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.

Graph based analysis for gene segment organization In a scrambled genome

DNA recombinant processes can involve gene segments that overlap or interleave with gene segments of another gene. Such gene segment appearances relative to each other are called here gene segment organization. We use graphs to represent the gene segment organization in a chromosome locus. Vertices of the graph represent contigs resulting after the recombination and the edges represent the gene segment organization prior to rearrangement. To each graph we associate a vector whose entries correspond to graph properties, and consider this vector as a point in a higher dimensional Euclidean space such that cluster formations and analysis can be performed with a hierarchical clustering method. The analysis is applied to a recently sequenced model organism Oxytricha trifallax, a species of ciliate with highly scrambled genome that undergoes massive rearrangement process after conjugation. The analysis shows some emerging star-like graph structures indicating that segments of a single gene can interleave, or even contain all of the segments from fifteen or more other genes in between its segments. We also observe that as many as six genes can have their segments mutually interleaving or overlapping.

Correlation between chemical composition and antibacterial activity of some Lamiaceae species essential oils from Tunisia

BACKGROUND

Lamiaceae family is one of the most diverse and common plant families in terms of ethnomedicine due to their potential therapeutic effects. The aim of this study is to investigate the correlation between the chemical composition and the antibacterial effect of five essential oils from this family against five reference bacterial strains responsible of nosocomial diseases and foodborne illnesses.

METHODS

The commercial essential oils of Tunisian Rosmarinus officinalis, Thymus capitatus, Origanum majorana and Salvia officinalis were analyzed by GC/FID and GC-MS. Essential oils were evaluated for their antibacterial activities by disc diffusion and microbroth dilution methods against five reference bacterial strains: Pseudomonas aeruginosa, Escherichia coli, Salmonella enterica, Bacillus subtilis and Staphylococcus aureus. The inhibition zone diameter values and the twenty major compounds of the selected essential oils were subjected to PCA and HCA analysis.

RESULTS

Analysis by GC/FID and GC/MS allowed the identification of ninety-one components representing 96.0 to 98.2% of the total oils. The different component contents varied according to the species. The main components were carvacrol, 1,8-cineole, α-thujone, α-terpineol and α-pinene. The PCA and the HCA of the selected essential oil components and the inhibition zone diameter (IZD) values identified four species groups and subgroups. Each essential oils group constituted a chemotype responsible for their bacterial inhibition ability. Thymus capitatus essential oil showed the strongest antibacterial activity with MBC ranging from 0.73 to 2.94 mg mL^- 1.

CONCLUSION

Rosmarinus officinalis, Thymus capitatus, Origanum majorana and Salvia officinalis essential oils have shown promising antibacterial activities against reference bacterial strains responsible for nosocomial diseases and foodborne illnesses.

Determination of the dose-dependent toxic effects of mad honey on mouse liver using ATR-FTIR spectroscopy

Mad honey (MH) is obtained from Rhododendron plants, which are extensively grown in some regions of the world such as Europe, North America, Tropical Asia and Turkey. Although it has been known that MH induces adverse effects in the body due to grayanotoxin (GTX) in it, it is widely used for some medical purposes by the public. In this study, the effects of MH (25, 50 and 75 mg/kg) and GTX-III (0.01 mg/kg), which is the pure form of the most toxic type of the GTXs in MH, were investigated on the mouse liver at molecular level via Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The results showed that 25 and 50 mg/kg of MH didn't cause any significant alterations in the liver tissue except a decrease in the glycogen amount. However, significant differences were observed between 75 mg/kg MH and GTX-III treated groups and control group. For example, the amounts of saturated lipids, nucleic acids and proteins increased in the 75 mg/kg MH and GTX-III treated groups. A decrease in the ratios of unsaturated/saturated lipid, CH₂/lipid and carbonyl/lipid and an increase in the ratio of CH₃/lipid were observed after the administration of 75 mg/kg MH and GTX-III, all of which may be a consequence of lipid peroxidation. Moreover, 75 mg/kg MH and GTX-III caused a decrease in the membrane order, an increase in the membrane fluidity and some important changes on the secondary structure of proteins indicating protein denaturation. In addition, Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) confirmed these findings. These results revealed that MH induces significant dose-dependent toxic effects in the structure and function of the liver tissue. This study also showed that ATR-FTIR spectroscopy provides a rapid and sensitive monitoring of the changes induced by a toxic compound on biological tissues at molecular level.

Simultaneous profiling of organic and inorganic impurities in α-pyrrolidinopentiophenone (α-PVP)

Abuse of recreational drugs (i.e., synthetic chemicals with the structure or expected neurotropic effects, or both, similar to those of controlled substances) is a serious and continuous social harm. Designer drugs are often manufactured or synthesized in small-scale clandestine laboratories with impure starting materials, poor handling skills and inferior storage conditions. Therefore, in addition to the objective compound, diverse impurities may be present, for example, from the starting material, intermediates, catalytic metals formed during chemical synthesis, and materials from the environment. Impurity profiling of drug seizures is a useful scientific tool to obtain information on the clandestine manufacturers and drug trafficking networks. 1-Phenyl-2-(1-pyrrolidinyl)-1-pentanone (α-PVP), a novel psychoactive substance of the cathinone type that is banned in many countries, is still supplied and distributed within the illicit drug market. By using GC-MS and ICP-MS, we identified and estimated the relative contents of organic and inorganic impurities in the bulk powder of 15 batches of α-PVP. We then conducted multivariate data analyses to reveal characteristic patterns of the profiles. Hierarchical cluster analysis of both the organic and inorganic impurities revealed two groups that showed similar impurity profiles, which suggested that the batches in these groups were synthesized in similar routes under similar synthetic environments. The initial groups revealed by the organic impurities were further divided when combined with the data from the inorganic impurities. The present study, therefore, demonstrated the effectiveness of integrated analyses of organic and inorganic impurities for the accurate clustering of designer drugs, to provide precise information to drug investigation authorities.

Application of Escherichia coli antibiotic resistance patterns for contamination source identification in watershed

Spatial correlation of pollution of the water resource in Taipei, Taiwan, were examined by analyzing the antibiotic resistance patterns (ARPs) of 96 Escherichia coli colonies, which were isolated from 7 sampling sites in 3 river sections. The ARPs were the growth patterns of isolated E. coli colonies in the medium with seven kinds of antibiotics, including ampicillin, chlortetracycline, erythromycin, oxytetracycline, streptomycin, tetracycline, and salinomycin of different concentrations. The results showed that the survival rate of E. coli decreased with increasing concentration of antibiotics; however, various ARPs under different antibiotics of different concentrations significantly increased both the useful information and complexities. Hierarchical cluster analysis (HCA) and two-stage principal component analysis (PCA) were applied to analyze the spatial correlations and interrelations of distinct ARPs among sampling sites in this study. It was found that the seven sampling sites can be categorized into three groups which may represent three possible pollution characteristics.

Transcriptional responses of Leishmania (Leishmania) amazonensis in the presence of trivalent sodium stibogluconate

Background

In the last decade, resistance to antimonials has become a serious problem due to the emergence of drug-resistant strains. Therefore, understanding the mechanisms used by Leishmania parasites to survive under drug pressure is essential, particularly for species of medical-veterinary importance such as L. amazonensis.

Methods

Here, we used RNA-seq technology to analyse transcriptome profiles and identify global changes in gene expression between antimony-resistant and -sensitive L. amazonensis promastigotes.

Results

A total of 723 differentially expressed genes were identified between resistant and sensitive lines. Comparative transcriptomic analysis revealed that genes encoding proteins involved in metabolism (fatty acids) and stress response, as well as those associated with antimony resistance in other Leishmania species, were upregulated in the antimony-resistant line. Most importantly, we observed upregulation of genes encoding autophagy proteins, suggesting that in the presence of trivalent stibogluconate (Sb^III) L. amazonensis can activate these genes either as a survival strategy or to induce cell death, as has been observed in other parasites.

Conclusions

This work identified global transcriptomic changes in an in vitro-adapted strain in response to Sb^III. Our results provide relevant information to continue understanding the mechanism used by parasites of the subgenus Leishmania (L. amazonensis) to generate an antimony-resistant phenotype.

Electronic supplementary material

The online version of this article (10.1186/s13071-019-3603-8) contains supplementary material, which is available to authorized users.

A subject-transfer framework for obviating inter- and intra-subject variability in EEG-based drowsiness detection

Inter- and intra-subject variability pose a major challenge to decoding human brain activity in brain-computer interfaces (BCIs) based on non-invasive electroencephalogram (EEG). Conventionally, a time-consuming and laborious training procedure is performed on each new user to collect sufficient individualized data, hindering the applications of BCIs on monitoring brain states (e.g. drowsiness) in real-world settings. This study proposes applying hierarchical clustering to assess the inter- and intra-subject variability within a large-scale dataset of EEG collected in a simulated driving task, and validates the feasibility of transferring EEG-based drowsiness-detection models across subjects. A subject-transfer framework is thus developed for detecting drowsiness based on a large-scale model pool from other subjects and a small amount of alert baseline calibration data from a new user. The model pool ensures the availability of positive model transferring, whereas the alert baseline data serve as a selector of decoding models in the pool. Compared with the conventional within-subject approach, the proposed framework remarkably reduced the required calibration time for a new user by 90% (18.00 min-1.72 ± 0.36 min) without compromising performance (p = 0.0910) when sufficient existing data are available. These findings suggest a practical pathway toward plug-and-play drowsiness detection and can ignite numerous real-world BCI applications.

Chemical characterization of polycyclic aromatic hydrocarbons (PAHs) in 2013 Rayong oil spill-affected coastal areas of Thailand

Among Southeast Asian countries, Thailand has gradually accustomed to extremely prompt urbanization, motorization, and industrialization. Chonburi and Rayong provinces are two provinces involved in "eastern seaboard" industrial zones, which is an emerging economic region that plays a key role in Thailand's economy. The 2013 Rayong oil spill did not only cause damages to the coastal and maritime environment, but also undermine trust in the overall safety system and negatively affect the investor confidence. In this study, 69 coastal soils collected around Koh Samed Island were chemically extracted and analyzed for 15 PAHs by using a Shimadzu GCMS-QP2010 Ultra system comprising a high-speed performance system with ASSP function. In this study, numerous diagnostic binary ratios were applied to identify potential sources of PAHs. Advanced statistical techniques such as hierarchical cluster analysis coupled with principal component analysis were also conducted for further investigations of source identifications.

A pilot study on fingerprinting Leishmania species from the Old World using Fourier transform infrared spectroscopy

Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains’ hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens.

Graphical abstract

Hierarchical cluster analysis in clinical research with heterogeneous study population: highlighting its visualization with R

Big data clinical research typically involves thousands of patients and there are numerous variables available. Conventionally, these variables can be handled by multivariable regression modeling. In this article, the hierarchical cluster analysis (HCA) is introduced. This method is used to explore similarity between observations and/or clusters. The result can be visualized using heat maps and dendrograms. Sometimes, it would be interesting to add scatter plot and smooth lines into the panels of the heat map. The inherent R heatmap package does not provide this function. A series of scatter plots can be created using lattice package, and then background color of each panel is mapped to the regression coefficient by using custom-made panel functions. This is the unique feature of the lattice package. Dendrograms and color keys can be added as the legend elements of the lattice system. The latticeExtra package provides some useful functions for the work.

Essential Oil Composition of Three Globularia Species

The chemical composition of the essential oils obtained by hydrodistillation from the aerial parts of Globularia cordifolia L., G. meridionalis (Podp.) O.Schwarz, and G. punctata Lapeyr. was characterized by GC-FID and GC/MS analyses. Among the 33 identified compounds, the most abundant present in all investigated samples were oct-1-en-3-ol (2.9-47.0%), 6-(1,5-dimethylhex-4-enyl)-3-methylcyclohex-2-enone (8.2-40.9%), and fukinanolid (7.4-31.6%). Multivariate statistical analyses (PCA and HCA) of the hitherto studied Globularia volatile compounds confirmed to some extent the assumed phylogenetic relationships of the Globularia species studied, including the close relationship between the morphologically similar species G. cordifolia and G. meridionalis, but also evidenced several discrepancies in the current classification of Globularia species.

How frequently do clusters occur in hierarchical clustering analysis? A graph theoretical approach to studying ties in proximity

Background

Hierarchical cluster analysis (HCA) is a widely used classificatory technique in many areas of scientific knowledge. Applications usually yield a dendrogram from an HCA run over a given data set, using a grouping algorithm and a similarity measure. However, even when such parameters are fixed, ties in proximity (i.e. two equidistant clusters from a third one) may produce several different dendrograms, having different possible clustering patterns (different classifications). This situation is usually disregarded and conclusions are based on a single result, leading to questions concerning the permanence of clusters in all the resulting dendrograms; this happens, for example, when using HCA for grouping molecular descriptors to select that less similar ones in QSAR studies.

Results

Representing dendrograms in graph theoretical terms allowed us to introduce four measures of cluster frequency in a canonical way, and use them to calculate cluster frequencies over the set of all possible dendrograms, taking all ties in proximity into account. A toy example of well separated clusters was used, as well as a set of 1666 molecular descriptors calculated for a group of molecules having hepatotoxic activity to show how our functions may be used for studying the effect of ties in HCA analysis. Such functions were not restricted to the tie case; the possibility of using them to derive cluster stability measurements on arbitrary sets of dendrograms having the same leaves is discussed, e.g. dendrograms from variations of HCA parameters. It was found that ties occurred frequently, some yielding tens of thousands of dendrograms, even for small data sets.

Conclusions

Our approach was able to detect trends in clustering patterns by offering a simple way of measuring their frequency, which is often very low. This would imply, that inferences and models based on descriptor classifications (e.g. QSAR) are likely to be biased, thereby requiring an assessment of their reliability. Moreover, any classification of molecular descriptors is likely to be far from unique. Our results highlight the need for evaluating the effect of ties on clustering patterns before classification results can be used accurately.Graphical abstract

Essential-oil diversity of Salvia tomentosa Mill. in Greece

Salvia tomentosa essential oils from Greece were studied for the first time here. The oils from five populations growing in Mediterranean pine forests on the island of Thassos (northern Aegean Sea) and from 14 populations situated in deciduous forests in Thrace (northeastern Greek mainland) were investigated. Their essential-oil contents ranged from 1.1 to 3.3% (v/w, based on the dry weight of the plant material). The populations from Thassos had high contents of α-pinene (18.0 ± 2.9%), 1,8-cineole (14.7 ± 3.0%), cis-thujone (14.0 ± 6.9%), and borneol (12.8 ± 2.2%) and smaller amounts of camphene, camphor, and β-pinene, whereas the populations from Thrace showed high α-pinene (16.7 ± 4.0%), β-pinene (22.8 ± 4.5%), camphor (18.3 ± 4.3%), and camphene (10.3 ± 2.4%) contents, much lower 1,8-cineole and borneol amounts, while cis-thujone was completely lacking. The comparison of the present results with published data showed that oils having cis-thujone as one of the main compounds were reported for the first time here. Multivariate statistical analyses indicate that the observed essential-oil variation was related to geographical and environmental factors.

Essential oil from black currant buds as chemotaxonomy marker and antimicrobial agent

Dormant buds are recognized as valuable side product of the blackcurrant cultivation. Four blackcurrant varieties cultivated in Serbia, i.e., Ben Sarek, Ometa, Ben Lomond, and Ben Nevis, were evaluated for the content, chemical composition, and antimicrobial activity of their bud essential oils. The oil yields of buds harvested during two different growth periods ranged from 1.2-2.0%, and the variety Ometa had the highest yield among the tested varieties. GC-FID and GC/MS analysis of the oils allowed the identification of eight main components, i.e., α-pinene (1.6-5.4%), sabinene (1.9-38.4%), δ-car-3-ene (13.0-50.7%), β-phellandrene (2.9-18.0%), terpinolene (6.6-11.9%), terpinen-4-ol (0.9-6.6%), β-caryophyllene (3.8-10.4%), and α-humulene (0.2-4.1%). In addition, the similarity degree of the essential-oil compositions of buds harvested from the upper and lower parts of the shrubs was investigated by hierarchical clustering. All essential oils originating from the same genotype were grouped in the same cluster, indicating the reliability of essential oils as chemotaxonomic markers. For more detailed chemotaxonomic investigations, the three compounds with the greatest variance were chosen, i.e., sabinene, δ-car-3-ene, and β-phellandrene, which proved to be efficient for the variety distinction. Factor analysis showed that the essential-oil composition as chemotaxonomic marker in blackcurrants was more reliable for variety Ben Sarek than for variety Ben Nevis. Moreover, it was demonstrated that the essential oils had very strong inhibitory activity against all tested microorganisms. Fungi were more sensitive than bacteria; indeed their growth was completely inhibited at much lower concentrations. In comparison to commercial antibiotics, significantly lower concentrations of the oils were necessary for the complete inhibition of fungal growth.

Volatile compounds in Thymus sect. Teucrioides (Lamiaceae): intraspecific and interspecific diversity, chemotaxonomic significance and exploitation potential

Thymus sect. Teucrioides comprises three species, namely, T. hartvigii, T. leucospermus, and T. teucrioides, distributed in Greece and Albania. The volatile constituents of all species of the section were obtained by hydrodistillation and investigated by GC-FID and GC/MS analyses. Twenty populations were sampled and a total of 103 compounds were identified, representing 98.0-99.9% of the oil compositions. The oils were mainly characterized by high contents of monoterpene hydrocarbons (42.7-92.4%), with the exception of three oils for which oxygenated monoterpenes were the dominating constituents, viz., that of T. hartvigii ssp. macrocalyx, with linalool as main compound (89.2±0.5%), and those of T. hartvigii ssp. hartvigii and of one population of T. teucrioides ssp. candilicus, containing thymol as major component (46.4±3.1 and 38.2±3.9%, resp.). The most common compound in the oils of the 20 populations of the section was p-cymene. Considerable variation was detected within and among populations, and seven chemotypes were distinguished, i.e., p-cymene, linalool, p-cymene/thymol, p-cymene/γ-terpinene, p-cymene/borneol, p-cymene/γ-terpinene/borneol, and p-cymene/linalool chemotypes. Different chemotypes may exist in the same population. Multivariate statistical analyses enabled the segregation of the oils within Thymus sect. Teucrioides into two groups, one consisting of the three subspecies of T. teucrioides and the second comprising the species T. hartvigii and T. leucospermus. A linalool-rich chemotype, unique within the section, distinguished the oil of T. hartvigii ssp. macrocalyx from all other oils. The high oil content of p-cymene and the preference for serpentine substrates render T. teucrioides species promising for future exploitation.

Phytochemical diversity of the essential oils of Mexican Oregano (Lippia graveolens Kunth) populations along an Edapho-climatic gradient

Mexican oregano (Lippia graveolens) is an important aromatic plant, mainly used as flavoring and usually harvested from non-cultivated populations. Mexican oregano essential oil showed important variation in the essential-oil yield and composition. The composition of the essential oils extracted by hydrodistillation from 14 wild populations of L. graveolens growing along an edaphoclimatic gradient was evaluated. Characterization of the oils by GC-FID and GC/MS analyses allowed the identification of 70 components, which accounted for 89-99% of the total oil composition. Principal component and hierarchical cluster analyses divided the essential oils into three distinct groups with contrasting oil compositions, viz., two phenolic chemotypes, with either carvacrol (C) or thymol (T) as dominant compounds (contents >75% of the total oil composition), and a non-phenolic chemotype (S) dominated by oxygenated sesquiterpenes. While Chemotype C was associated with semi-arid climate and shallower and rockier soils, Chemotype T was found for plants growing under less arid conditions and in deeper soils. The plants showing Chemotype S were more abundant in subhumid climate. High-oil-yield individuals (>3%) were identified, which additionally presented high percentages of either carvacrol or thymol; these individuals are of interest, as they could be used as parental material for scientific and commercial breeding programs.

Fast, reagentless and reliable screening of "white powders" during the bioterrorism hoaxes

The classification of dry powder samples is an important step in managing the consequences of terrorist incidents. Fluorescence decays of these samples (vegetative bacteria, bacterial endospores, fungi, albumins and several flours) were measured with stroboscopic technique using an EasyLife LS system PTI. Three pulsed nanosecond LED sources, generating 280, 340 and 460nm were employed for samples excitation. The usefulness of a new 460nm light source for fluorescence measurements of dry microbial cells has been demonstrated. The principal component analysis (PCA) and hierarchical cluster analysis (HCA) have been used for classification of dry biological samples. It showed that the single excitation wavelength was not sufficient for differentiation of biological samples of diverse origin. However, merging fluorescence decays from two or three excitation wavelengths allowed classification of these samples. An experimental setup allowing the practical implementation of this method for the real time fluorescence decay measurement was designed. It consisted of the LED emitting nanosecond pulses at 280nm and two fast photomultiplier tubes (PMTs) for signal detection in two fluorescence bands simultaneously. The positive results of the dry powder samples measurements confirmed that the fluorescence decay-based technique could be a useful tool for fast classification of the suspected "white powders" performed by the first responders.

Variation of the chemical composition and antimicrobial activity of the essential oils of natural populations of Tunisian Daucus carota L. (Apiaceae)

The essential oils of Daucus carota L. (Apiaceae) seeds sampled from ten wild populations spread over northern Tunisia were characterized by GC-FID and GC/MS analyses. In total, 36 compounds were identified in the D. carota seed essential oils, with a predominance of sesquiterpene hydrocarbons in most samples (22.63-89.93% of the total oil composition). The main volatile compounds identified were β-bisabolene (mean content of 39.33%), sabinene (8.53%), geranyl acetate (7.12%), and elemicin (6.26%). The volatile composition varied significantly across the populations, even for oils of populations harvested in similar areas. The chemometric principal component analysis and the hierarchical clustering identified four groups, each corresponding to a composition-specific chemotype. The in vitro antimicrobial activity of the isolated essential oils was preliminarily evaluated, using the disk-diffusion method, against one Gram-positive (Staphylococcus aureus) and two Gram-negative bacteria (Escherichia coli and Salmonella typhimurium), as well as against a pathogenic yeast (Candida albicans). All tested essential oils exhibited interesting antibacterial and antifungal activities against the assayed microorganisms.

Chemical composition and phytotoxic effects of essential oils obtained from Ailanthus altissima (Mill.) swingle cultivated in Tunisia

Ailanthus altissima Mill. Swingle (Simaroubaceae), also known as tree of heaven, is used in the Chinese traditional medicine as a bitter aromatic drug for the treatment of colds and gastric diseases. In Tunisia, Ailanthus altissima is an exotic tree, which was introduced many years ago and used particularly as a street ornamental tree. Here, the essential oils of different plant parts of this tree, viz., roots, stems, leaves, flowers, and samaras (ripe fruits), were obtained by hydrodistillation. In total, 69 compounds, representing 91.0-97.2% of the whole oil composition, were identified in these oils by GC-FID and GC/MS analyses. The root essential oil was clearly distinguishable for its high content in aldehydes (hexadecanal (1); 22.6%), while those obtained from flowers and leaves were dominated by oxygenated sesquiterpenes (74.8 and 42.1%, resp.), with caryophyllene oxide (4) as the major component (42.5 and 22.7%, resp.). The samara oil was rich in the apocarotenoid derivative hexahydrofarnesyl acetone (6; 58.0%), and the oil obtained from stems was characterized by sesquiterpene hydrocarbons (54.1%), mainly β-caryophyllene (18.9%). Principal component and hierarchical cluster analyses separated the five essential oils into four groups, each characterized by the major oil constituents. Contact tests showed that the germination of lettuce seeds was totally inhibited by all the essential oils except of the samara oil at a dose of 1 mg/ml. The flower oil also showed a significant phytotoxic effect against lettuce germination at 0.04 and 0.4 mg/ml (-55.0 ± 3.5 and -85.0 ± 0.7%, resp.). Moreover, the root and shoot elongation was even more affected by the oils than germination. The inhibitory effect of the shoot and root elongation varied from -9.8 to -100% and from -38.6 to -100%, respectively. Total inhibition of the elongation (-100%) at 1 mg/ml was detected for all the oils, with the exception of the samara oil (-74.7 and -75.1% for roots and shoots, resp.).

Derringer desirability and kinetic plot LC-column comparison approach for MS-compatible lipopeptide analysis

Lipopeptides are currently re-emerging as an interesting subgroup in the peptide research field, having historical applications as antibacterial and antifungal agents and new potential applications as antiviral, antitumor, immune-modulating and cell-penetrating compounds. However, due to their specific structure, chromatographic analysis often requires special buffer systems or the use of trifluoroacetic acid, limiting mass spectrometry detection. Therefore, we used a traditional aqueous/acetonitrile based gradient system, containing 0.1% (m/v) formic acid, to separate four pharmaceutically relevant lipopeptides (polymyxin B₁, caspofungin, daptomycin and gramicidin A₁), which were selected based upon hierarchical cluster analysis (HCA) and principal component analysis (PCA).

In total, the performance of four different C18 columns, including one UPLC column, were evaluated using two parallel approaches. First, a Derringer desirability function was used, whereby six single and multiple chromatographic response values were rescaled into one overall D-value per column. Using this approach, the YMC Pack Pro C18 column was ranked as the best column for general MS-compatible lipopeptide separation. Secondly, the kinetic plot approach was used to compare the different columns at different flow rate ranges. As the optimal kinetic column performance is obtained at its maximal pressure, the length elongation factor λ (P_max/P_exp) was used to transform the obtained experimental data (retention times and peak capacities) and construct kinetic performance limit (KPL) curves, allowing a direct visual and unbiased comparison of the selected columns, whereby the YMC Triart C18 UPLC and ACE C18 columns performed as best. Finally, differences in column performance and the (dis)advantages of both approaches are discussed.