Nurses and the acceptance of innovations in technology-intensive contexts: the need for tailored management strategies

BACKGROUND: Several technological innovations have been introduced in healthcare over the years, and their implementation proved crucial in addressing challenges of modern health. Healthcare workers have frequently been called upon to become familiar with technological innovations that pervade every aspect of their profession, changing their working schedule, habits, and daily actions. PURPOSE: An in-depth analysis of the paths towards the acceptance and use of technology may facilitate the crafting and adoption of specific personnel policies taking into consideration definite levers, which appear to be different in relation to the age of nurses. APPROACH: The strength of this study is the application of UTAUT model to analyse the acceptance of innovations by nurses in technology-intensive healthcare contexts. Multidimensional Item Response Theory is applied to identify the main dimensions characterizing the UTAUT model. Paths are tested through two stage regression models and validated using a SEM covariance analysis. RESULTS: The age is a moderator for the social influence: social influence, or peer opinion, matters more for young nurse. CONCLUSION: The use of MIRT to identify the most important items for each construct of UTAUT model and an in-depth path analysis helps to identify which factors should be considered a leverage to foster nurses' acceptance and intention to use new technologies (o technology-intensive devices). PRACTICAL IMPLICATIONS: Young nurses may benefit from the structuring of shifts with the most passionate colleagues (thus exploiting the social influence), the participation in ad hoc training courses (thus exploiting the facilitating conditions), while other nurses could benefit from policies that rely on the stressing of the perception of their expectations or the downsizing of their expectancy of the effort in using new technologies

NEW EVIDENCES OF TWO DIFFERENT KEY PATHOGENIC MECHANISMS IN HUNTINGTON'S DISEASE

Huntington\u2019s disease (HD) is an adult-onset neurodegenerative disorder characterized by several alterations in critical molecular and cellular pathways. Although genetic and experimental evidence has provided insights into HD pathogenesis, and many hypotheses concerning its underlying mechanisms have been proposed, a treatment that delays disease onset or slows its progression is still missing (Zuccato et al., 2010). During my PhD, my research activity was focused on the investigation of new aspects of two key pathogenic mechanisms of HD: i) the reduction of Brain-Derived Neurotrophic Factor (BDNF) and ii) the cholesterol dysfunction. Reduced BDNF levels have been described in a number of patho-physiological conditions, most notably, in HD. Since BDNF is also produced in blood, we have undertaken the measurement of its peripheral levels in the attempt to identify a possible link with HD prognosis and/or its progression. In the first part of my PhD, I evaluated BDNF level in 398 blood samples including 138 controls, 56 preHD, and 204 HD subjects. I found that BDNF protein levels were not reliably different between groups, whether measured in plasma (52 controls, 26 preHD, 105 HD) or serum (39 controls, 5 preHD, 29 HD). The analysis of the literature highlighted that intra-group variability and methodological aspects affect this measurement, especially in serum. Moreover during my PhD, I set up a novel strategy for mRNA normalization in quantitative real-time PCR that is based on expressed Alu repeat amplification as a measure for the mRNA fraction. I demonstrated that expressed Alu repeat amplification is a fast, accurate normalization tool that can be successfully used for quantification of selected mRNA in the human transcriptome. This result is particularly important for clinical diagnosis and biomarker validation studies based on mRNA detection in human blood. Based on this new normalization method, I measured BDNF mRNA levels in blood samples from 47 controls, 25 preHD, and 70 HD subjects, and found no differences among the groups. These results indicated that levels of BDNF in human blood were not informative (mRNA levels or plasma protein level) nor reliable (serum protein levels) as HD biomarkers. Brain cholesterol, which is synthesized locally, is a major component of myelin and cell membranes and participates in several neuronal activities, such as neurite outgrowth and synaptogenesis. In post-natal life, the cholesterol-dependent activities of neurons mainly rely on the transport of cholesterol from astrocytes on ApoE-containing lipoproteins. Mounting evidence indicates that reduced cholesterol biosynthesis occurs in the brain of several models of Huntington\u2019s disease (HD) and is manifest in astrocytes (Valenza et al., J. Neurosci 2010). However, how mutation in huntingtin elicits changes in cholesterol biosynthesis pathway is still unknown. In the second part of my thesis, I explored the cross-talk between neurons and astrocytes to determine whether reduced cholesterol biosynthesis/secretion by HD astrocytes influences cholesterol-dependent properties in wt (and HD) neurons, such as neurite outgrowth and synaptic vesicles formation/maintenance. Primary neurons and astrocytes expressing normal and mutant huntingtin have been used in different experimental settings, in order to evaluate i) the influence of cell non-autonomous mechanisms involving defective cholesterol synthesis/secretion by astrocytes bearing mutant htt and how this dysfunction affects networks and cholesterol-dependent properties of neurons that undergo degeneration in HD; ii) exploring the underlying molecular mechanism of the cholesterol biosynthesis dysfunction in HD astrocytes to identify potential targets of intervention from therapeutic standpoints. I show that glial-derived medium from wt astrocytes (GCMwt) and cholesterol administration improve neurite outgrowth and synaptic properties in wt and HD neurons. The same parameters are not increased after administration of GCM from primary HD astrocytes (GCMHD) or GCMwt depleted of lipoproteins. These findings support the hypothesis that non-cell autonomous mechanisms related to cholesterol and involving astrocytes may contribute to HD pathogenesis. Strategies aimed at selectively modulating brain cholesterol metabolism might be of impact in HD

DBS-Based Eutectogels: Organized Vessels to Perform the Michael Addition Reaction**

Supramolecular eutectogels were obtained from the gelation of 1,3 : 2,4-dibenzylidene-D-sorbitol (DBS) in cholinium chloride-based deep eutectic solvents (DES), differing for the nature of the hydrogen bond donor. Ethylene glycol, diethylene glycol, triethylene glycol, glycerol and urea were tested. Soft materials were fully characterized, determining critical gelation concentration, gel-sol transition temperatures and mechanical properties. Furthermore, to have information about the organization of the gelator in the tridimensional network, resonance light scattering, circular dichroism and microscopy investigations were performed. Eutectogels were used as organized “vessels” to perform the L-proline catalyzed Michael addition reaction. The probe reaction was carried out in gel phase and in DES solution. Data collected shed light on the effect that gel microenvironment exerts on the outcome of the reaction. In general, gel phases allowed having comparable or even better results than the ones collected in DES solution, with better results obtained in soft materials with the highest organization, as accounted for by the presence of larger aggregates and the occurrence of stronger intermolecular interactions. In turn, this accounts also for the effect of substrates structure that indicates that better yields could be obtained in the presence of more flexible nucleophile and dienones, having more extended π-surface

Observing The Mediterranean Sea from space: 21 years of Pathfinder-AVHRR Sea Surface Temperatures (1985 to 2005). Re-analysis and validation

International audienceThe time series of satellite infrared AVHRR data from 1985 to 2005 has been used to produce a daily series of optimally interpolated SST maps over the regular grid of the operational MFSTEP OGCM model of the Mediterranean basin. A complete validation of this OISST (Optimally Interpolated Sea Surface Temperature) product with in situ measurements has been performed in order to exclude any possibility of spurious trends due to instrumental calibration errors/shifts or algorithms malfunctioning related to local geophysical factors. The validation showed that satellite OISST is able to reproduce in situ measurements with a mean bias of less than 0.1°C and RMSE of about 0.5°C and that errors do not drift with time or with the percent interpolation error

Spatio-temporal variability of micro-, nano- and pico-phytoplankton in the Mediterranean Sea from satellite ocean colour data of SeaWiFS

Abstract. The seasonal and year-to-year variability of the phytoplankton size class (PSC) spatial distribution has been examined in the Mediterranean Sea by using the entire time series of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) space observations (1998–2010). Daily maps of PSCs have been determined using an empirical model based on a synoptic relationship between surface chlorophyll a and diagnostic pigments referred to different taxonomic groups. The analysis of micro-, nano- and pico-phytoplankton satellite time series (1998–2010) describes, quantitatively, the algal assemblage structure over the basin and reveals that the main contribution to chlorophyll a in most of the Mediterranean Sea comes from the pico-phytoplankton component, especially in nutrient-poor environments. Regions with different and peculiar features are the Northwestern Mediterranean Sea, the Alborán Sea and several coastal areas, such as the North Adriatic Sea. In these areas, local interactions between physical and biological components modulate the composition of the three phytoplankton size classes. It results that, during the spring bloom season, micro-phytoplankton dominates in areas of intense vertical winter mixing and deep/intermediate water formation, while in coastal areas micro-phytoplankton dominates in all seasons because of the nutrient supply from the terrestrial inputs. In the Alborán Sea, where the Atlantic inflow modulates the nutrient availability, any predominance of one class over the other two has been observed. The nano-phytoplankton component instead remains widespread over the entire basin along the year, and its contribution to chlorophyll a is of the order of 30–40 %. The largest inter-annual signal occurs in the Northwestern Mediterranean Sea, driven by the year-to-year variation in intensity and extension of the spring bloom, followed by the Alborán Sea, in which the inter-annual variability is strongly modulated by the Atlantic inflow. In absence of sufficient in situ data of community composition, the satellite-based analysis demonstrated that pico-, nano- and micro-phytoplankton classes often coexist. The predominance of one group over the other ones is strongly dependent on the physical and biological processes occurring at the mesoscale. These processes directly influence the nutrient and light availability, which are the principal forcing for the algae growth

Stochastic Coherence Over Attention Trajectory For Continuous Learning In Video Streams

Devising intelligent agents able to live in an environment and learn by observing the surroundings is a longstanding goal of Artificial Intelligence. From a bare Machine Learning perspective, challenges arise when the agent is prevented from leveraging large fully-annotated dataset, but rather the interactions with supervisory signals are sparsely distributed over space and time. This paper proposes a novel neural-network-based approach to progressively and autonomously develop pixel-wise representations in a video stream. The proposed method is based on a human-like attention mechanism that allows the agent to learn by observing what is moving in the attended locations. Spatio-temporal stochastic coherence along the attention trajectory, paired with a contrastive term, leads to an unsupervised learning criterion that naturally copes with the considered setting. Differently from most existing works, the learned representations are used in open-set class-incremental classification of each frame pixel, relying on few supervisions. Our experiments leverage 3D virtual environments and they show that the proposed agents can learn to distinguish objects just by observing the video stream. Inheriting features from state-of-the art models is not as powerful as one might expect

Biochar Particles Obtained from Agricultural Carob Waste as a Suitable Filler for Sustainable Biocomposite Formulations

In the context of sustainable and circular economy, the recovery of biowaste for sustainable biocomposites formulation is a challenging issue. The aim of this work is to give a new life to agricultural carob waste after glucose extraction carried out by a local factory for carob candy production. A pyrolysis process was carried out on bio-waste to produce biofuel and, later, the solid residual fraction of pyrolysis process was used as interesting filler for biocomposites production. In this work, biochar particles (BC) as a pyrolysis product, after fuels recovery of organic biowaste, specifically, pyrolyzed carobs after glucose extraction, were added on poly(butylene-adipate-co-terephthalate), (PBAT), at two different concentrations, i.e., 10 and 20 wt%. The BC have been produced using three pyrolysis processing temperatures (i.e., 280, 340 and 400 degrees C) to optimize the compositions of produced solid fractions and biofuels. The resulting particles from the pyrolysis process (BC280, BC340 and BC400) were considered as suitable fillers for PBAT. Firstly, the BC particles properties were characterized by elemental composition and spectroscopy analysis, particle size measurements and evaluation of radical scavenging activity and efficiency. Moreover, PBAT/BC composites were subjected to analysis of their rheological and thermal behavior, morphologies and mechanical properties. In addition, accelerated weathering, monitored by both tensile test and spectroscopic analysis, was carried out, and obtained results show that the biochar particles can exert a beneficial effect on photo-oxidation delay of PBAT matrix

Insights about the ability of folate based supramolecular gels to act as targeted therapeutic agents

With the aim to obtain targeted chemotherapeutic agents, imidazolium and ammonium-based folate salts were synthesized. Their photophysical behavior was investigated both in buffer and buffer/DMSO solution as well as in solid phase, performing UV-vis and fluorescence investigations. Properties of the aggregates were also analyzed by dynamic light scattering. Gelation ability of the salts was analyzed in biocompatible solvents, and gel phases obtained were characterized by determining critical gelation concentrations and gel-solution transition temperatures. Insights about gelator interactions in the tridimensional network were also gained performing ATR-FTIR investigation. Properties of soft materials were further analyzed performing rheology measurements, scanning electron microscopy, fluorescence and resonance light scattering investigations. Antiproliferative activity of organic salts was tested towards two breast cancer cell lines, expressing different levels of folate receptor, namely MDA-MB-231 and MCF-7, and a normal epithelial cell line, like h-TER T-RPE-1, by using MTT assay. Dichlodihydrofluorescein acetate test was performed to verify the role of oxidative stress in cell death. Finally, antiproliferative activity was also evaluated in gel phase, to verify if salts were able to retain biological activity also after the entrapment in the gelatinous network. Results collected evidence that folate based organic salts were able to behave as targeted chemotherapeutic agents both in solution and gel phase, showing uptake mechanism and selectivity indexes that depend on both cancer cell line nature and salt structure

An International Survey on Taking Up a Career in Cardiovascular Research: Opportunities and Biases toward Would-Be Physician-Scientists

Background Cardiovascular research is the main shaper of clinical evidence underpinning decision making, with its cyclic progression of junior researchers to mature faculty members. Despite efforts at improving cardiovascular research training, several unmet needs persist. We aimed to appraise current perceptions on cardiovascular research training with an international survey. Methods and Results We administered a 20-closed-question survey to mentors and mentees belonging to different international institutions. A total of 247 (12%) surveys were available (out of 2,000 invitations). Overall, mentees and mentors were reasonably satisfied with the educational and research resources. Significant differences were found analyzing results according to gender, geographic area, training and full-time researcher status. Specifically, women proved significantly less satisfied than men, disclosed access to fewer resources and less support from mentors (all P Conclusions Several potential biases appear to be present in the way training in cardiovascular research is provided worldwide, including one against women. If confirmed, these data require proactive measures to decrease discriminations and improve the cardiovascular research training quality