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Background & Aims: Malnutrition (over and under-nutrition) is highly prevalent in patients admitted to hospital and it is a well-known risk factor for increased morbidity and mortality. Nutritional problems are often misdiagnosed, and especially the coexistence of over and undernutrition is not usually recognized. We aimed to develop and validate a screening tool for the easy detection and reporting of both undernutrition and overnutrition, specifically identifying the clinical conditions where the two types of malnutrition coexist., Methods: The study consisted of three phases: 1) selection of an appropriate study population (estimation sample) and of the hospital admission parameters to identify overnutrition and undernutrition; 2) combination of selected variables to create a screening tool to assess the nutritional risk in case of undernutrition, overnutrition, or the copresence of both the conditions, to be used by non-specialist health care professionals; 3) validation of the screening tool in a different patient sample (validation sample)., Results: Two groups of variables (12 for undernutrition, 7 for overnutrition) were identified in separate logistic models for their correlation with the outcome variables. Both models showed high efficacy, sensitivity and specificity (overnutrition, 97.7%, 99.6%, 66.6%, respectively; undernutrition, 84.4%, 83.6%, 84.8%). The logistic models were used to construct a two-faced test (named JaNuS - Just A Nutritional Screening) fitting into a two-dimension Cartesian coordinate graphic system. In the validation sample the JaNuS test confirmed its predictive value. Internal consistency and test-retest analysis provide evidence for the reliability of the test., Conclusion: The study provides a screening tool for the assessment of the nutritional risk, based on parameters easy-to-use by health care personnel lacking nutritional competence and characterized by excellent predictive validity. The test might be confidently applied in the clinical setting to determine the importance of malnutrition (including the copresence of over and undernutrition) as a risk factor for morbidity and mortality., (Copyright © 2013 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.)

Background and Aims: Severe hypoglycemia is not rare in diabetes and markedly impacts on health resource use. We aimed to describe the characteristics of patients attending emergency departments (EDs) following a severe episode of hypoglycemia, the factors associated with the management of events and the final outcome., Methods and Results: We carried out a retrospective analysis of cases attending 46 Italian EDs for hypoglycemia from January 2011 to June 2012. A total of 3753 records were retrieved from the databases of the participating centers, part of a network repeatedly involved in collaborative studies; 3516 episodes occurred in subjects with diabetes (median age, 76 years; range, 1-102). Comorbidities were recorded in 2320 (65.9%) diabetes cases; association with trauma or road accidents in 287 (8.2%) and 47 (1.3%), respectively. Patients were treated with insulin (49.8%), oral agents (31.4%), or combination treatment (15.1%). The event required assistance by the out-of-hospital Emergency services in 1821 cases (51.8%). Following the ED visit, admission to hospital departments was deemed necessary in 1161 cases (33.1%). Diabetes treatment (oral agents: OR, 1.63; 95% confidence interval (CI), 1.37-1.94), increasing age (OR, 1.39; 95% CI, 1.31-1.48) and the number of comorbidities (OR, 1.51; 95% CI, 1.38-1.66) were the main drivers of admission. The in-hospital death rate was 10%, associated with the number of comorbidities (OR, 1.28; 95%CI, 1.01-1.63)., Conclusion: Severe hypoglycemia requiring referral to EDs is associated with a significant work-up of the Emergency services and a remarkable in-hospital death rate in frail individuals with diabetes., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The article is intended to provide an overview of the strengths and limits of controlled trials of pharmacologic treatment of nonalcoholic fatty liver disease. No drug has so far been approved, although validated on histologic outcomes. Several new drugs are under scrutiny, acting with different mechanisms along the chain of events from fatty liver to fibrosis, cirrhosis, and hepatocellular carcinoma. The article investigates which drug, if any, should be preferred for a tailored intervention in individual patients, according to age, comorbidities, and disease severity, and if treatment should be continued lifelong, to prevent disease progression and long-term occurrence of cirrhosis., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Objectives: To validate the modified Mini Nutritional Assessment (MNA) short-forms (MNA-SFs) with respect to agreement with full MNA classification in the target populations of the MNA., Design: Prospective analysis., Setting: Community, nursing home, rehabilitation., Participants: Six hundred fifty-seven individuals aged 65 and older (75.3% female; mean age 82.3 ± 7.4)., Measurements: Classification agreement between full MNA score and MNA-SF scores., Results: Agreement between the full MNA and classification using the MNA-SFs was 84.6% when the MNA-SF using body mass index (BMI) was applied and 81.4% when the MNA-SF using calf circumference (CC) was applied. The highest agreement of classification was found in the community setting (90.8% and 90.4%, respectively) and the lowest in the rehabilitation setting (72.4% and 71.4%, respectively). Both MNA-SFs tended to underestimate nutritional status, but that was significant only for the MNA-SF with CC., Conclusion: The modified MNA-SFs represent a valuable tool for rapid and reliable nutritional screening., (© 2011, Copyright the Authors Journal compilation © 2011, The American Geriatrics Society.)

The leaky integrate-and-fire neuronal model proposed in Stevens and Zador (1998), in which time constant and resting potential are postulated to be time dependent, is revisited within a stochastic framework in which the membrane potential is mathematically described as a gauss-diffusion process. The first-passage-time probability density, miming in such a context the firing probability density, is evaluated by either the Volterra integral equation of Buonocore, Nobile, and Ricciardi ( 1987 ) or, when possible, by the asymptotics of Giorno, Nobile, and Ricciardi (1990). The model examined here represents an extension of the classic leaky integrate-and-fire one based on the Ornstein-Uhlenbeck process in that it is in principle compatible with the inclusion of some other physiological characteristics such as relative refractoriness. It also allows finer tuning possibilities in view of its accounting for certain qualitative as well as quantitative features, such as the behavior of the time course of the membrane potential prior to firings and the computation of experimentally measurable statistical descriptors of the firing time: mean, median, coefficient of variation, and skewness. Finally, implementations of this model are provided in connection with certain experimental evidence discussed in the literature.

Objective: Artificial nutrition (AN) is now considered medical therapy and has progressively become one of the mainstays of the different therapeutic options available for home or hospitalized patients, including surgical, medical, and critically ill patients. The clinical relevance of any therapy is based on its efficacy and effectiveness and thus on the improvement of its cost efficiency, i.e., the ability to provide benefits to the patients with minimal wasting of human and financial resources. The aim of the present study was to identify those indices, clinical, functional, or nutritional, that may reliably predict, before the start of AN, those patients who are likely not to benefit from nutritional support., Methods: Three hundred twelve clinical charts of patients receiving AN between January 1999 and September 2006 were retrospectively examined. Data registered before starting AN were collected and analyzed: general data (age, sex), clinical conditions (comorbidity, quality of life, frailty), anthropometric and biochemical indices, type of AN treatment (total enteral nutrition, total parenteral nutrition, mixed AN), and outcome of treatment., Results: The percentage of negative outcomes (death or interruption of AN due to worsening clinical conditions within 10 d after starting AN) was meaningfully higher in subjects >80 y of age and with reduced social functions, higher comorbidity and/or frailty, reduced level of albumin, prealbumin, lymphocyte count, and cholinesterase and a higher level of C-reactive protein. The multivariate analysis showed that prealbumin and comorbidity were the best predictors of AN outcome. The logistic regression model with these variables showed a predictive value equal to 84.2%., Conclusion: Proper prognostic instruments are necessary to perform optimal evaluations. The present study showed that a patient's general status (i.e., comorbidity, social quality of life, frailty) and nutritional and inflammatory statuses (i.e., lymphocyte count, albumin, prealbumin, C-reactive protein) have good predictive value on the effectiveness of AN.

As a model of Brownian motor we consider the jump diffusion motion of a particle in the presence of an asymmetric periodic potential with a unique minimum and subject to half-period space shifts at the instants of occurrence of two Poisson processes. The relevant quantities, i.e., probability current, effective driving force, stall force, power and efficiency of the motor are explicitly calculated as averages of certain functions of the random variable representing the particle position.

An instantaneous return process in the presence of random refractoriness for Wiener model of single neuron activity is considered. The case of exponential distributed refractoriness is analyzed and expressions for output distributions and interspike intervals density are obtained in closed form. A computational study is performed to elucidate the role played by the model parameters in affecting the firing probabilities and the interspike distribution.

We address the controversial hot question concerning the validity of the loose coupling versus the lever-arm theories in the actomyosin dynamics by re-interpreting and extending the phenomenological washboard potential model proposed by some of us in a previous paper. In this new model a Brownian motion harnessing thermal energy is assumed to co-exist with the deterministic swing of the lever-arm, to yield an excellent fit of the set of data obtained by some of us on the sliding of Myosin II heads on immobilized actin filaments under various load conditions. Our theoretical arguments are complemented by accurate numerical simulations, and the robustness of the model is tested via different choices of parameters and potential profiles.

With reference to the experimental observations by Yanagida and his co-workers on actomyosin interaction, a Brownian motor of fluctuating ratchet kind is designed with the aim to describe the interaction between a Myosin II head and a neighboring actin filament. Our motor combines the dynamics of the myosin head with a chemical external system related to the ATP cycle, whose role is to provide the energy supply necessary to bias the motion. Analytical expressions for the duration of the ATP cycle, for the Gibbs free energy and for the net displacement of the myosin head are obtained. Finally, by exploiting a method due to Sekimoto [J. Phys. Soc. Jpn. 66 (1997) 1234], a formula is worked out for the amount of energy consumed during the ATP cycle.

With reference to the experimental observations by Yanagida and his co-workers concerning actomyosin interaction during muscle contraction processes, we propose a phenomenological model for the sliding of the myosin head on the actin filament, in which the myosin head is viewed as an active Brownian particle in a periodic, elastic-type potential subject to tilting. The sample paths thus obtained are qualitatively alike to those experimentally recorded. Furthermore, our model is proved to be susceptible of a consistent parameters regulation yielding step frequencies, mean step dwell time and dwell time distribution in excellent agreement with the experimental evidence.

A mathematical characterization of the membrane potential as an instantaneous return process in the presence of refractoriness is investigated for diffusion models of single neuron's activity, assuming that the firing threshold acts as an elastic barrier. Steady-state probability densities and asymptotic moments of the neuronal membrane potential are explicitly obtained in a form that is suitable for quantitative evaluations. For the Ornstein-Uhlenbeck (OU) and Feller neuronal models, closed form expression are obtained for asymptotic mean and variance of the neuronal membrane potential and an analysis of the different features exhibited by the above mentioned models is performed.

A stochastic model concerning the evolution of a multi-species population is presented assuming species competition for a habitat. The model takes into account colonization, death and replacement for all individuals. Two cases are treated: (i) colonizations follow the hierarchic rule by which species of lower rank are always outcompeted by those of higher rank and (ii) there are no privileged species. In both cases, under suitable assumptions, a thorough description of the evolution of the population is obtained. The two models are finally compared and the corresponding evolutionary behaviors of the populations are discussed.

The classical Ornstein-Uhlenbeck diffusion neuronal model is generalized by inclusion of a time-dependent input whose strength exponentially decreases in time. The behavior of the membrane potential is consequently seen to be modeled by a process whose mean and covariance classify, it as Gaussian-Markov. The effect of the input on the neuron's firing characteristics is investigated by comparing the firing probability densities and distributions for such a process with the corresponding ones of the Ornstein-Uhlenbeck model. All numerical results are obtained by implementation of a recently developed computational method.

With reference to the Ornstein-Uhlenbeck model for single neuron activity, computational results and theoretical arguments are provided to discuss the accuracy and the appropriateness of analytical approximations to first-passage-time densities and its moments. A gamma approximation is initially discussed, use of which is successively made to construct a probability density of a new form that appears to be particularly suitable to approximate the as yet unknown firing probability density function.

For the Ornstein-Uhlenbeck neuronal model a quantitative method is proposed for the estimation of the two parameters characterizing the unknown input process, namely the neuron's mean input per unit time mu and the infinitesimal standard deviation per unit time sigma. This method is based on the experimentally observed first- and second-order moments of interspike intervals. The dependence of the estimates mu and ŝigma on the moments of the observed interspike intervals and on the neuronal parameters is clarified, and a comparison is made between the estimates based on the classical Wiener model and those yielded by the Ornstein-Uhlenbeck model. Comprehensive tables are included in which the displayed values of mu and ŝigma have been calculated in terms of physiologically realistic pairs of first- and second-order moments. Our method is finally applied to interspike interval data recorded from neurons in the mesencephalic reticular formation of the cat during hypothetical sleep, slow-wave sleep stage, and wake stage.

Population growth is modelled by means of diffusion processes originating from fluctuation equations of a new type. These equations are obtained in the customary way by inserting random fluctuations into first order non linear differential equations. However, differently from the cases so far considered in the literature, equations possessing two non trivial fixed points are taken into account. The underlying deterministic models depict the regulated growth of a population whose size cannot decrease below some preassigned lower threshold naturally acting as an absorbing boundary. A fairly comprehensive mathematical description of these models is provided.

Mean and variance of the first passage time through a constant boundary for the Ornstein-Uhlenbeck process are determined by a straight-forward differentiation of the Laplace transform of the first passage time probability density function. The results of some numerical computations are discussed to shed some light on the input-output behavior of a formal neuron whose dynamics is modeled by a diffusion process of Ornstein-Uhlenbeck type.

A stochastic model for single neuron's activity is constructed as the continuous limit of a birth-and-death process in the presence of a reversal hyperpolarization potential. The resulting process is a one dimensional diffusion with linear drift and infinitesimal variance, somewhat different from that proposed by Lánský and Lánská in a previous paper. A detailed study is performed for both the discrete process and its continuous approximation. In particular, the neuronal firing time problem is discussed and the moments of the firing time are explicitly obtained. Use of a new computation method is then made to obtain the firing p.d.f. The behaviour of mean, variance and coefficient of variation of the firing time and of its p.d.f. is analysed to pinpoint the role played by the parameters of the model. A mathematical description of the return process for this neuronal diffusion model is finally provided to obtain closed form expressions for the asymptotic moments and steady state p.d.f. of the neuron's membrane potential.

Discrete stochastic models are constructed and their limit diffusion processes are derived to shed light on a controversial conjecture regarding the effects of environmental variance on the asymptotic behavior of a population subject to logistic growth in random environment.