Predição de curva de destilação de gasolina de pirólise a partir de resultados de cromatografia em fase gasosa e calibração multivariada

A gasolina de pirólise pesada, também conhecida por PYGAS pesada (do acrônimo em inglês “pyrolysis gasoline”), é uma mistura de hidrocarbonetos majoritariamente maiores que 8 carbonos, obtida a partir do fracionamento dos produtos obtidos a partir do craqueamento da nafta. PYGAS pesada tem seu controle no processo produtivo realizado por análises de destilação, segundo o ASTM D86, e composição por cromatografia em fase gasosa com uso de detector de ionização por chama. Uma vez que o volume de amostra para a análise de destilação é muito superior ao de cromatografia (100:1) e existe o risco de princípio de incêndio em destilações se houver vidraria trincada ou montagem inadequada do sistema, foi desenvolvido o trabalho de predizer os valores de destilação de PYGAS pesada a partir dos resultados de cromatografia em fase gasosa, com aplicação de calibração multivariada. Neste trabalho foram aplicadas Regressão Linear Múltipla (MLR) e Regressão pelo Método dos Quadrados Mínimos Parciais (PLS), comparando os resultados obtidos entre os dois métodos de regressão e com os valores de referência de repetibilidade e reprodutibilidade do ASTM D86 de 2018. Para os pontos de destilação 20%, 30%, 40%, 50%, 60%, 70%, 80% e 90%, tanto no MLR quanto no PLS, os valores de erro médio quadrático da predição (RMSEP) ficaram inferiores 1 ℃ e r maior que 0,94 e os valores de erro obtidos ficaram dentro do intervalo de reprodutibilidade para cada ponto. Para o Ponto Inicial de Ebulição, o RMSEP foi de 7,5 ℃ para o MLR e 9,9 ℃ para o PLS, enquanto os valores de r foram de 0,4 e -0,1, respectivamente. O Ponto Inicial de Ebulição predito obteve resultados insatisfatórios quando comparado aos valores de repetibilidade e reprodutibilidade da referência. Para destilação 5%, os RMSEPs foram de 2,4 ℃ e 3,1 ℃ e os valores de r foram de 0,78 e 0,73, respectivamente para MLR e PLS. O ponto de destilação 10% teve valores semelhantes aos pontos 20% e 30% no MLR, porém no PLS os resultados ficaram um pouco diferentes, com RMSEP de 1,5 ℃ e r de 0,8. No comparativo com o ASTM D86, com resultados foram satisfatórios. Para os pontos de destilação 95% e Ponto Final de Ebulição, os valores de RMSEP foram entre 1,5 ℃ e 2,5 ℃ e os valores de r foram superiores a 0,94 nos dois métodos, bem como os erros de cada ponto ficaram dentro do intervalo de reprodutibilidade do ASTM D86. O resíduo de destilação não tem valores de repetibilidade ou reprodutibilidade na referência, porém ficou evidente a impossibilidade do MLR e do PLS de predizerem valores menores 0,5% v/v, o que pode ser explicado pela etapa manual inerente a esta leitura. Comparativamente, os valores de MLR se apresentaram semelhantes ou melhores que PLS, porém nenhum dos dois métodos de calibração multivariada foi capaz de predizer os valores de Ponto Inicial de Ebulição da destilação de PYGAS pesada.The heavy pyrolysis gasoline, also known as heavy PYGAS, is a mixture of hydrocarbons mostly composed by more than 8 carbons, obtained through the fractionation of the products obtained in the fractionation of naphtha. The control of heavy PYGAS production process is developed through distillation analysis, according to ASTM D86, and chromatography composition through flame ionization detector usage. Since the sample volume is considerably higher compared to the chromatography volume (100:1), and there is a risk of fire onset in distillation if the glassware is cracked or if the system is improperly assembled, a work to predict the values of heavy PYGAS distillation was developed from the gas chromatography results, with multivariate calibration application. In this work, Multiple Linear Regression (MLR) and Partial Least Square (PLS) were applied to compare the results obtained between both methods and the reference values of ASTM D86 from 2018 repeatability and reproducibility. For the distillation values of 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90%, both for MLR and PLS, the root mean square error of prediction (RMSEP) values were 1 ºC inferior, presented a r higher than 0.94 and the error values obtained were in the reproducibility interval for each point. For Initial Boiling Point, the RMSEP value was 7.5 ºC to the MLR and 9.9 ºC to PLS, whilst the r values were 0.4 and -0.1, respectively. For a 5% distillation, the RMSEPs were 2.4 ºC and 3.1 ºC and the r value were 0.78 and 0.73, respectively for MLR and PLS. The 10% distillation point reached similar values to the 20% and 30% points in MLR, however, the PLS results were slightly different, with RMSEP of 1.5 ºC and r value of 0.8. According to the results comparison with the ASTM D86, the results were satisfactory. For the 95% distillation points and Final Boiling Point, the RMSEP were 1.5 ºC and 2.5 ºC, the r values were higher than 0.94 for both methods, as well as the errors for each point, which were in the ASTM D86 repeatability range. The distillation residue did not present reproducibility or repeatability values in the reference, yet the impossibility of MLR and PLS predictability for values inferior than 0.5% v/v became evident, which can be explained by the inherent manual step of this reading. In comparison, the MLR values were presented in similarity, or better, with the PLS, but none of the multivariate calibration methods were capable to predict the Initial Boiling Point distillation values for the heavy PYGAS

Plague Dot Text:Text mining and annotation of outbreak reports of the Third Plague Pandemic (1894-1952)

The design of models that govern diseases in population is commonly built on information and data gathered from past outbreaks. However, epidemic outbreaks are never captured in statistical data alone but are communicated by narratives, supported by empirical observations. Outbreak reports discuss correlations between populations, locations and the disease to infer insights into causes, vectors and potential interventions. The problem with these narratives is usually the lack of consistent structure or strong conventions, which prohibit their formal analysis in larger corpora. Our interdisciplinary research investigates more than 100 reports from the third plague pandemic (1894-1952) evaluating ways of building a corpus to extract and structure this narrative information through text mining and manual annotation. In this paper we discuss the progress of our ongoing exploratory project, how we enhance optical character recognition (OCR) methods to improve text capture, our approach to structure the narratives and identify relevant entities in the reports. The structured corpus is made available via Solr enabling search and analysis across the whole collection for future research dedicated, for example, to the identification of concepts. We show preliminary visualisations of the characteristics of causation and differences with respect to gender as a result of syntactic-category-dependent corpus statistics. Our goal is to develop structured accounts of some of the most significant concepts that were used to understand the epidemiology of the third plague pandemic around the globe. The corpus enables researchers to analyse the reports collectively allowing for deep insights into the global epidemiological consideration of plague in the early twentieth century.Comment: Journal of Data Mining & Digital Humanities 202

Effect of Experimental Thyrotoxicosis onto Blood Coagulation: A Proteomics Study

Background: Hyperthyroidism is known to induce a hypercoagulable state. It stimulates plasma levels of procoagulative factors and reduces fibrinolytic activity. So far most of the data have been derived from patients with endogenous hyperthyroidism with a wide variability in the underlying pathogenesis and severity of the disease. Objectives: In this study we experimentally induced thyrotoxicosis in healthy volunteers to explore the effects of thyroxine excess on the plasma proteome. Using a shotgun proteomics approach, the abundance of plasma proteins was monitored before, during and after thyrotoxicosis. Methods: Sixteen healthy male subjects were sampled at baseline, 4 and 8 weeks under 250 µg/day thyroxine p.o., as well as 4 and 8 weeks after stopping the application. Plasma proteins were analyzed after depletion of 6 high-abundance proteins (MARS6) by LC-ESI-MS/MS mass spectrometry. Mass spectrometric raw data were processed using a label-free, intensity-based workflow. Subsequently, the linear dependence between protein abundances and fT4 levels were calculated using a Pearson correlation. Results: All subjects developed biochemical thyrotoxicosis, and this effect was reversed within the first 4 weeks of follow-up. None of the volunteers noticed any subjective symptoms. Levels of 10 proteins involved in the coagulation cascade specifically correlated with fT4, supporting an influence of thyroid hormone levels on blood coagulation even at nonpathological levels. Conclusions: The results suggest that experimental thyrotoxicosis exerts selective and specific thyroxine-induced effects on coagulation markers. Our study design allows assessment of thyroid hormone effects on plasma protein levels without secondary effects of other diseases or therapies

Quantification of glyphosate and aminomethylphosphonic acid from microbiome reactor fluids

Rationale: Glyphosate is one of the most widely used herbicides and it is suspected to affect the intestinal microbiota through inhibition of aromatic amino acid synthesis via the shikimate pathway.In vitromicrobiome bioreactors are increasingly used as model systems to investigate effects on intestinal microbiota and consequently methods for the quantitation of glyphosate and its degradation product aminomethylphosphonic acid (AMPA) in microbiome model systems are required. Methods: An optimized protocol enables the analysis of both glyphosate and AMPA by simple extraction with methanol:acetonitrile:water (2:3:1) without further enrichment steps. Glyphosate and AMPA are separated by liquid chromatography on an amide column and identified and quantified with a targeted tandem mass spectrometry method using a QTRAP 5500 system (AB Sciex). Results: Our method has a limit of detection (LOD) in extracted water samples of <2 ng/mL for both glyphosate and AMPA. In complex intestinal medium, the LOD is 2 and 5 ng/mL for glyphosate and AMPA, respectively. These LODs allow for measurement at exposure-relevant concentrations. Glyphosate levels in a bioreactor model of porcine colon were determined and consequently it was verified whether AMPA was produced by porcine gut microbiota. Conclusions: The method presented here allows quantitation of glyphosate and AMPA in complex bioreactor fluids and thus enables studies of the impact of glyphosate and its metabolism on intestinal microbiota. In addition, the extraction protocol is compatible with an untargeted metabolomics analysis, thus allowing one to look for other perturbations caused by glyphosate in the same sample

The glyphosate formulation Roundup® LB plus influences the global metabolome of pig gut microbiota in vitro

Glyphosate is the world's most widely used herbicide, and its potential side effects on the intestinal microbiota of various animals, from honeybees to livestock and humans, are currently under discussion. Pigs are among the most abundant livestock animals worldwide and an impact of glyphosate on their intestinal microbiota function can have serious consequences on their health, not to mention the economic effects. Recent studies that addressed microbiota-disrupting effects focused on microbial taxonomy but lacked functional information. Therefore, we chose an experimental design with a short incubation time in which effects on the community structure are not expected, but functional effects can be detected. We cultivated intestinal microbiota derived from pig colon in chemostats and investigated the acute effect of 228 mg/d glyphosate acid equivalents from Roundup® LB plus, a frequently applied glyphosate formulation. The applied glyphosate concentration resembles a worst-case scenario for an 8–9 week-old pig and relates to the maximum residue levels of glyphosate on animal fodder. The effects were determined on the functional level by metaproteomics, targeted and untargeted meta-metabolomics, while variations in community structure were analyzed by 16S rRNA gene profiling and on the single cell level by microbiota flow cytometry. Roundup® LB plus did not affect the community taxonomy or the enzymatic repertoire of the cultivated microbiota in general or on the expression of the glyphosate target enzyme 5-enolpyruvylshikimate-3-phosphate synthase in detail. On the functional level, targeted metabolite analysis of short chain fatty acids (SCFAs), free amino acids and bile acids did not reveal significant changes, whereas untargeted meta-metabolomics did identify some effects on the functional level. This multi-omics approach provides evidence for subtle metabolic effects of Roundup® LB plus under the conditions applied

The Simplified Human Intestinal Microbiota (SIHUMIx) Shows High Structural and Functional Resistance against Changing Transit Times in In Vitro Bioreactors

Many functions in host–microbiota interactions are potentially influenced by intestinal transit times, but little is known about the effects of altered transition times on the composition and functionality of gut microbiota. To analyze these effects, we cultivated the model community SIHUMIx in bioreactors in order to determine the effects of varying transit times (TT) on the community structure and function. After five days of continuous cultivation, we investigated the influence of different medium TT of 12 h, 24 h, and 48 h. For profiling the microbial community, we applied flow cytometric fingerprinting and revealed changes in the community structure of SIHUMIx during the change of TT, which were not associated with changes in species abundances. For pinpointing metabolic alterations, we applied metaproteomics and metabolomics and found, along with shortening the TT, a slight decrease in glycan biosynthesis, carbohydrate, and amino acid metabolism and, furthermore, a reduction in butyrate, methyl butyrate, isobutyrate, valerate, and isovalerate concentrations. Specifically, B. thetaiotaomicron was identified to be affected in terms of butyrate metabolism. However, communities could recover to the original state afterward. This study shows that SIHUMIx showed high structural stability when TT changed—even four-fold. Resistance values remained high, which suggests that TTs did not interfere with the structure of the community to a certain degree

Plasma proteome and metabolome characterization of an experimental human thyrotoxicosis model.

BACKGROUND: Determinations of thyrotropin (TSH) and free thyroxine (FT4) represent the gold standard in evaluation of thyroid function. To screen for novel peripheral biomarkers of thyroid function and to characterize FT4-associated physiological signatures in human plasma we used an untargeted OMICS approach in a thyrotoxicosis model. METHODS: A sample of 16 healthy young men were treated with levothyroxine for 8 weeks and plasma was sampled before the intake was started as well as at two points during treatment and after its completion, respectively. Mass spectrometry-derived metabolite and protein levels were related to FT4 serum concentrations using mixed-effect linear regression models in a robust setting. To compile a molecular signature discriminating between thyrotoxicosis and euthyroidism, a random forest was trained and validated in a two-stage cross-validation procedure. RESULTS: Despite the absence of obvious clinical symptoms, mass spectrometry analyses detected 65 metabolites and 63 proteins exhibiting significant associations with serum FT4. A subset of 15 molecules allowed a robust and good prediction of thyroid hormone function (AUC = 0.86) without prior information on TSH or FT4. Main FT4-associated signatures indicated increased resting energy expenditure, augmented defense against systemic oxidative stress, decreased lipoprotein particle levels, and increased levels of complement system proteins and coagulation factors. Further association findings question the reliability of kidney function assessment under hyperthyroid conditions and suggest a link between hyperthyroidism and cardiovascular diseases via increased dimethylarginine levels. CONCLUSION: Our results emphasize the power of untargeted OMICs approaches to detect novel pathways of thyroid hormone action. Furthermore, beyond TSH and FT4, we demonstrated the potential of such analyses to identify new molecular signatures for diagnosis and treatment of thyroid disorders. This study was registered at the German Clinical Trials Register (DRKS) [DRKS00011275] on the 16th of November 2016

The Metabolomic-Gut-Clinical Axis of Mankai Plant-Derived Dietary Polyphenols

Background: Polyphenols are secondary metabolites produced by plants to defend themselves from environmental stressors. We explored the effect of Wolffia globosa ‘Mankai’, a novel cultivated strain of a polyphenol-rich aquatic plant, on the metabolomic-gut clinical axis in vitro, in-vivo and in a clinical trial. Methods: We used mass-spectrometry-based metabolomics methods from three laboratories to detect Mankai phenolic metabolites and examined predicted functional pathways in a Mankai artificial-gut bioreactor. Plasma and urine polyphenols were assessed among the 294 DIRECT-PLUS 18-month trial participants, comparing the effect of a polyphenol-rich green-Mediterranean diet (+1240 mg/polyphenols/day, provided by Mankai, green tea and walnuts) to a walnuts-enriched (+440 mg/polyphenols/day) Mediterranean diet and a healthy controlled diet. Results: Approximately 200 different phenolic compounds were specifically detected in the Mankai plant. The Mankai-supplemented bioreactor artificial gut displayed a significantly higher relative-abundance of 16S-rRNA bacterial gene sequences encoding for enzymes involved in phenolic compound degradation. In humans, several Mankai-related plasma and urine polyphenols were differentially elevated in the green Mediterranean group compared with the other groups (p < 0.05) after six and 18 months of intervention (e.g., urine hydroxy-phenyl-acetic-acid and urolithin-A; plasma Naringenin and 2,5-diOH-benzoic-acid). Specific polyphenols, such as urolithin-A and 4-ethylphenol, were directly involved with clinical weight-related changes. Conclusions: The Mankai new plant is rich in various unique potent polyphenols, potentially affecting the metabolomic-gut-clinical axis