Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

High-Resolution Mass Spectrometry applied to the identification of new metabolites and transformation products of quinolones in chicken muscle tissues

The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.

High-resolution mass spectrometry applied to the study of metabolome modifications in various chicken tissues after amoxicillin administration

The performance of high resolution accurate mass spectrometry (HRMS) operating in full scan MS mode was investigated for the quantitative determination of amoxicillin (AMX) as well as qualitative analysis of metabolomic profiles in tissues of medicated chickens. The metabolomic approach was exploited to compile analytical information on changes in the metabolome of muscle, kidney and liver from chickens subjected to a pharmacological program with AMX. Data consisting of m/z features taken throughout the entire chromatogram were extracted and filtered to be treated by Principal Component Analysis. As a result, it was found that medicated and non-treated animals were clearly clustered in distinct groups. Besides, the multivariate analysis revealed some relevant mass features contributing to this separation. In this context, recognizing those potential markers of each chicken class was a priority research for both metabolite identification and, obviously, evaluation of food quality and health effects associated to food consumption.

High-Resolution Mass Spectrometry applied to the identification of transformation products of quinolones from stability studies and new metabolites of enrofloxacin in chicken muscle tissues

The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.

Comparison between a high-resolution single-stage Orbitrap and a triple quadrupole mass spectrometer for quantitative analyses of drugs.

The capabilities of a high-resolution (HR), accurate mass spectrometer (Exactive-MS) operating in full scan MS mode was investigated for the quantitative LC/MS analysis of drugs in patients' plasma samples. A mass resolution of 50,000 (FWHM) at m/z 200 and a mass extracted window of 5 ppm around the theoretical m/z of each analyte were used to construct chromatograms for quantitation. The quantitative performance of the Exactive-MS was compared with that of a triple quadrupole mass spectrometer (TQ-MS), TSQ Quantum Discovery or Quantum Ultra, operating in the conventional selected reaction monitoring (SRM) mode. The study consisted of 17 therapeutic drugs including 8 antifungal agents (anidulafungin, caspofungin, fluconazole, itraconazole, hydroxyitraconazole posaconazole, voriconazole and voriconazole-N-oxide), 4 immunosuppressants (ciclosporine, everolimus, sirolimus and tacrolimus) and 5 protein kinase inhibitors (dasatinib, imatinib, nilotinib, sorafenib and sunitinib). The quantitative results obtained with HR-MS acquisition show comparable detection specificity, assay precision, accuracy, linearity and sensitivity to SRM acquisition. Importantly, HR-MS offers several benefits over TQ-MS technology: absence of SRM optimization, time saving when changing the analysis from one MS to another, more complete information of what is in the samples and easier troubleshooting. Our work demonstrates that U/HPLC coupled to Exactive HR-MS delivers comparable results to TQ-MS in routine quantitative drug analyses. Considering the advantages of HR-MS, these results suggest that, in the near future, there should be a shift in how routine quantitative analyses of small molecules, particularly for therapeutic drugs, are performed.

High-resolution mass spectrometry applied to theidentification of transformation products of quinolones from stability studies and new metabolites of enrofloxacin in chicken muscle tissues

The aim of this work was the identification of new metabolites and transformation products (TPs) in chicken muscle from Enrofloxacin (ENR), Ciprofloxacin (CIP), Difloxacin (DIF) and Sarafloxacin (SAR), which are antibiotics that belong to the fluoroquinolones family. The stability of ENR, CIP, DIF and SAR standard solutions versus pH degradation process (from pH 1.5 to 8.0, simulating the pH since the drug is administered until its excretion) and freeze-thawing (F/T) cycles was tested. In addition, chicken muscle samples from medicated animals with ENR were analyzed in order to identify new metabolites and TPs. The identification of the different metabolites and TPs was accomplished by comparison of mass spectral data from samples and blanks, using liquid chromatography coupled to quadrupole time-of-flight (LC-QqToF) and Multiple Mass Defect Filter (MMDF) technique as a pre-filter to remove most of the background noise and endogenous components. Confirmation and structure elucidation was performed by liquid chromatography coupled to linear ion trap quadrupole Orbitrap (LC-LTQ-Orbitrap), due to its mass accuracy and MS/MS capacity for elemental composition determination. As a result, 21 TPs from ENR, 6 TPs from CIP, 14 TPs from DIF and 12 TPs from SAR were identified due to the pH shock and F/T cycles. On the other hand, 14 metabolites were identified from the medicated chicken muscle samples. Formation of CIP and SAR, from ENR and DIF, respectively, and the formation of desethylene-quinolone were the most remarkable identified compounds.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.