A Bioinspired Fluid-Filled Soft Linear Actuator

In bioinspired soft robotics, very few studies have focused on fluidic transmissions and there is an urgent need for translating fluidic concepts into realizable fluidic components to be applied in different fields. Nature has often offered an inspiring reference to design new efficient devices. Inspired by the working principle of a marine worm, the sipunculid species Phascolosoma stephensoni (Sipunculidae, Annelida), a soft linear fluidic actuator is here presented. The natural hydrostatic skeleton combined with muscle activity enables these organisms to protrude a part of their body to explore the surrounding. Looking at the hydrostatic skeleton and protrusion mechanism of sipunculids, our solution is based on a twofold fluidic component, exploiting the advantages of both pneumatic and hydraulic actuations and providing a novel fluidic transmission mechanism. The inflation of a soft pneumatic chamber is associated with the stretch of an inner hydraulic chamber due to the incompressibility of the liquid. Actuator stretch and forces have been characterized to determine system performance. In addition, an analytical model has been derived to relate the stretch ability to the inlet pressure. Three different sizes of prototypes were tested to evaluate the suitability of the proposed design for miniaturization. The proposed actuator features a strain equal to 40–50% of its initial length—depending on size—and output forces up to 18 N in the largest prototypes. The proposed bioinspired actuator expands the design of fluidic actuators and can pave the way for new approaches in soft robotics with potential application in the medical field

Relationship between Pre-Implant Interleukin-6 Levels, Inflammatory Response, and Early Outcome in Patients Supported by Left Ventricular Assist Device: A Prospective Study

Purpose: The immune response is crucial in the development of multi-organ failure (MOF) and complications in end-stage heart failure patients supported by left ventricular assist device (LVAD). However, at pre-implant, the association between inflammatory state and post-LVAD outcome is not yet clarified. Aim of the study was to assess the relationship among preimplant levels of immune-related cytokines, postoperative inflammatory response and 3-month outcome in LVAD-patients. Methods: In 41 patients undergoing LVAD implantation, plasma levels of interleukin (IL)-6, IL-8, crucial for monocyte modulation, and urine neopterin/creatinine ratio (Neo/Cr), marker of monocyte activation, were assessed preoperatively, at 3 days, 1 and 4 weeks post-LVAD. MOF was evaluated by total sequential organ failure assessment (tSOFA) score. Intensive care unit (ICU)-death and/or post-LVAD tSOFA $11 was considered as main adverse outcome. Length of ICU-stay, 1 weektSOFA score, hospitalisation and 3-month survival were considered additional end-points. Results: During ICU-stay, 8 patients died of MOF, while 8 of the survivors experienced severe MOF with postoperative tSOFA score$11. Pre-implant level of IL-6 $ 8.3 pg/mL was identified as significant marker of discrimination between patients with or without adverse outcome (OR 6.642, 95% CI 1.201-36.509, p = 0.030). Patients were divided according to pre-implant IL-6 cutoff of 8.3 pg/ml in A [3.5 (1.2-6.1) pg/mL] and B [24.6 (16.4-38.0) pg/mL] groups. Among pre-implant variables, only white blood cells count was independently associated with pre-implant IL-6 levels higher than 8.3 pg/ml (OR 1.491, 95% CI 1.004-2.217, p = 0.048). The ICU-stay and hospitalisation resulted longer in B-group (p = 0.001 and p = 0.030, respectively). Postoperatively, 1 week-tSOFA score, IL-8 and Neo/Cr levels were higher in B-group. Conclusions: LVAD-candidates with elevated pre-implant levels of IL-6 are associated, after intervention, to higher release of monocyte activation related-markers, a clue for the development of MOF, longer clinical course and poor outcome

Unintentional injuries and potential determinants of falls in young children: Results from the Piccolipiù Italian birth cohort

Objectives: Unintentional injuries such as falls, are particularly frequent in early childhood. To date, epidemiological studies in this field have been carried out using routine data sources or registries and many studies were observational studies with a cross-sectional design. The aims of the study are to describe unintentional injuries in the first two years of life in the Piccolipiù birth cohort, and to investigate the association between mother and children characteristics and the First Event of Raised surface Fall (FERF). Methods: This longitudinal observational study included 3038 children from an Italian birth cohort. Data on socio-demographic factors, socio-economic indicators, maternal health and lifestyle characteristics and child’s sleeping behavior, obtained from questionnaires completed at birth, 12 and 24 months of age, were considered in the analyses as potential risk factors of FERF. Time of occurrence of FERF was analyzed using the Kaplan-Meier method. The multivariable analysis for time to event was carried out using a Cox proportional hazards model. Results: Falls from raised surfaces are the leading cause of unintentional injuries in the cohort with 610 (21.1%) and 577 (20.0%) cases among children during the first and second year of life, respectively. An increased risk of FERF was associated with several risk factors: maternal psychological distress (HR 1.41, 95%CI 1.10-1.81), maternal alcohol intake (HR 1.26, 95%CI 1.10-1.45), and child’s sleeping problems (HR 1.28, 95%CI 1.09-1.51). Children with older aged mothers (HR 0.98, 95%CI 0.96–0.99) and living in northern Italy (HR 0.64, 95%CI 0.55-0.75) had a lower risk of FERF. Conclusion: The results of the study suggest that a higher risk of FERF is associated with socio-demographic factors, maternal characteristics and child sleeping behavior that could hinder parent empowerment

A deep-learning model to continuously predict severe acute kidney injury based on urine output changes in critically ill patients

BACKGROUND: Acute Kidney Injury (AKI), a frequentcomplication of pateints in theIntensive Care Unit (ICU), is associated with a high mortality rate. Early prediction of AKI is essential in order to trigger the use of preventive careactions.METHODS: The aim of this study was to ascertain the accuracy of two mathematical analysis models in obtaining a predictive score for AKI development. A deep learning model based on a urine output trends was compared with a logistic regression analysis for AKI prediction in stages 2 and 3 (defined as the simultaneous increase of serum creatinine and decrease of urine output, according to the Acute Kidney Injury Network (AKIN) guidelines). Two retrospective datasets including 35,573 ICU patients were analyzed. Urine output data were used to train and test the logistic regression and the deep learning model.RESULTS: The deep learning model definedan area under the curve (AUC) of 0.89 (±0.01), sensitivity=0.8 and specificity=0.84, which was higher than the logistic regression analysis. The deep learning model was able to predict 88% of AKI cases more than 12h before their onset: for every 6 patients identified as being at risk of AKI by the deep learning model, 5 experienced the event. On the contrary, for every 12 patients not considered to be at risk by the model, 2 developed AKI.CONCLUSION: In conclusion, by using urine output trends, deep learning analysis was able to predict AKI episodes more than 12h in advance, and with a higher accuracy than the classical urine output thresholds. We suggest that this algorithm could be integrated inthe ICU setting to better manage, and potentially prevent, AKI episodes

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Sudden Unexpected Deaths and Vaccinations during the First Two Years of Life in Italy: A Case Series Study

Background The signal of an association between vaccination in the second year of life with a hexavalent vaccine and sudden unexpected deaths (SUD) in the two days following vaccination was reported in Germany in 2003. A study to establish whether the immunisation with hexavalent vaccines increased the short term risk of SUD in infants was conducted in Italy. Methodology/Principal Findings The reference population comprises around 3 million infants vaccinated in Italy in the study period 1999–2004 (1.5 million received hexavalent vaccines). Events of SUD in infants aged 1–23 months were identified through the death certificates. Vaccination history was retrieved from immunisation registries. Association between immunisation and death was assessed adopting a case series design focusing on the risk periods 0–1, 0–7, and 0–14 days after immunisation. Among the 604 infants who died of SUD, 244 (40%) had received at least one vaccination. Four deaths occurred within two days from vaccination with the hexavalent vaccines (RR = 1.5; 95% CI 0.6 to 4.2). The RRs for the risk periods 0–7 and 0–14 were 2.0 (95% CI 1.2 to 3.5) and 1.5 (95% CI 0.9 to 2.4). The increased risk was limited to the first dose (RR = 2.2; 95% CI 1.1 to 4.4), whereas no increase was observed for the second and third doses combined. Conclusions The RRs of SUD for any vaccines and any risk periods, even when greater than 1, were almost an order of magnitude lower than the estimates in Germany. The limited increase in RRs found in Italy appears confined to the first dose and may be partly explained by a residual uncontrolled confounding effect of age

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results from other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols

The adhesion molecule L1 regulates transendothelial migration and trafficking of dendritic cells

The adhesion molecule L1, which is extensively characterized in the nervous system, is also expressed in dendritic cells (DCs), but its function there has remained elusive. To address this issue, we ablated L1 expression in DCs of conditional knockout mice. L1-deficient DCs were impaired in adhesion to and transmigration through monolayers of either lymphatic or blood vessel endothelial cells, implicating L1 in transendothelial migration of DCs. In agreement with these findings, L1 was expressed in cutaneous DCs that migrated to draining lymph nodes, and its ablation reduced DC trafficking in vivo. Within the skin, L1 was found in Langerhans cells but not in dermal DCs, and L1 deficiency impaired Langerhans cell migration. Under inflammatory conditions, L1 also became expressed in vascular endothelium and enhanced transmigration of DCs, likely through L1 homophilic interactions. Our results implicate L1 in the regulation of DC trafficking and shed light on novel mechanisms underlying transendothelial migration of DCs. These observations might offer novel therapeutic perspectives for the treatment of certain immunological disorders