B Cells with a Senescent-Associated Secretory Phenotype Accumulate in the Adipose Tissue of Individuals with Obesity

Senescent cells accumulate in the adipose tissue (AT) of individuals with obesity and secrete multiple factors that constitute the senescence-associated secretory phenotype (SASP). This paper aimed at the identification of B cells with a SASP phenotype in the AT, as compared to the peripheral blood, of individuals with obesity. Our results show increased expression of SASP markers in AT versus blood B cells, a phenotype associated with a hyper-metabolic profile necessary to support the increased immune activation of AT-derived B cells as compared to blood-derived B cells. This hyper-metabolic profile is needed for the secretion of the pro-inflammatory mediators (cytokines, chemokines, micro-RNAs) that fuel local and systemic inflammation.     

Preliminary Evidence on the Diagnostic and Molecular Role of Circulating Soluble EGFR in Non-Small Cell Lung Cancer

Assessment of biological diagnostic factors providing clinically-relevant information to guide physician decision-making are still needed for diseases with poor outcomes, such as non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) is a promising molecule in the clinical management of NSCLC. While the EGFR transmembrane form has been extensively investigated in large clinical trials, the soluble, circulating EGFR isoform (sEGFR), which may have a potential clinical use, has rarely been considered. This study investigates the use of sEGFR as a potential diagnostic biomarker for NSCLC and also characterizes the biological function of sEGFR to clarify the molecular mechanisms involved in the course of action of this protein. Plasma sEGFR levels from a heterogeneous cohort of 37 non-advanced NSCLC patients and 54 healthy subjects were analyzed by using an enzyme-linked immunosorbent assay. The biological function of sEGFR was analyzed in vitro using NSCLC cell lines, investigating effects on cell proliferation and migration. We found that plasma sEGFR was significantly decreased in the NSCLC patient group as compared to the control group (median value: 48.6 vs. 55.6 ng/mL respectively; p = 0.0002). Moreover, we demonstrated that sEGFR inhibits growth and migration of NSCLC cells in vitro through molecular mechanisms that included perturbation of EGF/EGFR cell signaling and holoreceptor internalization. These data show that sEGFR is a potential circulating biomarker with a physiological protective role, providing a first approach to the functional role of the soluble isoform of EGFR. However, the impact of these data on daily clinical practice needs to be further investigated in larger prospective studies.     

Frequency of molecular alterations in heterozygous beta-thalassemia in southern Spain and their relation to the hematologic phenotype

INTRODUCTION: Heterozygous beta-thalassemia manifests hematologically with microcytosis, reduced red blood cell hemoglobin concentration and high hemoglobin A2 levels. Almost all molecular alterations are due to point mutations. We attempt to determinate the frequency of that mutations in the Oriental Andalusia Area, and its relationship with the hematological phenotype. PATIENTS AND METHODS: We have studied 45 heterozygous patients. DNA samples were amplified by PCR, using the printers CD7 and HI1. A 16 Kb fragment corresponding to beta globin gene was obtained and analyzed by Dot Blot assay and hybridized with allelic specific oligonucleotide (ASO) probes to detect the 6 more frequent mutations found in the South of Spain. RESULTS: Codon 39 nonsense mutation (31.1%) was the most frequent finding followed by IVS-1 NT 110 (26.7%). The relationship between hematological parameters and molecular mutations concluded that IVS-I NT 6 mutation developed a minimal anemia. DISCUSSION: From the practical point of view, this study indicates that we were able to detect more than 90% of heterozygous beta-tal. with 5 out of 6 ASO probes used in this work. Thus, our data also provides a further implication in prenatal diagnosis.     

Modelling of effects of ultrastructural morphology on the hygroelastic properties of wood fibres

Wood fibres constitute the structural framework of e.g. wood, paper, board and composites, where stiffness and dimensional stability are of importance. An analytical modelling approach has been used for prediction of hygroelastic response, and assessment of the stresses in thick-walled cylinder models of wood fibres. A wood fibre was idealised as a multilayered hollow cylinder made of orthotropic material with helical orientation. The hygroelastic response of the layered assembly due to axisymmetric loading and moisture content changes was obtained by solving the corresponding boundary value problem of elasticity. A simple solution scheme based on the state space approach and the transfer matrix method was employed. This was combined with an analytical ultrastructural homogenisation method, used to link hygroelastic properties of constituent wood polymers to properties of each layer. Predicted hygroelastic response captured experimentally measured behaviour. Fibres that were constrained not to twist showed a stiffer response than fibres allowed twisting under uniaxial loading. It was also shown that the ultrastructure, i.e. the microfibril angle, will control the hygroexpansion in the same way as it controls the compliance of the cell wall. Qualitative failure trends comparable with experimental observations could be established with stress analysis and a simple plane-stress failure criterion.     

Hydrogen adsorption studies in micro-size cobalt dots

Hydrogen desorption curves were obtained from a sample composed of a square arrangement of Co dots with average diameter of 4.4 μm, separated by a distance of 11.6 μm. A macroscopic sample of Co dots grown on a 2.5 × 2.5 cm Si substrate was made by standard lithographic techniques and used in these experiments. Thermal programmed desorption (TPD) was performed under ultra-high vacuum conditions. Hydrogen TPD curves were obtained from a 1 × 1 cm Co dots samples displaying a maximum of intensity at 425 K. Hydrogen TPD curve was also obtained from 1 cm× 1 cm samples of Co films and Co foils for comparison. The hydrogen TPD curves have decreasing intensity from the Co foils to the Co dots and finally to the Co films. This indicates that there are more sites for hydrogen adsorption on the Co dots than in the Co films. This is a surprising result because there is approximately 8.7 times less Co atoms exposed in the Co dots that in the Co film sample. A desorption energy of 27 kcal/mol was obtained for the Co dots suggesting that hydrogen is adsorbed on an hcp hollow site of the Co dot crystalline structure.     

Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.