Silvia Vitali

IMPAIRED FACIAL EMOTION RECOGNITION AND PRESERVED REACTIVITY TO FACIAL EXPRESSIONS IN PEOPLE WITH SEVERE DEMENTIA

The ability of decoding the emotional facial expressions may be early damaged in frontotemporal dementia, but relatively well preserved in the Alzheimers disease (AD). Nevertheless, the data about the relationship of the dementia severity with the ability of recognizing the face emotions are conflicting and insufficient, mainly for the moderate-severe stage of the disease. The present study extends to the existing literature by: (1) assessing people in the moderate and severe stage of dementia, compared with people without cognitive impairment; (2) assessing not only recognition but also reactivity to the facial expression of emotion. The capability of understanding the facial emotions has been evaluated in 79 patients with dementia compared to 64 healthy elderly people. The test consisted in showing them 14 photographic representations of 7 emotions both from male and from female faces, representing happiness, sadness, fear, disgust, boredom, anger and surprise. Patients were asked to observe the face and to recognize the emotion either with a denomination or a description. Then the spontaneous reactivity to the face expressions was videotaped and classified as a congruous or incongruous reaction by two independent observers who showed a good inter-rater reliability. Of the patients, 53% with dementia recognized up to 5 emotions out of 14, while in the healthy controls this number of mean recognition raised to 8.4, a value reached by the patients who scored 16 at MMSE. The most identified emotion is happiness both for the patients and for the controls. In general, positive emotions are better recognized than the negative ones, confirming the literary data. About the reactions to face emotion stimuli, there is no significant difference for any of the face emotion between the control group and the people with dementia. These data show that patients with dementia can recognize and react to facial emotions also in the severe stage of the disease, suggesting the usefulness of a non-verbal, emotional communication and supporting the need for more emotional education for care givers, both relatives and professionals.

Systems medicine of inflammaging

Systems Medicine (SM) can be defined as an extension of Systems Biology (SB) to Clinical-Epidemiological disciplines through a shifting paradigm, starting from a cellular, toward a patient centered framework. According to this vision, the three pillars of SM are Biomedical hypotheses, experimental data, mainly achieved by Omics technologies and tailored computational, statistical and modeling tools. The three SM pillars are highly interconnected, and their balancing is crucial. Despite the great technological progresses producing huge amount of data (Big Data) and impressive computational facilities, the Bio-Medical hypotheses are still of primary importance. A paradigmatic example of unifying Bio-Medical theory is the concept of Inflammaging. This complex phenotype is involved in a large number of pathologies and patho-physiological processes such as aging, age-related diseases and cancer, all sharing a common inflammatory pathogenesis. This Biomedical hypothesis can be mapped into an ecological perspective capable to describe by quantitative and predictive models some experimentally observed features, such as microenvironment, niche partitioning and phenotype propagation. In this article we show how this idea can be supported by computational methods useful to successfully integrate, analyze and model large data sets, combining cross-sectional and longitudinal information on clinical, environmental and omics data of healthy subjects and patients to provide new multidimensional biomarkers capable of distinguishing between different pathological conditions, e.g. healthy versus unhealthy state, physiological versus pathological aging.

Time fractional cable equation and applications in neurophysiology

Abstract We propose an extension of the cable equation by introducing a Caputo time fractional derivative. The fundamental solutions of the most common boundary problems are derived analytically via Laplace Transform, and result be written in terms of known special functions. This generalization could be useful to describe anomalous diffusion phenomena with leakage as signal conduction in spiny dendrites. The presented solutions are computed in Matlab and plotted.

Stochastic neutral modelling of the Gut Microbiota's relative species abundance from next generation sequencing data.

BackgroundInterest in understanding the mechanisms that lead to a particular composition of the Gut Microbiota is highly increasing, due to the relationship between this ecosystem and the host health state. Particularly relevant is the study of the Relative Species Abundance (RSA) distribution, that is a component of biodiversity and measures the number of species having a given number of individuals. It is the universal behaviour of RSA that induced many ecologists to look for theoretical explanations. In particular, a simple stochastic neutral model was proposed by Volkov et al. relying on population dynamics and was proved to fit the coral-reefs and rain forests RSA. Our aim is to ascertain if this model also describes the Microbiota RSA and if it can help in explaining the Microbiota plasticity.ResultsWe analyzed 16S rRNA sequencing data sampled from the Microbiota of three different animal species by Jeraldo et al. Through a clustering procedure (UCLUST), we built the Operational Taxonomic Units. These correspond to bacterial species considered at a given phylogenetic level defined by the similarity threshold used in the clustering procedure. The RSAs, plotted in the form of Preston plot, were fitted with Volkov’s model. The model fits well the Microbiota RSA, except in the tail region, that shows a deviation from the neutrality assumption. Looking at the model parameters we were able to discriminate between different animal species, giving also a biological explanation. Moreover, the biodiversity estimator obtained by Volkov’s model also differentiates the animal species and is in good agreement with the first and second order Hill’s numbers, that are common evenness indexes simply based on the fraction of individuals per species.ConclusionsWe conclude that the neutrality assumption is a good approximation for the Microbiota dynamics and the observation that Volkov’s model works for this ecosystem is a further proof of the RSA universality. Moreover, the ability to separate different animals with the model parameters and biodiversity number are promising results if we think about future applications on human data, in which the Microbiota composition and biodiversity are in close relationships with a variety of diseases and life-styles.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods:

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as “good”; “sufficient”; or “corrective action needed” based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

Fractional cable model for signal conduction in spiny neuronal dendrites

The cable model is widely used in several fields of science to describe the propagation of signals. A relevant medical and biological example is the anomalous subdiffusion in spiny neuronal dendrites observed in several studies of the last decade. Anomalous subdiffusion can be modelled in several ways introducing some fractional component into the classical cable model. The Chauchy problem associated to these kind of models has been investigated by many authors, but up to our knowledge an explicit solution for the signalling problem has not yet been published. Here we propose how this solution can be derived applying the generalized convolution theorem (known as Efros theorem) for Laplace transforms.The fractional cable model considered in this paper is defined by replacing the first order time derivative with a fractional derivative of order α ∈ (0, 1) of Caputo type. The signalling problem is solved for any input function applied to the accessible end of a semi-infinite cable, which satisfies the requir...

Subthreshold Depression and Clinically Significant Depression in an Italian Population of 70–74-Year-Olds: Prevalence and Association with Perceptions of Self

Estimates of depressive disorders in the elderly vary depending on how cases are defined. We estimated the prevalence of subthreshold depression (SD) and clinically significant depression (D) in a population of 70–74-year-olds. We also looked for associations with sociodemographic factors and perceptions of self. Participants underwent a multidimensional assessment (social, medical, and neuropsychological). The estimated prevalence of SD was 15.71% (95% CI: 13.70–17.72), while that of D was 5.58% (95% CI: 4.31–6.85). Multinomial logistic regression analysis revealed that female gender and dissatisfaction with family relationships were related to SD and D. A self-perception of physical age as older than actual age (but not comorbidity) and greater self-perceived stress caused by negative life events both increased the probability of SD. The likelihood of D was decreased in those who perceived their own health as good, whereas a self-perception of mental age as older than actual age and dissatisfaction with relationships with friends were both significantly associated with D. Both SD and D emerged as key problems in our population. Female gender and self-perceptions of various characteristics, which can be explored through simple questions, are associated with late-life depression in elderly people independently of their actual physical condition and other characteristics.

Emergence of Fractional Kinetics in Spiny Dendrites

Fractional extensions of the cable equation have been proposed in the literature to describe transmembrane potential in spiny dendrites. The anomalous behavior has been related in the literature to the geometrical properties of the system, in particular, the density of spines, by experiments, computer simulations, and in comb-like models. The same PDE can be related to more than one stochastic process leading to anomalous diffusion behavior. The time-fractional diffusion equation can be associated to a continuous time random walk (CTRW) with power-law waiting time probability or to a special case of the Erdely-Kober fractional diffusion, described by the ggBm. In this work, we show that time fractional generalization of the cable equation arises naturally in the CTRW by considering a superposition of Markovian processes and in a ggBm-like construction of the random variable.

Langevin equation in complex media and anomalous diffusion

The problem of biological motion is a very intriguing and topical issue. Many efforts are being focused on the development of novel modelling approaches for the description of anomalous diffusion in biological systems, such as the very complex and heterogeneous cell environment. Nevertheless, many questions are still open, such as the joint manifestation of statistical features in agreement with different models that can also be somewhat alternative to each other, e.g. continuous time random walk and fractional Brownian motion. To overcome these limitations, we propose a stochastic diffusion model with additive noise and linear friction force (linear Langevin equation), thus involving the explicit modelling of velocity dynamics. The complexity of the medium is parametrized via a population of intensity parameters (relaxation time and diffusivity of velocity), thus introducing an additional randomness, in addition to white noise, in the particles dynamics. We prove that, for proper distributions of these parameters, we can get both Gaussian anomalous diffusion, fractional diffusion and its generalizations.