Changes in the blood plasma lipidome associated with effective or poor response to atypical antipsychotic treatments in schizophrenia patients.

Atypical antipsychotics are widely used to manage schizophrenia symptoms. However, these drugs can induce deleterious side effects, such as MetS, which are associated with an increased cardiovascular risk to patients. Lipids play a central role in this context, and changes in lipid metabolism have been implicated in schizophrenia's pathobiology. Furthermore, recent evidence suggests that lipidome changes may be related to antipsychotic treatment response. The aim of this study was to evaluate the lipidome changes in blood plasma samples of schizophrenia patients before and after 6 weeks of treatment with either risperidone, olanzapine, or quetiapine. Liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis showed changes in the levels of ceramides (Cer), glycerophosphatidic acids (PA), glycerophosphocholines (PC), phosphatidylethanolamines (PE), phosphatidylinositols (PI), glycerophosphoglycerols (PG), and phosphatidylserines (PS) for all treatments. However, the treatment with risperidone also affected diacylglycerides (DG), ceramide 1-phosphates (CerP), triglycerides (TG), sphingomyelins (SM), and ceramide phosphoinositols (PI-Cer). Moreover, specific lipid profiles were observed that could be used to distinguish poor and good responders to the different antipsychotics. As such, further work in this area may lead to lipid-based biomarkers that could be used to improve the clinical management of schizophrenia patients.

Investigating weathering in light diesel oils using comprehensive two-dimensional gas chromatography-High resolution mass spectrometry and pixel-based analysis: Possibilities and limitations.

Petroleum-derived fuels are chronically spilled in urbanized areas, affecting the environment and the population's health. Forensic investigations of oil spills aim to find the responsible source of the spills. Weathering processes (dissolution, evaporation, photo-oxidation and biodegradation) change the chemical composition of the spills and hamper the matching of spill-source pairs, especially for light diesel oils (i.e. n-C9 - n-C20) in which the source diesels can be very similar due to the refining process and only compounds resistant to short- or middle-term weathering are present. In this study, comprehensive two-dimensional gas chromatography - high resolution mass spectrometry (GC × GC - HRMS) and pixel-based analysis were combined for: i) improve the identification of very similar diesel oils, and ii) identify weathering-resistant compounds that can also distinguish samples from different sources. Diesel oils from two sources that have been exposed to different degrees of evaporation, photo-oxidation and biodegradation in a laboratory setup. The study revealed the tentatively identified octanoic acid methyl ester and n-nonaldehyde were more resistance to evaporation than hydrocarbons < n-C15. Furthermore, the hydrocarbons > n-C17 could be used for source-apportionment of all the diesel oils susceptible to evaporation and photo-oxidation, but only pristane and phytane were also more resistant to biodegradation. Naphthenes, bicyclic sesquiterpanes and adamantanes were more resistant to only photo-oxidation and biodegradation. GC × GC - HRMS enhanced the separation of the highly similar naphthenes in the diesel oils; however, the diagnostic power for forensic spill investigations was still similar to 1D GC - HRMS.

Forensic Investigations of Diesel Oil Spills in the Environment Using Comprehensive Two-Dimensional Gas Chromatography-High Resolution Mass Spectrometry and Chemometrics: New Perspectives in the Absence of Recalcitrant Biomarkers.

Forensic investigations of oil spills aim to find the responsible source(s) of the spill. Oil weathering processes change the chemical composition of the spilled oil and make the matching of oil spill samples to potential sources difficult. Diesel oil spill cases are more challenging, because biomarkers recalcitrant to long-term weathering are absent. We developed and tested a new method for the analysis and matching of diesel oil spills using two-dimensional gas chromatography-high resolution mass spectrometry (GC × GC - HRMS) and 2D-CHEMSIC (2-Dimensional CHEMometric analysis of Selected Ion Chromatograms), an extension of the CHEMSIC method to GC × GC data. The 2D-CHEMSIC performs pixel-based analysis using chemometrics on concatenated sections of 2D extracted ion chromatograms to assess the overall chemical variability of the samples, with potential applications for matching spill-source pairs in forensic investigations. The method was tested on samples from a number of diesel oil spill cases, (i) distinguishing chemically similar source diesels, (ii) investigating weathering effects on spill samples to determine type and degree of weathering, and (iii) improving the matching of diesel oil spills affected by weathering. Positive matches for spill-source pairs were identified after excluding the signals from the hydrocarbons most susceptible to evaporation, and photo-oxidized spills were also matched due to the presence of unaffected hydrocarbons. Forensic diagnostics obtained by the 2D-CHEMSIC were validated by the conventional CEN-Tr method.

Blood-Based Lipidomics Approach to Evaluate Biomarkers Associated With Response to Olanzapine, Risperidone, and Quetiapine Treatment in Schizophrenia Patients.

This is the first study to identify lipidomic markers in plasma associated with response of acutely ill schizophrenia patients in response to specific antipsychotic treatments. The study population included 54 schizophrenia patients treated with antipsychotics for 6 weeks. Treatment led to significant improvement in positive and negative symptoms for 34 patients with little or no improvement for 20 patients. In addition, 37 patients showed an increase in body mass index after the 6 week treatment period, consistent with effects on metabolism and the association of such effects with symptom improvement. Profiling of plasma samples taken prior to therapy using liquid chromatography tandem mass spectrometry (LC-MS/MS) resulted in identification of 38, 10, and 52 compounds associated with the olanzapine, risperidone, and quetiapine treatment groups, which could be used to distinguish responders from non-responders. Limitations include the retroactive active nature of the study and the small sample size. Further investigations with larger sample sets could lead to the development of a molecular test that could be used to help psychiatrists determine the best treatment options for each patient.

Optimizing loop-type cryogenic modulation in comprehensive two-dimensional gas chromatography using time-variable combination of the dual-stage jets for analysis of crude oil.

The enhanced chromatographic capability of the comprehensive two-dimensional gas chromatography (GC×GC) has already found several applications in analytical chemistry comprising complex samples. However, setting the appropriate chromatographic conditions that maximize sensitivity and separation efficiency in GC×GC may be more difficult than in conventional one-dimension gas chromatography, mainly due to the additional parameters strictly related to the modulation. Loop-type cryogenic modulators have been currently used for crude oil analysis using GC×GC, requiring sometimes a laborious try-and-error procedure to properly tune the dual-jets elapsed times on modulation. In this work, the advantages of choosing a time-variable combination of cold and hot jets pulses in a loop-type cryogenic modulator is presented when performing the fingerprinting analysis of crude oils using GC×GC-QMS, contrary to the conventional procedure based on a single combination for the dual-stage jets. A design of experiments approach is proposed to most effectively optimize the time-variable combination of the dual-jets elapsed times while modulating the wide hydrocarbons range along the GC×GC analysis. The most abundant classes of hydrocarbons contained in the maltenes fraction of a crude oil sample, such as paraffins, aromatics, steranes and hopanes were successfully resolved.

Discriminating Brazilian crude oils using comprehensive two-dimensional gas chromatography-mass spectrometry and multiway principal component analysis.

The geochemical characterization of petroleum is an essential task to develop new strategies and technologies when analyzing the commercial potential of crude oils for exploitation. Due to the chemical complexity of these samples, the use of modern analytical techniques along with multivariate exploratory data analysis approaches is an interesting strategy to extract relevant geochemical characteristics about the oils. In this work, important geochemical information obtained from crude oils from different production basins were obtained analyzing the maltene fraction of the oils by comprehensive two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GC×GC-QMS), and performing multiway principal component analysis (MPCA) of the chromatographic data. The results showed that four MPC explained 93.57% of the data variance, expressing mainly the differences on the profiles of the saturated hydrocarbon fraction of the oils (C13-C18 and C19-C30n-alkanes and the pristane/phytane ratio). The MPC1 grouped the samples severely biodegraded oils, while the type of the depositional paleoenvironments of the oils and its oxidation conditions (as well as their thermal maturity) could be inferred analysing others relevant MPC. Additionally, considerations about the source of the oil samples was also possible based on the overall distribution of relevant biomarkers such as the phenanthrene derivatives, tri-, tetra- and pentacyclic terpanes.

Monitoring of multiple solid-state transformations at tablet surfaces using multi-series near-infrared hyperspectral imaging and multivariate curve resolution.

The assessment of the solid-state stability of active pharmaceutical ingredient (API) and/or excipients in solid dosage forms during manufacturing and storage is mandatory for safeguarding quality of the final products. In this work, the solid-state transformations in tablets prepared as blends of piroxicam monohydrate, polyvinylpyrrolidone and the lactose forms monohydrate or anhydrate were studied when the tablets were exposed to the 23-120 °C range. Multi-series near-infrared hyperspectral images were obtained from the surface of each sample for unveiling the local evolution of the solid-state transformations. The preprocessed spectra from the images (dataset) were arranged in augmented matrices, according to the composition of the tablets, and the profile of the overlapped compounds (relative concentration) along the solid-state transformations in the pixels was resolved by using multivariate curve resolution--alternating least squares (MCR-ALS). Therefore, the dehydration of piroxicam and lactose monohydrates could be mapped separately in the samples (explained variances by the models >96%) even when both compounds were being transformed simultaneously (80-120 °C). The images reproduced the same trends obtained from thermogravimetric analysis of the tablets, with the advantage that the pixel-to-pixel heterogeneity of each compound at the surface of the tablets was highlighted.

Study of the homogeneity of drug loaded in polymeric films using near-infrared chemical imaging and split-plot design.

Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.

NIR imaging spectroscopy for quantification of constituents in polymers thin films loaded with paracetamol.

Thin films loaded with the drug paracetamol were produced from polymer blends formed by hydroxypropylmethylcellulose (HPMC), polyvinylpyrrolidone (PVP) and polyethyleneglycol (PEG), at various mass ratios of polymers and drug defined by a D-optimal experimental design. NIR hyperspectral images were obtained from each thin film formulation and the pixel-to-pixel quantification of the constituents were carried out by partial least square (PLS) and multivariate curve resolution-alternating least square (MCR-ALS) with three different calibration/validation strategies. These strategies differ in the way to construct the calibration and validation matrices and they had to be carried out to suppress the bias on the quantification of the constituents in the polymer blend. The errors of prediction in the models from MCR-ALS were influenced by the calibration/validation strategy employed, but they were similar to the ones from PLS model. Concentration distribution maps were built after pixel-to-pixel predictions and their characteristics were analyzed.