Augmented visualization by computer vision and chromatographic fingerprinting on comprehensive two-dimensional gas chromatographic patterns: Unraveling diagnostic signatures in food volatilome.

Computer Vision is an approach of Artificial Intelligence (AI) that conceptually enables "computers and systems to derive useful information from digital images" giving access to higher-level information and "take actions or make recommendations based on that information". Comprehensive two-dimensional chromatography gives access to highly detailed, accurate, yet unstructured information on the sample's chemical composition, and makes it possible to exploit the AI concepts at the data processing level (e.g.

Extending the breadth of saliva metabolome fingerprinting by smart template strategies and effective pattern realignment on comprehensive two-dimensional gas chromatographic data.

Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOFMS) is one the most powerful analytical platforms for chemical investigations of complex biological samples. It produces large datasets that are rich in information, but highly complex, and its consistency may be affected by random systemic fluctuations and/or changes in the experimental parameters. This study details the optimization of a data processing strategy that compensates for severe 2D pattern misalignments and detector response fluctuations for saliva samples analyzed across 2 years.

c-Abl kinase-mediated phosphorylation of γ-tubulin promotes γ-tubulin ring complexes assembly and microtubule nucleation.

Cytoskeletal microtubules (MTs) are nucleated from γ-tubulin ring complexes (γTuRCs) located at MT organizing centers (MTOCs), such as the centrosome. However, the exact regulatory mechanism of γTuRC assembly is not fully understood. Here, we showed that the nonreceptor tyrosine kinase c-Abl was associated with and phosphorylated γ-tubulin, the essential component of the γTuRC, mainly on the Y443 residue by in vivo (immunofluorescence and immunoprecipitation) or in vitro (surface plasmon resonance) detection.

Exploring the Extra-Virgin Olive Oil Volatilome by Adding Extra Dimensions to Comprehensive Two-Dimensional Gas Chromatography and Time-of-Flight Mass Spectrometry Featuring Tandem Ionization: Validation of Ripening Markers in Headspace Linearity Conditions.

Background: Comprehensive two-dimensional gas chromatography (GC×GC) combined with time-of-flight (TOF) MS is the most informative analytical approach for chemical characterization of the complex food volatilome. Key analytical features include separation power and resolution enhancement, improved sensitivity, and structured separation patterns from chemically correlated analytes.

Objective: In this study, we explore the complex extra-virgin olive oil volatilome by combining headspace (HS) solid-phase microextraction (SPME), applied under HS linearity conditions to GC×GC-TOF MS and featuring hard and soft ionization in tandem.

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography.

Data processing and evaluation are critical steps of comprehensive two-dimensional gas chromatography (GCxGC), particularly when coupled to mass spectrometry. The rich information encrypted in the data may be highly valuable but difficult to access efficiently. Data density and complexity can lead to long elaboration times and require laborious, analyst-dependent procedures.

Magnetic Susceptibility Difference-Induced Nucleus Positioning in Gradient Ultrahigh Magnetic Field.

Despite the importance of magnetic properties of biological samples for biomagnetism and related fields, the exact magnetic susceptibilities of most biological samples in their physiological conditions are still unknown. Here we used superconducting quantum interferometer device to detect the magnetic properties of nonfixed, nondehydrated live cell and cellular fractions at a physiological temperature of 37°C (310 K). It is obvious that there are paramagnetic components within human nasopharyngeal carcinoma CNE-2Z cells.

Untargeted and Targeted Fingerprinting of Extra Virgin Olive Oil Volatiles by Comprehensive Two-Dimensional Gas Chromatography with Mass Spectrometry: Challenges in Long-Term Studies.

Comprehensive two-dimensional gas chromatography coupled with mass spectrometric detection (GC × GC-MS) offers an information-rich basis for effective chemical fingerprinting of food. However, GC × GC-MS yields 2D-peak patterns (i.e.

Comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry featuring tandem ionization: Challenges and opportunities for accurate fingerprinting studies.

The capture of volatile patterns from food is a fingerprinting that opens access to a high level of information related to functional variables (origin, processing, shelf-life etc.) and their impact on sample composition and quality. When the focus is on food volatilome, comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC-TOF MS) is undoubtedly the most effective technique to obtain a highly representative fingerprinting.

Benchmarking machine learning methods for comprehensive chemical fingerprinting and pattern recognition.

Machine learning (ML) has been used previously to recognize particular patterns of constituent compounds. Here, ML is used with comprehensive chemical fingerprints that capture the distribution of all constituent compounds to flexibly perform various pattern recognition tasks. Such pattern recognition requires a sequence of chemical analysis, data analysis, and pattern analysis.

Moderate intensity low frequency rotating magnetic field inhibits breast cancer growth in mice.

Moderate intensity low frequency rotating magnetic field (LF-RMF) has been shown to inhibit melanoma, liver and lung cancer growth in mice. However, its effects on other types of cancers have not been investigated in vivo. Here, we show that 0-0.

Advanced fingerprinting of high-quality cocoa: Challenges in transferring methods from thermal to differential-flow modulated comprehensive two dimensional gas chromatography.

The possibility to transfer methods from thermal to differential-flow modulated comprehensive two-dimensional gas chromatographic (GC×GC) platforms opens interesting perspectives for routine analysis of complex samples. Flow modulated platforms avoid the use of cryogenics, thereby simplifying laboratory operations and analyst supervision during intensive analytical sessions. This study evaluates the feasibility of transferring a fingerprinting method capable of classifying and discriminating cocoa samples based on the volatiles fraction composition according to their origin and processing steps.

Pixel-by-pixel correction of retention time shifts in chromatograms from comprehensive two-dimensional gas chromatography coupled to high resolution time-of-flight mass spectrometry.

A pixel-by-pixel method for correcting retention time (RT) shifts in whole chromatograms from comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC×GC-HRTOFMS) is introduced. A previously developed robust algorithm for correcting RT shifts was extended to high-resolution mass-spectral data. The performance of the new method in terms of decreasing RT shifts and peak volume changes was tested on GC×GC-HRTOFMS data.

Effectiveness of Global, Low-Degree Polynomial Transformations for GCxGC Data Alignment.

As columns age and differ between systems, retention times for comprehensive two-dimensional gas chromatography (GCxGC) may vary between runs. To properly analyze GCxGC chromatograms, it often is desirable to align the retention times of chromatographic features, such as analyte peaks, between chromatograms. Previous work by the authors has shown that global, low-degree polynomial transformation functions, namely affine, second-degree polynomial, and third-degree polynomial, are effective for aligning pairs of two-dimensional chromatograms acquired with dual second columns and detectors (GC×2GC).

Alignment for comprehensive two-dimensional gas chromatography with dual secondary columns and detectors.

In each sample run, comprehensive two-dimensional gas chromatography with dual secondary columns and detectors (GC × 2GC) provides complementary information in two chromatograms generated by its two detectors. For example, a flame ionization detector (FID) produces data that is especially effective for quantification and a mass spectrometer (MS) produces data that is especially useful for chemical-structure elucidation and compound identification. The greater information capacity of two detectors is most useful for difficult analyses, such as metabolomics, but using the joint information offered by the two complex two-dimensional chromatograms requires data fusion.

Non-targeted analysis of electronics waste by comprehensive two-dimensional gas chromatography combined with high-resolution mass spectrometry: Using accurate mass information and mass defect analysis to explore the data.

Comprehensive two-dimensional gas chromatography (GC×GC) and high-resolution mass spectrometry (HRMS) offer the best possible separation of their respective techniques. Recent commercialization of combined GC×GC-HRMS systems offers new possibilities for the analysis of complex mixtures. However, such experiments yield enormous data sets that require new informatics tools to facilitate the interpretation of the rich information content.

c-Abl regulates proteasome abundance by controlling the ubiquitin-proteasomal degradation of PSMA7 subunit.

The ubiquitin-proteasome system is a vital proteolytic pathway required for cell homeostasis. However, the turnover mechanism of the proteasome subunit itself is still not understood. Here, we show that the 20S proteasome subunit PSMA7 is subjected to ubiquitination and proteasomal degradation, which was suppressed by PSMA7 phosphorylation at Y106 mediated by the nonreceptor tyrosine kinases c-Abl/Arg.

Reliable peak selection for multisample analysis with comprehensive two-dimensional chromatography.

Comprehensive two-dimensional chromatography is a powerful technology for analyzing the patterns of constituent compounds in complex samples, but matching chromatographic features for comparative analysis across large sample sets is difficult. Various methods have been described for pairwise peak matching between two chromatograms, but the peaks indicated by these pairwise matches commonly are incomplete or inconsistent across many chromatograms. This paper describes a new, automated method for postprocessing the results of pairwise peak matching to address incomplete and inconsistent peak matches and thereby select chromatographic peaks that reliably correspond across many chromatograms.

Features for non-targeted cross-sample analysis with comprehensive two-dimensional chromatography.

This review surveys different approaches for generating features from comprehensive two-dimensional chromatography for non-targeted cross-sample analysis. The goal of non-targeted cross-sample analysis is to discover relevant chemical characteristics (such as compositional similarities or differences) from multiple samples. In non-targeted analysis, the relevant characteristics are unknown, so individual features for all chemical constituents should be analyzed, not just those for targeted or selected analytes.

Comparative analysis of peak-detection techniques for comprehensive two-dimensional chromatography.

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful technology for separating complex samples. The typical goal of GC×GC peak detection is to aggregate data points of analyte peaks based on their retention times and intensities. Two techniques commonly used for two-dimensional peak detection are the two-step algorithm and the watershed algorithm.

Global and selective detection of organohalogens in environmental samples by comprehensive two-dimensional gas chromatography-tandem mass spectrometry and high-resolution time-of-flight mass spectrometry.

We successfully detected halogenated compounds from several kinds of environmental samples by using a comprehensive two-dimensional gas chromatograph coupled with a tandem mass spectrometer (GC×GC-MS/MS). For the global detection of organohalogens, fly ash sample extracts were directly measured without any cleanup process. The global and selective detection of halogenated compounds was achieved by neutral loss scans of chlorine, bromine and/or fluorine using an MS/MS.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS).

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods.

Profiling food volatiles by comprehensive two-dimensional ga schromatography coupled with mass spectrometry: advanced fingerprinting approaches for comparative analysis of the volatile fraction of roasted hazelnuts (Corylus avellana L.) from different origins.

This study examined how advanced fingerprinting methods (i.e., non-targeted methods) provide reliable and specific information about groups of samples based on their component distribution on the GC x GC chromatographic plane.

Targeted and non-targeted approaches for complex natural sample profiling by GCxGC-qMS.

The present study examines the ability of targeted and non-targeted methods to provide specific and complementary information on groups of samples on the basis of their component distribution on the two-dimensional gas chromatography (GCxGC) plane. The volatile fraction of Arabica green and roasted coffee samples differing in geographical origins and roasting treatments and the volatile fraction from juniper needles, sampled by headspace-solid phase microextraction, were analyzed by GCxGC-qMS and sample profiles processed by different approaches. In the target analysis profiling, samples submitted to different roasting cycles and/or differing in origin and post-harvest treatment are characterized on the basis of known constituents (botanical, technological, and/or aromatic markers).

Comprehensive feature analysis for sample classification with comprehensive two-dimensional LC.

Comprehensive two-dimensional LC (LC x LC) is a powerful tool for analysis of complex biological samples. With its multidimensional separation power and increased peak capacity, LC x LC generates information-rich, but complex, chromatograms, which require advanced data analysis to produce useful information. An important analytical challenge is to classify samples on the basis of chromatographic features, e.