Objective chemical fingerprinting of oil spills by partial least-squares discriminant analysis

An objective method based on partial least-squares discriminant analysis (PLS-DA) was used to assign an oil lump collected on the coastline to a suspected source. The approach is an add-on to current US and European oil fingerprinting standard procedures that are based on lengthy and rather subjective visual comparison of chromatograms. The procedure required an initial variable selection step using the selectivity ratio index (SRI) followed by a PLS-DA model. From the model, a "matching decision diagram" was established that yielded the four possible decisions that may arise from standard procedures (i.e., match, non-match, probable match, and inconclusive). The decision diagram included two limits, one derived from the Q-residuals of the samples of the target class and the other derived from the predicted y of the PLS model. The method was used classify 45 oil lumps collected on the Galician coast after the Prestige wreckage. The results compared satisfactorily with those from the standard methods.     

Multilevel component analysis of time-resolved metabolic fingerprinting data

Genomics-based technologies in systems biology have gained a lot of popularity in recent years. These technologies generate large amounts of data. To obtain information from this data, multivariate data analysis methods are required. Many of the datasets generated in genomics are multilevel datasets, in which the variation occurs on different levels simultaneously (e.g. variation between organisms and variation in time). We introduce multilevel component analysis (MCA) into the field of metabolic fingerprinting to separate these different types of variation. This is in contrast to the commonly used principal component analysis (PCA) that is not capable of doing this: in a PCA model the different types of variation in a multilevel dataset are confounded.

MCA generates different submodels for different types of variation. These submodels are lower-dimensional component models in which the variation is approximated. These models are easier to interpret than the original data. Multilevel simultaneous component analysis (MSCA) is a method within the class of MCA models with increased interpretability, due to the fact that the time-resolved variation of all individuals is expressed in the same subspace.

MSCA is applied on a time-resolved metabolomics dataset. This dataset contains ¹H NMR spectra of urine collected from 10 monkeys at 29 time-points during 2 months. The MSCA model contains a submodel describing the biorhythms in the urine composition and a submodel describing the variation between the animals. Using MSCA the largest biorhythms in the urine composition and the largest variation between the animals are identified.

Comparison of the MSCA model to a PCA model of this data shows that the MSCA model is better interpretable: the MSCA model gives a better view on the different types of variation in the data since they are not confounded.     

A non-destructive interferometric technique for analysis of crystal growth and fluid dynamics

The Electronic Speckle Interferometry (ESPI) may be applied to the observation of physical phenomena in transparent fluids, where variations of physical properties produce a change in refractive index. With this non-destructive method it is possible to analyze the fluidodynamics in the growth cell or the dynamics of concentration gradients in chosen points around the crystal. Some KDP crystal growths from solution have been observed with the ESPI technique in order to prove its validity.     

A Chemogenetic Approach for the Optical Monitoring of Voltage in Neurons

Optical monitoring of neuronal voltage using fluorescent indicators is a powerful approach for the interrogation of the cellular and molecular logic of the nervous system. Herein, a semisynthetic tethered voltage indicator (STeVI1) based upon nile red is described that displays voltage sensitivity when genetically targeted to neuronal membranes. This environmentally sensitive probe allows for wash‐free imaging and faithfully detects supra‐ and sub‐threshold activity in neurons.     

Scenarios of heterogeneous nucleation and growth studied by cell dynamics simulation

The dynamics of phase transformation due to homogeneous nucleation has long been analyzed using the classic Kolmogorov-Johnson-Mehl-Avrami (KJMA) theory. However, the dynamics of phase transformation due to heterogeneous nucleation has not been studied systematically even though it is vitally important technologically. In this report, the author studies the dynamics of heterogeneous nucleation theoretically and systematically using the phenomenological time-dependent Ginzburg-Landau (TDGL)-type model combined with the cell dynamics method. In this study the author focuses on the dynamics of phase transformation when the material is sandwiched by two supporting substrates. This model is supposed to simulate phase change storage media. Since both homogeneous and heterogeneous nucleations can occur simultaneously, the author predicts a few scenarios of phase transformation including homogeneous nucleation regime, heterogeneous nucleation regime, and the homogeneous-heterogeneous coexistence regime. These predictions are directly confirmed by numerical simulation using the TDGL model. The outcome of the study was that the KJMA formula has limited use when heterogeneous nucleation exists, but it could still give some information about the microscopic mechanism of phase transformation at various stages during phase transformation.     

液相色谱指纹图谱在泽泻动态研究中的应用

应用指纹图谱技术,结合指标成分测定,采用高效液相色谱法,乙腈-水梯度洗脱,流速1．0mL／min,柱温20℃,色谱图光谱采集范围200～800nm,探讨了泽泻动态积累的规律。以泽泻标准对照药材为参照,用指标成分24-乙酰泽泻醇A和23-乙酰泽泻醇B进行了定位和测定,找出了21个共有峰,其中12号和20号峰分别为24-乙酰泽泻醇A和23-乙酰泽泻醇B。结果表明：泽泻样品指纹图谱及指标成分测定可为泽泻的最佳采收期提供科学依据。     

Phospho-proteomic analysis of cellular signaling

Reversible protein phosphorylation plays an important role in the regulation of many different processes, such as cell growth, differentiation, migration, metabolism, and apoptosis. Identification of differentially phosphorylated proteins by means of phospho-proteomic analysis provides insight into signal transduction pathways that are activated in response to, for example, growth factor stimulation or toxicant-induced apoptosis. This review summarizes recent advances made in the field of phospho-proteomics and provides examples of how phospho-proteomic techniques can be combined to quantitatively investigate the dynamic changes in protein phosphorylation in time. By linking experimental data to clinical data (e.g., disease progression or response to therapy) new disease markers could be identified, which could then be validated for applications in disease diagnosis and progression or prediction of a response to drugs.     

Myelin growth and initial dynamics

During the dissolution of solid surfactants in water, various types of nonequilibrium microstructures have been observed. The most important one is the myelin growth which can be observed when some poorly water soluble surfactants such as phosphatidylcholine (PC), Aerosol-OT (AOT), etc. are contacted with water. In this study initial myelin growth for a period of 2-4 s is studied both qualitatively as well as quantitatively in all the directions with respect to water flow in a PC system using digital video microscopy. Further, overall myelin growth is studied by means of optical microscopy to understand the effect of distance between cover slip and glass slide on myelin growth. Experiments are also performed to study effect of additives (silica) to lamellar phase on diffusion coefficients. It has been observed that the presence of silica particles causes extensive coiling of myelin structures. The mechanism of water transport into the lamellar phase during myelin growth is investigated by using silica in a colloidal range as dopant material.     

Ecosystem discrimination and fingerprinting of Romanian propolis by hierarchical fuzzy clustering and image analysis of TLC patterns

The fingerprinting capacity of thin layer chromatography (TLC) and image analysis in the case of propolis samples collected in different area in Romania has been investigated. Fuzzy divisive hierarchical clustering approach was used as a powerful tool of samples discrimination and fingerprinting according to the geographical origin and local flora. The fuzzy partition and patterns obtained by membership degrees plot were in a very good agreement with floral origin and geographic location of Romanian propolis samples, and clearly illustrate the fuzziness concerning their similarities and difference. The results obtained strongly support that TLC via image analysis can be successfully employed in the fingerprinting methodologies if they are combined with appropriate fuzzy clustering method. The method developed in this paper might be also extended in the authenticity and origin control of fruits, herbs or derived products.     

Biological fingerprinting analysis of the interactome of a kinase inhibitor in human plasma by a chemiproteomic approach

In this study, a gel free chemiproteomic method based on chromatography was developed and applied for the biological fingerprinting analysis of complex biological system. p-Aminobenzamidine (ABA), an inhibitor of trypsin-like serine proteases, was immobilized for characterizing their interacting proteins in human plasma. By the proteomic analysis method, 214 proteins were identified with obvious affinity to the immobilized ABA. By searching the sequences of above proteins with consensus patterns of the two active sites, seven proteins belong to trypsin-like serine protease group were found. Based on the Gene Ontology annotation, the identified trypsin-like serine proteases have the function of catalytic activity and calcium ion binding, and are mainly involved in the biological process of blood coagulation. Eight more other proteins related to calcium ion binding and blood coagulation were found. Nearly all of these proteins cannot be identified by directly analyzing the plasma sample demonstrating the chemiproteomics a useful approach to characterize interacting proteins in the low abundance range.     

Exploring the feasibility of bioaerosol analysis as a novel fingerprinting technique

The purpose of this review is to investigate the feasibility of bioaerosol fingerprinting based on current understanding of cellular debris (with emphasis on human-emitted particulates) in aerosols and arguments regarding sampling, sensitivity, separations, and detection schemes. Target aerosol particles include cellular material and proteins emitted by humans, animals, and plants and can be regarded as information-rich packets that carry biochemical information specific to the living organisms present where the sample is collected. In this work we discuss sampling and analysis techniques that can be integrated with molecular (e.g. protein)-detection procedures to properly assess the aerosolized cellular material of interest. Developing a detailed understanding of bioaerosol molecular profiles in different environments suggests exciting possibilities of bioaerosol analysis with applications ranging from military defense to medical diagnosis and wildlife identification     

Chemogenetic protein engineering: an efficient tool for the optimization of artificial metalloenzymes

Artificial metalloenzymes, based on the incorporation of a catalytically active organometallic moiety within a host protein, lie at the interface between organometallic and enzymatic catalysis. In terms of activity, reaction repertoire, substrate range and operating conditions, they take advantage of the versatility of the organometallic chemistry. In contrast, the enantioselectivity is determined by the biomolecular scaffold, which provides a well defined second coordination sphere to the organometallic moiety, reminiscent of enzymes. The attractive feature of such systems is their optimization potential, which combines chemical and genetic methods (i.e. chemogenetic) to screen diversity space. This feature article describes the implementation of such an optimization protocol for artificial transfer hydrogenases, for which we have the most detailed understanding.     

Rapid fingerprinting of red wines by MALDI mass spectrometry

Here we report a simple and fast method for wine fingerprinting based on direct matrix-assisted laser desorption/ionization (MALDI) mass spectrometry analysis of different red wine samples, useful for batch-to-batch analysis and for the detection of key compounds even in trace amounts which may vary from vintage to vintage, and from one treatment to another one. A series of 20 samples from different wines were subjected to MALDI mass spectrometry. We found that 2,5-dihydroxybenzoic acid is far superior with respect to all the matrices tested To the best of our knowledge this is the first application of an effective wine profiling not limited to detection of anthocyanins. More than 80 molecular species were detected. Moreover, qualitative and quantitative differences were observed, owing to the nature and relative abundance of different chemical compounds among the wines.     

Molecular dynamics analysis of multiple site growth and coalescence effects on homogeneous and heterogeneous nucleations

Homogeneous and heterogeneous nucleations were simulated by molecular dynamics (MD). The behavior of Lennard-Jones molecules was studied inside a liquid-gas system where all dimensions of the wall were periodic and a soft core carrier gas within the system controlled the temperature. In this study, the classical nucleation theory was found to underestimate the homogeneous nucleation rate by five orders of magnitude, which complies with other MD studies. The discrepancy in the nucleation rate between theory and simulation was mainly caused by the fundamental assumption that there are no volumetric interactions in the growth process. In this particular case, however, growth was observed at multiple sites due to Ostwald ripening and coalescence between nuclei by Brownian motion. Furthermore, even though the supersaturation ratio is inadequate for homogeneous nucleation, once a seed is introduced to the system, a cluster can be created. The addition of seeds not only enhances nucleation but also renders coalescence as an important nucleation mechanism in the earlier stages compared to homogeneous nucleation.     

Time series analysis of ion dynamics in glassy ionic conductors obtained by a molecular dynamics simulation

We present several characteristics of ionic motion in glassy ionic conductors brought out by time series analysis of molecular dynamics (MD) simulation data. Time series analysis of data obtained by MD simulation can provide crucial information to describe, understand and predict the dynamics in many systems. The data have been treated by the singular spectrum analysis (SSA), which is a method to extract information from noisy short time series and thus provide insight into the unknown or partially unknown dynamics of the underlying system that generated the time series. Phase-space plot reconstructed using the principal components of SSA exhibited complex but clear structures, suggesting the deterministic nature of the dynamics.     

Proteomic analysis of Helicobacter pylori cellular proteins fractionated by ammonium sulfate precipitation

Among 1590 ORFs in the Helicobacter pylori genome, >250 have been identified as authentic genes by proteomic analysis. Low-abundance proteins need to be enriched to a minimal amount for MALDI-TOF analysis and salt precipitation has generally been used for protein enrichment. Here, a whole-cell extract of H. pylori strain 26695 was subjected to protein fractionation with stepwise concentrations of ammonium sulfate and the proteins were displayed by 2-DE. The protein spots were quantified using PDQUEST software and identified by peptide fingerprinting. The 2-DE profiles and intensities of individual protein spots differed among the protein fractions. Out of the 98 identified proteins, 61 were found in the stepwise ammonium sulfate fractions but not in the whole-cell extract. Out of these, 37 proteins, including KdsA, were found exclusively in a single fraction. In contrast, GroEL, UreA, UreB, TrxA, NapA, and FldA were ubiquitously present in all fractions. Iron-containing proteins such as NapA, SodB, CeuE, and Pfr were found predominantly in the 100% saturated ammonium sulfate precipitate. Additionally, 29 proteins were newly identified in this study. These data will facilitate the preparation of significant H. pylori proteins, as well as provide information about low-abundance proteins.     

Quantitative analysis and chromatographic fingerprinting of the semen zizyphi spinosae by ultra-high-performance liquid chromatography coupled with diode-array detector

A simple and sensitive method was developed and validated for fingerprint analysis of semen zizyphi spinosae (SZS) and simultaneous determination of six flavonoids in SZS by ultra‐high‐performance liquid chromatography coupled to diode‐array detector (DAD). The analysis was performed on an Agilent ZORBAX Eclipse Plus C18 RRHD column. The column was maintained at 40°C and the eluents were monitored with DAD at 270 nm. A gradient elution of acetonitrile and water containing 20 mM sodium dihydrogen phosphate was used. The solvent flow rate was 0.4 mL/min. The method was validated. Standard calibration curves showed good linear behaviors (r=1.000) in the range of 0.33–201.00 μg/mL. Acceptable intra‐day precision (RSD<1.9%), inter‐day precision (RSD<4.0%), repeatability (RSD<4.1%) and recovery in the range of 97.4–104% were obtained. The validated method was successfully applied to obtain the chromatographic fingerprints and the contents of six flavonoids in 23 samples of SZS. The principal component analysis (PCA) had been applied for the chromatographic fingerprint analysis and quantitative analysis of six flavonoids to classify and discriminate the 23 samples of SZS. These results demonstrated that the method was very suitable in the analysis and quality control of SZS.     

Characterization of cellular chemical dynamics using combined microfluidic and Raman techniques

The integration of a range of technologies including microfluidics, surface-enhanced Raman scattering and confocal microspectroscopy has been successfully used to characterize in situ single living CHO (Chinese hamster ovary) cells with a high degree of spatial (in three dimensions) and temporal (1 s per spectrum) resolution. Following the introduction of a continuous flow of ionomycin, the real time spectral response from the cell was monitored during the agonist-evoked Ca²⁺ flux process. The methodology described has the potential to be used for the study of the cellular dynamics of a range of signalling processes. Figure Spectral mapping of a single CHO cell