Exploration of the core protein network under endometriosis symptomatology using a computational approach.

Background: Endometriosis is defined by implantation and invasive growth of endometrial tissue in extra-uterine locations causing heterogeneous symptoms, and a unique clinical picture for each patient. Understanding the complex biological mechanisms underlying these symptoms and the protein networks involved may be useful for early diagnosis and identification of pharmacological targets. Methods: In the present study, we combined three approaches (i) a text-mining analysis to perform a systematic search of proteins over existing literature, (ii) a functional enrichment analysis to identify the biological pathways in which proteins are most involved, and (iii) a protein-protein interaction (PPI) network to identify which proteins modulate the most strongly the symptomatology of endometriosis. Results: Two hundred seventy-eight proteins associated with endometriosis symptomatology in the scientific literature were extracted. Thirty-five proteins were selected according to degree and betweenness scores criteria. The most enriched biological pathways associated with these symptoms were (i) Interleukin-4 and Interleukin-13 signaling (p = 1.11 x 10-16), (ii) Signaling by Interleukins (p = 1.11 x 10-16), (iii) Cytokine signaling in Immune system (p = 1.11 x 10-16), and (iv) Interleukin-10 signaling (p = 5.66 x 10-15). Conclusion: Our study identified some key proteins with the ability to modulate endometriosis symptomatology. Our findings indicate that both pro- and anti-inflammatory biological pathways may play important roles in the symptomatology of endometriosis. This approach represents a genuine systemic method that may complement traditional experimental studies. The current data can be used to identify promising biomarkers for early diagnosis and potential therapeutic targets.

Development of an SPME-GC-MS method for the specific quantification of dimethylamine and trimethylamine: use of a new ratio for the freshness monitoring of cod fillets.

BACKGROUND: Fish is a highly perishable food, so it is important to be able to estimate its freshness to ensure optimum quality for consumers. The present study describes the development of an SPME-GC-MS technique capable of quantifying both trimethylamine (TMA) and dimethylamine (DMA), components of what has been defined as partial volatile basic nitrogen (PVB-N). This method was used, together with other reference methods, to monitor the storage of cod fillets (Gadus morhua) conserved under melting ice. RESULTS: Careful optimisation enabled definition of the best parameters for extracting and separating targeted amines and an internal standard. The study of cod spoilage by sensory analysis and TVB-N assay led to the conclusion that the shelf-life of cod fillet was between 6 and 7 days. Throughout the study, TMA and DMA were specifically quantified by SPME-GC-MS; the first was found to be highly correlated with the values returned by steam distillation assays. Neither TMA-N nor DMA-N were able to successfully characterise the decrease in early freshness, unlike dimethylamine/trimethylamine ratio (DTR), whose evolution is closely related to the results of sensory analysis until the stage where fillets need to be rejected. CONCLUSION: DTR was proposed as a reliable indicator for the early decrease of freshness until fish rejection. © 2015 Society of Chemical Industry.

Differentiation of fresh and frozen/thawed fish, European sea bass (Dicentrarchus labrax), gilthead seabream (Sparus aurata), cod (Gadus morhua) and salmon (Salmo salar), using volatile compounds by SPME/GC/MS.

BACKGROUND: A simple method based on solid phase microextraction/gas chromatography/mass spectrometry (SPME/GC/MS) was applied for studying the volatile profiles of whole fish samples of European sea bass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata) and fillets of cod (Gadus morhua) and salmon (Salmo salar) during frozen storage in order to be able to differentiate a fresh product from one that has been frozen. Analysis of volatile compounds was performed on these two product types, fresh and after freezing/thawing following storage at - 20 °C for 30 and 90 days. RESULTS: More than a hundred volatile compounds were found by SPME/GC/MS. Statistical processing by principal component analysis and ascending hierarchical classification was used to classify the samples into categories and verify the possibility of separating fresh samples from those that had been frozen and thawed. The compounds to be used as differentiators were identified. Four compounds were common to all species: dimethyl sulfide, 3-methylbutanal, ethyl acetate and 2-methylbutanal. Not only were they found in larger quantities after thawing but they also increased with the duration of storage at - 20 °C. CONCLUSION: These four compounds can therefore be considered as potential markers of differentiation between a fresh product and one that has been frozen.

Freshness characterisation of whiting (Merlangius merlangus) using an SPME/GC/MS method and a statistical multivariate approach.

BACKGROUND: The freshness of whiting was studied at five stages of ice storage by comparing the analysis of volatile compounds obtained through solid phase microextraction/gas chromatography/mass spectrometry (SPME/GC/MS) with two sensory methods. RESULTS: Of the volatile compounds identified, 38 were analysed using a statistical multivariate approach and classified according to their role in the estimation of freshness during storage as markers of freshness or spoilage. Regarding the evolution of the presence or absence of individual compounds, three categories were defined. For example, the volatile compounds propanal, hexanal, 1-penten-3-ol, pentanal, 2,3-pentanedione, 1-penten-3-one, heptanal, (E)-2-pentenal, 2,3-octanedione, (Z)-2-penten-1-ol, 1-pentanol, butanal, octanal, 3,5,5-trimethyl-2-hexene, 1-hexanol and 4,4-dimethyl-1,3-dioxane appeared highly relevant, because they are found throughout storage and can be divided into several categories that are directly related to the quality of fish. CONCLUSION: SPME/GC/MS combined with a statistical multivariate approach may be a useful method to identify volatile compounds and characterise fish freshness during storage.