Unsupervised clustering to differentiate rheumatoid arthritis patients based on proteomic signatures.

OBJECTIVE: Patients with rheumatoid arthritis (RA) have different presentations and prognoses. Cluster analysis based on proteomic signatures creates independent phenogroups of patients with different pathophysiological backgrounds. We aimed to identify distinct pathophysiological clusters of RA patients based on circulating proteomic biomarkers. METHOD: This was a cohort study including 399 RA patients. Clustering was performed on 94 circulating proteins (92 CVDII Olink®, high-sensitivity troponin T, and C-reactive protein). Unsupervised clustering was performed using a partitioning cluster algorithm. RESULTS: The clustering algorithm identified two distinct clusters: cluster 1 (n = 223) and cluster 2 (n = 176). Compared with cluster 1, cluster 2 included older patients with a higher burden of comorbidities (cardiovascular and RA related), more erosive and longer RA duration, more dyspnoea and fatigue, walking a shorter distance in the Six-Minute Walk Test, with more severe diastolic dysfunction, and a 4.5-fold higher risk of death or hospitalization for cardiovascular reasons. Tumour necrosis factor (TNF) receptor superfamily-related pathways were mainly responsible for the model's discriminative ability. CONCLUSION: Using unsupervised cluster analysis based on proteomic phenotypes, we identified two clusters of RA patients with distinct biomarkers profiles, clinical characteristics, and different outcomes that could reflect different pathophysiological backgrounds. TNF receptor superfamily-related proteins may be used to distinguish subgroups.

Allergic asthma exhaled breath metabolome: a challenge for comprehensive two-dimensional gas chromatography.

Allergic asthma represents an important public health issue, most common in the paediatric population, characterized by airway inflammation that may lead to changes in volatiles secreted via the lungs. Thus, exhaled breath has potential to be a matrix with relevant metabolomic information to characterize this disease. Progress in biochemistry, health sciences and related areas depends on instrumental advances, and a high throughput and sensitive equipment such as comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GC-ToFMS) was considered. GC×GC-ToFMS application in the analysis of the exhaled breath of 32 children with allergic asthma, from which 10 had also allergic rhinitis, and 27 control children allowed the identification of several hundreds of compounds belonging to different chemical families. Multivariate analysis, using Partial Least Squares-Discriminant Analysis in tandem with Monte Carlo Cross Validation was performed to assess the predictive power and to help the interpretation of recovered compounds possibly linked to oxidative stress, inflammation processes or other cellular processes that may characterize asthma. The results suggest that the model is robust, considering the high classification rate, sensitivity, and specificity. A pattern of six compounds belonging to the alkanes characterized the asthmatic population: nonane, 2,2,4,6,6-pentamethylheptane, decane, 3,6-dimethyldecane, dodecane, and tetradecane. To explore future clinical applications, and considering the future role of molecular-based methodologies, a compound set was established to rapid access of information from exhaled breath, reducing the time of data processing, and thus, becoming more expedite method for the clinical purposes.

Probing beer aging chemistry by nuclear magnetic resonance and multivariate analysis.

This paper describes the use of nuclear magnetic resonance (NMR) spectroscopy, in tandem with multivariate analysis (MVA), for monitoring the chemical changes occurring in a lager beer exposed to forced aging (at 45°C for up to 18 days). To evaluate the resulting compositional variations, both principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were applied to the NMR spectra of beer recorded as a function of aging and a clear aging trend was observed. Inspection of PLS-DA loadings and peak integration enabled the changing compounds to be identified, revealing the importance of well known markers such as 5-hydroxymethylfurfural (5-HMF) as well as a range of other relevant compounds: amino acids, higher alcohols, organic acids, dextrins and some still unassigned spin systems. In addition, the multivariate analysis method of 2D correlation analysis was applied to the NMR data enabling the relevant compound variations to be confirmed and inter-compound correlations to be assessed, some reflecting common metabolic/chemical pathways and, therefore, offering improved insight into the chemical aspects of beer aging.

Profiling allergic asthma volatile metabolic patterns using a headspace-solid phase microextraction/gas chromatography based methodology.

Allergic asthma represents an important public health issue with significant growth over the years, especially in the paediatric population. Exhaled breath is a non-invasive, easily performed and rapid method for obtaining samples from the lower respiratory tract. In the present manuscript, the metabolic volatile profiles of allergic asthma and control children were evaluated by headspace solid-phase microextraction combined with gas chromatography-quadrupole mass spectrometry (HS-SPME/GC-qMS). The lack of studies in breath of allergic asthmatic children by HS-SPME led to the development of an experimental design to optimize SPME parameters. To fulfil this objective, three important HS-SPME experimental parameters that influence the extraction efficiency, namely fibre coating, temperature and time extractions were considered. The selected conditions that promoted higher extraction efficiency corresponding to the higher GC peak areas and number of compounds were: DVB/CAR/PDMS coating fibre, 22 °C and 60 min as the extraction temperature and time, respectively. The suitability of two containers, 1L Tedlar® bags and BIOVOC®, for breath collection and intra-individual variability were also investigated. The developed methodology was then applied to the analysis of children exhaled breath with allergic asthma (35), from which 13 had also allergic rhinitis, and healthy control children (15), allowing to identify 44 volatiles distributed over the chemical families of alkanes (linear and ramified) ketones, aromatic hydrocarbons, aldehydes, acids, among others. Multivariate studies were performed by Partial Least Squares-Discriminant Analysis (PLS-DA) using a set of 28 selected metabolites and discrimination between allergic asthma and control children was attained with a classification rate of 88%. The allergic asthma paediatric population was characterized mainly by the compounds linked to oxidative stress, such as alkanes and aldehydes. Furthermore, more detailed information was achieved combining the volatile metabolic data, suggested by PLS-DA model, and clinical data.

Quantification of organic acids in beer by nuclear magnetic resonance (NMR)-based methods.

The organic acids present in beer provide important information on the product's quality and history, determining organoleptic properties and being useful indicators of fermentation performance. NMR spectroscopy may be used for rapid quantification of organic acids in beer and different NMR-based methodologies are hereby compared for the six main acids found in beer (acetic, citric, lactic, malic, pyruvic and succinic). The use of partial least squares (PLS) regression enables faster quantification, compared to traditional integration methods, and the performance of PLS models built using different reference methods (capillary electrophoresis (CE), both with direct and indirect UV detection, and enzymatic essays) was investigated. The best multivariate models were obtained using CE/indirect detection and enzymatic essays as reference and their response was compared with NMR integration, either using an internal reference or an electrical reference signal (Electronic REference To access In vivo Concentrations, ERETIC). NMR integration results generally agree with those obtained by PLS, with some overestimation for malic and pyruvic acids, probably due to peak overlap and subsequent integral errors, and an apparent relative underestimation for citric acid. Overall, these results make the PLS-NMR method an interesting choice for organic acid quantification in beer.

Improving the detection of significant factors using ANOVA-PCA by selective reduction of residual variability.

Selective elimination of residual error can be used when applying Harrington's ANOVA-PCA in order to improve the capabilities of the method. ANOVA-PCA is sometimes unable to discriminate between levels of a factor when sources of high residual variability are present. In some cases this variability is not random, possesses some structure and is large enough to be responsible for the first principal components calculated by the PCA step in the ANOVA-PCA. This fact sometimes makes it impossible for the interesting variance to be in the first two PCA components. By using the proposed selective residuals elimination procedure, one may improve the ability of the method to detect significant factors as well as have an understanding of the different kinds of residual variance present in the data. Two datasets are used to show how the method is used in order to iteratively detect variance associated with the factors even when it is not initially visible. A permutation method is used to confirm that the observed significance of the factors was not accidental.

Quantitation of aliphatic suberin in Quercus suber L. cork by FTIR spectroscopy and solid-state (13)C-NMR spectroscopy.

This work determined that the percentage of suberin in cork may be found by solid-state (13)C cross polarization/magic angle spinning (CP/MAS) NMR spectroscopy and by FTIR with photoacoustic detection (FTIR-PAS) spectroscopy. A linear relationship is found between the suberin content measured through CP/MAS spectral areas and that measured gravimetrically. Furthermore, application of a partial least squares (PLS1) regression model to the NMR and gravimetric data sets clearly correlates the two sets, enabling suberin quantification with 90% precision. Suberin quantitation by FTIR-PAS spectroscopy is also achieved by a PLS1 regression model, giving 90% accurate estimates of the percentage of suberin in cork. Therefore, (13)C-CP/MAS NMR and FTIR-PAS proved to be useful and accurate noninvasive techniques to quantify suberin in cork, thus avoiding the traditional time consuming and destructive chemical methods.

[Comparative analysis of conventional dental floss and alternative materials]. / Análise comparativa entre a fita dental convencional e materiais alternativos.

The interproximal plaque-removing effect of three different materials (classic dental floss, rafia floss and indian floss) was tested in a group of 80 males (18 years-old). After two weeks all the materials had the same efficacy in removing the bacterial plaque, with significant reduction in interproximal plaque index. According to an opinion inquiry the rafia floss was the most comfortable material to use and has the lowest cost as well.

Variability of cork from Portuguese Quercus suber studied by solid-state (13)C-NMR and FTIR spectroscopies.

A new approach is presented for the study of the variability of Portuguese reproduction cork using solid-state (13)C-NMR spectroscopy and photoacoustic (PAS) FTIR (FTIR-PAS) spectroscopy combined with chemometrics. Cork samples were collected from 12 different geographical sites, and their (13)C-cross-polarization with magic angle spinning (CP/MAS) and FTIR spectra were registered. A large spectral variability among the cork samples was detected by principal component analysis and found to relate to the suberin and carbohydrate contents. This variability was independent of the sample geographical origin but significantly dependent on the cork quality, thus enabling the distinction of cork samples according to the latter property. The suberin content of the cork samples was predicted using multivariate regression models based on the (13)C-NMR and FTIR spectra of the samples as reported previously. Finally, the relationship between the variability of the (13)C-CP/MAS spectra with that of the FTIR-PAS spectra was studied by outer product analysis. This type of multivariate analysis enabled a clear correlation to be established between the peaks assigned to suberin and carbohydrate in the FTIR spectrum and those appearing in the (13)C-CP/MAS spectra.

Cardiotocografia anteparto de repouso. Estudo da cinetica fetal e sua correlacao com as aceleracoes transitorias. / Nonstress antepartum cardiotocograpy. Study of fetal kinetics and its relations to transient fetal heart accelerations

Sao apresentadas 49 cardiotocografias anteparto de repouso obtidas de 49 gestantes de alto risco, objetivando-se caracterizar as aceleracoes transitorias da frequencia cardiaca fetal quanto a sua amplitude e duracao, correlacionando-as com os movimentos fetais agrupados e isolados e com as contracoes uterinas. A incidencia de movimentos isolados e agrupados foi semelhante. Entretanto, os agrupados desencadearam maior numero de aceleracoes transitorias que os isolados, considerando-se a amplitude minima de 10 bpm na definicao da aceleracao transitoria; esta diferenca ampliou-se quando a amplitude minima considerada foi 15 bpm. As aceleracoes transitorias foram mais duradouras com os movimentos agrupados e a maioria teve duracao minima de 15 segundos. Um grande numero de registros nao exibiu nenhuma contracao uterina e poucas contracoes desencadearam aceleracoes transitorias