Endothelial Glycocalyx as a Regulator of Fibrotic Processes

The endothelial glycocalyx, the gel layer covering the endothelium, is composed of glycosaminoglycans, proteoglycans, and adsorbed plasma proteins. This structure modulates vessels’ mechanotransduction, vascular permeability, and leukocyte adhesion. Thus, it regulates several physiological and pathological events. In the present review, we described the mechanisms that disturb glycocalyx stability such as reactive oxygen species, matrix metalloproteinases, and heparanase. We then focused our attention on the role of glycocalyx degradation in the induction of profibrotic events and on the possible pharmacological strategies to preserve this delicate structure.     

Cyanogenic,carotenoids and protein composition in leaves and roots across seven diverse population found in the world cassava germplasm collection at CIAT,Colombia

The objective of this study was to characterise the nutritional potential of leaves and identify a diversity centre with low cyanide and high nutrient content among 178 Latin American cassava genotypes. This field-based collection represents the seven diversity centres, held at The International Center for Tropical Agriculture (CIAT Palmira, Colombia) by the Cassava Program. The cyanide, all-trans-β-carotene and lutein concentrations in cassava leaves ranged from 346 to 7484 ppm dry basis (db), from 174–547 μg g⁻¹ db and 15–181 μg g⁻¹ db, respectively. Cassava leaves also showed significant levels of essential amino acids leucine, lysine, phenylalanine, valine and threonine, and average total protein content of 26.24 g 100 g⁻¹ db. Among seven diversity centres, South American rainforest group showed low cyanide and high carotene content in leaves. In addition, VEN77 and PAN51 genotypes stood out for having low cyanide in leaves and roots and high carotene in leaves. This genetic diversity can be used to select high potential progenitors for breeding purposes.     

Milk from cows fed a diet with a high forage:concentrate ratio improves inflammatory state,oxidative stress,and mitochondrial function in rats

Excessive energy intake may evoke complex biochemical processes characterized by inflammation, oxidative stress, and impairment of mitochondrial function that represent the main factors underlying noncommunicable diseases. Because cow milk is widely used for human nutrition and in food industry processing, the nutritional quality of milk is of special interest with respect to human health. In our study, we analyzed milk produced by dairy cows fed a diet characterized by a high forage:concentrate ratio (high forage milk, HFM). In view of the low n-6:n-3 ratio and high content of conjugated linoleic acid of HFM, we studied the effects of this milk on lipid metabolism, inflammation, mitochondrial function, and oxidative stress in a rat model. To this end, we supplemented for 4 wk the diet of male Wistar rats with HFM and with an isocaloric amount (82 kJ, 22 mL/d) of milk obtained from cows fed a diet with low forage:concentrate ratio, and analyzed the metabolic parameters of the animals. Our results indicate that HFM may positively affect lipid metabolism, leptin:adiponectin ratio, inflammation, mitochondrial function, and oxidative stress, providing the first evidence of the beneficial effects of HFM on rat metabolism.     

Role of Extracellular Vesicles in Epithelial Ovarian Cancer: A Systematic Review

Extracellular vesicles (EVs) are a heterogeneous group of cell-derived submicron vesicles released under physiological or pathological conditions. EVs mediate the cellular crosstalk, thus contributing to defining the tumor microenvironment, including in epithelial ovarian cancer (EOC). The available literature investigating the role of EVs in EOC has been reviewed following PRISMA guidelines, focusing on the role of EVs in early disease diagnosis, metastatic spread, and the development of chemoresistance in EOC. Data were identified from searches of Medline, Current Contents, PubMed, and from references in relevant articles from 2010 to 1 April 2020. The research yielded 194 results. Of these, a total of 36 papers, 9 reviews, and 27 original types of research were retained and analyzed. The literature findings demonstrate that a panel of EV-derived circulating miRNAs may be useful for early diagnosis of EOC. Furthermore, it appears clear that EVs are involved in mediating two crucial processes for metastatic and chemoresistance development: the epithelial–mesenchymal transition, and tumor escape from the immune system response. Further studies, more focused on in vivo evidence, are urgently needed to clarify the role of EV assessment in the clinical management of EOC patients.     

Microwave heating controlled reactive melt infiltration for graphite-Si-SiC ceramics manufacturing

In this work, we investigated a procedure which exploits microwave ovens to produce SiC- based components by reactive melt infiltration of silicon into graphite preforms. The employed oven is designed to grant optical access to the sample surface, which allows to measure its temperature evolution though a noncontact pyrometer. This signal was used as a feedback to control the power provided to the preform and as an experimental output whose analysis provides insight into the reaction mechanism. Specifically, it is found that complete infiltration is achieved much before the end of the reaction. The latter is not fully self-sustained as the global reaction rate continuously decreases with time until it is no more able to keep the temperature above the silicon solidification value. At that point, the reaction stops. The analysis of the processed samples proved that this procedure allows producing fully infiltrated samples without material failure by adjusting the heat provided during the infiltration stage rather than by tuning the preform structure and composition, which is the usual approach. The proposed method is less time and energy consuming than the standard one.     

Scheduling Algorithms for Packet-Oriented MAC Protocols in Wireless Multimedia Systems

Future generation wireless multimediacommunications will require efficient Medium AccessControl (MAC) protocols able to guarantee suitable Qualityof Service (QoS) levels for different traffic classes whileachieving a high utilization of radio resources. This paperproposes a new scheduling technique to be adopted at the MAClevel in wireless access systems, named Dynamic Scheduling-Time DivisionDuplexing (DS-TDD), that efficiently managesvideo, voice, Web and background traffics. A theoretical approachis proposed in this paper to evaluate the DS-TDD performance withvoice and Web traffics. Simulation results have permitted tohighlight the following promising characteristics of the DS-TDDscheme: (i) a high capacity of real-time traffics isattained with a QoS insensitive to Web and background trafficloads; (ii) a high throughput can be guaranteed whilepreserving the QoS levels of the different traffic classes;(iii) heavier downlink traffic loads do not modify the QoSof uplink traffics. Finally, extensive comparisons with differentscheduling schemes proposed in the literature have permitted tohighlight the better performanceof DS-TDD.     

Profiling Voids Embedded in a Slab by a Non-Linear Model

In this paper, by applying a non linear model for the electromagnetic inverse scattering, a technique for the dielectric profiling of a planarly layered medium is investigated and applied to void localization and diagnostics inside a homogeneous lossless slab (one-dimensional geometry). Data are collected under plane wave multifrequency normal incidence. Suitable finite dimensional representations for the unknown functions are introduced and their influence on the model is discussed. The resulting functional equation is solved by the method of weighted residuals and the solution algorithm amounts to minimizing a non quadratic function, where particular attention is devoted to reduce the occurrence of local minima. Finally, the inversion algorithm is validated by applications to both simulated and experimental data.     

Low standby power state storage for sub-130-nm technologies

Handheld and other battery-powered ICs require process scaling to increase functional integration and reduce active power consumption. Scaling also increases leakage current components to the point where standby power is frequently a limiting design factor. A scheme combining low-leakage thick-gate shadow latches and high-performance transistors is presented that decouples performance from standby power in sub-130-nm technologies. Circuit design and operation, including pulse-clocked latches, use of dynamic circuits, and inclusion of scan is presented. The approach is validated by experimental results on a 90-nm process.     

Neural network systems to reproduce crash behavior of structural components

The use of neural networks as global approximation tool in crashworthiness problems is here investigated. Neural networks are not only asked to return some meaningful indices of the structural behavior but also to reproduce load-time curves during crash phenomena. To contain the number of examples required for the training process, parallel subsystems of small neural networks are designed. Design points for the training process are obtained by explicit finite element analyses performed by PAMCRASH. The settlement of the points in the design domain is defined using a maximum distance concept. The procedure is applied to different typical absorption structures made of aluminum alloy: riveted tubes, honeycomb structures, longitudinal keel beam and intersection elements of helicopter subfloors.     

Modeling video sources for real-time scheduling

What is the impact of the autocorrelation of variable-bit-rate (VBR) sources on real-time scheduling algorithms? Our results show that the impact of long term, or interframe, autocorrelation is negligible, while the impact of short term, or intraframe, autocorrelation can be significant. Such results are essentially independent of the video coding scheme employed. To derive these results, video sequences are modeled as a collection of stationary subsequences called scenes. Within a scene, a statistical model is derived for both the sequence of frames and of slices. The model captures the distribution and the autocorrelation function of real-time video data. In previous work, the pseudoperiodicity of the slice level auto-correlation function made it difficult to develop a simple yet accurate model. We present a generalization of previous methods that can easily capture this pseudoperiodicity and is suited for modeling a greater variety of autocorrelation functions. By simply tuning a few parameters, the model reproduces the statistic behavior of sources with different types and levels of correlation on both the frame and the slice level.