Selective extraction of intracellular components from the microalga Chlorella vulgaris by combined pulsed electric field–temperature treatment

Author's accepted version (post-print).Available from 16/12/2017

Plasma Proteomic Variables Related to COVID-19 Severity: An Untargeted nLC-MS/MS Investigation

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection leads to a wide range of clinical manifestations and determines the need for personalized and precision medicine. To better understand the biological determinants of this heterogeneity, we explored the plasma proteome of 43 COVID-19 patients with different outcomes by an untargeted liquid chromatography-mass spectrometry approach. The comparison between asymptomatic or pauci-symptomatic subjects (MILDs), and hospitalised patients in need of oxygen support therapy (SEVEREs) highlighted 29 proteins emerged as differentially expressed: 12 overexpressed in MILDs and 17 in SEVEREs. Moreover, a supervised analysis based on a decision-tree recognised three proteins (Fetuin-A, Ig lambda-2chain-C-region, Vitronectin) that are able to robustly discriminate between the two classes independently from the infection stage. In silico functional annotation of the 29 deregulated proteins pinpointed several functions possibly related to the severity; no pathway was associated exclusively to MILDs, while several only to SEVEREs, and some associated to both MILDs and SEVEREs; SARS-CoV-2 signalling pathway was significantly enriched by proteins up-expressed in SEVEREs (SAA1/2, CRP, HP, LRG1) and in MILDs (GSN, HRG). In conclusion, our analysis could provide key information for 'proteomically' defining possible upstream mechanisms and mediators triggering or limiting the domino effect of the immune-related response and characterizing severe exacerbations

Effect of PEF and steam blanching treatments on the extraction yield of carotenoids from tomato wastes

Introduction. Industrial transformation of tomatoes typically include a thermophysical peeling phase of the fruits, which lead to the production of large amount of wastes, namely peels. These wastes are currently used as feed for animal or sent to landfill leading to environmental and economical problems for the industry. However, they represent a cheap and rich source of several carotenoids, particularly lycopene. Therefore, in order to pursue the concept of ―zero waste‖ or ―total use‖ of agri-food residues with increasing industrial profitability, the recovery of these high-added value compounds is a challenge. Traditionally, these compounds are recovered by extraction with solvent which is a time consuming process and requires large quantities of solvents. The aim of this work, which was carried out in the frame of the European project ―FieldFood‖, was to assess the potential of pulsed electric field (PEF) technology alone or in combination with steam blanching, to improve the recovery of carotenoids from tomato peels. Materials and Methods. PEF treatments of whole tomato fruit were carried out at field strengths in the range 0.25-0.75 kV/cm and energy input between 0.25 and 5 kJ/kg. The evaluation of the cell disintegration index via impedance analysis was used to select optimal PEF treatment conditions. Tomato samples treated under these optimal conditions were then peeled with or without the application of a thermal treatment by steam (50–60–70°C). The achieved peels were subjected to solvent extraction in acetone for 24h, and the extracts were analysed by both spectrophotometric and HPLC analysis in order to evaluate the total carotenoids content and antioxidant activity of the extracts as well as the chemical composition of the extracts. Results. Results showed that, for each field strength applied, the cell disintegration index increased with increasing the energy input, reaching a saturation value for an energy input of 1 kJ/kg. The application of PEF pretreatment at different field strengths and at 1 kJ/kg at room temperature, allowed to increase the total carotenoids content and antioxidant activity of the extracts up to, respectively, 2.7 and 4.2-fold those detected in the untreated samples. The application of a combined treatment (PEF + steam blanching) significantly increased the carotenoids content and the antioxidant power of the extracts, allowing to save energy with respect to a conventional steam blanching treatment. HPLC analyses revealed that PEF pre-treatment alone or in combination with steam blanching increased lycopene concentration in the extracts with respect to the untreated samples. Moreover, no evidence of selective release or degradation of individual carotenoids due to PEF application was detected. Conclusions. Results obtained from this study demonstrate the potential of PEF as pre-treatment method to improve the efficiency of industrial processing of tomato fruits

FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks

Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can be tested by means of targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the one hand, detailed mechanistic models can involve hundreds or thousands of molecular species and their intermediate complexes, as well as hundreds or thousands of chemical reactions, a situation generally occurring in rule-based modeling. On the other hand, the computational analysis of a model typically requires the execution of a large number of simulations for its calibration or to test the effect of perturbations. As a consequence, the computational capabilities of modern Central Processing Units can be easily overtaken, possibly making the modeling of biochemical networks a worthless or ineffective effort. To the aim of overcoming the limitations of the current state-of-the-art simulation approaches, we present in this paper FiCoS, a novel “black-box” deterministic simulator that effectively realizes both a fine-grained and a coarse-grained parallelization on Graphics Processing Units. In particular, FiCoS exploits two different integration methods, namely, the Dormand–Prince and the Radau IIA, to efficiently solve both non-stiff and stiff systems of coupled Ordinary Differential Equations. We tested the performance of FiCoS against different deterministic simulators, by considering models of increasing size and by running analyses with increasing computational demands. FiCoS was able to dramatically speedup the computations up to 855×, showing to be a promising solution for the simulation and analysis of large-scale models of complex biological processes

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

Introduction: Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions. Areas covered: This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions. Expert commentary: Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis

Synthesis and characterization of a paramagnetic sialic acid conjugate as probe for magnetic resonance applications

11 páginas, 8 figuras, 4 tablas, 3 esquemas -- PAGS nros. 21-31Magnetic Resonance Imaging (MRI) using paramagnetic systems as contrast agents is receiving increased attention as diagnostic tool in the clinic. At the same time, NMR of paramagnetic systems can also be applied in biochemical fields; for example, the use of Paramagnetic Relaxation Enhancement (PRE) allows structure refinement and the analysis of transient dynamic processes involved in macromolecular complex formation. Herein we report the synthesis and computational characterization of a new DOTA-like sialic acid conjugate, which can be used both in MRI and PRE applications when coordinated to a suitable paramagnetic metalWe gratefully acknowledge financial supports from the University of Milano-Bicocca (FAR2008) and computational facilities from CILEA (Consorzio Interuniversitario Lomabardo per l’Elaborazione Automatica), Programma Operativo Regione Lombardia Ob. 3 Fondo Sociale Europeo 2000–2006, Sovvenzione Globale Progetto Ingenio A0001127/2007 and Consorzio Interuniversitario Nazionale ‘Metodologie e Processi Innovativi di Sintesi’ (C.I.N.M.P.I.S.).Peer reviewe

Synthesis and characterization of a paramagnetic sialic acid conjugate as probe for magnetic resonance applications

11 páginas, 8 figuras, 4 tablas, 3 esquemas -- PAGS nros. 21-31Magnetic Resonance Imaging (MRI) using paramagnetic systems as contrast agents is receiving increased attention as diagnostic tool in the clinic. At the same time, NMR of paramagnetic systems can also be applied in biochemical fields; for example, the use of Paramagnetic Relaxation Enhancement (PRE) allows structure refinement and the analysis of transient dynamic processes involved in macromolecular complex formation. Herein we report the synthesis and computational characterization of a new DOTA-like sialic acid conjugate, which can be used both in MRI and PRE applications when coordinated to a suitable paramagnetic metalWe gratefully acknowledge financial supports from the University of Milano-Bicocca (FAR2008) and computational facilities from CILEA (Consorzio Interuniversitario Lomabardo per l’Elaborazione Automatica), Programma Operativo Regione Lombardia Ob. 3 Fondo Sociale Europeo 2000–2006, Sovvenzione Globale Progetto Ingenio A0001127/2007 and Consorzio Interuniversitario Nazionale ‘Metodologie e Processi Innovativi di Sintesi’ (C.I.N.M.P.I.S.).Peer reviewe