidants as a result of their abundance in biological systems. The purpose of the present study is to examine the radical scavenging, reducing power and chelating capacity of the free proteinogenic amino acids, using several analytical assays based on different mechanisms and monitored via molecular UV-vis absorption spectrophotometry.

Characterization and classification of wines according to geographical origin, vintage and specific variety based on elemental content: a new chemometric approach.

A highly informative chemometric approach using elemental data to distinguish and classify wine samples according to different criteria was successfully developed. The robust chemometric methods, such fuzzy principal component analysis (FPCA), FPCA combined with linear discriminant analysis (LDA), namely FPCA-LDA and mainly fuzzy divisive hierarchical associative-clustering (FDHAC), including also classical methods (HCA, PCA and PCA-LDA) were efficaciously applied for characterization and classification of white wines according to the geographical origin, vintage or specific variety. The correct rate of classification applying LDA was 100% in all cases, but more compact groups have been obtained for FPCA scores.

Epidemiological Aspects of Cognitive and Socio-Professional Integration in Schizophrenia.

Schizophrenia is one of the major psychiatric disorders with global impairment of cognition, emotional status and personality destruction having a major medical, social and economic impact worldwide. In this paper, we evaluated the correlation of disease progression with cognitive deficit, socio-professional and family disjunction using the MMSE (Mini Mental State Examination) and GAFS (Global Assessment of Functioning Scale) scales on a group of 191 schizophrenic patients admitted to the Psychiatric Clinic II Craiova during 2017. The fact that both scales show reduced values in patients with schizophrenia reveals a significant alteration in the quality of life of patients with this pathology having major implications on the individuals and on the community.

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.

A comprehensive classification of edible oils according to their radical scavenging spectral profile evaluated by advanced chemometrics.

A comprehensive study concerning the characterization and classification of 30 cold-pressed edible oils according to their UV-Vis spectra and radical scavenging profiles using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay is presented. Considering the principal component analysis (PCA) and fuzzy-principal component analysis (FPCA) loadings profiles, the characteristic spectral regions with a significant influence in oil samples classification were identified and associated with characteristic factors in each group. Much more, the oils with high antiradical capacity were revealed.

Therapeutic Particularities with Depot Medications in Schizophrenia.

Schizophrenia is a neurodegenerative disease with personality degradation, changes in behavior, cognition, affective disorder and reduced socio-professional insertion. Early diagnosis is necessary and maintenance is ensured by antipsychotic treatment and for non-compliant patients there is an alternative to depot medication that greatly improves therapeutic adherence. The study presents the case of a 43-year-old patient diagnosed with paranoid schizophrenia using the Diagnostic and Statistical Manual of Mental Disorders V-TR criteria that showed a favorable evolution under depot treatment.

Classification of Romanian medicinal plant extracts according to the therapeutic effects using thin layer chromatography and robust chemometrics.

Thin layer chromatography in combination with image analysis and advanced chemometric methods were successfully used to classify the medicinal herbs according to their therapeutic effects and usage. The investigations were conducted using two types of plates (HPTLC Silica gel 60 and HPTLC Silica gel 60 F254) which were evaluated in UV light at 254 and 365 nm. The holistic evaluation of the numerical data corresponding different image processing channels (blue, grey, red, green) was performed by employing appropriate multivariate methods: hierarchical cluster analysis (HCA), principal component analysis (PCA), fuzzy principal component analysis (FPCA) and linear discriminant analysis (LDA) applied to the first relevant principal components.

Characterization of Clinically Relevant Fungi via SERS Fingerprinting Assisted by Novel Chemometric Models.

Nonculture-based tests are gaining popularity and upsurge in the diagnosis of invasive fungal infections (IFI) fostered by their main asset, the reduced analysis time, which enables a more rapid diagnosis. In this project, three different clinical isolates of relevant filamentous fungal species were discriminated by using a rapid (less than 5 min) and sensitive surface-enhanced Raman scattering (SERS)-based detection method, assisted by chemometrics. The holistic evaluation of the SERS spectra was performed by employing appropriate chemometric tools-classical and fuzzy principal component analysis (FPCA) in combination with linear discriminant analysis (LDA) applied to the first relevant principal components.

Influence of Mixed Additives on the Physicochemical Properties of a 5.25% Sodium Hypochlorite Solution: An Unsupervised Multivariate Statistical Approach.

Introduction: This article reports for the first time the effects of multiple additives (polyethylene glycol 400, Triton X-100, benzalkonium chloride, and ethyl formate) on the surface tension, pH, and viscosity of 5.25% sodium hypochlorite (NaOCl) irrigant solution. Advanced statistical approaches based on unsupervised multivariate analysis (cluster analysis and principal component analysis) were used to quantify the variability of the physicochemical properties of the modified NaOCl solution for the first time in dentistry.

Chemometric Assessment of Chromatographic Methods for Herbal Medicines Authentication and Fingerprinting.

Nowadays, increasingly more individuals turn to supplementation of the diet with herbal medicines and many such products are marketed lately. Thus the problem that this article focuses on is that these products are not subjected to rigorous quality control like synthetic drugs are, which rises a constant debate whether the supplements actually contain the herb or mixture of herbs that the manufacturer claims they do. As a solution, micellar electrokinetic chromatography and high performance liquid chromatography were investigated in order to fingerprint and authenticate herbal medicines.

Assessment of Lipophilicity Indices Derived from Retention Behavior of Antioxidant Compounds in RP-HPLC.

Reverse phase high pressure liquid chromatography was employed in order to evaluate the lipophilicity of antioxidant compounds from different classes, such as phenolic acids, flavanones, flavanols, flavones, anthocyanins, stilbenes, xantonoids, and proanthocyanidins. The retention time of each compound was measured using five different HPLC columns: RP18 (LiChroCART, Purosphere RP-18e), C8 (Zorbax, Eclipse XDBC8), C16-Amide (Discovery RP-Amide C16), CN100 (Saulentechnik, Lichrosphere), and pentafluorophenyl (Phenomenex, Kinetex PFP), and the mobile phase consisted of methanol and water (0.1% formic acid) in different proportions.

Chemical modeling of groundwater in the Banat Plain, southwestern Romania, with elevated As content and co-occurring species by combining diagrams and unsupervised multivariate statistical approaches.

The study proposes a combined model based on diagrams (Gibbs, Piper, Stuyfzand Hydrogeochemical Classification System) and unsupervised statistical approaches (Cluster Analysis, Principal Component Analysis, Fuzzy Principal Component Analysis, Fuzzy Hierarchical Cross-Clustering) to describe natural enrichment of inorganic arsenic and co-occurring species in groundwater in the Banat Plain, southwestern Romania. Speciation of inorganic As (arsenite, arsenate), ion concentrations (Na, K, Ca, Mg, HCO, Cl, F, SO, PO, NO), pH, redox potential, conductivity and total dissolved substances were performed. Classical diagrams provided the hydrochemical characterization, while statistical approaches were helpful to establish (i) the mechanism of naturally occurring of As and F species and the anthropogenic one for NO, SO, PO and K and (ii) classification of groundwater based on content of arsenic species.

Experimental variability and data pre-processing as factors affecting the discrimination power of some chemometric approaches (PCA, CA and a new algorithm based on linear regression) applied to (+/-)ESI/MS and RPLC/UV data: Application on green tea extracts.

The influence of the experimental variability (instrumental repeatability, instrumental intermediate precision and sample preparation variability) and data pre-processing (normalization, peak alignment, background subtraction) on the discrimination power of multivariate data analysis methods (Principal Component Analysis -PCA- and Cluster Analysis -CA-) as well as a new algorithm based on linear regression was studied. Data used in the study were obtained through positive or negative ion monitoring electrospray mass spectrometry (+/-ESI/MS) and reversed phase liquid chromatography/UV spectrometric detection (RPLC/UV) applied to green tea extracts. Extractions in ethanol and heated water infusion were used as sample preparation procedures.

Prediction of the fate of Hg and other contaminants in soil around a former chlor-alkali plant using Fuzzy Hierarchical Cross-Clustering approach.

An associative simultaneous fuzzy divisive hierarchical algorithm was used to predict the fate of Hg and other contaminants in soil around a former chlor-alkali plant. The algorithm was applied on several natural and anthropogenic characteristics of soil including water leachable, mobile, semi-mobile, non-mobile fractions and total Hg, Al, Ba, Ca, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Sr, Zn, water leachable fraction of Cl(-), NO3(-) and SO4(2)(-), pH and total organic carbon. The cross-classification algorithm provided a divisive fuzzy partition of the soil samples and associated characteristics.

Evaluation of a hydrophobic gel adhering to the gingiva in comparison with a standard water-soluble 1% chlorhexidine gel after scaling and root planing in patients with moderate chronic periodontitis. A randomized clinical trial.

Objectives: To evaluate the clinical, microbiological and enzymatic activity of a hydrophobic chlorhexidine-based gingiva-adhering gel containing herbal ingredients, compared with a commercially available 1% chlorhexidine water-soluble gel, during non-surgical therapy of moderate chronic periodontitis.

Methods: A total of 34 subjects participated in this 6-month blinded randomized parallel controlled trial (ISRCTN35210084). After scaling and root planing (SRP), test group received the gel, by rubbing on the gingiva, once every second day, for 14 days.

Thin-layer chromatography--an image-processing method for the determination of acidic catecholamine metabolites.

A sensitive and convenient method for acidic catecholamine metabolites (including homovanillic acid, vanillylmandelic acid, 3,4-dihydroxymandelic acid, and 3,4-dihydroxyphenylacetic acid) determination was developed based on thin-layer chromatography and image-processing analysis. The metabolites were separated without a prederivatization step using reversed phase RP-18W high-performance plates. The mobile phase composition, detection, and quantification conditions were systematically investigated through several trials.

Lipophilicity indices derived from the liquid chromatographic behavior observed under bimodal retention conditions (reversed phase/hydrophilic interaction): application to a representative set of pyridinium oximes.

The liquid chromatographic behavior observed under bimodal retention conditions (reversed phase and hydrophilic interaction) offers a new basis for the determination of some derived lipophilicity indices. The experiments were carried out on a representative group (30 compounds) of pyridinium oximes, therapeutically tested in acetylcholinesterase reactivation, covering a large range of lipophilic character. The chromatographic behavior was observed on a mixed mode acting stationary phase, resulting from covalent functionalization of high purity spherical silica with long chain alkyl groups terminated by a polar environment created through the vicinal diol substitution at the lasting carbon atoms (Acclaim Mixed Mode HILIC 1 column).

Fuzzy clustering evaluation of the discrimination power of UV-Vis and (±) ESI-MS detection system in individual or coupled RPLC for characterization of Ginkgo Biloba standardized extracts.

Aim: Discrimination power evaluation of UV-Vis and (±) electrospray ionization/mass spectrometric techniques, (ESI-MS) individually considered or coupled as detectors to reversed phase liquid chromatography (RPLC) in the characterization of Ginkgo Biloba standardized extracts, is used in herbal medicines and/or dietary supplements with the help of Fuzzy hierarchical clustering (FHC).

Experimental: Seventeen batches of Ginkgo Biloba commercially available standardized extracts from seven manufacturers were measured during experiments. All extracts were within the criteria of the official monograph dedicated to dried refined and quantified Ginkgo extracts, in the European Pharmacopoeia.

Localized Juvenile Spongiotic Gingival Inflammation: A Report on 3 Cases.

Background And Aims: A new pathological entity with distinct clinicopathological features has been recently described and termed as juvenile spongiotic gingivitis. Histopathological associated features are unique and characterized by prominent intercellular edema (spongiosis) and neutrophil infiltrate. The aims of this paper were to: introduce juvenile spongiotic gingivitis to the dental and pediatric communities, to report three cases based on clinical and histopathological findings, and to discuss the most common clinical differential diagnoses.