A Three-Dimensional Study of the Morphology and Topography of Pericytes in the Microvascular Bed of Skeletal Muscle

Digested tissue specimens and corrosion casts of rat soleus and tibialis anterior muscles were employed for this Scanning Electron Microscopy (SEM) study. The shape, morphology, and position of pericytes were compared to corresponding imprints on the cast surfaces. Pericytes, observed in digested tissue specimens, showed a typical morphological pattern: a central body with two primary processes that run along the capillary in opposite directions. From these primary processes, secondary ones arise and often encircle the vessel almost completely. On the surface of corrosion casts, roundish imprints were found in the microvascular tree at the same level where digested tissue specimens showed the presence of pericyte bodies. Along and around the cast surface, shallow grooves reproduced the course of the primary and secondary processes. The peculiar tridimensional arrangement of pericytes at the level of capillary bifurcations underlines their role in red cell flow regulation. However, if the mechanical linkage of the pericytes to the endothelium and their contractability is taken into account, additional roles of these perivascular cells may be hypothesized

NetCausality: A time-delayed neural network tool for causality detection and analysis

The analysis of causality between systems is still an important research activity, which finds application in several fields of science. The software presented is a new tool for causality detection and analysis between time series. The proposed technique is based on time-delayed neural networks (TDNN). The tool is developed in MATLAB and it comprises three main functions. The first one returns the total causality between two or more systems of equations. The second tool is used to find the ‘‘time horizon’’, id est the time delay at which the influence between the systems occurs. The last function is a causality feature detection to determine the time intervals, in which the mutual coupling is sufficiently strong to have a real influence on the target

Architectures and Key Technical Challenges for 5G Systems Incorporating Satellites

Satellite Communication systems are a promising solution to extend and complement terrestrial networks in unserved or under-served areas. This aspect is reflected by recent commercial and standardisation endeavours. In particular, 3GPP recently initiated a Study Item for New Radio-based, i.e., 5G, Non-Terrestrial Networks aimed at deploying satellite systems either as a stand-alone solution or as an integration to terrestrial networks in mobile broadband and machine-type communication scenarios. However, typical satellite channel impairments, as large path losses, delays, and Doppler shifts, pose severe challenges to the realisation of a satellite-based NR network. In this paper, based on the architecture options currently being discussed in the standardisation fora, we discuss and assess the impact of the satellite channel characteristics on the physical and Medium Access Control layers, both in terms of transmitted waveforms and procedures for enhanced Mobile BroadBand (eMBB) and NarrowBand-Internet of Things (NB-IoT) applications. The proposed analysis shows that the main technical challenges are related to the PHY/MAC procedures, in particular Random Access (RA), Timing Advance (TA), and Hybrid Automatic Repeat reQuest (HARQ) and, depending on the considered service and architecture, different solutions are proposed.Comment: Submitted to Transactions on Vehicular Technologies, April 201

KDM4 Involvement in Breast Cancer and Possible Therapeutic Approaches

Breast cancer (BC) is the second leading cause of cancer death in women, although recent scientific and technological achievements have led to significant improvements in progression-free disease and overall survival of patients. Genetic mutations and epigenetic modifications play a critical role in deregulating gene expression, leading to uncontrolled cell proliferation and cancer progression. Aberrant histone modifications are one of the most frequent epigenetic mechanisms occurring in cancer. In particular, methylation and demethylation of specific lysine residues alter gene accessibility via histone lysine methyltransferases (KMTs) and histone lysine demethylases (KDMs). The KDM family includes more than 30 members, grouped into six subfamilies and two classes based on their sequency homology and catalytic mechanisms, respectively. Specifically, the KDM4 gene family comprises six members, KDM4A-F, which are associated with oncogene activation, tumor suppressor silencing, alteration of hormone receptor downstream signaling, and chromosomal instability. Blocking the activity of KDM4 enzymes renders them “druggable” targets with therapeutic effects. Several KDM4 inhibitors have already been identified as anticancer drugs in vitro in BC cells. However, no KDM4 inhibitors have as yet entered clinical trials due to a number of issues, including structural similarities between KDM4 members and conservation of the active domain, which makes the discovery of selective inhibitors challenging. Here, we summarize our current knowledge of the molecular functions of KDM4 members in BC, describe currently available KDM4 inhibitors, and discuss their potential use in BC therapy

An alternative SNR-based weighted-LSM algorithm to classify and measure the concentration of Biological Agents from Laser-Induced Fluorescence

Optical spectroscopic techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) or Laser-Induced Fluorescence (LIF), have already been used to study and detect Biological Agents (BAs). Unfortunately, BAs usually share similar-shaped emitted spectra and low-signal intensities, making their detection and classification difficult to assess. Least-Square Minimisation (LSM) based algorithms are usually deployed to measure the concentration of agents from spectra. Recently, it has been shown how the use of ad hoc weights can help in improving the performance of the concentration evaluation. More specifically, it has been observed that the “weight matrix” should be modelled as a function of the boundary conditions of the problem. This work proposes a new weight matrix that is based on the Signal-to-Noise Ratio (SNR) of the measurements. The idea is based on the fact that more noisy data are less reliable and therefore weight should be lowered. The paper, after a brief introduction and review of the LSM applied to spectra, will show the new methodology. A systematic analysis of the new algorithm is done and the comparison with the other LSM algorithms is presented. The results clearly show that there is a range of parameters for which the new algorithm performs better

Acoustic attenuation rate in the Fermi-Bose model with a finite-range fermion-fermion interaction

We study the acoustic attenuation rate in the Fermi-Bose model describing a mixtures of bosonic and fermionic atom gases. We demonstrate the dramatic change of the acoustic attenuation rate as the fermionic component is evolved through the BEC-BCS crossover, in the context of a mean-field model applied to a finite-range fermion-fermion interaction at zero temperature, such as discussed previously by M.M. Parish et al. [Phys. Rev. B 71, 064513 (2005)] and B. Mihaila et al. [Phys. Rev. Lett. 95, 090402 (2005)]. The shape of the acoustic attenuation rate as a function of the boson energy represents a signature for superfluidity in the fermionic component