Mobile customer relationship management : An explorative investigation of the italian consumer market

Mobile customer relationship management (CRM) services seem to have all the characteristics commonly associated with successful mobile services and have accordingly been predicted to be among the most promising. However, real development of this sector has not been well explored so far, especially in relation to the actual supply of mobile CRM services to the public. The purpose of this paper is to reduce this gap by giving a first snapshot of the current development of the supply of mobile CRM services to consumers taken in the context of the Italian market. In order to do so, it firstly proposes a conceptual framework indicating the relevant aspects to investigate for assessing this kind of environments: the market, value propositions, actors and issues. Then it applies this framework to get an overview of the supply of mobile CRM services in Italy and provides some empirical insight about its current development obtained through an exhaustive survey of the current supply of 750 services from 353 firms

Relapse of Human Chorionic Gonadotropin-Induced Hyperthyroidism and Severe Hyperemesis Gravidarum Secondary to Twin-Twin Transfusion Syndrome, With Rapid Recovery Following Fetoscopic Laser Coagulation: Case Report.

Limited data have shown that, compared to uncomplicated twin pregnancies, pregnancies complicated by twin-twin transfusion syndrome (TTTS), a life-threatening condition, are associated with higher maternal serum levels of both human chorionic gonadotropin (hCG) and thyroid hormones. With the continuing expansion of assisted reproductive technologies, the rate of twin pregnancies, including those complicated by TTTS and associated hyperemesis gravidarum, is expected to increase further. Therefore, detailed descriptions of the maternal and fetal clinical outcomes of maternal thyrotoxicosis linked to TTTS can be useful for timely diagnosis and management. However, such descriptions are currently lacking in the literature. We report the case of a 30-year-old woman carrying a monochorionic twin pregnancy complicated by TTTS that induced a relapse of severe hyperemesis gravidarum with overt non-autoimmune hyperthyroidism at 17 weeks of gestation. Following fetoscopic laser coagulation (FLC), both hyperemesis and hyperthyroidism improved within 1 week. The present experience contributes to the knowledge base on maternal thyrotoxicosis linked to TTTS and can be useful in the diagnosis and treatment of future cases; it also emphasizes the need for a high degree of clinical suspicion and for close collaboration between endocrinologists and obstetricians. Another key point is that TTTS-associated hyperemesis gravidarum and maternal hyperthyroidism should be considered in the differential diagnosis of refractory or relapsing hyperemesis gravidarum in women with monochorionic twin pregnancy, because this condition may require more stringent supportive treatment before and during the FLC procedure when the mother is overtly hyperthyroid

Mechanistic within-host models of the asexual; Plasmodium falciparum; infection: a review and analytical assessment

BACKGROUND: Malaria blood-stage infection length and intensity are important drivers of disease and transmission; however, the underlying mechanisms of parasite growth and the host's immune response during infection remain largely unknown. Over the last 30 years, several mechanistic mathematical models of malaria parasite within-host dynamics have been published and used in malaria transmission models. METHODS: Mechanistic within-host models of parasite dynamics were identified through a review of published literature. For a subset of these, model code was reproduced and descriptive statistics compared between the models using fitted data. Through simulation and model analysis, key features of the models were compared, including assumptions on growth, immune response components, variant switching mechanisms, and inter-individual variability. RESULTS: The assessed within-host malaria models generally replicate infection dynamics in malaria-naive individuals. However, there are substantial differences between the model dynamics after disease onset, and models do not always reproduce late infection parasitaemia data used for calibration of the within host infections. Models have attempted to capture the considerable variability in parasite dynamics between individuals by including stochastic parasite multiplication rates; variant switching dynamics leading to immune escape; variable effects of the host immune responses; or via probabilistic events. For models that capture realistic length of infections, model representations of innate immunity explain early peaks in infection density that cause clinical symptoms, and model representations of antibody immune responses control the length of infection. Models differed in their assumptions concerning variant switching dynamics, reflecting uncertainty in the underlying mechanisms of variant switching revealed by recent clinical data during early infection. Overall, given the scarce availability of the biological evidence there is limited support for complex models. CONCLUSIONS: This study suggests that much of the inter-individual variability observed in clinical malaria infections has traditionally been attributed in models to random variability, rather than mechanistic disease dynamics. Thus, it is proposed that newly developed models should assume simple immune dynamics that minimally capture mechanistic understandings and avoid over-parameterization and large stochasticity which inaccurately represent unknown disease mechanisms

Mass campaigns combining antimalarial drugs and anti-infective vaccines as seasonal interventions for malaria control, elimination and prevention of resurgence: a modelling study

The only licensed malaria vaccine, RTS,S/AS01, has been developed for morbidity-control in young children. The potential impact on transmission of deploying such anti-infective vaccines to wider age ranges, possibly with co-administration of antimalarial treatment, is unknown. Combinations of existing malaria interventions is becoming increasingly important as evidence mounts that progress on reducing malaria incidence is stalling and threatened by resistance.; Malaria transmission and intervention dynamics were simulated using OpenMalaria, an individual-based simulation model of malaria transmission, by considering a seasonal transmission setting and by varying epidemiological and setting parameters such as transmission intensity, case management, intervention types and intervention coverages. Chemopreventive drugs and anti-infective vaccine efficacy profiles were based on previous studies in which model parameters were fitted to clinical trial data. These intervention properties were used to evaluate the potential of seasonal mass applications of preventative anti-infective malaria vaccines, alone or in combination with chemoprevention, to reduce malaria transmission, prevent resurgence, and/or reach transmission interruption.; Deploying a vaccine to all ages on its own is a less effective intervention strategy compared to chemoprevention alone. However, vaccines combined with drugs are likely to achieve dramatic prevalence reductions and in few settings, transmission interruption. The combined mass intervention will result in lower prevalence following the intervention compared to chemoprevention alone and will increase chances of interruption of transmission resulting from a synergistic effect between both interventions. The combination of vaccine and drug increases the time before transmission resurges after mass interventions cease compared to mass treatment alone. Deploying vaccines and drugs together requires fewer rounds of mass intervention and fewer years of intervention to achieve the same public health impact as chemoprevention alone.; Through simulations we identified a previously unidentified value of deploying vaccines with drugs, namely the greatest benefit will be in preventing and delaying transmission resurgence for longer periods than with other human targeted interventions. This is suggesting a potential role for deploying vaccines alongside drugs in transmission foci as part of surveillance-response strategies

Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

BACKGROUND: Substantial research is underway to develop next-generation interventions that address current malaria control challenges. As there is limited testing in their early development, it is difficult to predefine intervention properties such as efficacy that achieve target health goals, and therefore challenging to prioritize selection of novel candidate interventions. Here, we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning. Our analysis identifies requirements of efficacy, coverage, and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence. METHODS: A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational, health-system, population, and disease characteristics. Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications. We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals. RESULTS: We apply our approach to five malaria interventions under development. Aiming for malaria prevalence reduction, we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals. While coverage is generally identified as the largest driver of impact, higher efficacy, longer protection duration or multiple deployments per year are needed to increase prevalence reduction. We show that interventions on multiple parasite or vector targets, as well as combinations the new interventions with drug treatment, lead to significant burden reductions and lower efficacy or duration requirements. CONCLUSIONS: Our approach uses disease dynamic models and machine learning to support decision-making and resource investment, facilitating development of new malaria interventions. By evaluating the intervention capabilities in relation to the targeted health goal, our analysis allows prioritization of interventions and of their specifications from an early stage in development, and subsequent investments to be channeled cost-effectively towards impact maximization. This study highlights the role of mathematical models to support intervention development. Although we focus on five malaria interventions, the analysis is generalizable to other new malaria interventions

Phthalates: Potential sources and control measures

The issue of endocrine disruptors is a subject of debate in the agri-food sector and questioning for consumers through the media. Among these compounds, some of the family of phthalates, are used in the composition of some materials used in wineries. This makes it a worrying issue in terms of image and safety. The objective ok this work was to identify the sources of phthalates and the factors favoring their diffusion in wines to propose preventive and curative solutions to the wine makers. The modalities were therefore selected in different French wine regions to represent the diversity of oenological practices. This survey also led to examine more thoroughly the parameters involved in the situations that favored migration of the highest levels. Additional experiments were performed specifically on certain sources or contributing factors. The first identified sources include epoxy resin, fiberglass reinforced polyester as well as PVC materials (pipes …). Favorable factors include alcohol content, temperature, duration and contact area