SGLT2is and Renal Protection: From Biological Mechanisms to Real-World Clinical Benefits

In recent years, following the publication of results from several RCTs, first on cardiovascular and more recently on renal outcomes, SGLT2is have become the standard of care to prevent diabetic kidney disease and slow its progression. This narrative review focuses on biological mechanisms, both renal and extrarenal, underlying kidney protection with SGLT2is. Furthermore, data from cardiovascular as well as renal outcome trials, mostly conducted in diabetic patients, are presented and discussed to provide an overview of current uses as well as the future therapeutic potential of these drugs.     

Adhesion of resin cements to contaminated zirconia resin cements on zirconia: effect saliva-contamination and surface conditioning

This study evaluated the adhesion of resin cements to zirconia after saliva contamination using resin cements with different chemistries. Zirconia discs (N?=?240, n?=?10 per group) were randomly divided into three groups: (a) C: No contamination (Control), (b) S: Contamination with saliva, (c) S?+?AA: Contamination with saliva followed by air-abrasion (CoJet). While half of the specimens were not conditioned, the other half were conditioned with 37.5% H₃PO₄ for 60?s. After rinsing, all specimen surfaces were silanized (Monobond Plus). Resin cements based on either methacrylate (Variolink II–VL) or MDP monomer (Panavia 21-PN) were polymerized on the substrates. The specimens were randomly divided into two further groups to be tested either after (a) 24?h dry storage at 37?°C or (b) thermocycling (×5000, 5–55?°C). Microshear bond (MSB) tests were conducted in a Universal Testing Machine and failure types were analyzed. Data were analyzed using Univariate analysis and Tukey’s tests (alpha = 0.05). While saliva contamination, 37.5% H₃PO₄ application (p?<?.001) and aging (p?<?.05) significantly affected the bond results, cement type did not show significant difference after aging (p?>?.05). Adhesive strength of PN (1.2–4.4?MPa) on saliva contaminated and etched zirconia was more stable than that of VL (0–2.8?MPa). After aging, bond strength results decreased the most with VL (3–100%) compared to PN (32–71%) but the decrease was less in the air-abraded groups after aging (VL: 3%; PN: 32%). Exclusively adhesive failures were experienced in all groups.     

On the use of formal methods to model and verify neuronal archetypes

Having a formal model of neural networks can greatly help in understanding and verifying their properties, behavior, and response to external factors such as disease and medicine. In this paper, we adopt a formal model to represent neurons, some neuronal graphs, and their composition. Some specific neuronal graphs are known for having biologically relevant structures and behaviors and we call them archetypes. These archetypes are supposed to be the basis of typical instances of neuronal information processing. In this paper we study six fundamental archetypes (simple series, series with multiple outputs, parallel composition, negative loop, inhibition of a behavior, and contralateral inhibition), and we consider two ways to couple two archetypes: (i) connecting the output(s) of the first archetype to the input(s) of the second archetype and (ii) nesting the first archetype within the second one. We report and compare two key approaches to the formal modeling and verification of the proposed neuronal archetypes and some selected couplings. The first approach exploits the synchronous programming language Lustre to encode archetypes and their couplings, and to express properties concerning their dynamic behavior. These properties are verified thanks to the use of model checkers. The second approach relies on a theorem prover, the Coq Proof Assistant, to prove dynamic properties of neurons and archetypes.     

Effect of surface modification on NO2 sensing properties of SnO2 varistor-type sensors

NO₂ sensing properties of SnO₂-based varistor-type sensors have been investigated in the temperature range of 400-650°C and in the NO₂ concentration range of 15–30 ppm. Pure SnO₂ exhibited a weak nonlinear I–V characteristic in air, but clear nonlinearity in NO₂ at 450°C. The breakdown voltage of SnO₂ shifted to a high electric field upon exposure to NO₂ and the magnitude of the shift was well correlated with NO₂ concentration. Thus, SnO₂ exhibited some sensitivity to NO₂ as a varistor-type sensor. When SnO₂ particles coated with a SiO₂ thin film were used as a raw material for fabricating a varistor, the breakdown voltage in air was approximately the double that of pure SnO₂ and the sensitivity to 15 ppm NO₂ was enhanced slightly. However, the sensitivity to 30 ppm NO₂ decreased. The Cr₂O₃-loading on SnO₂ also led to an increase in the breakdown voltage in air, but the Cr₂O₃ addition was not effective for promoting the NO₂ sensitivity under the present experimental conditions.     

A comparison of graph-based word sense induction clustering algorithms in a pseudoword evaluation framework

This article presents a comparison of different Word Sense Induction (wsi) clustering algorithms on two novel pseudoword data sets of semantic-similarity and co-occurrence-based word graphs, with a special focus on the detection of homonymic polysemy. We follow the original definition of a pseudoword as the combination of two monosemous terms and their contexts to simulate a polysemous word. The evaluation is performed comparing the algorithm’s output on a pseudoword’s ego word graph (i.e., a graph that represents the pseudoword’s context in the corpus) with the known subdivision given by the components corresponding to the monosemous source words forming the pseudoword. The main contribution of this article is to present a self-sufficient pseudoword-based evaluation framework for wsi graph-based clustering algorithms, thereby defining a new evaluation measure (top2) and a secondary clustering process (hyperclustering). To our knowledge, we are the first to conduct and discuss a large-scale systematic pseudoword evaluation targeting the induction of coarse-grained homonymous word senses across a large number of graph clustering algorithms.     

Interfacing human and computer with wireless body area sensor networks: the WiMoCA solution

Wireless Body Area Sensor Networks (WBASN) are an emerging technology enabling the design of natural human–computer interfaces (HCI). Automatic recognition of human motion, gestures, and activities is studied in several contexts. For example, mobile computing technology is being considered as a replacement of traditional input systems. Moreover, body posture and activity monitoring can be used for entertainment and health-care applications. However, until now, little work has been done to develop flexible and efficient WBASN solutions suitable for a wide range of applications. Their requirements pose new challenges for sensor network designs, such as optimizing traditional solutions for use as environmental monitoring-like applications and developing on-the-field stress tests. In this paper, we demonstrate the flexibility of a custom-designed WBASN called WiMoCA with respect to a wide range of posture and activity recognition applications by means of practical implementation and on-the-field testing. Nodes of the network mounted on different parts of the human body exploit tri-axial accelerometers to detect its movements. The advanced digital Micro-electro-mechanical system (MEMS) based inertial sensor has been chosen for WiMoCA because it demonstrated high flexibility of use in many different situations, providing the chance to exploit both static and dynamic acceleration components for different purposes. Furthermore, the sensibility and accuracy of the sensing element is perfectly adequate for monitoring human movement, while keeping cost low and size compact, thus meeting our requirements. We implemented three types of applications, stressing the WBASN in many aspects. In fact, they are characterized by different requirements in terms of accuracy, timeliness, and computation distributed on sensing nodes. For each application, we describe its implementation, and we discuss results about performance and power consumption.

Income, Time Effects and Direct Preferences in a Multimodal Choice Context: Application of Mixed RP/SP Models with Non-Linear Utilities

Transport problems typically involve at least two types of constraints, on income and on time. Therefore, the indirect utility function depends either on the income available after having subtracted the cost of the discrete alternative and on the free time left after having worked and travelled by each competing option. In the typical linear-in-the-attributes and in-the-parameters specification, that represents the first grade approximation of the indirect utility function, the effect of income and time constraints cancel out and only the cost and time of the alternatives matter in the comparison between them. From a microeconomic point of view this is equivalent to assume that income and time effects could be disregarded; which is not always the case. To account for these effects the utility function should include second order attributes; however, in non-linear utility functions it may not be easy to distinguish among several effects that could be relevant: direct preferences for good and leisure, and simple interactions between attributes other than income and time effects. This paper analyses these effects from a theoretical point of view focusing on the possible confounding problem in detecting income and time effects. We use a dataset collected for a modal choice context and containing both revealed and stated preference data, and estimate several NL models examining the effect of the different second-order terms on detecting income and time effects. We compared specifications including square cost and time attributes, interactions between time and cost, cost divided by the income available to be spent on free time, and time multiplied by free time. Our results confirm the strong effect of direct preferences for goods and leisure time on choice, and the potential confounding effect between quadratic attributes and other non-linear omitted terms. Finally, we also found that care should be taken in highlighting income and time effects using mixed data sources, since confounding effects can occur when non-linearities are accounted for in both data sets.