Cancer evaluation in dogs using cerumen as a source for volatile biomarker prospection.

Cancer is one of the deadliest diseases in humans and dogs. Nevertheless, most tumor types spread faster in canines, and early cancer detection methods are necessary to enhance animal survival. Here, cerumen (earwax) was tested as a source of potential biomarkers for cancer evaluation in dogs. Earwax samples from dogs were collected from tumor-bearing and clinically healthy dogs, followed by Headspace/Gas Chromatography-Mass Spectrometry (HS/GC-MS) analyses and multivariate statistical workflow. An evolutionary-based multivariate algorithm selected 18 out of 128 volatile metabolites as a potential cancer biomarker panel in dogs. The candidate biomarkers showed a full discrimination pattern between tumor-bearing dogs and cancer-free canines with high accuracy in the test dataset: an accuracy of 95.0% (75.1-99.9), and sensitivity and specificity of 100.0% and 92.9%, respectively. In summary, this work raises a new perspective on cancer diagnosis in dogs, being carried out painlessly and non-invasive, facilitating sample collection and periodic application in a veterinary routine.

Evaluating the impact of a cemetery on groundwater by multivariate analysis.

Water analyses in conjunction with hydrological and geotechnical investigations were carried out to assess the potential for groundwater contamination from the decomposition of buried human bodies. Water samples were collected from 2007 to 2018 in three monitoring wells built within the cemetery area. Water quality was evaluated based on the determination of 25 analytical parameters (20 physical-chemical and 5 microbiological). Laboratory data reported by the local sewage water company for water collected in household cisterns located outside the cemetery area were also evaluated. Multivariate analysis showed a similar pattern between iron content, turbidity, and rainfall data collected at the rainfall station closest to the study area. This behavior is a direct consequence of soil leaching (oxisol). The physical characterization of the soil of the unsaturated area above the aquifer indicates that the absorption of body waste by the soil is favored, preventing surface contaminants from reaching the aquifer. This work also found that the water samples collected outside the cemetery area do not comply with the Brazilian limits for drinking water. In conclusion, water samples collected from monitoring wells located within the cemetery area have little to none impact on both subsurface and underground contamination.

A cerumenolomic approach to bovine trypanosomosis diagnosis.

INTRODUCTION: Trypanosomiasis caused by Trypanosoma vivax (T. vivax, subgenus Duttonella) is a burden disease in bovines that induces losses of billions of dollars in livestock activity worldwide. To control the disease, the first step is identifying the infected animals at early stages. However, convention tools for animal infection detection by T. vivax present some challenges, facilitating the spread of the pathogenesis. OBJECTIVES: This work aims to develop a new procedure to identify infected bovines by T. vivax using cerumen (earwax) in a volatilomic approach, here named cerumenolomic, which is performed in an easy, quick, accurate, and non-invasive manner. METHODS: Seventy-eight earwax samples from Brazilian Curraleiro Pé-Duro calves were collected in a longitudinal study protocol during health and inoculated stages. The samples were analyzed using Headspace/Gas Chromatography-Mass Spectrometry followed by multivariate analysis approaches. RESULTS: The cerumen analyses lead to the identification of a broad spectrum of volatile organic metabolites (VOMs), of which 20 VOMs can discriminate between healthy and infected calves (AUC = 0.991, sensitivity = 0.967, specificity = 1.000). Furthermore, 13 VOMs can indicate a pattern of discrimination between the acute and chronic phases of the T. vivax infection in the animals (AUC = 0.989, sensitivity = 0.944, specificity = 1.000). CONCLUSION: The cerumen volatile metabolites present alterations in their occurrence during the T.vivax infection, which may lead to identifying the infection in the first weeks of inoculation and discriminating between the acute and chronic phases of the illness. These results may be a breakthrough to avoid the T. vivax outbreak and provide a faster clinical approach to the animal.

A volatolomic approach using cerumen as biofluid to diagnose bovine intoxication by Stryphnodendron rotundifolium.

An innovative volatolomic approach employs the detection of biomarkers present in cerumen (earwax) to identify cattle intoxication by Stryphnodendron rotundifolium Mart., Fabaceae (popularly known as barbatimão). S. rotundifolium is a poisonous plant with the toxic compound undefined and widely distributed throughout the Brazilian territory. Cerumen samples from cattle of two local Brazilian breeds ('Curraleiro Pé-Duro' and 'Pantaneiro') were collected during an experimental intoxication protocol and analyzed using headspace (HS)/GC-MS followed by multivariate analysis (genetic algorithm for a partial least squares, cluster analysis, and classification and regression trees). A total of 106 volatile organic metabolites were identified in the cerumen samples of bovines. The intoxication by S. rotundifolium influenced the cerumen volatolomic profile of the bovines throughout the intoxication protocol. In this way, it was possible to detect biomarkers for cattle intoxication. Among the biomarkers, 2-octyldecanol and 9-tetradecen-1-ol were able to discriminate all samples between intoxicated and nonintoxicated bovines. The cattle intoxication diagnosis by S. rotundifolium was accomplished by applying the cerumen analysis using HS/GC-MS, in an easy, accurate, and noninvasive way. Thus, the proposed bioanalytical chromatography protocol is a useful tool in veterinary applications to determine this kind of intoxication.

Direct Dielectric Barrier Discharge Ionization Promotes Rapid and Simple Lubricant Oil Fingerprinting.

Petroleomics, which is the characterization, separation, and quantification of the components of petroleum and crude oil, is an emerging area of study. However, the repertoire of analytical methods available to understand commercial automotive lubricant oils (ALOs) is very limited. Ambient mass spectrometry is one of the most sensitive analytical methods for real-time and in situ chemical analysis. With this technique, the chemical fingerprinting of ALOs can be performed quickly and simply using dielectric barrier discharge ionization time-of-flight mass spectrometry. In this study, the mass spectra of 35 samples were obtained without any sample preparation in positive-ion mode, and no carryover was observed. To elucidate the similarities and differences between the ALO samples, the data generated from these spectra were analyzed using four chemometric techniques: principal component analysis, multivariate curve resolution, hierarchical cluster analysis, and pattern recognition entropy. The ALO samples were readily differentiated according to their American Petroleum Institute classification and base oil types: mineral, semisynthetic, and synthetic. The development of this new methodology will aid in the semiquantitative control analysis of ALOs and offers an improved ability to identify the components therein.

Multiresponse optimization of an extraction procedure of carnosol and rosmarinic and carnosic acids from rosemary.

A green solvent-based optimization for rosmarinic acid (RA), carnosol (COH), and carnosic acid (CA) extraction, the three main antioxidants from rosemary, was performed. The conventional solid-liquid extraction was optimized using a central composite design (CCD) followed by the desirability approach. In the CCD analysis the quantitative effects of extraction time (4.8-55.2min), liquid-to-solid ratio (4.6-21.4mLg(-1)), and ethanol content (44.8-95.2% v/v) were determined for the extracted amount of antioxidants, their concentrations in the extract, and the extraction yield. Samples were analyzed by HPLC and the antioxidants were identified by comparison with pure standard retention times and UV spectra. The desirability function that simultaneously maximizes the antioxidants extraction and their concentrations in the final product was validated. The extraction using a hydroalcoholic solution 70% v/v, at low liquid-to-solid ratio (5mLg(-1)), and after 55-min yielded an antioxidant recovery rate of 89.8%, and a final product 4.75 times richer in the main antioxidants than the raw material.

Evaluation of transformer insulating oil quality using NIR, fluorescence, and NMR spectroscopic data fusion.

Power transformers are essential components in electrical energy distribution. One of their most important parts is the insulation system, consisting of Kraft paper immersed in insulating oil. Interfacial tension and color are major parameters used for assessing oil quality and the system׳s degradation. This work proposes the use of near infrared (NIR), molecular fluorescence, and (1)H nuclear magnetic resonance (NMR) spectroscopy methods combined with chemometric multivariate calibration methods (Partial Least Squares - PLS) to predict interfacial tension and color in insulating mineral oil samples. Interfacial tension and color were also determined using tensiometry and colorimetry as standard reference methods, respectively. The best PLS model was obtained when NIR, fluorescence, and NMR data were combined (data fusion), demonstrating synergy among them. An optimal PLS model was calculated using the selected group of variables according to their importance on PLS projections (VIP). The root mean square errors of prediction (RMSEP) values of 2.9 mN m(-1) and 0.3 were estimated for interfacial tension and color, respectively. Mean relative standard deviations of 1.5% for interfacial tension and 6% for color were registered, meeting quality control requirements set by electrical energy companies. The methods proposed in this work are rapid and simple, showing great advantages over traditional approaches, which are slow and environmentally unfriendly due to chemical waste generation.

Comparison of CIS- and EOM-CCSD-calculated adiabatic excited-state structures. Changes in charge density on going to adiabatic excited states.

The CIS and EOM-CCSD adiabatic geometries for the first excited states of a set of small molecules (C2H4, C2H2, H2C=O, H2C=S, CS2, CO2, SO2, NO2) have been calculated using the 6-311++G** basis set to see if the former geometries can be good starting points for optimizations at the latter theoretical level. With most of the molecules, there is fairly good agreement between the results from the two methods, and EOM-CCSD gives good agreement with the available experimental data. A detailed discussion of the lowest-lying singlet excited states in CO2 and CS2 is presented, highlighting the pronounced differences in electronic character and equilibrium structure displayed by these isovalent species. The origins of the structural distortions that are frequently found for the adiabatic excited states are examined with the aid of deformation density plots and the electron localization function (ELF).