Glycopattern analysis and structure of the egg extra-cellular matrix in the Apennine yellow-bellied toad, Bombina pachypus (Anura: Bombinatoridae)

We studied the glycopatterns and ultrastructure of the extra-cellular matrix (ECM) of the egg of theApennine yellow-bellied toad Bombina pachypus, by light and electron microscopy in order to determine structure,chemical composition and function. Histochemical techniques in light microscopy included PAS and AlcianBlue pH 2.5 and 1.0, performed also after b-elimination. Lectin-binding was tested with nine lectins (AAA,ConA, DBA, HPA, LTA, PNA, SBA, UEA-I, WGA). An inner fertilization envelope (FE) and five jelly layers(J1–J5) were observed, differing in histochemical staining, lectin binding and ultrastructure. Most glycans wereO-linked, with many glucosamylated and fucosylated residues. The fertilization envelope presented a perivitellinespace and a fertilization layer, with mostly neutral glycans. The jelly layers consisted of fibers and granules,whose number and orientation differed between layers. Fibers were densely packed in J1 and J4 layers,whereas a looser arrangement was observed in the other layers. Jelly-layer glycans were mostly acidic and particularlyabundant in the J1 and J4 layers. In the J1, J2 and J5 layers, neutral, N-linked glycans were also observed.Mannosylated and/or glucosylated as well as galactosyl/galactosaminylated residues were more abundant in theouter layers. Many microorganisms were observed in the J5 layer. We believe that, apart from their functions inthe fertilization process, acidic and fucosylated glycans could act as a barrier against pathogen penetration

The dynamical structure of the MEO region: long-term stability, chaos, and transport

It has long been suspected that the Global Navigation Satellite Systems exist in a background of complex resonances and chaotic motion; yet, the precise dynamical character of these phenomena remains elusive. Recent studies have shown that the occurrence and nature of the resonances driving these dynamics depend chiefly on the frequencies of nodal and apsidal precession and the rate of regression of the Moon's nodes. Woven throughout the inclination and eccentricity phase space is an exceedingly complicated web-like structure of lunisolar secular resonances, which become particularly dense near the inclinations of the navigation satellite orbits. A clear picture of the physical significance of these resonances is of considerable practical interest for the design of disposal strategies for the four constellations. Here we present analytical and semi-analytical models that accurately reflect the true nature of the resonant interactions, and trace the topological organization of the manifolds on which the chaotic motions take place. We present an atlas of FLI stability maps, showing the extent of the chaotic regions of the phase space, computed through a hierarchy of more realistic, and more complicated, models, and compare the chaotic zones in these charts with the analytical estimation of the width of the chaotic layers from the heuristic Chirikov resonance-overlap criterion. As the semi-major axis of the satellite is receding, we observe a transition from stable Nekhoroshev-like structures at three Earth radii, where regular orbits dominate, to a Chirikov regime where resonances overlap at five Earth radii. From a numerical estimation of the Lyapunov times, we find that many of the inclined, nearly circular orbits of the navigation satellites are strongly chaotic and that their dynamics are unpredictable on decadal timescales.Comment: Submitted to Celestial Mechanics and Dynamical Astronomy. Comments are greatly appreciated. 28 pages, 15 figure

Formal verification of storm topologies through D-VerT

Data-intensive applications (DIAs) based on so-called Big Data technologies are nowadays a common solution adopted by IT companies to face their growing computational needs. The need for highly reliable applications able to handle huge amounts of data and the availability of infrastructures for distributed computing rapidly led industries to develop frame-works for streaming and big-data processing, like Apache Storm and Spark. The definition of methodologies and principles for good software design is, therefore, fundamental to support the development of DIAs. This paper presents an approach for non-functional analysis of DIAs through D- VerT, a tool for the architectural assessment of Storm applications. The verification is based on a translation of Storm topologies into the CLTLoc metric temporal logic. It allows the designer of a Storm application to check for the existence of components that cannot process their workload in a timely manner, typically due to an incorrect design of the topology

Role of Fibre in Nutritional Management of Pancreatic Diseases

The role of fibre intake in the management of patients with pancreatic disease is still controversial. In acute pancreatitis, a prebiotic enriched diet is associated with low rates of pancreatic necrosis infection, hospital stay, systemic inflammatory response syndrome and multiorgan failure. This protective effect seems to be connected with the ability of fibre to stabilise the disturbed intestinal barrier homeostasis and to reduce the infection rate. On the other hand, in patients with exocrine pancreatic insufficiency, a high content fibre diet is associated with an increased wet fecal weight and fecal fat excretion because of the fibre inhibition of pancreatic enzymes. The mechanism by which dietary fibre reduces the pancreatic enzyme activity is still not clear. It seems likely that pancreatic enzymes are absorbed on the fibre surface or entrapped in pectin, a gel-like substance, and are likely inactivated by anti-nutrient compounds present in some foods. The aim of the present review is to highlight the current knowledge on the role of fibre in the nutritional management of patients with pancreatic disorders

Modelling the length of hospital stay after knee replacement surgery through Machine Learning and Multiple Linear Regression at San Giovanni di Dio e Ruggi daAragonaa University Hospital

Knee arthroplasty is one of the most commonly performed procedures within a hospital. The progressive aging of the population and the spread of clinical conditions such as obesity will lead to an increasing use of this procedure. Therefore, being able to make the process related to this procedure more effective and efficient becomes strategic within hospitals, subject to increasingly stringent clinical and financial pressures. A useful parameter for this purpose is the length of stay (LOS), whose early prediction allows for better bed management and resource allocation, models patient expectations and facilitates discharge planning. In this work, the data of 124 patients who underwent knee surgery in the two-year period 2019-2020 at the San Giovanni di Dio and Ruggi d’Aragona university hospital were studied using multiple linear regression and machine learning algorithms in order to evaluate and predict how patient data affect LOS

Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy

The rapid growth in the complexity of services and stringent quality requirements present a challenge to all healthcare facilities, especially from an economic perspective. The goal is to implement different strategies that allows to enhance and obtain health processes closer to standards. The Length Of Stay (LOS) is a very useful parameter for the management of services within the hospital and is an index evaluated for the management of costs. In fact, a patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. To reduce and better manage the LOS it is necessary to be able to predict this value

Use of Electrical Coductivity Sensors to monitor Health Status and Quality of Milk in Dairy Goats

Intramammary infection (IMI) can adversely affect, in dairy goats, milk quality and milk yield leading to high economical losses. Although somatic cell count (SCC) and microbiological tests could be valid approaches to detect IMI, other methods of IMI early detection may be useful to detect infected animals and to improve milk quality.The aim of this study was to test a new multivariate model developed with the fuzzy logic technology and based on the milk EC - acquired on-line for each gland by dedicated sensors - and on new qualitative and quantitative indexes derived from the spectrum of the recorded signals.Results obtained showed that the fuzzy logic model tested could achive better results than those already reached in dairy goat research. Nevertheless, further experiment and more field data could be useful to reach the best possible accuracy that this multivariate approach could show