UPLC-Q/TOF-MS coupled with multivariate analysis for comparative analysis of metabolomic in Dendrobium nobile from different growth altitudes

Dendrobium nobile alkaloids (DNLA) and glycosides are the main active components extracted from Dendrobium nobile Lindl. (D. nobile) used for thousands of years in China. The pharmacological effects of the above chemical components are significantly different. D. nobile is mainly grown at an altitude ranging from 230 to 800 m in Chishui City, Northwest Guizhou Province. However, it is unclear whether the metabolite in D. nobile is influenced by the planting altitude. Hence, to reveal the different metabolite in D. nobile cultivated at the altitude of 336 m, 528 m, and 692 m, ultra-high performance liquid chromatography with Q/TOF-MS couple with multivariate analysis were developed. Using the orthogonal partial least squares-discriminant analysis, 19 different metabolites were discovered and then tentatively assigned their structures as alkaloids and glycosides by comparing mass spectrometry data with in-house database and literature. Moreover, the result of semiquantitative analysis showed the content of dendrobine that was belonged to alkaloids significantly increased at the altitude of 692 m, whereas the content of glycosides demonstrated an accumulation trend at the altitude of 528 m. The results could provide valuable information for the optimal clinical drug therapeutics and provide a reference for quality control.     

Development of an Organic Dye-Conjugated β-Diketonate-Europium Complex Luminescence Probe for Discrimination and Detection of Intracellular Biothiols

Small molecular biothiols, cysteine (Cys), homocysteine (Hcy) and glutathione (GSH), play important roles in organisms, and their concentration levels are indicative of some human diseases. Herein we report an organic dye-conjugated β-diketonate-Eu³⁺ complex, [Eu(NBD-keto)₃(DPBT)] (NBD-keto: 7-nitro-2,1,3-benzoxadiazole (NBD)-conjugated to 1,1,1,2,2-pentafluoro-5-phenyl-3,5-pentanedionate through a “O” ether bond; DPBT: 2-(N,N-diethylanilin-4-yl)-4,6-bis(3,5-dimethylpyrazol-1-yl)-1,3,5-triazine), which acts as a unique luminescent probe for detecting and discriminating biothiols. [Eu(NBD-keto)₃(DPBT)] itself is not luminescent due to intramolecular interactions between NBD and β-diketonate-Eu³⁺ moieties. Upon reaction with biothiols, the β-diketonate-Eu³⁺ complex [Eu(keto)₃(DPBT)] is generated, which emits long-lived red emission at 610 nm. Meanwhile, three biothiol-substituted NBD derivatives that exhibit different luminescence behaviors, green emissive (short-lived) NBD-NR (R=Cys or Hcy) at 540 nm and non-luminescent NBD-SR (R=GSH), are also generated. These luminescence response behaviors allow time-gated and steady-state luminescence modes to be combined for detecting total biothiols and discriminating GSH and Cys/Hcy. Using this probe, the quantitative detection and discrimination of GSH and Cys/Hcy in lysis solutions of HeLa cells were realized, which revealed the potential of the probe for biomedical applications.     

Genetic diversity and haplotype structure of 21 Y‐STRs,including nine noncore loci,in South Tunisian Population: Forensic relevance

Y chromosome STRs (Y‐STRs) are being used frequently in forensic laboratories. Previous studies of Y‐STR polymorphisms in different groups of the Tunisian population identified low levels of diversity and discrimination capacity (DC) using various commercial marker sets. This definitely limits the use of such systems for Y‐STRs genotyping in Tunisia. In our investigation on South Tunisia, 200 unrelated males were typed for the 12 conventional Y‐STRs included in the PowerPlex® Y System. Additional set of nine noncore Y‐STRs including DYS446, DYS456, DYS458, DYS388, DYS444, DYS445, DYS449, DYS710, and DYS464 markers were genotyped and evaluated for their potential in improving DC. Allele frequency, gene diversity, haplotype diversity (HD), and DC calculation revealed that DYS464 was the most diverse marker followed by DYS710 and DYS449 markers. The standard panel of 12 Y‐STRs (DC = 80.5%) and the nine markers were combined to obtain DC of 99%. Among the 198 different haplotypes observed, 196 haplotypes were unique (HD = 99.999). Out of the nine noncore set, six Y‐STRs (DYS458, DYS456, DYS449, DYS710, DYS444, and DYS464) had the greatest impact on enhancing DC. Our data provided putative Y‐STRs combination to be used for genetic and forensic applications.     

Optical metal-organic framework sensor for selective discrimination of some toxic metal ions in water

This paper reports the development of a facile and effective approach, based on the use of Zr-based metal-organic frameworks (UiO-66) sensor with micropores geometry, shape and particle morphology for the visual detection and removal of ultra-traces of some toxic metal ions such as Bi(III), Zn(II), Pb(II), Hg(II) and Cd(II). UiO-66 was used as selective carriers for accommodating hydrophobic chromophore probes such as dithizone (DZ) without coupling agent for sensitive and selective discrimination of trace level of toxic analytes. The developed UiO-66 sensor was utilized for the detection of ultra-traces of some toxic metal ions with the naked eye. The new sensor displays high sensitivity and selectivity of a wide range of detectable metals analytes up to 10⁻¹⁰ mol dm⁻³ in solution, in a rapid analyte uptake response (seconds). The developed sensor is stable, cost effective, easy to prepare, and would be useful for rapid detection and removal of ultra-traces of toxic metal ions in water samples.     

Improving discrimination in data envelopment analysis: PCA–DEA or variable reduction

Within the data envelopment analysis context, problems of discrimination between efficient and inefficient decision-making units often arise, particularly if there are a relatively large number of variables with respect to observations. This paper applies Monte Carlo simulation to generalize and compare two discrimination improving methods; principal component analysis applied to data envelopment analysis (PCA–DEA) and variable reduction based on partial covariance (VR). Performance criteria are based on the percentage of observations incorrectly classified; efficient decision-making units mistakenly defined as inefficient and inefficient units defined as efficient. A trade-off was observed with both methods improving discrimination by reducing the probability of the latter error at the expense of a small increase in the probability of the former error. A comparison of the methodologies demonstrates that PCA–DEA provides a more powerful tool than VR with consistently more accurate results. PCA–DEA is applied to all basic DEA models and guidelines for its application are presented in order to minimize misclassification and prove particularly useful when analyzing relatively small datasets, removing the need for additional preference information.     

Stability of the FID sensitivity during an analysis in capillary GC

The sensitivity of an FID may change when the carrier gas flow rate changes during a chromatographic run. Sample parts which are eluted at reduced FID sensitivity produce a reduced peak area, hence are discriminated as compared to other components. Sensitivity changes were studied for hydrogen as carrier gas. For the detector tested, differences in the carrier gas flow rates of 1 ml/min shifted the FID sensitivity by 1 to 5% (depending on the fuel gas supply). Thus the stability of the sensitivity is no longer ensured as soon as the carrier gas flow rate is changed manually or by an automatic programmer during an analysis. Sensitivity drifts may also occur during temperature programmed runs with a pressure regulated carrier gas supply since the gas flow through the capillary drops with increasing temperature. Such shifts in the response became noticeable as soon as relatively high carrier gas flow rates combined with long range temperature programmes were used. The typical patterns of such discriminations are shown, closing with a discussion on the possibilities for minimizing such undesired effects.     

Determination of effective wavelengths for discrimination of fruit vinegars using near infrared spectroscopy and multivariate analysis

Near infrared (NIR) spectroscopy based on effective wavelengths (EWs) and chemometrics was proposed to discriminate the varieties of fruit vinegars including aloe, apple, lemon and peach vinegars. One hundred eighty samples (45 for each variety) were selected randomly for the calibration set, and 60 samples (15 for each variety) for the validation set, whereas 24 samples (6 for each variety) for the independent set. Partial least squares discriminant analysis (PLS-DA) and least squares-support vector machine (LS-SVM) were implemented for calibration models. Different input data matrices of LS-SVM were determined by latent variables (LVs) selected by explained variance, and EWs selected by x-loading weights, regression coefficients, modeling power and independent component analysis (ICA). Then the LS-SVM models were developed with a grid search technique and RBF kernel function. All LS-SVM models outperformed PLS-DA model, and the optimal LS-SVM model was achieved with EWs (4021, 4058, 4264, 4400, 4853, 5070 and 5273 cm⁻¹) selected by regression coefficients. The determination coefficient (R²), RMSEP and total recognition ratio with cutoff value ±0.1 in validation set were 1.000, 0.025 and 100%, respectively. The overall results indicted that the regression coefficients was an effective way for the selection of effective wavelengths. NIR spectroscopy combined with LS-SVM models had the capability to discriminate the varieties of fruit vinegars with high accuracy.     

Method of gas mixtures discrimination based on sensor array, temporal response and data driven approach

This work presents a method of gas mixtures discrimination. The principal concept of the method is to apply measurement data provided by a combination of sensors at single time point of their temporal response as input of the discrimination models. The pattern data combinations are selected for classes of target gases based on the criterion of 100% efficient discrimination. Combinations of sensors and time points, which provide pattern data combinations in course or repeated measurements, are encoded in the form of addresses. The designer of sensor system is responsible for their selection and they are included in the software of the final instrument. The study of the method involved the discrimination of gas mixtures composed of air and single chemical: hexane, ethanol, acetone, ethyl acetate and toluene. Two sensor arrays were utilized. Each consisted of six TGS sensors of the same type. The dynamic operation of sensors was employed. As an example the stop-flow mode was chosen. The work provides the evidence of the existence of sensor combinations and time points, which are successful in discrimination of studied classes of target gases. The persistence of addresses was discussed considering the ability of sensor array to recognize analytes, variability of repeated measurement results, number of repeated measurements and a twin sets of sensors. Altogether, the validity of the method was demonstrated.     

FTIR spectroscopy in medical mycology: applications to the differentiation and typing of <Emphasis Type="Italic">Candida</Emphasis>

The incidence of fungal infections, in particular candidiasis and aspergillosis, has considerably increased during the last three decades. This is mainly due to advances in medical treatments and technologies. In high risk patients (e.g. in haematology or intensive care), the prognosis of invasive candidiasis is relatively poor. Therefore, a rapid and correct identification of the infectious agent is important for an efficient and prompt therapy. Most clinical laboratories rely on conventional identification methods that are based on morphological, physiological and nutritional characteristics. However, these have their limitations because they are time-consuming and not always very accurate. Moreover, molecular methods may be required to determine the genetic relationship between the infectious strains, for instance in Candida outbreaks. In addition, the latter methods require time, expensive consumables and highly trained staff to be performed adequately. In this study, we have applied the FTIR spectroscopic approach to different situations encountered in routine mycological diagnosis. We show the potentials of this phenotypic approach, used in parallel with routine identification methods, for the differentiation of 3 frequently encountered Candida species (C. albicans, C. glabrata and C. krusei) by using both suspensions and microcolonies. This approach, developed for an early discrimination, may help in the initial choice of antifungal treatment. Furthermore, we demonstrate the feasibility of the method for intraspecies comparison (typing) of 3 Candida species (C. albicans, C. glabrata and C. parapsilosis), particularly when an outbreak is suspected.     

Illuminating the flesh of bone identification – An application of near infrared spectroscopy

Near infrared (NIR) reflectance spectroscopy coupled with chemometric analysis was evaluated as a non-destructive tool to discriminate skull bone samples from different animal species. In total 70 skull bones from animals of three classes (mammalians, avian and reptiles) were scanned in the wavelength range between 950 to 1650 nm. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyse the NIR spectra of the skull samples. Correct classification rates of 96% and 81% were obtained for the classification of skull bone samples according to avian and mammalian classes, respectively. Overall, a 91% correct classification rate was obtained for the classification of skull samples according to the class (mammalian and avian). This study demonstrates the potential of NIR spectroscopy coupled with chemometric as data processing, as a means of a rapid, non-destructive classification technique for skull bone samples.