A Structural Description of the Chapel of the Holy Shroud in Torino

The structural investigations performed on Guarini’s Chapel of the Holy Shroud in Torino have made it possible to come closer than ever before to understanding its structural behaviour. They have also shed light on the building’s history. This paper presents some of the new findings about key elements of the structure, and mentions some of the still open questions.     

Magnetoresistivity of DyNi2B2C thin film

We present high-resolution resistivity and magnetoresistivity measurements on a DyNi₂B₂C thin film obtained by laser ablation. The measurements are interpreted in the framework of the theory developed by Yamada and Takada (YT) in the early 1970s (Yamada H., Takada S. Prog Theor Phys 1973;49:1401) for the magnetoresistivity of the antiferromagnetic materials and permit identification of the magnetic field H_c2 that destroys the magnetic ordering. So, we obtain a H–T phase diagram where the antiferromagnetic and paramagnetic states are unambiguously determined and that we compare with data in the literature. Finally, in the paramagnetic state we have found a linear dependence between magnetoresistivity and the square of the magnetization.     

Power rectifier model including self heating effects

A compact circuit model for power PiN diode is presented in this paper. The model includes thermal and electrical characteristics. Emitter efficiency effect, voltage drop due to epilayer region and accurate modeling of reverse recovery and forward recovery are main features of the electric part of the model. The thermal part of the model dynamically takes into account heat generation and flow through the device and includes the effect of temperature on diode model parameters. Circuit implementation of device thermal equations includes the effect of the non uniform heat generation in the chip and, hence, is very effective in modeling thermal response to short current pulses, which give a substantial modification of power rectifiers characteristics with negligible case heating. Modeling of charge distribution in the epilayer and of heat flow, is achieved through an approximation of the Laplace transform of the exact solution. The model is implemented as a Pspice subcircuit. Medici device simulations, including self heating, are used to validate the Pspice model.     

Novel P2X7 Antagonist Ameliorates the Early Phase of ALS Disease and Decreases Inflammation and Autophagy in SOD1-G93A Mouse Model

Amyotrophic lateral sclerosis (ALS) is a disease with a resilient neuroinflammatory component caused by activated microglia and infiltrated immune cells. How to successfully balance neuroprotective versus neurotoxic actions through the use of anti-inflammatory agents is still under debate. There has been a boost of awareness regarding the role of extracellular ATP and purinergic receptors in modulating the physiological and pathological mechanisms in the nervous system. Particularly in ALS, it is known that the purinergic ionotropic P2X7 receptor plays a dual role in disease progression by acting at different cellular and molecular levels. In this context, we previously demonstrated that the P2X7 receptor antagonist, brilliant blue G, reduces neuroinflammation and ameliorates some of the pathological features of ALS in the SOD1-G93A mouse model. Here, we test the novel, noncommercially available, and centrally permeant Axxam proprietary P2X7 antagonist, AXX71, in SOD1-G93A mice, by assessing some behavioral and molecular parameters, among which are disease progression, survival, gliosis, and motor neuron wealth. We demonstrate that AXX71 affects the early symptomatic phase of the disease by reducing microglia-related proinflammatory markers and autophagy without affecting the anti-inflammatory markers or motor neuron survival. Our results suggest that P2X7 modulation can be further investigated as a therapeutic strategy in preclinical studies, and exploited in ALS clinical trials.     

Mint: MDL-based approach for Mining INTeresting Numerical Pattern Sets

Data Mining and Knowledge Discovery - Pattern mining is well established in data mining research, especially for mining binary datasets. Surprisingly, there is much less work about numerical...     

Direct digital frequency synthesizers with polynomial hyperfolding technique

A new approach to design the phase to sine mapper of a direct digital frequency synthesizer (DDFS) is presented. The proposed technique uses an optimized polynomial expansion of sine and cosine functions to achieve either a 60-dBc spurious free dynamic range (SFDR), with a second-order polynomial, or a 80-dBc SFDR, with third-order polynomials. Polynomial computation is done by using new canonical-signed-digit (CSD) hyperfolding technique. This approach exploits all the symmetries of polynomials parallel computation and uses CSD encoding to minimize hardware complexity. CSD hyperfolding technique is also presented in the paper. The performances of new DDFS compares favorably with circuits designed using state-of-the-art Cordic algorithm technique.     

Renal hydatidosis. Discussion of a clinical case complicated by post acute pancreatitic cyst

In this paper the authors describes a rare case of renal hydatidosis complicated by post acute pancreatitic cyst. There have been no reports up till now either of any physiopathological between the development of hydatid cysts in the vicinity of the pancreas and subsequent pancreatitis, or of any correlation between long-term albendazole therapy and acute pancreatitis. In our particular case, however, the volumetric increase of the renal cyst caused external compression of the pancreas and the consequent slowing-down of bilio-pancreatic flow, which probably led to the development of acute pancreatitis. Since, in our opinion, the pancreatic pseudocyst required surgical removal, we decided to perform the operation there and then; intraoperative examination of the cystic fluid and the presence of daughter cysts confirmed the suspected diagnosis of hydatidosis, of clear renal origin since it was closely attached to the upper pole and continued along the upper calyces renales; the cyst was easily detached from the lower and posterior edge of the liver, and was completely removed, together with its pericystium, which was detached from the lower surface of the liver and from the inferior subhepatic vein; only a tiny disk of pericystium was left in communication with a calyx, sutured to the rest of the kidney. The pancreatic cyst was drained by means of a mesocolic Roux-loop cysto-jejunostomy.     

Down-regulated expression of transforming growth factor beta 1 mRNA in endometrial carcinoma

Transforming growth factor beta1 (TGF-beta1) is a potent modulator of cell proliferation in vitro, and recent studies have demonstrated its overexpression in several different tumours; nevertheless, the molecular mechanisms of TGF-beta1 action on cell growth and differentiation have not been fully elucidated. To clarify the role of TGF-beta and its receptor in human endometrial proliferation and differentiation, TGF-beta1 expression at both the mRNA and protein levels has been evaluated by using Northern blotting and immunohistochemistry, in both normal (atrophic, proliferative and secretory) and neoplastic (adenocarcinoma) endometrial samples. This study demonstrates that TGF-beta1 mRNA expression is dramatically reduced in endometrial carcinomas with respect to non-neoplastic tissues, whereas the immunohistochemical expression of TGF-beta1 is enhanced in the epithelial component of endometrial carcinomas compared with non-neoplastic tissues. These data suggest that TGF-beta1 acts as a paracrine regulator of endometrial cell proliferation and that it may contribute to the carcinogenic mechanisms of endometrial carcinoma.     

Numerical simulation of precipitation in multicomponent Ni-base alloys

A comprehensive particle size distribution model has been developed for the simulation of γ′ precipitation in multicomponent Ni alloys. Nucleation, growth and coarsening of the precipitates are described by a particle size distribution. The growth rate of each precipitate class is calculated with a multi-component diffusion model formulated for non-diagonal matrices of diffusion coefficients. The model is fully coupled with CALPHAD calculations of the thermodynamic equilibrium at the interface, including a direct treatment of the effect of curvature through modification of the Gibbs free energy. An optimization strategy was developed to minimize the computational cost. The model was used to simulate ageing heat treatment at 600 °C of Ni–7.56 at.% Al–8.56 at.% Cr, which was studied experimentally by Booth-Morrison and others (Booth-Morrison C, Weninger J, Sudbrack CK, Mao Z, Noebe RD, Seidman DN. Acta Mater 2008;56:3422; Mao Z, Booth-Morrison C, Sudbrack CK, Martin G, Seidman DN. Acta Mater 2012;60:1871). The comparisons showed that the precipitation stages of γ′ precipitates are correctly captured by the numerical model. It was shown that non-diagonal diffusion coefficients substantially influence the selection of the operating tie-line and the overall transformation kinetics. With non-diagonal diffusion matrices, complex phenomena such as uphill diffusion of Cr due to the Al gradients were evidenced and explained.     

Network Medicine Approach in Prevention and Personalized Treatment of Dyslipidemias

Dyslipidemias can affect molecular networks underlying the metabolic homeostasis and vascular function leading to atherogenesis at early stages of development. Since disease-related proteins often interact with each other in functional modules, many advanced network-oriented algorithms were applied to patient-derived big data to identify the complex gene–environment interactions underlying the early pathophysiology of dyslipidemias and atherosclerosis. Both the proprotein convertase subtilisin/kexin type 7 (PCSK7) and collagen type 1 alpha 1 chain (COL1A1) genes arose from the application of TFfit and WGCNA algorithms, respectively, as potential useful therapeutic targets in prevention of dyslipidemias. Moreover, the Seed Connector algorithm (SCA) algorithm suggested a putative role of the neuropilin-1 (NRP1) protein as drug target, whereas a regression network analysis reported that niacin may provide benefits in mixed dyslipidemias. Dyslipidemias are highly heterogeneous at the clinical level; thus, it would be helpful to overcome traditional evidence-based paradigm toward a personalized risk assessment and therapy. Network Medicine uses omics data, artificial intelligence (AI), imaging tools, and clinical information to design personalized therapy of dyslipidemias and atherosclerosis. Recently, a novel non-invasive AI-derived biomarker, named Fat Attenuation Index (FAI™) has been established to early detect clinical signs of atherosclerosis. Moreover, an integrated AI-radiomics approach can detect fibrosis and microvascular remodeling improving the customized risk assessment. Here, we offer a network-based roadmap ranging from novel molecular pathways to digital therapeutics which can improve personalized therapy of dyslipidemias.