Opening the Black Box: Explaining the Process of Basing a Health Recommender System on the I-Change Behavioral Change Model

Recommender systems are gaining traction in healthcare because they can tailor recommendations based on users' feedback concerning their appreciation of previous health-related messages. However, recommender systems are often not grounded in behavioral change theories, which may further increase the effectiveness of their recommendations. This paper's objective is to describe principles for designing and developing a health recommender system grounded in the I-Change behavioral change model that shall be implemented through a mobile app for a smoking cessation support clinical trial. We built upon an existing smoking cessation health recommender system that delivered motivational messages through a mobile app. A group of experts assessed how the system may be improved to address the behavioral change determinants of the I-Change behavioral change model. The resulting system features a hybrid recommender algorithm for computer tailoring smoking cessation messages. A total of 331 different motivational messages were designed using 10 health communication methods. The algorithm was designed to match 58 message characteristics to each user pro le by following the principles of the I-Change model and maintaining the bene ts of the recommender system algorithms. The mobile app resulted in a streamlined version that aimed to improve the user experience, and this system's design bridges the gap between health recommender systems and the use of behavioral change theories. This article presents a novel approach integrating recommender system technology, health behavior technology, and computer-tailored technology. Future researchers will be able to build upon the principles applied in this case study.European Union's Horizon 2020 Research and Innovation Programme under Grant 68112

Early Science with the Large Millimetre Telescope: Molecules in the Extreme Outflow of a proto-Planetary Nebula

Extremely high velocity emission likely related to jets is known to occur in some proto-Planetary Nebulae. However, the molecular complexity of this kinematic component is largely unknown. We observed the known extreme outflow from the proto-Planetary Nebula IRAS 16342-3814, a prototype water fountain, in the full frequency range from 73 to 111 GHz with the RSR receiver on the Large Millimetre Telescope. We detected the molecules SiO, HCN, SO, and $^{13}$CO. All molecular transitions, with the exception of the latter are detected for the first time in this source, and all present emission with velocities up to a few hundred km s$^{-1}$. IRAS 16342-3814 is therefore the only source of this kind presenting extreme outflow activity simultaneously in all these molecules, with SO and SiO emission showing the highest velocities found of these species in proto-Planetary Nebulae. To be confirmed is a tentative weak SO component with a FWHM $\sim$ 700 km s$^{-1}$. The extreme outflow gas consists of dense gas (n$_{\rm H_2} >$ 10$^{4.8}$--10$^{5.7}$ cm$^{-3}$), with a mass larger than $\sim$ 0.02--0.15 M$_{\odot}$. The relatively high abundances of SiO and SO may be an indication of an oxygen-rich extreme high velocity gas.Comment: Accepted for publication in Monthly Notices of the Royal Astronomical Society Letter

A personalized intervention to prevent depression in primary care based on risk predictive algorithms and decision support systems: protocol of the e-predictD study

The predictD is an intervention implemented by general practitioners (GPs) to prevent depression, which reduced the incidence of depression-anxiety and was cost-effective. The e-predictD study aims to design, develop, and evaluate an evolved predictD intervention to prevent the onset of major depression in primary care based on Information and Communication Technologies, predictive risk algorithms, decision support systems (DSSs), and personalized prevention plans (PPPs). A multicenter cluster randomized trial with GPs randomly assigned to the e-predictD intervention + care-as-usual (CAU) group or the active-control + CAU group and 1-year follow-up is being conducted. The required sample size is 720 non-depressed patients (aged 18–55 years), with moderate-to-high depression risk, under the care of 72 GPs in six Spanish cities. The GPs assigned to the e-predictD-intervention group receive brief training, and those assigned to the control group do not. Recruited patients of the GPs allocated to the e-predictD group download the e-predictD app, which incorporates validated risk algorithms to predict depression, monitoring systems, and DSSs. Integrating all inputs, the DSS automatically proposes to the patients a PPP for depression based on eight intervention modules: physical exercise, social relationships, improving sleep, problem-solving, communication skills, decision-making, assertiveness, and working with thoughts. This PPP is discussed in a 15-min semi-structured GP-patient interview. Patients then choose one or more of the intervention modules proposed by the DSS to be self-implemented over the next 3 months. This process will be reformulated at 3, 6, and 9 months but without the GP–patient interview. Recruited patients of the GPs allocated to the control-group+CAU download another version of the e-predictD app, but the only intervention that they receive via the app is weekly brief psychoeducational messages (active-control group). The primary outcome is the cumulative incidence of major depression measured by the Composite International Diagnostic Interview at 6 and 12 months. Other outcomes include depressive symptoms (PHQ-9) and anxiety symptoms (GAD-7), depression risk (predictD risk algorithm), mental and physical quality of life (SF-12), and acceptability and satisfaction (‘e-Health Impact' questionnaire) with the intervention. Patients are evaluated at baseline and 3, 6, 9, and 12 months. An economic evaluation will also be performed (cost-effectiveness and cost-utility analysis) from two perspectives, societal and health systems.Trial registrationClinicalTrials.gov, identifier: NCT03990792

Understanding structure-activity relationships in highly active La promoted Ni catalysts for CO₂ methanation

Ni-based catalysts are selective in the hydrogenation of CO_{2} to CH_{4} but their activity and stability need improvement. Herein, we propose a hydrotalcite-derived high loaded Ni-Al_{2}O_{3} catalyst promoted by La. The effect of La on the catalyst properties is investigated and compared with that of Y and Ce. The NiO_{x} rystallite size and basic properties (rather than the nickel reducibility) as well as the catalytic activity depend on the rare-earth element. The La-catalyst achieves a more relevant activity enhancement at low temperature and high space velocity (480 L g^{-1} h^{-1}, CO_{2}/H_{2}/N_{2} = 1/4/1 v/v), high CH_{4} productivity (101 L_{CH4} gNi^{-1} h^{-1}) and stability, even under undiluted feeds. In situ DRIFTS and the characterization of spent catalysts confirm that this enhanced performance is related to the combination of dissociative and associative CO_{2} activation on more reduced, highly dispersed and stable Ni nanoparticles and basic sites in the La_{2}O_{3}-Al_{2}O_{3} matrix, respectively

Variation in Competence for ZIKV Transmission by Aedes aegypti and Aedes albopictus in Mexico

BACKGROUND: ZIKV is a new addition to the arboviruses circulating in the New World, with more than 1 million cases since its introduction in 2015. A growing number of studies have reported vector competence (VC) of Aedes mosquitoes from several areas of the world for ZIKV transmission. Some studies have used New World mosquitoes from disparate regions and concluded that these have a variable but relatively low competence for the Asian lineage of ZIKV. METHODOLOGY/PRINCIPAL FINDINGS: Ten Aedes aegypti (L) and three Ae. albopictus (Skuse) collections made in 2016 from throughout Mexico were analyzed for ZIKV (PRVABC59-Asian lineage) VC. Mexican Ae. aegypti had high rates of midgut infection (MIR), dissemination (DIR) and salivary gland infection (SGIR) but low to moderate transmission rates (TR). It is unclear whether this low TR was due to heritable salivary gland escape barriers or to underestimating the amount of virus in saliva due to the loss of virus during filtering and random losses on surfaces when working with small volumes. VC varied among collections, geographic regions and whether the collection was made north or south of the Neovolcanic axis (NVA). The four rates were consistently lower in northeastern Mexico, highest in collections along the Pacific coast and intermediate in the Yucatan. All rates were lowest north of the NVA. It was difficult to assess VC in Ae. albopictus because rates varied depending upon the number of generations in the laboratory. CONCLUSIONS/SIGNIFICANCE: Mexican Ae. aegypti and Ae. albopictus are competent vectors of ZIKV. There is however large variance in vector competence among geographic sites and regions. At 14 days post infection, TR varied from 8-51% in Ae. aegypti and from 2-26% in Ae. albopictus

Parasitism by the Endoparasitoid, Cotesia flavipes Induces Cellular Immunosuppression and Enhances Susceptibility of the Sugar Cane Borer, Diatraea saccharalis to Bacillus thuringiensis

Cotesia flavipes Cameron (Hymenoptera: Braconidae), is a gregarious larval endoparasitoid of the sugarcane borer, Diatraea saccharalis Fabricius (Lepidoptera: Crambidae). The aim of this research was to analyze cellular immunosuppression of D. saccharalis parasitized by C. flavipes in terms of encapsulation, melanization, and hemocyte nodule formation. The encapsulation assay was done 1 and 6 days after parasitoid oviposition. In addition, the susceptibility of parasitized and nonparasitzed larvae to Bacillus thuringiensis HD 73 strain was assessed. 3, 12, and 24 h after bead injection; the percentages of encapsulation were significantly higher in unparasitized larvae compared to larvae parasitized 1 and 6 days after oviposition. Interestingly, there was a significant reduction in numbers of beads encapsulated at 1 day after oviposition compared to 6 days, and unparasitized larvae. The percentage of melanized beads decreased significantly in parasitized larvae compared to control. There was a reduction in the number of nodules in parasitized larvae compared to unparasitized controls. Larvae that were injected with polyndavirus 24 h before beads were injected showed significantly reduced encapsulation responses relative to control larvae. The D. saccharalis parasitized by C. flavipes exhibited higher susceptibility to B. thuringiensis. These results suggest that parasitization induced host immunosuppression, and the immunosuppression factors could impair the defense capacity against microbial pathogens - causing an increase in pathogen susceptibility

Insights into the pathological mechanisms of p85α mutations using a yeast-based phosphatidylinositol 3-kinase model

In higher eukaryotes, cell proliferation is regulated by class I phosphatidylinositol 3-kinase (PI3K), which transduces stimuli received from neighboring receptors by local generation of PtdIns(3,4,5)P 3 in cellular membranes. PI3K is a heterodimeric protein consisting of a regulatory and a catalytic subunit (p85 and p110 respectively). Heterologous expression of p110α in Saccharomyces cerevisiae leads to toxicity by conversion of essential PtdIns(4,5)P 2 into futile PtdIns(3,4,5)P 3 , providing a humanized yeast model for functional studies on this pathway. Here, we report expression and functional characterization in yeast of all regulatory and catalytic human PI3K isoforms, and exploitation of the most suitable setting to functionally assay panels of tumor-and germ line-associated PI3K mutations, with indications to the limits of the system. The activity of p110α in yeast was not compromised by truncation of its N-terminal adaptor-binding domain (ABD) or inactivation of the Ras-binding domain (RBD). In contrast, a cluster of positively charged residues at the C2 domain was essential. Expression of a membrane-driven p65α oncogenic-truncated version of p85α, but not the full-length protein, led to enhanced activity of α, β, and δ p110 isoforms. Mutations impairing the inhibitory regulation exerted by the p85α iSH2 domain on the C2 domain of p110α yielded the latter non-responsive to negative regulation, thus reproducing this oncogenic mechanism in yeast. However, p85α germ line mutations associated with short stature, hyperextensibility of joints and/or inguinal hernia, ocular depression, Rieger anomaly, and teething delay (SHORT) syndrome did not increase PI3K activity in this model, supporting the idea that SHORT syndrome-associated p85α mutations operate through mechanisms different from the canonical disruption of inhibitory p85-p110 interactions typical of cancer

A personalized intervention to prevent depression in primary care based on risk predictive algorithms and decision support systems: protocol of the e-predictD study

The predictD is an intervention implemented by general practitioners (GPs) to prevent depression, which reduced the incidence of depression-anxiety and was cost-effective. The e-predictD study aims to design, develop, and evaluate an evolved predictD intervention to prevent the onset of major depression in primary care based on Information and Communication Technologies, predictive risk algorithms, decision support systems (DSSs), and personalized prevention plans (PPPs). A multicenter cluster randomized trial with GPs randomly assigned to the e-predictD intervention + care-as-usual (CAU) group or the active-control + CAU group and 1-year follow-up is being conducted. The required sample size is 720 non-depressed patients (aged 18–55 years), with moderate-to-high depression risk, under the care of 72 GPs in six Spanish cities. The GPs assigned to the e-predictD-intervention group receive brief training, and those assigned to the control group do not. Recruited patients of the GPs allocated to the e-predictD group download the e-predictD app, which incorporates validated risk algorithms to predict depression, monitoring systems, and DSSs. Integrating all inputs, the DSS automatically proposes to the patients a PPP for depression based on eight intervention modules: physical exercise, social relationships, improving sleep, problem-solving, communication skills, decision-making, assertiveness, and working with thoughts. This PPP is discussed in a 15-min semi-structured GP-patient interview. Patients then choose one or more of the intervention modules proposed by the DSS to be self-implemented over the next 3 months. This process will be reformulated at 3, 6, and 9 months but without the GP–patient interview. Recruited patients of the GPs allocated to the control-group+CAU download another version of the e-predictD app, but the only intervention that they receive via the app is weekly brief psychoeducational messages (active-control group). The primary outcome is the cumulative incidence of major depression measured by the Composite International Diagnostic Interview at 6 and 12 months. Other outcomes include depressive symptoms (PHQ-9) and anxiety symptoms (GAD-7), depression risk (predictD risk algorithm), mental and physical quality of life (SF-12), and acceptability and satisfaction (‘e-Health Impact' questionnaire) with the intervention. Patients are evaluated at baseline and 3, 6, 9, and 12 months. An economic evaluation will also be performed (cost-effectiveness and cost-utility analysis) from two perspectives, societal and health systems.Trial registrationClinicalTrials.gov, identifier: NCT03990792

Towards a new quality-controlled daily climate dataset for the Pyrenees, 1950-2015

Póster presentado en: EMS Annual Meeting: European Conference for Applied Meteorology and Climatology celebrado del 4 al 8 de septiembre de 2017 en Dublin, IrlandaPrevious works using lower-density datasets addressed warming rates with slight differences depending on the season and diffuse trends for precipitation. New and more accurate results in spatio-temporal variations of these climate variables are expected on behalf the development of the CLIM’PY project, which aims to: i) detect past trends with instrumental data and, ii) estimate future behaviours in climatic variables based on projected scenarios. Temperature, precipitation and snow cover in the Pyrenees will be analysed within the framework of the project. In this communication, we present the methodology we will follow to conduct the quality control analysis of daily temperature and precipitation, which will include 673 stations of Spain, France and Andorra, covering the period 1950-2015