Centre of Statistics and its Applications

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Parametric regression models for recurrent events analysis based on Chen distribution

Publication . Sousa-Ferreira, Ivo; Abreu, Ana Maria; Rocha, Cristina

In this paper, two parametric regression models based on Chen dis tribution are proposed for situations where recurrent events have the same or dif ferent risks of occurrence. Inference is based on a maximum likelihood approach, which ensures consistent parameter estimators. However, since in recurrent event data there is within-subject correlation, the “one step” jackknife estimator is used. An application on a real data set is also provided for illustrative purposes.

2019Conference object

Open access

An integrative approach based on GC–qMS and NMR metabolomics data as a comprehensive strategy to search potential breast cancer biomarkers

Publication . Silva, Catarina Luís; Perestrelo, Rosa; Capelinha, Filipa; Tomás, Helena; Câmara, José S.

Introduction Globally, breast cancer (BC) is leading at the top of women's diseases and, as a multifactorial disease, there is the need for the development of new approaches to aid clinicians on monitoring BC treatments. In this sense, metabo lomic studies have become an essential tool allowing the establishment of interdependency among metabolites in biological samples. Objective The combination of nuclear magnetic resonance (NMR) and gas chromatography–quadrupole mass spectrometry (GC–qMS) based metabolomic analyses of urine and breast tissue samples from BC patients and cancer-free individuals was used. Methods Multivariate statistical tools were used in order to obtain a panel of metabolites that could discriminate malignant from healthy status assisting in the diagnostic feld. Urine samples (n=30), cancer tissues (n=30) were collected from BC patients, cancer-free tissues were resected outside the tumor margin from the same donors (n=30) while cancer-free urine samples (n=40) where obtained from healthy subjects and analysed by NMR and GC–qMS methodologies. Results The orthogonal partial least square discriminant analysis model showed a clear separation between BC patients and cancer-free subjects for both classes of samples. Specifcally, for urine samples, the goodness of ft (R2 Y) and predictive ability (Q2 ) was 0.946 and 0.910, respectively, whereas for tissue was 0.888 and 0.813, revealing a good predictable accuracy. The discrimination efciency and accuracy of tissue and urine metabolites was ascertained by receiver operating charac teristic curve analysis that allowed the identifcation of metabolites with high sensitivity and specifcity. The metabolomic pathway analysis identifed several dysregulated pathways in BC, including those related with lactate, valine, aspartate and glutamine metabolism. Additionally, correlations between urine and tissue metabolites were investigated and fve metabo lites (e.g. acetone, 3-hexanone, 4-heptanone, 2-methyl-5-(methylthio)-furan and acetate) were found to be signifcant using a dual platform approach. Conclusion Overall, this study suggests that an improved metabolic profle combining NMR and GC–qMS may be useful to achieve more insights regarding the mechanisms underlying cancer.

2021Journal article

Open access

A note on global stability in the periodic logistic map

Publication . Luís, Rafael; Mendonça, Sandra

In this paper, the dynamics of the celebrated p−periodic one dimensional logistic map is explored. A result on the global stability of the origin is provided and, under certain conditions on the parameters, the local stability condition of the p−periodic orbit is shown to imply its global stability.

2020Journal article

Open access

Lipid biosignature of breast cancer tissues by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Publication . Silva, Catarina L.; Perestrelo, Rosa; Sousa-Ferreira, Ivo; Capelinha, Filipa; Câmara, José S.; Petković, Marijana

Purpose One of the hallmarks of cancer cells is the demand of supply for the synthesis of new membranes involved in cell proliferation and lipids have an important role in cellular structure, signaling pathways and progression of cancer. In this sense, lipid studies have become an essential tool allowing the establishment of signatures associated with breast cancer (BC). In this regard, some metabolic processes including proteins, nucleic acids and lipid synthesis are enhanced as part of cancer-associated metabolic reprogramming, as a requirement for cell growth and proliferation. Methods Pairwise samples of breast active carcinoma (BAC) and breast cancer-free tissues were collected from n=28 patients and analyzed by MALDI-TOF MS. Results Major lipid species are identifed in the MALDI-TOF mass spectra, with certain phosphatidylinositols (PIs) detect able only in BAC. Statistical analysis revealed signifcant diferences (p<0.05) between ratios lysophosphatidylcholine (LPC) 16:0/phosphatidylcholine (PC) 16:0_18:2 between AC and CF groups as well as for BC stages II and III. The ratio PC 16:0_18:2/PC16:0_18:1 was statistically diferent between AC and CF groups. The one-way ANOVA revealed that there are no statistical diferences among BC stages (I, II and III) within AC group. Comparing BC stages, the signifcance impact increased (p<0.05) with stage. Conclusion The obtained data revealed MALDI-TOF MS as a powerful tool to explore lipid signatures and the enzyme activity associated with BC and possibly establish novel disease markers.

2020Journal article

Open access