The State of the Art of Piezo1 Channels in Skeletal Muscle Regeneration

Piezo1 channels are highly mechanically-activated cation channels that can sense and transduce the mechanical stimuli into physiological signals in different tissues including skeletal muscle. In this focused review, we summarize the emerging evidence of Piezo1 channel-mediated effects in the physiology of skeletal muscle, with a particular focus on the role of Piezo1 in controlling myogenic precursor activity and skeletal muscle regeneration and vascularization. The disclosed effects reported by pharmacological activation of Piezo1 channels with the selective agonist Yoda1 indicate a potential impact of Piezo1 channel activity in skeletal muscle regeneration, which is disrupted in various muscular pathological states. All findings reported so far agree with the idea that Piezo1 channels represent a novel, powerful molecular target to develop new therapeutic strategies for preventing or ameliorating skeletal muscle disorders characterized by an impairment of tissue regenerative potential.     

Eco-Sustainable Silk Fibroin/Pomegranate Peel Extract Film as an Innovative Green Material for Skin Repair

Skin disorders are widespread around the world, affecting people of all ages, and oxidative stress represents one of the main causes of alteration in the normal physiological parameters of skin cells. In this work, we combined a natural protein, fibroin, with antioxidant compounds extracted in water from pomegranate waste. We demonstrate the effective and facile fabrication of bioactive and eco-sustainable films of potential interest for skin repair. The blended films are visually transparent (around 90%); flexible; stable in physiological conditions and in the presence of trypsin for 12 days; able to release the bioactive compounds in a controlled manner; based on Fickian diffusion; and biocompatible towards the main skin cells, keratinocytes and fibroblasts. Furthermore, reactive oxygen species (ROS) production tests demonstrated the high capacity of our films to reduce the oxidative stress induced in cells, which is responsible for various skin diseases.     

Building kernels from binary strings for image matching.

In the statistical learning framework, the use of appropriate kernels may be the key for substantial improvement in solving a given problem. In essence, a kernel is a similarity measure between input points satisfying some mathematical requirements and possibly capturing the domain knowledge. In this paper, we focus on kernels for images: we represent the image information content with binary strings and discuss various bitwise manipulations obtained using logical operators and convolution with nonbinary stencils. In the theoretical contribution of our work, we show that histogram intersection is a Mercer's kernel and we determine the modifications under which a similarity measure based on the notion of Hausdorff distance is also a Mercer's kernel. In both cases, we determine explicitly the mapping from input to feature space. The presented experimental results support the relevance of our analysis for developing effective trainable systems.     

On Adaptive Density Deployment to Mitigate the Sink-Hole Problem in Mobile Sensor Networks

The use of mobile sensors is of great relevance to monitor critical areas where sensors cannot be deployed manually. The presence of data collector sinks causes increased energy depletion in their proximity, due to the higher relay load under multi-hop communication schemes (sink-hole phenomenon). We propose a new approach towards the solution of this problem by means of an autonomous deployment algorithm that guarantees the adaptation of the sensor density to the sink proximity and enables their selective activation. The proposed algorithm also permits a fault tolerant and self-healing deployment, and allows the realization of an integrated solution for deployment, dynamic relocation and selective sensor activation. We formally prove the termination of our algorithm. Performance comparisons between our proposal and previous approaches show how the former can efficiently reach a deployment at the desired variable density with moderate energy consumption under a wide range of operative settings.     

Nanowire Assisted Mechanotyping of Cellular Metastatic Potential

Nanotechnology has provided tools for next generation biomedical devices which rely on nanostructure interfaces with living cells. In vitro biomimetic structures have enabled observation of cell response to various mechanical and chemical cues, and there is a growing interest in isolating and harnessing the specific cues that 3D microenvironments can provide without the requirement for such culture and the experimental drawbacks associated with it. Here, a randomly oriented gold coated Si nanowire substrate with patterned hydrophobic–hydrophilic areas for the differentiation of isogenic breast cancer cells of varying metastatic potential is reported. When considering synthetic surfaces for the study of cell-nanotopography interfaces, randomly oriented nanowires more closely resemble the isotropic architecture of a natural extracellular matrix. In the study reported here, the authors show that primary cancer cells preferably attach to the hydrophilic region of randomly oriented nanowire substrate while secondary cancer cells do not adhere. Using machine learning analysis of fluorescence images, cells are found to spread and elongate on the nanowire substrates as compared to a flat substrate, where they mostly remain round. Such platforms can not only be used for developing bioassays but also as stepping stones for tissue printing technologies where cells can be selectively patterned at desired locations.     

Push &; Pull: autonomous deployment of mobile sensors for a complete coverage

Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push & Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push & Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.     

Olive oil traceability by means of chemical and sensory analyses: A comparison with SSR biomolecular profiles

The relationship between genetic diversity and phenotype in olive, instrumental to improve the efficacy of olive clonal selection, is still far from being fully understood. This work reports on a comparison made between plant SSR genetic data and quality of monovarietal olive oils. Nine monovarietal oils produced by selected genotypes were characterised under chemical and sensory profiles. Fatty acid compositions were determined to evaluate quantitative differences among oils; some fatty acids are actually highly correlated with the genetic matrix, and PCA of fatty acids composition explains 85.53% variability. Moreover some oils characterised by high levels of oleic acid appeared interesting from a nutritional standpoint. Organoleptic profiles evidenced differences especially for the attributes defined as “pleasant flavours”; oils obtained by different genetic matrices were characterised by different flavour intensities of tomato or artichoke, almond or aromatic herbs, correspondence analysis among sensory pleasant attributes and olive oil samples explaining 91.68% variability.     

In-House Validation and Comparison of Two Wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis>) Taxon-Specific Real-Time PCR Methods for GMO Quantification Supported by Droplet Digital PCR

Common wheat is one of the most important staple food crops worldwide. However, unlike other important staple crops such as maize or soybean, genetically modified (GM) wheat is not yet present in the global food market. Nonetheless, in the recent past, the adventitious presence of GM glyphosate-tolerant volunteers was reported in open wheat fields in the USA. The European Union Reference Laboratory for GM Food and Feed (EURL-GMFF) was therefore called to develop a strategy to detect such unauthorised GM wheat in wheat samples by using both taxon-specific and screening tests. Two candidate common wheat taxon-specific real-time PCR methods were suggested, one targeting ssII-D gene coding for starch synthase and the other targeting waxy-D1 gene, coding for granule-bound starch synthase. In the present study, the two above-mentioned real-time PCR taxon-specific methods were in-house verified and compared, proposing droplet digital PCR (ddPCR) as a new tool for supporting the application of the European Network of GMO Laboratories (ENGL) established method performance criteria. Preliminary performance data of waxy-D1 and ssII-D methods in ddPCR format are shown too to give a contribution to the bridging process from the consolidated to the emerging quantitative PCR methodology.     

Shelf life of ready‐to‐cook cauliflower mixtures as affected by packaging film mass transport properties

In this work, the influence of packaging mass transport properties on quality loss of fresh‐cut cauliflower mixtures was addressed. The study was organised in two subsequent experimental steps; first, the selection of micro‐perforated packaging films was carried out by monitoring the package headspace gas concentrations of fresh‐cut white, green cauliflower and roman cabbage. Then, the effects of the barrier properties of the selected micro‐perforated film on shelf life of two different fresh‐cut cauliflower mixtures, stored at 4 ± 1 °C, were addressed. Results suggested that, among the investigated films, the micro‐perforated polymeric matrix with the lowest oxygen transmission rate value showed the best performance as it created the optimum headspace gas composition for each cauliflower variety, as well as, for the product mixtures. The appearance of visible moulds was the factor limiting product shelf life that accounted for about 18 days for both the investigated cauliflower mixtures.