Cytotoxicity and Antiviral Activities of Haplophyllum tuberculatum Essential Oils, Pure Compounds, and Their Combinations against Coxsackievirus B3 and B4.

Haplophyllum tuberculatum is a plant commonly used in folk medicine to treat several diseases including vomiting, nausea, infections, rheumatism, and gastric pains. In the current study, H. tuberculatum essential oils, hydrosols, the pure compounds R-(+)-limonene, S-(-)-limonene, and 1-octanol, as well as their combinations R-(+)-limonene/1-octanol and S-(-)-limonene/1-octanol, were screened for their cytotoxicity on HEp-2 cells after 24, 48, and 72 h, and then tested for their activity against Coxsackievirus B3 and B4 (CV-B3 and CV-B4) at 3 different moments: addition of the plant compounds before, after, or together with virus inoculation. Results showed that the samples were more cytotoxic after 72 h than after 24 h or 48 h cell contact. However, the combinations R-(+)-limonene/1-octanol and S-(-)-limonene/1-octanol showed less effect on HEp-2 cells than pure R-(+)-limonene and S-(-)-limonene after 24 h, 48 h, and 72 h. 1-octanol exhibited the highest concentration causing 50% cytotoxicity (CC50) on HEp-2 cells after 24 h (CC50 = 93 µg/mL) and 48 h (CC50 = 83 µg/mL). The antiviral assays showed that the tested samples exhibited potent inhibition of CV-B. IC50 values ranged from 0.66 µg/mL to 28.4 µg/mL. In addition, CV-B3 was more sensitive than CV-B4. Both CV-B strains are more inhibited when cells were pretreated with the plant compounds. The hydrosols have no effect, neither on HEp-2 cells nor on the virus. 1-octanol, S-(-), and R-(+)-limonene/1-octanol had important selectivity indexes over time. Although essential oils had potent antiviral activity, they can be considered for application in the pretreatment of cells. However, 1-octanol and the combinations are within the safety limits, and thus, they can be used as an active natural antiviral agent for CV-B3 and CV-B4 inhibition.

Quality Control of Herbal Medicines: From Traditional Techniques to State-of-the-art Approaches.

Herbal medicines are important options for the treatment of several illnesses. Although their therapeutic applicability has been demonstrated throughout history, several concerns about their safety and efficacy are raised regularly. Quality control of articles of botanical origin, including plant materials, plant extracts, and herbal medicines, remains a challenge. Traditionally, qualitative (e.g., identification and chromatographic profile) and quantitative (e.g., content analyses) markers are applied for this purpose. The compound-oriented approach may stand alone in some cases (e.g., atropine in Atropa belladonna). However, for most plant materials, plant extracts, and herbal medicines, it is not possible to assure quality based only on the content or presence/absence of one (sometimes randomly selected) compound. In this sense, pattern-oriented approaches have been extensively studied, introducing the use of multivariate data analysis on chromatographic/spectroscopic fingerprints. The use of genetic methods for plant material/plant extract authentication has also been proposed. In this study, traditional approaches are reviewed, although the focus is on the applicability of fingerprints for quality control, highlighting the most used approaches, as well as demonstrating their usefulness. The literature review shows that a pattern-oriented approach may be successfully applied to the quality assessment of articles of botanical origin, while also providing directions for a compound-oriented approach and a rational marker selection. These observations indicate that it may be worth considering to include fingerprints and their data analysis in the regulatory framework for herbal medicines concerning quality control since this is the foundation of the holistic view that these complex products demand.

LC-MS analysis combined with principal component analysis and soft independent modelling by class analogy for a better detection of changes in N-glycosylation profiles of therapeutic glycoproteins.

Therapeutic proteins are among the top selling drugs in the pharmaceutical industry. More than 60 % of the approved therapeutic proteins are glycosylated. Nowadays, it is well accepted that changes in glycosylation may affect the safety and the efficacy of the therapeutic proteins. For this reason, it is important to characterize both the protein and the glycan structures. In this study, analytical and data processing methods were developed ensuring an easier characterization of glycoprofiles. N-glycans were (i) enzymatically released using peptide-N-glycosidase F (PNGase F), (ii) reduced, and (iii) analyzed by hydrophilic interaction liquid chromatography coupled to a high-resolution mass spectrometer (HILIC-HRMS). Glycosylation changes were analyzed in human plasma immunoglobulin G samples which had previously been artificially modified by adding other glycoproteins (such as ribonuclease B and fetuin) or by digesting with enzyme (neuraminidase). Principal component analysis (PCA) and classification through soft independent modelling by class analogy (SIMCA) were used to detect minor glycosylation changes. Using HILIC-MS-PCA/SIMCA approach, it was possible to detect small changes in N-glycosylation, which had not been detected directly from the extracted-ion chromatograms, which is current technique to detect N-glycosylation changes in batch-to-batch analysis. The HILIC-MS-PCA/SIMCA approach is highly sensitive approach due to the sensitivity of MS and appropriate data processing approaches. It could help in assessing the changes in glycosylation, controlling batch-to-batch consistency, and establishing acceptance limits according to the glycosylation changes, ensuring safety and efficacy. Graphical abstract N-glycosylation characterization using LC-MS-PCA approach.

Targeted Isolation of Monoterpene Indole Alkaloids from Palicourea sessilis.

Phytochemical investigation of the alkaloid extract of Palicourea sessilis by LC-HRMS/MS using molecular networking and an in silico MS/MS fragmentation approach suggested the presence of several new monoterpene indole alkaloids. These compounds were isolated by semipreparative HPLC, and their structures confirmed by means of HRMS, NMR, and ECD measurements as 4-N-methyllyaloside (3), 4-N-methyl-3,4-dehydrostrictosidine (4), 4ß-hydroxyisodolichantoside (6), and 4α-hydroxyisodolichantoside (7), as well as the known alkaloids alline (1), N-methyltryptamine (2), isodolichantoside (5), and 5-oxodolichantoside (8). In addition, the acetylcholinesterase inhibitory activity of the compounds was evaluated up to 50 µM.

Antiplasmodial Activity, Cytotoxicity and Structure-Activity Relationship Study of Cyclopeptide Alkaloids.

Cyclopeptide alkaloids are polyamidic, macrocyclic compounds, containing a 13-, 14-, or 15-membered ring. The ring system consists of a hydroxystyrylamine moiety, an amino acid, and a ß-hydroxy amino acid; attached to the ring is a side chain, comprised of one or two more amino acid moieties. In vitro antiplasmodial activity was shown before for several compounds belonging to this class, and in this paper the antiplasmodial and cytotoxic activities of ten more cyclopeptide alkaloids are reported. Combining these results and the IC50 values that were reported by our group previously, a library consisting of 19 cyclopeptide alkaloids was created. A qualitative SAR (structure-activity relationship) study indicated that a 13-membered macrocyclic ring is preferable over a 14-membered one. Furthermore, the presence of a ß-hydroxy proline moiety could correlate with higher antiplasmodial activity, and methoxylation (or, to a lesser extent, hydroxylation) of the styrylamine moiety could be important for displaying antiplasmodial activity. In addition, QSAR (quantitative structure-activity relationship) models were developed, using PLS (partial least squares regression) and MLR (multiple linear regression). On the one hand, these models allow for the indication of the most important descriptors (molecular properties) responsible for the antiplasmodial activity. Additionally, predictions made for interesting structures did not contradict the expectations raised in the qualitative SAR study.

Aqueous size-exclusion chromatographic separations of intact proteins under native conditions: Effect of pressure on selectivity and efficiency.

The selectivity and separation efficiency of aqueous size-exclusion chromatographic separations of intact proteins were assessed for different flow rates, using columns packed with 3 and 5 µm silica particles containing 150 and 290 Å stagnant pores. A mixture of intact proteins with molecular weights ranging between 17 000 and 670 000 Da was used to construct the calibration curves. Both the model fit and the predictive properties, using a leave-one-out strategy, of different polynomial models (up to fifth order) were evaluated for different flow rates. The best compromise between model fit and predictive properties was obtained using a third-order polynomial model. The accuracy of the predictive properties decreased with 10% with an eightfold increase in the flow rate. No changes in retention factors (hence selectivity) were observed in the flow-rate range applied. A strong correlation between molecular weight and plate height was observed. Exclusion of large-molecular-weight proteins led to a significant reduction in the stationary-phase mass-transfer contribution to the total plate-height value, and this effect was also independent of the flow rate applied. The kinetic-performance limits, in terms of plate number and time, and optimal column-length particle-size combinations were determined at the maximum recommended operating pressure of the size-exclusion chromatography columns (20 MPa). Finally, the possibilities of method speed-up using ultra-high-pressure size-exclusion chromatography in combination with columns packed with sub-2 µm particles are discussed.

A chiral separation strategy for acidic drugs in capillary electrochromatography using both chlorinated and nonchlorinated polysaccharide-based selectors.

A generic chiral separation strategy for the analysis of acidic compounds in CEC is proposed in completion of an earlier defined strategy for nonacidic compounds. The screening step of this strategy uses a 45 mM ammonium formate (pH 2.9)/ACN (35/65, v/v) mobile phase, a temperature of 25°C, and an applied voltage of 15 kV. To update the screening step, eight chiral stationary phases, which all possessed chlorinated and nonchlorinated polysaccharide-based chiral selectors, were evaluated using the earlier defined screening conditions. A combination of the two types of polysaccharide-based chiral phases proved to have the highest cumulative success rate. In the updated screening step, amylose tris(3,5-dimethylphenylcarbamate) (ADH), cellulose tris(4-methylbenzoate) (OJH), cellulose tris(3,5-dichlorophenylcarbamate) (SP5), and cellulose tris(3,5-dimethylphenylcarbamate) (ODRH) were included as selectors and their preferred screening sequence was determined as ADH > OJH > SP5 > ODRH. New optimization steps were also defined for SP5 by investigating the influences of different parameters on the separation outcome using an experimental design approach. After application of the updated strategy, 15 of 17 acidic pharmaceuticals were separated under screening conditions, of which 9 were baseline resolved. When the optimization steps were applied, another three compounds were baseline separated, while the total number of separations was increased by one, which brings the total number of separations to 16 of 17 with 12 baseline separated compounds. This reflects the successful performance of the updated strategy on acidic compounds.

Three versus five micrometer chlorinated polysaccharide-based packings in chiral capillary electrochromatography: efficiency and precision evaluation.

In an earlier part of this study (performance evaluation) it was observed, for home-made capillary electrochromatography (CEC) columns, that smaller particle diameters do not always generate higher efficiencies. This phenomenon was further examined in this study, evaluating Van Deemter curves. Naphthalene and trans-stilbene oxide were analyzed on four 3 µm and four 5 µm chlorinated polysaccharide-based chiral stationary phases (CSPs) applying voltages ranging from 5 to 30 kV. Neither the 3 nor the 5 µm packings generated systematically the highest efficiencies. The varying column efficiencies were optimized by evaluating nine packing procedures for both 3 and 5 µm CSPs. Again it was observed that smaller particle-size packings were not necessarily beneficial for the efficiency of the CEC analysis. This observation was statistically evaluated. A variability study evaluated different precision estimates related to column packing and replicate measurement conditions. The best columns with the highest efficiencies (for chiral separations) and good precision, that is, the lowest RSD values, were generated by the packing procedure in which an MeOH-slurry and a water rinsing step of 8 h were applied.

Three versus five micrometer chlorinated polysaccharide-based packings in chiral capillary electrochromatography: performance evaluation.

In this study, a test set of 44 nonacidic compounds was analyzed on four 3 µm chlorinated polysaccharide-based chiral stationary phases with cellulose tris (3-chloro-4-methylphenylcarbamate) (Lux Cellulose-2®; LC2), amylose tris (5-chloro-2-methylphenylcarbamate) (Lux Amylose-2®, LA2), cellulose tris (4-chloro-3-methylphenylcarbamate) (Lux Cellulose-4®; LC4) and cellulose tris (3,5-dichlorophenylcarbamate) (Sepapak-5®, Sp5) as selectors. The analysis times, retention factors, efficiencies and enantioselectivities were compared with the results obtained on their 5 µm analogs. All 3 µm packings, except for LA2, individually separated more compounds than their 5 µm analogs. When the cumulative success rates on the 3 and 5 µm packings were considered, it was observed that they were similar for both particle sizes; the combination of three or four 5 µm columns separated one compound more from the considered test set than that of the same number of 3 µm columns. Furthermore, it was observed that the 3 and 5 µm packings showed some complementarity. Only four compounds were not separated on any of the columns, while the use of only either the 3 or 5 µm columns resulted in 10 and nine not-separated compounds, respectively. The analyses on 5 µm LC2 and Sp5 were faster than on their 3 µm analogs. For LC4 the 3 µm packing showed the shortest analysis times and diverse analysis times for both particle sizes were obtained on LA2. Furthermore, three out of four 3 µm packings, that is, LC2, LC4, and Sp5, were found to be more efficient than their 5 µm analogs.

Predictive-property-ranked variable reduction with final complexity adapted models in partial least squares modeling for multiple responses.

For partial least-squares regression with one response (PLS1), many variable-reduction methods have been developed. However, only a few address the case of multiple-response partial-least-squares (PLS2) modeling. The calibration performance of PLS1 can be improved by elimination of uninformative variables. Many variable-reduction methods are based on various PLS-model-related parameters, called predictor-variable properties. Recently, an important adaptation, in which the model complexity is optimized, was introduced in these methods. This method was called Predictive-Property-Ranked Variable Reduction with Final Complexity Adapted Models, denoted as PPRVR-FCAM or simply FCAM. In this study, variable reduction for PLS2 models, using an adapted FCAM method, FCAM-PLS2, is investigated. The utility and effectiveness of four new predictor-variable properties, derived from the multiple response PLS2 regression coefficients, are studied for six data sets consisting of ultraviolet-visible (UV-vis) spectra, near-infrared (NIR) spectra, NMR spectra, and two simulated sets, one with correlated and one with uncorrelated responses. The four properties include the mean of the absolute values as well as the norm of the PLS2 regression coefficients and their significances. The four properties were found to be applicable by the FCAM-PLS2 method for variable reduction. The predictive abilities of models resulting from the four properties are similar. The norm of the PLS2 regression coefficients has the best selective abilities, low numbers of variables with an informative meaning to the responses are retained. The significance of the mean of the PLS2 regression coefficients is found to be the least-selective property.

Amylose-3,5-dimethylphenylcarbamate immobilized on monolithic silica stationary phases for chiral separations in capillary electrochromatography.

Chiral monolithic silica capillary columns were prepared by immobilization of amylose-3,5-dimethylphenylcarbamate (ADMPC) bearing a small fraction of 3-(triethoxysilyl)propyl residues through intermolecular polycondensation of the triethoxysilyl groups. The obtained columns were used for chiral separations in capillary electrochromatography (CEC). The effects of the silica monolith nature and the used chiral selector concentration on the resulting enantiomeric separations were investigated. Fifteen chiral compounds, including acidic, neutral, and basic substances were evaluated and twelve showed partial or baseline separation at some of the different conditions tested. These results demonstrated the promising applicability of ADMPC-immobilized monolithic silica columns in CEC enantioseparations, but also revealed the need for further improvements on the level of baseline separations and efficiencies.

Modelling approaches for chiral chromatography on polysaccharide-based and macrocyclic antibiotic chiral selectors: A review.

An overview of molecular modelling approaches, related to chiral separations on polysaccharide-based and macrocyclic antibiotic chiral selectors, is presented. Both atomistic calculations and empirical fitting procedures are discussed. Atomistic calculations, such as docking and molecular dynamics can be used to model the interactions between enantiomers and the chiral stationary phase. This may help obtaining information about the chiral recognition mechanism. Conversely, in empirical fitting procedures, mathematical models for relevant separation parameters are fitted to experimental observations. The latter use theoretical molecular descriptors, calculated from the molecular structure, which are combined into a model to predict a given response, for example, retention. Such relationships, when used in chiral separations, are often called quantitative structure enantioselective retention relationships (QSERR) and an increased interest in them can be observed in the literature. Different regression models are discussed, such as multiple linear regression and partial least squares.

Secondary-metabolites fingerprinting of Argania spinosa kernels using liquid chromatography-mass spectrometry and chemometrics, for metabolite identification and quantification as well as for geographic classification.

Argan (Argania spinosa L.) fruit kernels' composition has been poorly studied and received less research intensity than the resulting Argan oil. The Moroccan Argan kernels contain a wealth of metabolites and can be investigated for nutritional and health aspects as well as for economic benefits. Ultra-Performance Liquid Chromatography Mass Spectrometry (UPLC-MS) was employed to trace the geographical origin of Argan kernels based on secondary-metabolite profiles. One-hundred and twenty Argan fruit kernels from five regions ('Agadir', 'Ait-Baha' 'Essaouira', 'Tiznit' and 'Taroudant') were studied. Characterization and quantification of 36 secondary metabolites (33 polyphenolic and 3 non-phenolic) were achieved. Those metabolites are highly influenced by the geographic origin. Then, the untargeted UPLC-MS fingerprint was decomposed by metabolomic data handling tools, such as multivariate curve resolution alternating least squares (MCR-ALS) and XCMS. The two resulting data matrices were pretreated and prepared separately by chemometric tools and then two data fusion strategies (low- and mid-levels) were applied on them. The four data sets were comparatively investigated. Principal component analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Soft Independent Modeling of Class Analogies (SIMCA) were used to classify samples. The exploration or classification models demonstrated a good ability to discriminate and classify the samples in the geographical-origin based classes. Summarized, the developed fingerprints and their metabolomics-based data handling successfully allowed geographical traceability evaluation of Moroccan Argan kernels.

Azepine-Indole Alkaloids From Psychotria nemorosa Modulate 5-HT2A Receptors and Prevent in vivo Protein Toxicity in Transgenic Caenorhabditis elegans.

Nemorosine A (1) and fargesine (2), the main azepine-indole alkaloids of Psychotria nemorosa, were explored for their pharmacological profile on neurodegenerative disorders (NDs) applying a combined in silico-in vitro-in vivo approach. By using 1 and 2 as queries for similarity-based searches of the ChEMBL database, structurally related compounds were identified to modulate the 5-HT2A receptor; in vitro experiments confirmed an agonistic effect for 1 and 2 (24 and 36% at 10 µM, respectively), which might be linked to cognition-enhancing properties. This and the previously reported target profile of 1 and 2, which also includes BuChE and MAO-A inhibition, prompted the evaluation of these compounds in several Caenorhabditis elegans models linked to 5-HT modulation and proteotoxicity. On C. elegans transgenic strain CL4659, which expresses amyloid beta (Aß) in muscle cells leading to a phenotypic paralysis, 1 and 2 reduced Aß proteotoxicity by reducing the percentage of paralyzed worms to 51%. Treatment of the NL5901 strain, in which α-synuclein is yellow fluorescent protein (YFP)-tagged, with 1 and 2 (10 µM) significantly reduced the α-synuclein expression. Both alkaloids were further able to significantly extend the time of metallothionein induction, which is associated with reduced neurodegeneration of aged brain tissue. These results add to the multitarget profiles of 1 and 2 and corroborate their potential in the treatment of NDs.

Capillary methods for drug analysis.

This review gives an overview of the applicability of capillary electrophoresis, capillary liquid chromatography, capillary electrochromatography, and their derived techniques to analyze drug impurity mixtures, formulations, biological samples, and chiral compounds. For each application type, a few examples are given to illustrate the potential of the capillary technique. Details are provided about the capillaries used, chiral selectors, and stationary and mobile phases.

Four Pistacia atlantica subspecies (atlantica, cabulica, kurdica and mutica): A review of their botany, ethnobotany, phytochemistry and pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: Pistacia atlantica (wild pistachio) belongs to the Anacardiaceae family, and growing from the Mediterranean basin to central Asia, especially in Iran, Turkey, Iraq and Saudi Arabia where it is extensively used in traditional medicine for a wide range of ailments related to relieving upper abdominal discomfort and pain, dyspepsia and peptic ulcer. OBJECTIVE: Despite the diverse biological activities of P. atlantica, there is no current review summarizing medicinal properties of its subspecies, including cabulica, kurdica and mutica. Thus, this paper aims to explore the current understanding of the chemical, pharmacological, and biochemical properties of the extracts and the main active constituents found in each subspecies of this plant. METHODS: Peer-reviewed articles, using "Pistacia atlantica" as search term (″all fields″), were retrieved from Scifinder, Pubmed, Science direct, Wiley, Springer, ACS, Scielo, Web of Science and other web search instruments (Google Scholar, Yahoo search). Papers published until July 2020 are considered. In addition, various books were consulted that contained botanical and ethnopharmacological information. The information provided in this review is based on peer-reviewed papers in English and French. RESULTS: Phytochemical studies have shown the presence of numerous valuable compounds, including volatile compounds, flavonoids, phenolic compounds, fatty acids, tocopherols and phytosterols. P. atlantica contains also minerals and trace elements, like iron, lead, copper, potassium, sodium and calcium; fatty acids, like oleic, linoleic, and palmitic acid; fat-soluble vitamins, such as α, ß, γ and δ tocopherols; phytosterols, like betasitosterol, stigmasterol, campesterol and Δ5-avenasterol. Crude extracts and isolated compounds from P. atlantica show a wide range of pharmacological properties, such as antimicrobial, antifungal, anti-inflammatory, analgesic, antinociceptive, wound healing, anticancer, cytotoxic, anticholinesterase, antidiabetic, hepatoprotective, urease inhibition, antihypertension, nipple fissure healing, antileishmanial and antiplasmodial activities. However, there are no reports summarizing the P. atlantica bioactivity, its therapeutic value, and the roles played by each of the numerous phytoconstituents. CONCLUSION: Many traditional uses of P. atlantica and its subspecies have now been confirmed by pharmacologic research. Systematic phytochemical investigation of the P. atlantica subspecies and the pharmacological properties, especially the mechanisms of action and toxicology, to illustrate their ethnomedicinal use, to explore the therapeutic potential and support further health-care product development, will undoubtedly be the focus of further research. Therefore, detailed and extensive studies and clinical evaluation of P. atlantica subspecies should be carried out in future for the safety approval of therapeutic applications.

In Vitro & In Vivo Anti-Hyperglycemic Potential of Saponins Cake and Argan Oil from Argania spinosa.

The Argan tree (Argania spinosa. L) is an evergreen tree endemic of southwestern Morocco. For centuries, various formulations have been used to treat several illnesses including diabetes. However, scientific results supporting these actions are needed. Hence, Argan fruit products (i.e., cake byproducts (saponins extract) and hand pressed Argan oil) were tested for their in-vitro anti-hyperglycemic activity, using α-glucosidase and α-amylase assays. The in-vivo anti-hyperglycemic activity was evaluated in a model of alloxan-induced diabetic mice. The diabetic animals were orally administered 100 mg/kg body weight of aqueous saponins cake extract and 3 mL/kg of Argan oil, respectively, to evaluate the anti-hyperglycemic effect. The blood glucose concentration and body weight of the experimental animals were monitored for 30 days. The chemical properties and composition of the Argan oil were assessed including acidity, peroxides, K232, K270, fatty acids, sterols, tocopherols, total polyphenols, and phenolic compounds. The saponins cake extract produced a significant reduction in blood glucose concentration in diabetic mice, which was better than the Argan oil. This decrease was equivalent to that detected in mice treated with metformin after 2-4 weeks. Moreover, the saponins cake extract showed a strong inhibitory action on α-amylase and α-glucosidase, which is also higher than that of Argan oil.

UPLC-PDA-ESI-QTOF-MS/MS and GC-MS analysis of Iranian Dracocephalum moldavica L.

Dracocephalum moldavica L. is a significant component in the Iranian food basket. This study aimed to investigate the bioactive compounds and biological activities of different extracts obtained from D. moldavica aerial parts. From the aerial parts, a crude methanolic (MeOH) extract and its four sub-fractions, that is, petroleum ether (Pet), ethyl acetate (EtOAc), n-butanol (n-BuOH), and aqueous (water) extracts were obtained. The total phenolic and flavonoid contents as well as the antioxidant and cytotoxic activities of the extracts were determined. Moreover, the phytochemical profiles of the essential oil (EO) and of those extracts with the highest antioxidant activity measured by GC/MS and UPLC-PDA-ESI-QTOF-MS/MS. Results showed that the highest concentrations of phenols and flavonoids as well as the most potent antioxidant potential according to the DPPH method were determined in the EtOAc and MeOH extracts with IC50 values of 22.0 and 34.4 µg.ml-1, respectively. Quantitative analysis of these extracts was subsequently performed by UPLC-PDA-ESI-QTOF-MS/MS. Both extracts contained mainly rosmarinic acid, caffeic acid, and 2-hydroxycinnamic acid, which may be responsible for their high antioxidant activity. Moreover, none of the extracts showed cytotoxic effects against MCF7, SW48, and a normal cell line of mouse embryonic fibroblast cells (NIH/3T3) in the tested concentrations (up to 400 µg.ml-1). Additionally, GC-MS analysis showed that oxygenated monoterpenes (55.4%) were the main constituents of the EO of D. moldavica.

New insights into the Argan oil categories characterization: Chemical descriptors, FTIR fingerprints, and chemometric approaches.

The characterization of Argan oils to classify them in three categories ('Extra Virgin', 'Virgin' and 'Lower quality') was evaluated. A total of 120 Moroccan Argan oils samples from the Taroudant Argan forest was investigated. The free acidity, peroxide value, spectrophotometric indices (K232 and K270), fatty acids, sterols, and tocopherol contents were assessed. The samples were also scanned by FTIR spectroscopy. The Principal Component Analysis (PCA) and four classification methods, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modelling of Class Analogy (SIMCA), K-nearest Neighbors (KNN), and Support Vector Machines (SVM), were applied on both the chemical and spectral data. Besides the conventional chemical profiling, FTIR spectra were evaluated for their feasibility as a rapid non-invasive approach for classifying and predicting the oil quality categories. The most important variables for differentiating the oil categories were identified as K232, peroxide value, É£-tocopherol, δ-tocopherol, acidity, stigma-8-22-dien-3ß-ol, stearic acid (C18:0) and linoleic acid (C18:2) and could be used as quality indicators. Eight chemical descriptors or key features from the FTIR spectra (selected by interval-PLS) could also be established as indicators of quality and freshness of Argan oils.

Improvement of quantitative structure-retention relationship models for chromatographic retention prediction of peptides applying individual local partial least squares models.

In Reversed-Phase Liquid Chromatography, Quantitative Structure-Retention Relationship (QSRR) models for retention prediction of peptides can be built, starting from large sets of theoretical molecular descriptors. Good predictive QSRR models can be obtained after selecting the most informative descriptors. Reliable retention prediction may be an aid in the correct identification of proteins/peptides in proteomics and in chromatographic method development. Traditionally, global QSRR models are built, using a calibration set containing a representative range of analytes. In this study, a strategy is presented to build individual local Partial Least Squares (PLS) models for peptides, based on selected local calibration samples, most similar to the specific query peptide to be predicted. Similar local calibration peptides are selected from a possible calibration set. The calibration samples with the lowest Euclidian distances to the query peptide are considered as most similar. Two Euclidian distances are investigated as similarity parameter, (i) in the autoscaled descriptor space and, (ii) in the PLS factor space of the global calibration samples, both after variable selection by the Final Complexity Adapted Models (FCAM) method. The predictive abilities of individual local QSRR PLS models for peptides, developed with both Euclidian distances, are found significantly better than those of two global models, i.e. before and after FCAM variable selection. The predictive abilities of the local models, developed with distances calculated in the PLS factor space, were best.