Optimization of the Cold Water Extraction Method for High-Value Bioactive Compounds from Chamomile ( L.) Flower Heads Through Chemometrics.

This study focused on optimizing a cold water extraction method to obtain bioactive compounds from chamomile ( L.), addressing increasing consumer demand for natural products and nutraceuticals. A full-factorial design was employed to evaluate the effects of temperature, time, and chamomile amount on the polyphenolic profile of extracts.

Comprehensive Extraction and Chemical Characterization of Bioactive Compounds in Tepals of L.

L. is largely cultivated because it is the source of saffron, a well-appreciated and valued spice, not only for its culinary use but also because of its significant biological activities. Stigmas are the main product obtained from flowers, but in addition, tepals, largely considered a waste product, represent a big source of flavonoids and anthocyanins.

Quantitative Structure-Retention Relationship Analysis of Polycyclic Aromatic Compounds in Ultra-High Performance Chromatography.

A comparative quantitative structure-retention relationship (QSRR) study was carried out to predict the retention time of polycyclic aromatic hydrocarbons (PAHs) using molecular descriptors. The molecular descriptors were generated by the software Dragon and employed to build QSRR models. The effect of chromatographic parameters, such as flow rate, temperature, and gradient time, was also considered.

Experimental Design and Response Surface Methodology Applied to Graphene Oxide Reduction for Adsorption of Triazine Herbicides.

In this work, pristine graphene oxide and its thermally reduced derivatives, rGO, were tested for the removal of triazines (atraton, prometryn, and atrazine) from water. The reduction process was optimized by means of design of experiments (DOE) coupled with response surface methodology (RSM), relying on the adsorption efficiency of the material. The optimal reduction conditions were calculated at a temperature of 110 °C maintained for 24 h; the mildest and simplest reduction protocol was chosen, as it allows in-air heat treatment with a common laboratory oven.

Multivariate optimization of an analytical method for the analysis of Abruzzo white wines by ICP OES.

An inductively coupled plasma-optical emission spectrometry (ICP OES) method was optimized and applied for determining the concentration of 14 elements (Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sr, V, and Zn) in three representative white wines of the Abruzzo region (Italy). In order to optimise an ICP OES method a three level factorial design for three variables was used. The intensity of the emission lines for analytes was simultaneously maximised by using Derringer's desirability function.

Geographical discrimination of red garlic (Allium sativum L.) produced in Italy by means of multivariate statistical analysis of ICP-OES data.

Sixty-five samples of red garlic (Allium sativum L.) coming from four different production territories of Italy were analysed by means of inductively coupled plasma optical emission spectrometry. The garlic samples were discriminated according to the geographical origin using the content of seven elements (Ba, Ca, Fe, Mg, Mn, Na and Sr).

UHPLC Analysis of Saffron ( L.): Optimization of Separation Using Chemometrics and Detection of Minor Crocetin Esters.

Ultra-high performance liquid chromatography (UHPLC) coupled with diode array detection (DAD) was applied to improve separation and detection of mono- and bis-glucosyl esters of crocetin (crocins), the main red-colored constituents of saffron ( L.), and other polar components. Response surface methodology (RSM) was used to optimise the chromatographic resolution on the Kinetex C18 (Phenomenex) column taking into account of the combined effect of the column temperature, the eluent flow rate and the slope of a linear eluent concentration gradient.

Extraction of curcuminoids by using ethyl lactate and its optimisation by response surface methodology.

Response surface methodology (RSM) was applied to optimise the extraction of curcuminoids (curcumin, demethoxycurcumin and bisdemethoxycurcumin) from turmeric using ethyl lactate (EL), ethanol and water under mild conditions (magnetic stirring at room temperature). An augmented simplex-centroid mixture design was used to monitor the dependence of the extraction efficiency from the proportions of the three solvents in the extraction medium. HPLC was used to establish the content of curcuminoids in turmeric and in the extracts.

Geographical classification of Italian saffron (Crocus sativus L.) based on chemical constituents determined by high-performance liquid-chromatography and by using linear discriminant analysis.

One hundred and forty-four Italian saffron samples produced in the years from 2009 to 2015 in five distinct areas located in four different regions, Abruzzo (L'Aquila), Tuscany (Florence), Umbria (Cascia and Città della Pieve) and Sardinia, have been analysed by high-performance liquid chromatography with diode array detection. Intensities of the chromatographic peaks attributed to crocins, safranal, picrocrocin and its derivatives and flavonoids were considered as variables in linear discriminant analysis to attempt geographical classification. The results revealed that spices produced at different sites of the Italian territory can be discriminated with good accuracy.

Optimisation by response surface methodology of microextraction by packed sorbent of non steroidal anti-inflammatory drugs and ultra-high performance liquid chromatography analysis of dialyzed samples.

A procedure based on microextraction by packed sorbent (MEPS) followed by ultra-high performance liquid chromatography (UHPLC) with photodiode array (PDA) detection has been developed for the analysis of seven selected non steroidal anti-inflammatory drugs (NSAIDs) in human dialysates. The influence on MEPS efficiency of pH of the sample, pH of the washing solvent and methanol content in the hydro-alcoholic elution mixture has been investigated by response surface methodology based on a Box-Behnken design of experiments. Among the above factors, pH of sample is the variable that mostly influences MEPS recovery.

Optimisation of temperature-programmed gas chromatographic separation of organochloride pesticides by response surface methodology.

A response surface methodology (RSM) approach is applied to optimise the temperature-programme gas-chromatographic separation of 16 organochloride pesticides, including 12 compounds identified as highly toxic chemicals by the Stockholm Convention on Persistent Organic Pollutants. A three-parameter relationship describing both linear and curve temperature programmes is derived adapting a model previously used in literature to describe concentration gradients in liquid chromatography with binary eluents. To investigate the influence of the three temperature profile descriptors (the starting temperature, the gradient duration and a shape parameter), a three-level full-factorial design of experiments is used to identify suitable combinations of the above variables spanning over a useful domain.

Quantitative structure-retention relationships of cannabimimetic aminoalkilindole derivatives and their metabolites.

Development of chromatographic analyses of synthetic cannabinoids is complicated by the lack of commercial reference standards, especially for new analogues introduced in the clandestine market to bypass legal controls and for their metabolites. In the present work, we explore the possibility of predicting the retention behaviour of the cannabimimetic aminoalkilindoles and their urinary metabolites in high-performance liquid-chromatography using a quantitative structure-retention relationship (QSRR) generated by multilinear regression. To represent the structure of the 43 investigated analytes, 617 computational molecular descriptors are subjected to genetic algorithm variable selection aimed at identifying a small but informative subset.

Artificial neural network prediction of multilinear gradient retention in reversed-phase HPLC: comprehensive QSRR-based models combining categorical or structural solute descriptors and gradient profile parameters.

A multilayer artificial neural network (ANN) is used to model the reversed-phase liquid chromatography retention times of 16 selected compounds, including purines, pyrimidines and nucleosides. The analysed data, taken from literature, were collected in acetonitrile-water eluents under the application of 16 different multilinear gradients. The parameters describing the gradient profile together with solute descriptors are considered as the independent variables of an ANN-based model providing the retention time as response.

Cross-column prediction of gas-chromatographic retention indices of saturated esters.

We combine computational molecular descriptors and variables related with the gas-chromatographic stationary phase into a comprehensive model able to predict the retention of solutes in external columns. To explore the quality of various approaches based on alternative column descriptors, we analyse the Kováts retention indices (RIs) of 90 saturated esters collected with seven columns of different polarity (SE-30, OV-7, DC-710, OV-25, XE-60, OV-225 and Silar-5CP). Cross-column retention prediction is evaluated on an internal validation set consisting of data of 40 selected esters collected with each of the seven columns, sequentially excluded from calibration.

Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditions.

In this paper, a multilayer artificial neural network is used to model simultaneously the effect of solute structure and eluent concentration profile on the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient elution. The retention data of 24 triazines, including common herbicides and their metabolites, are collected under 13 different elution modes, covering the following experimental domain: starting acetonitrile volume fraction ranging between 40 and 60% and gradient slope ranging between 0 and 1% acetonitrile/min. The gradient parameters together with five selected molecular descriptors, identified by quantitative structure-retention relationship modelling applied to individual separation conditions, are the network inputs.

Modelling of UPLC behaviour of acylcarnitines by quantitative structure-retention relationships.

In the present work, the retention time (RT) of acylcarnitines, collected by ultra-performance liquid-chromatography after formation of butyl esters, is modelled by quantitative structure-retention relationship (QSRR) method. The investigated set consists of free carnitine and 46 different acylcarnitines, including the isomers commonly monitored in screening metabolic disorders. To describe the structure of (butylated) acylcarnitines, a large number of computational molecular descriptors generated by software Dragon are subjected to variable selection methods aimed at identifying a small informative subset.

Near-field electrospinning of light-emitting conjugated polymer nanofibers.

The authors report on the realization of ordered arrays of light-emitting conjugated polymer nanofibers by near-field electrospinning. The fibers, made from poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylenevinylene], have diameters of a few hundreds of nanometers and their emission peaked at 560 nm. The observed blue-shift compared to the emission from reference films is attributed to different polymer packing in the nanostructures.

Impact of water quality on removal of carbamazepine in natural waters by N-doped TiO2 photo-catalytic thin film surfaces.

Photocatalytic experiments on the pharmaceutical pollutant carbamazepine (CBZ) were conducted using sol-gel nitrogen-doped TiO(2)-coated glass slides under a solar simulator. CBZ was stable to photodegradation under direct solar irradiation. No CBZ sorption to the catalyst surface was observed, as further confirmed by surface characterization using X-ray photoelectron spectroscopic analysis of N-doped TiO(2) surfaces.

Protective effects of flavanol-rich dark chocolate on endothelial function and wave reflection during acute hyperglycemia.

Nitric oxide plays a pivotal role in regulating vascular tone. Different studies show endothelial function is impaired during hyperglycemia. Dark chocolate increases flow-mediated dilation in healthy and hypertensive subjects with and without glucose intolerance; however, the effect of pretreatment with dark chocolate on endothelial function and other vascular responses to hyperglycemia has not been examined.

Quantitative structure/eluent-retention relationships in reversed-phase high-performance liquid chromatography based on the solvatochromic method.

Some predictive approaches aimed at modelling the combined effect of solute molecular structure and mobile phase composition on retention in reversed-phase high-performance chromatography (RP-HPLC) have been developed in the literature. These models are established for a given binary eluent (normally acetonitrile-water or methanol-water) by non-linear (curvilinear or artificial neural network) regression assuming as the mobile phase descriptor the volume fraction φ of the organic modifier. In the present investigation, we propose a model applicable simultaneously to acetonitrile-water and methanol-water eluents.

Cross-column retention prediction in reversed-phase high-performance liquid chromatography by artificial neural network modelling.

Linear solvation energy relationships (LSERs) are commonly applied to model the effect of solute structure on the retention of analytes in reversed-phase high-performance liquid chromatography (RP-HPLC). Standard LSER approaches can be used, in principle, to predict RP-HPLC behaviour of unknown analytes under fixed separation condition. However, as solute structure is the only source of variability described by the model, a LSER established for a given column/eluent pair cannot be transferred to external separation conditions.

Cross-column prediction of gas-chromatographic retention of polychlorinated biphenyls by artificial neural networks.

In this paper, we build a multiple-column retention model able to predict the behaviour of polychlorinated biphenyls (PCBs) in capillary gas-chromatography (GC) within a wide range of separation conditions. To this end, GC retention is related to both chemical structure of PCBs, encoded by selected theoretical molecular descriptors, and the kind of stationary phase, represented by the relative retention time (RRT) of a suitable small number of analytes. The model was generated using the retention data of 70 PCBs extracted from the pool of the 209 possible congeners collected on 17 different capillary columns featured by non-polar or moderately polar stationary phases, reported in the literature.

Multi-variable retention modelling in reversed-phase high-performance liquid chromatography based on the solvation method: a comparison between curvilinear and artificial neural network regression.

The linear solvation energy relationships (LSERs) have been widely used in the last decades for description and prediction of retention in reversed-phase high-performance liquid chromatography (RP-HPLC). LSERs are usually applied to model the effect of solute structure on the RP-HPLC retention at a fixed separation condition. Some authors by combining LSER with known empirical relationships relating retention with mobile phase composition of binary eluents (ϕ) have proposed a predictive model able to simultaneously relate RP-HPLC retention to both solute LSER descriptors and mobile phase composition.

Retention modelling of polychlorinated biphenyls in comprehensive two-dimensional gas chromatography.

In this paper, we use a quantitative structure-retention relationship (QSRR) method to predict the retention times of polychlorinated biphenyls (PCBs) in comprehensive two-dimensional gas chromatography (GC×GC). We analyse the GC×GC retention data taken from the literature by comparing predictive capability of different regression methods. The various models are generated using 70 out of 209 PCB congeners in the calibration stage, while their predictive performance is evaluated on the remaining 139 compounds.