Chemical compositions of Eucalyptus sp. Essential oils and the evaluation of their combinations as a promising treatment against ear bacterial infections.

BACKGROUND: The chemical composition and biological activities of Eucalyptus essential oils (EOs) have been documented in numerous studies against multiple infectious diseases. The antibacterial activity of individual Eucalyptus EOs against strains that cause ear infections was investigated in our previous study. The study's antibacterial activity was promising, which prompted us to explore this activity further with EO blends. METHODS: We tested 15 combinations (9 binary combinations and 6 combinations of binary combinations) of Eucalyptus EOs extracted by hydrodistillation from eight Tunisian Eucalyptus species dried leaves against six bacterial strains responsible for ear infections: three bacterial isolates (Haemophilus influenzae, Haemophilus parainfluenzae, and Klebsiella pneumoniae) and three reference bacteria strains (Pseudomonas aeruginosa, ATTC 9027; Staphylococcus aureus, ATCC 6538; and Escherichia coli, ATCC 8739). The EOs were analyzed using GC/FID and GC/MS. The major compounds, as well as all values obtained from the bacterial growth inhibition assay, were utilized for statistical analysis. RESULTS: The antibacterial activity of the EO blends exhibited significant variation within Eucalyptus species, bacterial strains, and the applied methods. Principal component analysis (PCA) and hierarchical cluster analysis (HCA), based on the diameters of the inhibition zone, facilitated the identification of two major groups and ten subgroups based on the level of antibacterial activity. The highest antibacterial activity was observed for the mixture of EOs extracted from E. panctata, E. accedens, and E. cladoclayx (paac) as well as E. panctata, E. wandoo, E. accedens, and E. cladoclayx (pwac) using the disc diffusion method. Additionally, significant activity was noted with EOs extracted from E. panctata, E. wandoo (pw) and E. panctata, E. accedens (pa) using the broth microdilution method. CONCLUSION: Our findings suggest that certain EO combinations (paac, pwac, pw, and pa) could be considered as potential alternative treatment for ear infections due to their demonstrated highly promising antibacterial activities.

Chemical Characterization of the Essential Oil Compositions of Mentha spicata and M. longifolia ssp. cyprica from the Mediterranean Basin and Multivariate Statistical Analyses.

This present study aims to characterize the essential oil compositions of the aerial parts of M. spicata L. and endemic M. longifolia ssp. cyprica (Heinr. Braun) Harley by using GC-FID and GC/MS analyses simultaneously. In addition, it aims to perform multivariate statistical analysis by comparing with the existing literature, emphasizing the literature published within the last two decades, conducted on both species growing within the Mediterranean Basin. The major essential oil components of M. spicata were determined as carvone (67.8%) and limonene (10.6%), while the major compounds of M. longifolia ssp. cyprica essential oil were pulegone (64.8%) and 1,8-cineole (10.0%). As a result of statistical analysis, three clades were determined for M. spicata: a carvone-rich chemotype, a carvone/trans-carveol chemotype, and a pulegone/menthone chemotype, with the present study result belonging to the carvone-rich chemotype. Carvone was a primary determinant of chemotype, along with menthone, pulegone, and trans-carveol. In M. longifolia, the primary determinants of chemotype were identified as pulegone and menthone, with three chemotype clades being pulegone-rich, combined menthone/pulegone, and combined menthone/pulegone with caryophyllene enrichment. The primary determinants of chemotype were menthone, pulegone, and caryophyllene. The present study result belongs to pulegone-rich chemotype.

Application of sandpaper spray ionization mass spectrometry to comprehensively examine maple leaves infected with distinct fungi.

This study describes a novel application for sandpaper spray ionization mass spectrometry (SPS-MS), to examine the surface of maple tree (Acer sp.) leaves. By comparing mass spectrometry fingerprints, healthy leaves from those infected with powdery mildew and Rhytisma acerinum were distinguished. Leaves were grated with sandpaper, cut into triangles, and placed before the mass spectrometer, with the addition of a methanol-formic acid solution. Multivariate statistical analysis categorized the samples into three groups. Overall, SPS-MS effectively analyzed leaves with infectious microorganisms, potentially aiding in the creation of fungal identification databanks.

Raman developmental markers in root cell walls are associated with lodging tendency in tef.

MAIN CONCLUSION: Using Raman micro-spectroscopy on tef roots, we could monitor cell wall maturation in lines with varied genetic lodging tendency. We describe the developing cell wall composition in root endodermis and cylinder tissue. Tef [Eragrostis tef (Zucc.) Trotter] is an important staple crop in Ethiopia and Eritrea, producing gluten-free and protein-rich grains. However, this crop is not adapted to modern farming practices due to high lodging susceptibility, which prevents the application of mechanical harvest. Lodging describes the displacement of roots (root lodging) or fracture of culms (stem lodging), forcing plants to bend or fall from their vertical position, causing significant yield losses. In this study, we aimed to understand the microstructural properties of crown roots, underlining tef tolerance/susceptibility to lodging. We analyzed plants at 5 and 10 weeks after emergence and compared trellised to lodged plants. Root cross sections from different tef genotypes were characterized by scanning electron microscopy, micro-computed tomography, and Raman micro-spectroscopy. Lodging susceptible genotypes exhibited early tissue maturation, including developed aerenchyma, intensive lignification, and lignin with high levels of crosslinks. A comparison between trellised and lodged plants suggested that lodging itself does not affect the histology of root tissue. Furthermore, cell wall composition along plant maturation was typical to each of the tested genotypes independently of trellising. Our results suggest that it is possible to select lines that exhibit slow maturation of crown roots. Such lines are predicted to show reduction in lodging and facilitate mechanical harvest.

Hydrogeochemical and multivariate statistical approaches to investigate the characteristics of groundwater quality in fluoride-enriched hard rock region in Tirupathur district of Tamil Nadu, India.

Fluoride pollution is a major issue worldwide, posing health risks such as dental and skeletal fluorosis. This study was conducted in fluoride enrichment hard rock regions of Vaniyambadi and Ambur talks in Tirupathur district, Tamil Nadu. Four hundred eighty groundwater samples were collected from May 2021 to April 2022 and grouped as summer, southwest monsoon (SWM), northeast monsoon (NEM), and winter. Maximum concentration of fluoride was found to be 4 mg/L in the summer season in Vellakuttai region of Vaniyambadi taluk. The study aims to investigate the hydrogeochemical process and mechanism influencing groundwater chemistry and it also provides the confirmation of exploratory data analysis in groundwater quality using structural equation modeling. The Piper and Gibbs diagrams illustrate the rock-water interaction and anthropogenic sources that contribute to the NaHCO3 and NaCl-type waters, respectively. Multivariate statistical analysis such as hierarchical cluster analysis (HCA), principal component analysis (PCA), multiple linear regression (MLR), and structural equation modeling (SEM) has been carried out to determine the groundwater quality. HCA manifests the nature and sources of groundwater, whereas PCA divides all the physicochemical parameters into two PC loadings, accounting for 97.46%, 99.46%, 99.18%, and 98.93% of cumulative % of variance during the summer, SWM, NEM, and winter seasons, respectively. PC1 has a higher loading factor to Cl, Ca, and Mg, whereas PC2 has a higher loading factor to Na, HCO3, SO4, and NO3. The results of the MLR model provide higher accuracy in detecting the contamination factors associated with the environment and natural rocks. SEM revealed the goodness-of-fit indices 0.993, 0.999, 1.000, and 0.999 in summer, SWM, NEM, and winter, respectively. Hence, this study provides insight view of variation of fluoride concentration in groundwater in different seasons and also mentions the factors that influence fluoride concentration in Vaniyambadi and Ambur taluk.

ATR-FTIR combined with machine learning for the fast non-targeted screening of new psychoactive substances.

Due to the diversity and fast evolution of new psychoactive substances (NPS), both public health and safety are threatened around the world. Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), which serves as a simple and rapid technique for targeted NPS screening, is challenging with the rapid structural modifications of NPS. To achieve the fast non-targeted screening of NPS, six machine learning (ML) models were constructed to classify eight categories of NPS, including synthetic cannabinoids, synthetic cathinones, phenethylamines, fentanyl analogues, tryptamines, phencyclidine types, benzodiazepines, and "other substances" based on the 1099 IR spectra data items of 362 types of NPS collected by one desktop ATR-FTIR and two portable FTIR spectrometers. All these six ML classification models, including k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), extra trees (ET), voting, and artificial neural networks (ANNs) were trained through cross validation, and f1-scores of 0.87-1.00 were achieved. In addition, hierarchical cluster analysis (HCA) was performed on 100 synthetic cannabinoids with the most complex structural variation to investigate the structure-spectral property relationship, which leads to a summary of eight synthetic cannabinoid sub-categories with different "linked groups". ML models were also constructed to classify eight synthetic cannabinoid sub-categories. For the first time, this study developed six ML models, which were suitable for both desktop and portable spectrometers, to classify eight categories of NPS and eight synthetic cannabinoids sub-categories. These models can be applied for the fast, accurate, cost-effective, and on-site non-targeted screening of newly emerging NPS with no reference data available.

Analysis of Metabolites and Metabolic Pathways of Three Chinese Jujube Cultivar.

Most studies on metabolites in jujube fruits focus on specific types of metabolites, but there are only a few comprehensive reports on the metabolites in jujube fruits. In order to understand the variance of metabolites in fruits of different jujube varieties. The objective of this study was to explore the metabolic components of jujube fruit by comparing three cultivars, namely Linyi LiZao (LZ), Jiaocheng SuantianZao (STZ), and Xianxian Muzao (MZ). The metabolites present in the fruits of these three cultivars were evaluated and compared. The results revealed the detection of 1059 metabolites across the three jujube varieties, with each cultivar exhibiting distinct metabolic characteristics. Notably, MZ exhibited a higher abundance of six metabolite classes, namely amino acids and derivatives, flavonoids, lipids, organic acids, phenolic acids, and terpenoids, compared to LZ. Conversely, LZ exhibited higher concentrations of alkaloids, lignans, coumarins, nucleotides, and their derivatives compared to the other two cultivars. In terms of STZ, its content of amino acids and derivatives, lignans and coumarins, organic acids, and phenolic acids was largely similar to that of LZ. However, the content of alkaloids, nucleotides, and their derivatives, and terpenoids was significantly higher in STZ compared to LZ. Additionally, STZ exhibited lower levels of flavonoids and lipids compared to LZ. Moreover, MZ was found to be less nutritionally rich than STZ, except for lignans and coumarins, as it displayed lower levels of all the metabolites. KEGG pathway enrichment analysis revealed six significantly different metabolic pathways (p < 0.05) between LZ and MZ, including arginine and proline metabolism, sphingolipid metabolism, flavonoid biosynthesis, glutathione metabolism, glycerophospholipid metabolism, and cysteine and methionine metabolism. The metabolites in STZ and MZ exhibited three significantly different pathways (p < 0.05), primarily associated with flavonoid biosynthesis, arginine and proline metabolism, and sphingolipid metabolism. The significantly differential metabolites between LZ and STZ were observed in the phenylpropionic acid biosynthesis pathway and the ubiquinone and other terpenoid-quinone biosynthesis pathways. LZ showed a closer relationship with STZ than with MZ. STZ and LZ exhibited higher medicinal values, while LZ had lower acidity and MZ displayed better antioxidant activity. This study presents the first thorough analysis of metabolites in LZ, STZ, and MZ cultivars, which can serve as a theoretical basis for quality analysis, functional research, and classification processing of jujube fruit.

Contextualizing bilateral asymmetry and gender: A multivariate approach to femoral cross-sectional geometry at rural Medieval Pieve di Pava, Italy.

OBJECTIVES: Our objective was to identify the relationship between biocultural factors of sex-gender and age and patterns of femoral cross-sectional geometry with historical evidence about labor and activity from an archeological skeletal sample excavated from the rural Medieval site Pieve di Pava. MATERIALS AND METHODS: The study site, Pieve di Pava, was a rural parish cemetery in Tuscany with osteoarcheological remains from the 7th to 12th centuries. Cross-sectional geometric analysis of femora from 110 individuals dated to the 10th-12th centuries were used to examine trends in bone quantity, shape, and bending strength between age and sex groups, as well as in clusters identified through Hierarchical Cluster Analysis (HCA). RESULTS: Overall, our study sample showed remarkable heterogeneity and our cluster analysis revealed a complex underlying structure, indicating that divisions of labor did not follow a strict gender binary in our sample. We found high levels of bilateral asymmetry in our sample in multiple cross-sectional areas for a significant proportion of the population. We found minimal differences between age groups or sex. DISCUSSION: Our results suggest that males and females had varied experiences of labor and work during their lives that did not reflect the strict binary gender roles sometimes documented for medieval Europe. One important axis of difference is the direction and magnitude of bilateral asymmetry observed in our femur sample, which is associated with divergent trends in section moduli and bone area measures.

Using Canadian Water Quality Index method to evaluate the spatio-variation of water quality and the impacts of quality parameters: a case study of Amasya's surface water (Northern Turkey).

In this study, the spatial variation of water quality in Yesilirmak River passing through Amasya was investigated using the Canadian Water Quality Index (CWQI). For this aim, the measured 15 parameters in 3-month periods between the years 2008 and 2015 were used at 11 sample points from the Yesilirmak River and its tributaries. The calculated CWQI scores using parameters of pH, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), ammonia, ammonium, nitrite, nitrate, phosphate, iron, copper, zinc, potassium, sulfate, sulfite and chlorine range from 33 to 64. These scores indicate that the surface waters in the studied area are poor to marginal in quality. The effect of each parameter on the CWQI scores by excluding each parameter, one by one, considering the water quality of the Yesilirmak River was investigated using the Hierarchical Cluster Analysis (HCA) method. It was determined that the presence and/or absence of the parameters, which caused an increase or decrease in CWQI scores, were ammonia, phosphate, COD, sulfide, iron, ammonium, nitrite, DO. On the other hand, the parameters having positive effects on CWQI are nitrate, chlorine and potassium. The HCA statistical analysis method is suitable for interpreting complex water quality datasets and understanding time/location dependent changes in water quality. HCA can be used effectively to group parameters in river water quality monitoring programs.

[Quality evaluation of Fufang Jinqiancao granules based on ultra performance liquid chromatography-ultraviolet detection quantitative fingerprint combined with chemical pattern recognition].

Fufang Jinqiancao granules have a large market demand due to the fact that they contain diuretics, inhibit urinary calculi formation, and exhibit both anti-inflammatory and antioxidant effects. In the current study, a fast and efficient quantitative ultra performance liquid chromatography-ultraviolet detection (UPLC-UV) fingerprinting method was established to analyze the Fufang Jinqiancao granules, while a chemical pattern recognition technology was used to evaluate the quality of the granules over different years. More specifically, the UPLC-UV system consisted of a Waters Acquity UPLC BEH C18 column (100 mm×2.1 mm, 1.7 µm), acetonitrile (mobile phase A), and a 0.1% formic acid aqueous solution (mobile phase B), wherein a gradient elution protocol was followed. Ultra performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF-MS, Agilent Infinity Ⅱ 1290-6545) was used in combination with reference substances and literature comparisons to identify the common peaks present in the quantitative fingerprint. The fingerprints of 35 batches of Fufang Jinqiancao granules were established by means of the quantitative UPLC-UV fingerprinting method, and the fingerprint data obtained for these samples were further analyzed by chemical pattern recognition techniques, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). The quality difference markers, namely mangiferin and isomangiferin, were screened, and their contents were determined. It was found that 12 common peaks existed in the fingerprint of the Fufang Jinqiancao granules, and the similarities of all 35 batches of samples were greater than 0.952. In addition, for the purpose of HCA, the 35 batches were divided into two categories, of which sample years 2018 and 2019 belonged to one category, and sample years 2020 and 2021 belonged to another category. Notably, PCA gave the same clustering trends as HCA. Based on the obtained results, the mangiferin and isomangiferin components responsible for the differences between the 2018, 2019 and 2020, 2021 samples were further screened by orthogonal partial least squares discriminant analysis (OPLS-DA). Moreover, the contents of the 35 batches of samples were determined using the two differential markers mangiferin and isomangiferin as indicators. The obtained results indicated that the chromatographic peaks of all 35 batches had acceptable resolutions, with mangiferin exhibiting a good linear relationship in the range of 5.3291-133.2276 mg/L, and isomangiferin exhibiting a similar linear relationship in the range of 4.1847-104.6170 mg/L. The average recovery of mangiferin was 101.7%-105.6%, with a relative standard deviation (RSD) of 0.63%-1.43%, while that of isomangiferin was 103.4%-105.5%, with an RSD of 0.60%-1.18%. Importantly, all RSD values were less than 1.43%, thereby indicating that our method meets the requirements of the Chinese Pharmacopoeia (2020 Edition). Among the 35 batches of samples, the contents of mangiferin and isomangiferin were higher in the 2020 and 2021 samples, and the content fluctuation range was smaller. Overall, the development of an accurate and reliable quality control method for Fufang Jinqiancao granules, and a reasonable and effective quality evaluation of Fufang Jinqiancao granule samples from different years was realized. We therefore expect that this study will provide a reference for establishing a more systematic and comprehensive quality control system.

Elucidation of Analytical-Compositional Fingerprinting of Three Different Species of Chili Pepper by Using Headspace Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry Analysis, and Sensory Profile Evaluation.

The aim of the present study was to determine the volatile compounds of three different species of chili peppers, using solid-phase microextraction (SPME) methods in combination with gas chromatography-mass spectrometry (GC-MS). The detection of marker aroma compounds could be used as a parameter to differentiate between species of chili peppers for their detection and traceability in chili pepper food. The sensorial contribution was also investigated to identify the predominant notes in each species and to evaluate how they can influence the overall aroma. Three different pepper species belonging to the Capsicum genus were analyzed: Chinense, Annuum, and Baccatum. A total of 269 volatile compounds were identified in these species of chili peppers. The Capsicum annum species were characterized by a high number of acids and ketones, while the Capsicum chinense and Capsicum baccatum were characterized by esters and aldehydes, respectively. The volatile profile of extra virgin olive oils (EVOOs) flavored with chili peppers was also investigated, and principal component analysis (PCA) and hierarchical cluster analysis (HCA) of the volatile profiles were demonstrated to be a powerful analytical strategy for building a model that highlights the potential of a volatile characterization approach for use in evaluating food traceability and authenticity.

The effects of different protease treatments on the techno-functional, structural, and bioactive properties of bovine casein.

In this study, bovine sodium caseinate (NaCas) was hydrolyzed with four proteases, alcalase, savinase, subtilisin A, and flavourzyme. In addition to the structural changes occurred through the enzymatic hydrolysis, the solubility, oil binding capacity, zeta potential, emulsification properties, and in vitro antioxidant capacity, anti-carcinogenic and antidiabetic properties of hydrolysates were determined. FTIR combined with hierarchical cluster analysis (HCA) made in Amide I region enable to classification of the samples based on the changes of the secondary structure depending on the enzyme type and degree of fragmentation. Technological properties of NaCas were enhanced through the enzymatic hydrolysis, and those were more prominent in serine-type enzymes, regardless of the enzyme type, all hydrolysates showed high antioxidant capacities. All hydrolysates, specifically those produced by savinase and alcalase, reduced the viability of the carcinogenic Caco-2 cells in a dose-dependent manner and showed a very low level of cytotoxicity against healthy HEK-293 cells. The hydrolysis treatment made a significant contribution to the antidiabetic activity of NaCas. Particularly alcalase and savinase hydrolysates suppressed the activity of α- amylase and α- glucosidase. Therefore, the generated milk protein hydrolysates could be used in functional food developments for specific dietary purposes.

HS-SPME-GC-MS Volatile Profile Characterization of Peach (Prunus persica L. Batsch) Varieties Grown in the Eastern Balkan Peninsula.

The volatile compounds of eight peach varieties (Prunus persica L.)-"Filina", "Gergana", "Ufo-4", "July lady", "Laskava", "Flat Queen", "Evmolpiya", and "Morsiani 90"-growing in Bulgaria were analyzed for the first time. Gas chromatography-mass spectrometry (GC-MS) analysis and the HS-SPME technique revealed the presence of 65 volatile compounds; the main identified components were aldehydes, esters, and fatty acids. According to the provided principal component analysis (PCA) and hierarchical cluster analysis (HCA), the relative quantities of the identified volatile compounds depended on the studied peach variety. The results obtained could be successfully applied for the metabolic chemotaxonomy of peaches.

Monitoring of Hazelnut oil quality during thermal processing in comparison with extra virgin olive oil by using ATR-FTIR spectroscopy combined with chemometrics.

Hazelnut oil (HO), which is not widely used because its healthy properties are not fully known yet, is an excellent nutrient due to its high content of monounsaturated fatty acids and antioxidants. In this study, the effects of thermal processing on the quality of HO in comparison to extra virgin olive oil (EVOO), which is one of the healthiest and heat-resistant oils, were investigated using Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. Oil samples were heated at a frying temperature (180 °C) for 24 h in periods of 8 h per day and alterations in the spectra of these oils sampled every 2 h were evaluated. The heating process caused decreases in the areas of the bands at 3007 and 722 cm-1 and the area ratios of 3007/2854 and 722/2854 cm-1 and increases in the areas of the bands at 987 and 965 cm-1 and the area ratio of 965/2854 cm-1 in both oils suggesting the conjugation and cis-trans isomerization of unsaturated fatty acids. In addition, heating caused increases in the areas of the bands at 3475 and 1744 cm-1 and the ratios of 3475/2854 cm-1 and 1744/2854 cm-1, a shift to a lower value in the wavenumber and a broadening of the 1744 cm-1 band indicating the formation of primary and secondary oxidation products in the heated oils, which were also supported by chemical studies. Most of these changes began earlier in EVOO and all occurred to a higher extent, revealing that HO has a higher thermal stability than EVOO. Principal component analysis and hierarchical cluster analysis confirmed that HO is more resistant to heat than EVOO. These results showed that HO is superior to EVOO and it could be used for frying as a healthier and cheaper oil alternative. This study also indicated that oil oxidation could be monitored easily and rapidly via ATR-FTIR spectroscopy.

An Evaluation of the Potential of Essential Oils against SARS-CoV-2 from In Silico Studies through the Systematic Review Using a Chemometric Approach.

Essential oils (EOs) and their compounds have attracted particular attention for their reported beneficial properties, especially their antiviral potential. However, data regarding their anti-SARS-CoV-2 potential are scarce in the literature. Thus, this study aimed to identify the most promising EO compounds against SARS-CoV-2 based on their physicochemical, pharmacokinetic, and toxicity properties. A systematic literature search retrieved 1669 articles; 40 met the eligibility criteria, and 35 were eligible for analysis. These studies resulted in 465 EO compounds evaluated against 11 human and/or SARS-CoV-2 target proteins. Ninety-four EO compounds and seven reference drugs were clustered by the highest predicted binding affinity. Furthermore, 41 EO compounds showed suitable drug-likeness and bioactivity score indices (≥0.67). Among these EO compounds, 15 were considered the most promising against SARS-CoV-2 with the ADME/T index ranging from 0.86 to 0.81. Some plant species were identified as EO potential sources with anti-SARS-CoV-2 activity, such as Melissa officinalis Arcang, Zataria multiflora Boiss, Eugenia brasiliensis Cambess, Zingiber zerumbet Triboun & K.Larsen, Cedrus libani A.Rich, and Vetiveria zizanoides Nash. Our work can help fill the gap in the literature and guide further in vitro and in vivo studies, intending to optimize the finding of effective EOs against COVID-19.

Volatile Composition and Biological Activity of Jordanian Commercial Samples of R. coriaria L. Fruits.

The present paper reports the GC-HS-SPME analysis of volatile emission and GC-MS analysis of chemical composition of essential oil of R. coriaria fruits of eight different samples of R. coriaria L. fruits ("sumac" folk name), collected from Jordanian agricultural field and the local market. The analyses show an important variability among the Sumac samples probably due to the origin, cultivation, harvesting period, drying, and conservation of the plant material. The main class of component present in all samples was monoterpenes (43.1 to 72.9%), except for one sample which evidenced a high percentage of sesquiterpene hydrocarbons (38.5%). The oxygenated monoterpenes provided a contribution to total class of monoterpenes ranging from 10.1 to 24.3%. A few samples were rich in monoterpene hydrocarbons. Regarding the single components present in all the volatile emissions, ß-caryophyllene was the main compound in most of the analyzed samples, varying from 34.6% to 7.9%. Only two samples were characterized by α-pinene as the main constituent (42.2 and 40.8% respectively). Essential oils were collected using hydro-distillation method. Furfural was the main constituent in almost all the analyzed EOs (4.9 to 48.1%), except in one of them, where ß-caryophyllene was the most abundant one. ß-caryophyllene ranged from 1.2 to 10.6%. Oxygenated monoterpenes like carvone and carvacrol ranged from 3.2-9.1% and 1.0-7.7% respectively. Cembrene was present in good amount in EO samples EO-2 to EO-8. The antioxidant capacities of the fruit essential oils from R. coriaria were assessed using spectrophotometry to measure free radical scavenger 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and inhibition of ß-carotene bleaching (BCB). The essential oils from the fruits of the different samples of R. coriaria exhibited the MIC value ranging from 32.8 to 131.25 µg/mL against S. aureus ATCC 6538 and 131.25 to 262.5 µg/mL against E. coli ATCC 8739. The MIC values of ciprofloxacin were 0.59 and 2.34 µg/mL against S. aureus ATCC 6538 and E. coli ATCC 8739, respectively.

Chemical composition of essential oils of eight Tunisian Eucalyptus species and their antibacterial activity against strains responsible for otitis.

BACKGROUND: The chemical composition and biological activity of Eucalyptus essential oils have been studied extensively (EOs). A few of them were tested for antibacterial effectiveness against otitis strains. The chemical composition and antibacterial activity of the EOs of eight Tunisian Eucalyptus species were assessed in the present study. METHODS: Hydrodistillation was used to extract EOs from the dried leaves of eight Eucalyptus species: Eucalyptus accedens, Eucalyptus punctata, Eucalyptus robusta, Eucalyptus bosistoana, Eucalyptus cladocalyx, Eucalyptus lesouefii, Eucalyptus melliodora and Eucalyptus wandoo. They are assessed by GC/MS and GC/FID and evaluated for antibacterial activity using agar diffusion and broth microdilution techniques against three bacterial isolates (Haemophilus influenzae, Haemophilus parainfluenzae, Klebsiella pneumoniae) and three reference bacteria strains (Pseudomonas aeruginosa, ATTC 9027; Staphylococcus aureus, ATCC 6538; and Escherichia coli, ATCC 8739). Furthermore, the selected twenty-one major compounds and all values of the inhibition zone diameters were subjected to further statistical analysis using PCA and HCA. RESULTS: The EO yields of the studied Eucalyptus species range from 1.4 ± 0.4% to 5.2 ± 0.3%. Among all the species studied, E. lesouefii had the greatest mean percentage of EOs. The identification of 128 components by GC (RI) and GC/MS allowed for 93.6% - 97.7% of the total oil to be identified. 1,8-cineole was the most abundant component found, followed by α-pinene, p-cymene, and globulol. The chemical components of the eight EOs, extracted from the leaves of Eucalyptus species, were clustered into seven groups using PCA and HCA analyses, with each group forming a chemotype. The PCA and HCA analyses of antibacterial activity, on the other hand, identified five groups. CONCLUSION: The oils of E. melliodora, E. bosistoana, and E. robusta show promise as antibiotic alternatives in the treatment of otitis media.

Multivariate Raman mapping for phenotypic characterization in plant tissue sections.

Identifying and characterizing the biochemical variation in plant tissues is an important task in many research fields. Small spectral differences of the plant cell wall that are caused by genetic or environmental influences may be superimposed by individual variation as well as by a microscopic heterogeneity in molecular composition and structure of different histological substructures. A set of 56 samples from Cucumis sativus (cucumber) plants, comprising a total of ~168,000 spectra from tissue sections of leaf, stem, and roots was investigated by Raman microspectroscopic mapping excited at 532 nm. A multivariate analysis was carried out in order to assess the variation of the spectra with respect to origin of the tissue, the histological (cell wall) substructures, and the possibility to discriminate the spectra obtained from different individuals that had been subjected to two different conditions during growth. Combining the results of principal component analysis (PCA) based classification with the original spatial information in the maps of 23 sections of leaf xylem, variation in cell wall composition is found for four different individuals that also includes a discrimination of tissue grown in the presence and absence of additional silicic acid in the irrigation water of the plants. The spectral data point to differences in a contribution by carotenoids, as well as by hydroxycinnamic acids to the spectra. The results give new insight into the chemical heterogeneity of plant tissues and may be useful for elucidating biochemical processes associated with biomineralization by vibrational spectroscopy.

Rapid detection of green-pea adulteration in pistachio nuts using Raman spectroscopy and chemometrics.

BACKGROUND: Ground pistachio nut is prone to adulteration because of its high economic value and wide usage. Green pea is known as the main adulterant in frauds involving pistachio nuts. The present study developed a new, rapid, reliable and low-cost methodology by using a portable Raman spectrometer in combination with chemometrics for the detection of green pea in pistachio nuts. RESULTS: Three different methods of Raman spectroscopy-based chemometrics analysis were developed for the determination of green-pea adulteration in pistachio nuts. The first method involved the development of hierarchical cluster analysis (HCA) and principal component analysis (PCA), which differentiated authentic pistachio nuts from green pea and green pea-adulterated samples. The best classification pattern was observed in the adulteration range of 20-80% (w/w). In addition to classification methods, partial least squares regression (PLSR) and genetic algorithm-based inverse least squares (GILS) were also used to develop multivariate calibration models to determine quantitatively the degree of green-pea adulteration in grounded pistachio nuts. The spectral range of 1790-283 cm-1 was used in the case of multivariate data analysis. A green-pea adulteration level of 5-80% (w/w) was successfully identified by PLSR and GILS. The correlation coefficient of determination (R2 ) was determined as 0.91 and 0.94 for the PLSR and GILS analyses, respectively. CONCLUSION: A Raman spectrometer combined with chemometrics has a high capability with regard to the detection of adulteration in pistachio nuts, combined with low cost, strong reliability, a high level of accuracy, rapidity of analysis, and minimum sample preparation. © 2020 Society of Chemical Industry.

Molecular Spectroscopic Markers of Abnormal Protein Aggregation.

Abnormal protein aggregation has been intensively studied for over 40 years and broadly discussed in the literature due to its significant role in neurodegenerative diseases etiology. Structural reorganization and conformational changes of the secondary structure upon the aggregation determine aggregation pathways and cytotoxicity of the aggregates, and therefore, numerous analytical techniques are employed for a deep investigation into the secondary structure of abnormal protein aggregates. Molecular spectroscopies, including Raman and infrared ones, are routinely applied in such studies. Recently, the nanoscale spatial resolution of tip-enhanced Raman and infrared nanospectroscopies, as well as the high sensitivity of the surface-enhanced Raman spectroscopy, have brought new insights into our knowledge of abnormal protein aggregation. In this review, we order and summarize all nano- and micro-spectroscopic marker bands related to abnormal aggregation. Each part presents the physical principles of each particular spectroscopic technique listed above and a concise description of all spectral markers detected with these techniques in the spectra of neurodegenerative proteins and their model systems. Finally, a section concerning the application of multivariate data analysis for extraction of the spectral marker bands is included.