Leptin Signaling in Obesity and Colorectal Cancer

Obesity and colorectal cancer (CRC) are among the leading diseases causing deaths in the world, showing a complex multifactorial pathology. Obesity is considered a risk factor in CRC development through inflammation, metabolic, and signaling processes. Leptin is one of the most important adipokines related to obesity and an important proinflammatory marker, mainly expressed in adipose tissue, with many genetic variation profiles, many related influencing factors, and various functions that have been ascribed but not yet fully understood and elucidated, the most important ones being related to energy metabolism, as well as endocrine and immune systems. Aberrant signaling and genetic variations of leptin are correlated with obesity and CRC, with the genetic causality showing both inherited and acquired events, in addition to lifestyle and environmental risk factors; these might also be related to specific pathogenic pathways at different time points. Moreover, mutation gain is a crucial factor enabling the genetic process of CRC. Currently, the inconsistent and insufficient data related to leptin’s relationship with obesity and CRC indicate the necessity of further related studies. This review summarizes the current knowledge on leptin genetics and its potential relationship with the main pathogenic pathways of obesity and CRC, in an attempt to understand the molecular mechanisms of these associations, in the context of inconsistent and contradictory data. The understanding of these mechanisms linking obesity and CRC could help to develop novel therapeutic targets and prevention strategies, resulting in a better prognosis and management of these diseases.     

Targeting CD10 on B-Cell Leukemia Using the Universal CAR T-Cell Platform (UniCAR)

Chimeric antigen receptor (CAR)-expressing T-cells are without a doubt a breakthrough therapy for hematological malignancies. Despite their success, clinical experience has revealed several challenges, which include relapse after targeting single antigens such as CD19 in the case of B-cell acute lymphoblastic leukemia (B-ALL), and the occurrence of side effects that could be severe in some cases. Therefore, it became clear that improved safety approaches, and targeting multiple antigens, should be considered to further improve CAR T-cell therapy for B-ALL. In this paper, we address both issues by investigating the use of CD10 as a therapeutic target for B-ALL with our switchable UniCAR system. The UniCAR platform is a modular platform that depends on the presence of two elements to function. These include UniCAR T-cells and the target modules (TMs), which cross-link the T-cells to their respective targets on tumor cells. The TMs function as keys that control the switchability of UniCAR T-cells. Here, we demonstrate that UniCAR T-cells, armed with anti-CD10 TM, can efficiently kill B-ALL cell lines, as well as patient-derived B-ALL blasts, thereby highlighting the exciting possibility for using CD10 as an emerging therapeutic target for B-cell malignancies.     

La transition secondaire postsecondaire abordée sous l'angle de l'harmonisation des manières d'utiliser le symbolisme chez les enseignants

Nos observations au secondaire et au collégial et les travaux menés sur la transition secondaire postsecondaire en mathématiques ont permis de documenter un ensemble de ruptures dans le passage d'un ordre à l'autre, soulignant l'importance de s'attarder à l'articulation entre ces deux ordres. C'est afin de mieux comprendre ces articulations possibles qu'une recherche collaborative a été menée avec des enseignants des deux ordres. L'analyse, puisant ses fondements en ethnométhodologie, fait apparaître l'utilisation du symbolisme comme un thème central de cette articulation interordres, et permet de retracer une trajectoire d'harmonisation qui se développe durant les rencontres en lien avec cette utilisation.     

On human–machine relations

Cognition, Technology & Work - This paper presents an approach to human–machine interactions based on the concept of teamwork and the psychological theory of object relations. We envision...     

Selective extraction,structural characterisation and antifungal activity assessment of napins from an industrial rapeseed meal

This article reports an extraction–purification of napins from an industrial rapeseed meal and the assessment of their antimicrobial activity against Fusarium langsethiae. The best extraction conditions are observed at pH 2, 12% (w/w) of rapeseed meal after 15 min of extraction in water at room temperature. Under these conditions the extraction is highly selective, allowing a simple purification process (ammonium sulfate precipitation followed by desalting size exclusion chromatography) to get purified napins. These napins possessed significant anti-Fusarium activity (IC₅₀ = 70 μM) and a compact secondary structure rich in α-helix, which may explain this bioactivity.     

Enhancement effect on apparent viscosity of aqueous tragacanth gum dispersions promoted by sugars

Flow curves of aqueous dispersions of tragacanth gum (T) with sucrose and glucose at different temperatures were determined using a controlled‐stress rheometer. The effect of sodium chloride without or with sucrose (at the highest content) on the rheology of T dispersions was evaluated. The presence of sucrose and glucose promoted a noticeable enhancement impact on the apparent viscosity of aqueous T dispersions, which depended on sugar type/content, shear rate and temperature. In all cases, the glucose addition led to the largest enhanced viscosities at low shear rates (<10 s^?1) and temperature. The joint action of sugar and salt exhibited a notable effect on apparent viscosity at low shear rates, softening the strong shear‐thinning behaviour of T samples. Flow curves of T in the presence of sugars were satisfactorily described by the Cross‐Williamson model, being semi‐empirical correlations of the model parameters with ingredients content and temperature stablished.     

Propagating and evanescent waves associated with inhibited reflection in uniaxial crystals: Extraordinary incidence

Abstract

When an extraordinary wave under inhibited reflection conditions is incident on an interface between a uniaxial crystal and an isotropic medium, the reflected extraordinary wave is evanescent and the polarization of the refracted wave changes from linear to elliptical. In the present paper it is shown that the refracted ray undergoes a shift which is not only longitudinal (as the Goos—Hänchen effect in total reflection in isotropic interfaces) but also transversal. The structure of the evanescent reflected wave is studied and the polarization of the transmitted wave is analysed.     

Experimental tests on the limit states of dry-jointed tuff blocks

A proper definition of the yield domains governing the frictional behaviour at contact interfaces is generally required to perform the limit analysis of 3D dry-jointed masonry block structures. However, the modelling of the actual behaviour of frictional contact interfaces under simultaneous normal and shear forces, torsion and bending moments is a topic still poorly studied, especially from the experimental point of view. In this paper the single contact interface of a system composed of two dry-jointed tuff blocks under different loading conditions is experimentally investigated. The programme includes several sets of tests based on different eccentricities of the vertical and horizontal loading implying pure strengths and interactions among shear, torsion and bending moments. The results of each set are then compared with those obtained by a recently proposed numerical model for 3D masonry block assemblages, based on the assumptions of infinite strength in compression, tension and shear for blocks and no-tension and frictional behaviour at their contact. The comparison is useful, on the one hand, as a further validation the efficacy of the previously proposed yield domains in order to be used in 3D limit analysis formulations and, on the other, to highlight which yield domains need to be better represented.     

Efficient energy-based embedding models for link prediction in knowledge graphs

We focus on the problem of link prediction in Knowledge Graphs, with the goal of discovering new facts. To this purpose, Energy-Based Models for Knowledge Graphs that embed entities and relations in continuous vector spaces have been largely used. The main limitation in their applicability lies in the parameter learning phase, which may require a large amount of time for converging to optimal solutions. In this article, we first propose an unified view on different Energy-Based Embedding Models. Hence, for improving the model training phase, we propose the adoption of adaptive learning rates. We show that, by adopting adaptive learning rates during training, we can improve the efficiency of the parameter learning process by an order of magnitude, while leading to more accurate link prediction models in a significantly lower number of iterations. We extensively evaluate the proposed learning procedure on a variety of new models: our result show a significant improvement over state-of-the-art link prediction methods on two large Knowledge Graphs, namely WordNet and Freebase.