Optimal therapy of type 2 diabetes: a controversial challenge

Type 2 diabetes mellitus (T2DM) is one of the most common chronic disorders in older adults and the number of elderly diabetic subjects is growing worldwide. Nonetheless, the diagnosis of T2DM in elderly population is often missed or delayed until an acute metabolic emergency occurs. Accumulating evidence suggests that both aging and environmental factors contribute to the high prevalence of diabetes in the elderly. Clinical management of T2DM in elderly subjects presents unique challenges because of the multifaceted geriatric scenario. Diabetes significantly lowers the chances of "successful" aging, notably it increases functional limitations and impairs quality of life. In this regard, older diabetic patients have a high burden of comorbidities, diabetes-related complications, physical disability, cognitive impairment and malnutrition, and they are more susceptible to the complications of dysglycemia and polypharmacy. Several national and international organizations have delivered guidelines to implement optimal therapy in older diabetic patients based on individualized treatment goals. This means appreciation of the heterogeneity of the disease as generated by life expectancy, functional reserve, social support, as well as personal preference. This paper will review current treatments for achieving glycemic targets in elderly diabetic patients, and discuss the potential role of emerging treatments in this patient population

Chronic bacterial prostatitis: efficacy of short-lasting antibiotic therapy with prulifloxacin (Unidrox®) in association with saw palmetto extract, lactobacillus sporogens and arbutin (Lactorepens®)

Bacterial prostatitis (BP) is a common condition accounting responsible for about 5-10% of all prostatitis cases; chronic bacterial prostatitis (CBP) classified as type II, are less common but is a condition that significantly hampers the quality of life, (QoL) because not only is it a physical condition but also a psychological distress. Commonly patients are treated with antibiotics alone, and in particular fluoroquinolones are suggested by the European Urology guidelines. This approach, although recommended, may not be enough. Thus, a multimodal approach to the prolonged antibiotic therapy may be helpful.210 patients affected by chronic bacterial prostatitis were enrolled in the study. All patients were positive to Meares-Stamey test and symptoms duration was > 3 months. The purpose of the study was to evaluate the efficacy of a long lasting therapy with a fluoroquinolone in association with a nutraceutical supplement (prulifloxacin 600 mg for 21 days and an association of Serenoa repens 320 mg, Lactobacillus Sporogens 200 mg, Arbutin 100 mg for 30 days). Patients were randomized in two groups (A and B) receiving respectively antibiotic alone and an association of antibiotic plus supplement.Biological recurrence at 2 months in Group A was observed in 21 patients (27.6%) and in Group B in 6 patients (7.8%). Uropathogens found at the first follow-up were for the majority Gram - (E. coli and Enterobacter spp.). A statistically significant difference was found at the time of the follow-up between Group A and B in the NIH-CPSI questionnaire score, symptoms evidence and serum PSA.Broad band, short-lasting antibiotic therapy in association with a nutritional supplement (serenoa repens, lactobacillus sporogens and arbutin) show better control and recurrence rate on patients affected by chronic bacterial prostatitits in comparison with antibiotic treatment alone.NCT02130713Date of trial Registration: 30/04/2014

FEM and ANN combined approach for predicting pressure source

A hybrid approach for forward and inverse geophysical modeling, based on Artificial Neural Networks (ANN) and Finite Element Method (FEM), is proposed in order to properly identify the parameters of volcanic pressure sources from geophysical observations at ground surface. The neural network is trained and tested with a set of patterns obtained by the solutions of numerical models based on FEM. The geophysical changes caused by magmatic pressure sources were computed developing a 3-D FEM model with the aim to include the effects of topography and medium heterogeneities at Etna volcano. ANNs are used to interpolate the complex non linear relation between geophysical observations and source parameters both for forward and inverse modeling. The results show that the combination of neural networks and FEM is a powerful tool for a straightforward and accurate estimation of source parameters in volcanic regions

Fitting Parton Distribution Data with Multiplicative Normalization Uncertainties

We consider the generic problem of performing a global fit to many independent data sets each with a different overall multiplicative normalization uncertainty. We show that the methods in common use to treat multiplicative uncertainties lead to systematic biases. We develop a method which is unbiased, based on a self--consistent iterative procedure. We demonstrate the use of this method by applying it to the determination of parton distribution functions with the NNPDF methodology, which uses a Monte Carlo method for uncertainty estimation.Comment: 33 pages, 5 figures: published versio

Dissipative Dynamic Libraries (DDLs) and Dissipative Dynamic Combinatorial Chemistry (DDCC)

This Concept is focused on the key features of dissipative dynamic combinatorial chemistry (DDCC). DDCC deals with transient libraries of compounds, maintained out-of-equilibrium by the consumption of a fuel, whose composition changes upon the selection pressure of kinetic and/or thermodynamic processes. Concepts and definitions of kinetic and thermodynamic dissipative dynamic libraries ("KDDL" and "TDDL"), are introduced and illustrated by a number of actual cases, thus showing the consistency of the present approach. Such concepts and definitions can help establish a common language for this emerging field, which, in our view, has the potential to become highly relevant to supramolecular chemistry

Lentil fortified spaghetti: Technological properties and nutritional characterization

Lentil (Lens culinaris), consumed as a part of the diet worldwide, is a functional dietary ingredient that plays a function in human nutrition as a rich source of bioactive nutrients (low quantities of fat, sodium, and vitamin K; high content of potassium, essential amino acids, insoluble dietary fiber, and polyphenols). In this study spaghetti fortified with lentil flours (40% w/w) were developed and characterized. The addition of two different lentil flours significantly affected the sensory attributes and cooking properties of dry spaghetti. Therefore, the addition of carboxymethyl cellulose was adopted as technological option to improve the quality of fortified pasta; specifically, sensory acceptability, cooking loss, swelling index, and water absorption were studied. Chemical results highlighted that the addition of lentil to semolina significantly increased the content of lysine and threonine. It was observed an increase in essential and branched-chain amino acids. Contrary to what was expected, no increase in mono and polyunsaturated fatty acids was observed in fortified spaghetti, due to their loss during cooking, even after the addition of carboxymethyl cellulose

Time Programmable Locking/Unlocking of the Calix[4]arene Scaffold by Means of Chemical Fuels

In this work, we report that 2-cyano-2-phenylpropanoic acid and its p-Cl, p-CH3 and p-OCH3 derivatives can be used as chemical fuels to control the geometry of the calix[4]arene scaffold in its cone conformation. It is shown that, under the action of the fuel, the cone calix[4]arene platform assumes a “locked” shape with two opposite aromatic rings strongly convergent and the other two strongly divergent (“pinched cone” conformation). Only when the fuel is exhausted, the cone calix[4]arene scaffold returns to its resting, “unlocked” shape. Remarkably, the duration of the “locked” state can be controlled at will by varying the fuel structure or amount. A kinetic study of the process shows that the consume of the fuel is catalyzed by the “unlocked” calixarene that behaves as an autocatalyst for its own production. A mechanism is proposed for the reaction of fuel consumption

Comparison of predictive and descriptive models in order to plan the monitoring and research on the rock partridge (Alectoris graeca) in the North Eastern Alps

Within the implementation of the Management Plan for the Alpi Carniche region (SPA IT3321001, SCI IT3320001, SCI IT3320002, SCI IT3320003, SCI IT3320004) and the realization of the monitoring plan referred to art. 8 of RL No. 7/2008 (Friuli Venezia Giulia) some predictive and descriptive models for the presence and abundance of rock partridge Alectoris graeca saxatilis have been developed and tested. During 2010 the monitoring plan has been carried out during the spring (play-back censuses) and the summer (pointing dog censuses) in 10 sample areas to assess the presence, abundance and reproductive success of the species. These areas have been identified through expert knowledge and predictive models developed by the superimposition on regional UTM 1x1 kilometer grid quadrants of some CORINE Biotopes habitat parameters (open vegetation coverage >50% and open + transitional vegetation coverage >80%) and slope (>10%) and elevation (1000-2200 m above sea level), subsequently ranked from 0 to 4 for a suitability index. The census results related to UTM quadrants (n = 46, 40% with the presence of partridges) and buffer areas (100 meters of radius) created from the locations of the observed animals and the transect points of the censuses (n = 89) have been described by linear selection models that contain habitat classes from the Habitat Map of Friuli Venezia Giulia (Map of the Nature at the scale 1:50.000, ISPRA 2009) and morphological characteristics such as slope, elevation and aspect. The descriptive models have selected different variables according to the season (reproductive and post-reproductive), identifying the presence of Eastern Alpine calcicolous larch with moorland as one of the most important variables to define habitat suitability. Moreover, the descriptive models that use the lesser spatial scale (100 m buffer) seemed to describe better the presence and abundance of this species. The predictive models however were inappropriate to describe the presence of this species and should be used with caution to plan the monitoring activities. The research was supported by the Friuli Venezia Giulia Autonomous Region

Twisted Eguchi-Kawai Reduced Chiral Models

We study the twisted Eguchi-Kawai (TEK) reduction procedure for large-N unitary matrix lattice models. In particular, we consider the case of two-dimensional principal chiral models, and use numerical Monte Carlo (MC) simulations to check the conjectured equivalence of TEK reduced model and standard lattice model in the large-N limit. The MC results are compared with the large-N limit of lattice principal chiral models to verify the supposed equivalence. The consistency of the TEK reduction procedure is verified in the strong-coupling region, i.e. for $\beta<\beta_c$ where $\beta_c$ is the location of the large-N phase transition. On the other hand, in the weak-coupling regime $\beta>\beta_c$, relevant for the continuum limit, our MC results do not support the equivalence of the large-N limits of the lattice chiral model and the corresponding TEK reduction. The implications for the correspondence between TEK model and noncommutative field theory are also discussed.Comment: 16 page