Search

Social media can directly support disease management by creating online spaces where patients can interact with clinicians, and share experiences with other patients. Nevertheless, much more work remains to be carried out for providing and sharing an optimized information content. In this paper we formulate, from a theoretical perspective, an optimization problem aimed to encourage the creation of a sub-network of patients which, being recently diagnosed, wish to deepen their knowledge about their pathologies with some other patients, whose clinical profile turn to be similar, and have already been followed up within specific, even alternative, care centers. We will focus on the hardness of the proposed problem and provide a Genetic Algorithm (GAbased) approach to seek faster approximated solutions.

Objectives: We studied the effect of Telehomecare (THC) in a group of Cystic Fibrosis (CF) patients. Specifically, in order to investigate the evolution of the clinical trend, we examined the monitoring activities of CF patients followed at home for a period of 4.5 years. Methods: Forced Expiratory Volume in the first second (FEV1) was monitored at home, with the aim of an early recognition of the relapses of pulmonary infections. FEV1 was monitored by Spirotel-MIR instrumentation for 4.5 years, using THC as a tool, in addition to the standard therapeutic protocol. 16 CF patients were followed by doctors specialized in the treatment, over a period of 4.5 years. As control group, we enrolled 16 CF patients with similar characteristics of age, degree of pulmonary involvement, bacterial colonization and O2 dependency. Results: While in the first 5 year report we showed statistically significant reduction in hospital admissions and a tendency over time towards a better stability of the respiratory function, here we provide an evidence of the significant different evolution between THCs and controls measured as the difference between the values of average annual FEV1 and those values observed during a starting reference year (i.e. 2011). Discussion: The obtained results in both quantitative and qualitative parameters of our work during these 10 years is positive. Data are encouraging concerning the possible role of Telemedicine as a tool for domestic assistance of patients affected by chronic diseases, such as CF.

New technologies are multiplying at an enormous speed and the produced data is not only massive but also complex. In fact, despite the abundance of tools to capture, process and share information (e.g. data) one cannot broadly assume the standard hypothesis that such data are identically and independently distributed (i.i.d.). As a result, proper handling of data is fundamental in order to convert the available observation in to useful information that leads to knowledge and suitable decision making. In this paper, we focus on network data. That is, we introduce the reader to a theoretical perspective concerning the knowledge mining of huge amount of relational information collected in all the network systems which are ubiquitous in our life. In this context, following a numerical evaluation we show the reader how different kind of information can provide a benefit for a typical machine learning problem i.e. classification. The main issue of our investigation is to provide a case where the accuracy of a classification model benefits when considering the additional information given by both network and dissimilarity features. Moreover, we treat a clinical example that will serve as running case for our analysis.

Spinal cord injury (SCI) counts about 17,000 new cases each year in the United States. Since axons lose the competence to regenerate in adult mammals, SCI can lead to permanent neurological damages with dramatic personal, social and economic impacts. The long-term deficit of SCI results first from the type of insult and then from the secondary phase that includes many pathophysiological events. Among these, inflammation and epigenetic factors play a crucial role in the recovery of neuron connections. Variations in epigenetic and immune contribution, in turn, depend on age and health status as well as to microbiota profile of individuals at the time of, or consequent to SCI. Indeed, gut microorganisms, highly influence the immune system, but also produce bioactive substances such as folates, butyrate and acetate that participate to the epigenetic processes. Interestingly, variations in the profile of microbiota and bioactive substances have been described in patients with neurologic intestine because of SCI. Recently, different approaches, including stem cell therapy, use of biomaterial and laser therapy, have been proposed for neuronal regeneration after SCI but they are still far from resolutive interventions. As the complexity of pathophysiological processes of the secondary phase can deeply condition the success of regeneration, we provide a landscape of microbiota-epigenetic-immune modulation of neurological recovery predisposition or prevention. We discuss most of data about epigenetics (microRNAs, circulating microRNAs and chromatin remodelling) after SCI in animal models as well as microbiome profile of patients with SCI. We also propose a bioinformatics approach to compare "comics" data (gut microbiome, circulating microRNAs and inflammatory profiles) of patiens with SCI before and after laser therapy to evaluate and improve laser induced neuroregeneration. Acknowledgements: Flagship InterOmics (PB05).

Objectives: spinal cord injury (SCI) triggers a cascade of intrinsic pathophysiological events that influence the SCI long-term deficit and that should be therapeutically modulated. The aim is to identify biomarkers to favour neuronal recovery after SCI. Material and Methods: we reviewed the literature indexed in PubMed about SCI, SCI epigenetics, SCI microbiota and novel therapeutic strategies for SCI repair. Results: inflammation-epigenetics-microbiota vicious cycle affects recovery after SCI. The dysregulation of specific microRNAs and circulating microRNAs was found in spinal cord and in serum, respectively, after SCI thus circulating microRNAs are promising biomarkers for evaluating the severity of SCI, as demonstrated in animal models. SCI patients often display neurogenic intestine dysfunction including changes in gut microbiome composition with a significant reduction in butyrate producing bacteria. Butyrate is a potent anti-inflammatory agent, a histone deacetylase inhibitor and suppresses inflammation in the CNS probably reducing microglia-mediated neurotoxicity. In mice, induced gut dysbiosis exacerbates neurologic damage impairing recovery after SCI. To date, there is not a cure for SCI, however new regenerative approaches are recently suggested. In rats, valproic acid administration after SCI protects motoneurons through modulation of apoptotic pathways. The microRNA-based therapy, manipulating the expression of specific microRNAs can activate or block target genes involved in neuro-regeneration; advances in CNS microRNA delivery technologies able to cross the spinal cord blood barrier have been reached. In SC injured rats, passive cycling exercises modulated microRNAs and gene transcription favouring biochemical and cellular restore, and potentially damage recovery. Then again, regarding microbiota, probiotic-induced eubiosis improves loco-motor recovery in mice. New nutraceuticals have also been demonstrated to help in neuro-regeneration and SCI recovery. This is the case of Naringin, curcumin epigallocathechin-3-gallate, omega-3 polyunsaturated fatty acid docosahexaenoic acid (DHA) that play anti-oxidant, anti-inflammatory and anti-apoptotic rules.

The aim of this paper was to describe exhaustively, but concisely, the matter of the health technology assessment. It is a method of evaluating health technologies based on principles and tools of Evidence Based Medicine. We started from etymology to speak about its definition and implementation methodology. Moreover we guide the reader throughout the constellation of international societies of health technology assessment and the meaning of their international cooperation. Finally, we deal with the health technology assessment as a tool being an integral part of the clinical governance process.

An integrated system for the multimedia management of images and clinical information has been developed at the Isituto Nazionale Neurologico C. Besta in Milan. The Institute physicians have the daily need of consulting images coming from various modalities. The high volume of archived material and the need of retrieving and displaying new and past images and clinical information has motivated the development of a Picture Archiving and Communication System (PACS) for the automatic management of images and clinical data, related not only to the Radiology Department, but also to the Radiotherapy Department for 3D virtual simulation, to remote teleconsulting, and in the following to all the wards, ambulatories and labs.

Obesity is now one of the most critical and demanding public health condition due to the correlation with many medical and psychological comorbidities, such as cardiovascular, orthopedic, pneumological, endocrinological, psychopathological complications, above all the type 2 diabetes. Obesity traditionally needs long and expensive treatments in a chronic care management approach. So clinical research has to develop, test and validate cheaper rehabilitation programs. For this reason, we developed the DIABESITY study, the design of a mHealth integrated platform to promote the empowerment of patients in self-monitoring and successfully managing their pathological conditions (focusing on obesity and type 2 diabetes) through the use of mobile devices. In this paper we report this study by discussing the following two important aspects of DIABESITY. (i) Dietary mHealth tools for home-patients; (ii) Measures to capture the psychological factors and processes which mediate change of behavior and affect initiation and maintenance phases.

Since 2001, in the Cystic Fibrosis Center of the Pediatric Hospital Bambino Gesù in Rome, we use telemedicine for monitoring of our patients. While in our first published works reporting this experience, we showed statistically significant reduction in hospital admissions and a tendency over time towards a better stability of the respiratory function for telehomecare (THC) patients, here we focus on the trend of the Forced Expiratory Volume in the first second (FEV1). In particular, we investigate the evolution of the clinical trend of the FEV1 index, by monitoring the activities of home patients from 2011 to 2014. THC is applied in addition to the standard therapeutic protocol by following 16 Cystic Fibrosis (CF) patients with specialized doctors. Our results show that THC patients improve their FEV1 values with a trend which can be considered significantly better than the one reported by the control group.

Chronic diseases and conditions typically require long-term monitoring and treatment protocols both in traditional settings and in out-patient frameworks. The economic burden of chronic conditions is a key challenge and new and mobile technologies could offer good solutions. mHealth could be considered an evolution of eHealth and could be defined as the practice of medicine and public health supported by mobile communication devices. mHealth approach could overcome limitations linked with the traditional, restricted, and highly expensive in-patient treatment of many chronic pathologies. Possible applications include stepped mHealth approach, where patients can be monitored and treated in their everyday contexts. Unfortunately, many barriers for the spread of mHealth are still present. Due the significant impact of psychosocial factors on disease evolution, psychotherapies have to be included into the chronic disease protocols. Existing psychological theories of health behavior change have to be adapted to the new technological contexts and requirements. In conclusion, clinical psychology and medicine have to face the “chronic care management” challenge in both traditional and mHealth settings.

Social media, online social networks and apps for smartphones and tablets are changing the way we communicate. According to a recent Pew Research Center survey, 73% of Internet users among US adults engage in social networking to access, create, and share contents (Duggan and Smith, 2013). The number of smartphone users is growing worldwide [56% of American adults are currently smartphone owners (Smith, 2013)], and millions of applications (most of them related to social media or other communication tools) are available on the Google Play or iTunes store. The increased prevalence of chronic (and non-communicable) diseases in high-income countries is today largely attributable to the convergence of an aging population with the persistence of several risk factors, including physical inactivity, use of tobacco and alcohol, high blood pressure and cholesterol, stress, depression, and overweight and obesity. Many of these risk factors can be mitigated by health interventions and education, and communication tools could support healthy lifestyle and behavior change. In the past years there was an increasing interest in the use of digital technologies to support these changes because they contribute to enhance levels of surveillance over behaviors and have the potential to provide acceptable and cost-effective interventions by transferring treatment, rehabilitation and prevention of a condition to self-care in the community (Castelnuovo et al., 2010). Social media and smartphone-based applications are now changing how people interact with the healthcare and public health systems (Santoro, 2013; Santoro and Quintaliani, 2013). The participatory, interactive nature of social media platforms allows for information to be generated and shared in a viral fashion, and provide new mechanisms to foster engagement and partnership with consumers, to change their behaviors and to fight against unhealthy lifestyles. More than 100,000 health related apps are also available in the market allowing people to record, track, and analyze vital signs and physical health data over time, to obtain feedback and general information about the disease they suffer from, and to receive alerts to remind them to take their medications or to measure their blood glucose levels. Due to their possible implications in public health a growing number of scientists suggests to incorporate social media and mobile health in health promotion and healthcare programs (Burke-Garcia and Scally, 2014).