Long-term physical evolution of an elastomeric ultrasound contrast microbubble

Hypothesis: One of the main assets of crosslinked polymer-shelled microbubbles (MBs) as ultrasound-active theranostic agents is the robustness of the shells, combined with the chemical versatility in modifying the surface with ligands and/or drugs. Despite the long shelf-life, subtle modifications occur in the MB shells involving shifts in acoustic, mechanical and structural properties. Experiments: We carried out a long-term morphological and acoustic evolution analysis on elastomeric polyvinyl-alcohol (PVA)-shelled MBs, a novel platform accomplishing good acoustic and surface performances in one agent. Confocal laser scanning microscopy, acoustic spectroscopy and AFM nanomechanics were integrated to understand the mechanism of PVA MBs ageing. The changes in the MB acoustic properties were framed in terms of shell thickness and viscoelasticity using a linearised oscillation theory, and compared to MB morphology and to nanomechanical analysis. Findings: We enlightened a novel, intriguing ageing time evolution of the PVA MBs with double behaviour with respect to a crossover time of ∼50 days. Before, significant changes occur in MB stiffness and shell thickness, mainly due to a massive release of entangled PVA chains. Then, the MB resonance frequency increases together with shell thickening and softening. Our benchmark study is of general interest for emerging viscoelastomeric bubbles towards personalised medicine

To Look Beyond Vasospasm in Aneurysmal Subarachnoid Haemorrhage.

Delayed cerebral vasospasm has classically been considered the most important and treatable cause of mortality and morbidity in patients with aneurysmal subarachnoid hemorrhage (aSAH). Secondary ischemia (or delayed ischemic neurological deficit, DIND) has been shown to be the leading determinant of poor clinical outcome in patients with aSAH surviving the early phase and cerebral vasospasm has been attributed to being primarily responsible. Recently, various clinical trials aimed at treating vasospasm have produced disappointing results. DIND seems to have a multifactorial etiology and vasospasm may simply represent one contributing factor and not the major determinant. Increasing evidence shows that a series of early secondary cerebral insults may occur following aneurysm rupture (the so-called early brain injury). This further aggravates the initial insult and actually determines the functional outcome. A better understanding of these mechanisms and their prevention in the very early phase is needed to improve the prognosis. The aim of this review is to summarize the existing literature on this topic and so to illustrate how the presence of cerebral vasospasm may not necessarily be a prerequisite for DIND development. The various factors determining DIND that worsen functional outcome and prognosis are then discussed

Experimental investigation on tensile and shear bond behaviour of Basalt-FRCM composites for strengthening calcarenite masonry elements

The use of Fabric Reinforced Cementitious Matrix (FRCM) composites for structural retrofit has seen an increased interest among the scientific community, during the last decade. Various studies have revealed their effectiveness as external retrofitting technique of masonry elements, offering numerous advantages respect to the well know Fibre Reinforced Polymer (FRP) in terms of compatibility with masonry support, reversibility of intervention and sustainability. Despite the growing use, the characterization of FRCM mechanical behaviour is still an open issue, due to numerous uncertainties involved in test set-up adopted and fibre-mortar combination. The proposed experimental study aims to investigate the tensile and shear bond behaviour of Basalt-FRCM for strengthening calcarenite masonry elements. Calcarenite is a natural stone with sedimentary origin and it is widely present in existing buildings of the Mediterranean areas. Direct tensile tests are performed on two types of Basalt-FRCM coupons, with cement-based and lime-based mortar, adopting two different test-set-up based on clamping and clevis grip methods. Moreover, double shear bond tests are carried out to evaluate the adhesion properties of the two types of Basalt-FRCM with calcarenite support. Experimental outcomes are compared in terms of stress-strain curves, evaluating the influence of mortar grade and test set-up on the mechanical performances of Basalt-FRCM composites. The comparisons provide information about the mechanical stress transfer phenomena that occur at the fibre-to-matrix and FRCM-to-substrate interface level and the failure modes

Monte Carlo analysis of masonry structures under tsunami action: Reliability of lognormal fragility curves and overall uncertainty prediction

Tsunami vulnerability of coastal buildings has gained more and more interest in recent years, in the consciousness of what losses may be caused. The improvement of the available approaches for the quantitative estimation of the probability of building damage and for defining possible strategies for risk mitigation is an actual goal. In this framework, several authors have provided empirical fragility curves based on field surveys after tsunamis. Nevertheless, a predictive approach based on analytical fragility curves, which can be extended to many classes of buildings, is essential for the scopes of civil protection and risk mitigation. In this paper, an approach for the construction of fragility curves, proposed for masonry structures under tsunami waves, is discussed and refined in the part regarding the assignment of the uncertainties. Further, an assessment of the reliability of the lognormal fragility distribution is carried out based on a Monte Carlo simulation applied to 4 classes of buildings. Here, it is shown that Monte Carlo analysis allows a direct evaluation of the uncertainties without the need to resort to ambiguous regression analyses and rules of combination of the uncertainties of demand and capacity based on the regression analysis results or other uncertainty estimation approaches

A Neural network based observation operator for coupled ocean acoustic variational data assimilation

Variational data assimilation requires implementing the tangent-linear and adjoint (TA/AD) version of any operator. This intrinsically hampers the use of complicated observations.Here, we assess a new data-driven approach to assimilate acoustic underwater propagation measurements [transmission loss (TL)] into a regional ocean forecasting system. TL measurements depend on the underlying sound speed fields, mostly temperature, and their inversion would require heavy coding of the TA/AD of an acoustic underwater propagation model. In this study, the nonlinear version of the acoustic model is applied to an ensemble of perturbed oceanic conditions. TL outputs are used to formulate both a statistical linear operator based on canonical correlation analysis (CCA), and a neural network based (NN) operator. For the latter, two linearization strategies are compared, the best-performing one relying on reverse-mode automatic differentiation. The new observation operator is applied in data assimilation experiments over the Ligurian Sea (Mediterranean Sea), using the observing system simulation experiments (OSSE) methodology to assess the impact of TL observations onto oceanic fields. TL observations are extracted from a nature run with perturbed surface boundary conditions and stochastic ocean physics. Sensitivity analyses indicate that theNNreconstruction of TL is significantly better than CCA. BothCCAandNNare able to improve the upper-ocean skill scores in forecast experiments, with NN outperforming CCA on the average. The use of the NN observation operator is computationally affordable, and its general formulation appears promising for the adjoint-free assimilation of any remote sensing observing network. SIGNIFICANCE STATEMENT: Deep learning algorithms are now widely spread in a diverse range of fields to help with solving automatic classification and regression problems. Here, we present and assess a strategy aimed at introducing an observation operator based on neural networks in data assimilation. Linearization of such an operator, required by variational schemes, is also discussed and implemented. The methodology is applied to the coupled oceanic acoustic data assimilation problem, and provides promising results. Our approach may be extended in the future to assimilate any remotely sensed type of observations

Variazione degli stock di carbonio del suolo in seguito ai processi di abbandono dei coltivi: il caso studio dell\u2019isola di Pantelleria (TP)

The recent abandonment of marginal agricultural areas in the Mediterranean has caused an increase of the surface occupied by pre-forest and forest formations. In order to study the carbon accumulation processes on Pantelleria Island was selected a North-facing area. This area includes 5 stages of succession (sds) that compose a chronosequence (from 0 to 30 years) to understand soil C accumulation processes after abandonment. These are abandoned vineyards or caperbushes, not disturbed (grazing, fire) since agricultural abandonment, and they are situated in thermomediterranean belt and on the same parent material and consequently considered in the same ecological conditions. Samples at 1 cm, 10 cm and 40 cm depth, respectively, were taken for every sds in three different soil relief areas. Litter samples were taken too. Organic carbon content was determined for every sample. Carbon content increases from a sds to the next one. There is a duplication of C from sds0 (cultivated field) to sd1 (abandoned since few years) and from sds4 (abandoned since 16-30 years) to sds5 (abandoned since > 30 years). It seems that different types of vegetation play a key-role in soil C dynamics and there are 85 t C ha-1 in the top 40 cm of the soil after 30 years from the abandonment in the chronosequence and an annual C sequestration rate equal to 3.4 t ha-1. These results show that revegetation offers good opportunities to sequestrate CO2 from the atmosphere and, therefore, to mitigate the greenhouse effect as it is requested by international agreements

Outcome Prognostication of Acute Brain Injury using the Neurological Pupil Index (ORANGE) study: protocol for a prospective, observational, multicentre, international cohort study.

The pupillary examination is an important part of the neurological assessment, especially in the setting of acutely brain-injured patients, and pupillary abnormalities are associated with poor outcomes. Currently, the pupillary examination is based on a visual, subjective and frequently inaccurate estimation. The use of automated infrared pupillometry to measure the pupillary light reflex can precisely quantify subtle changes in pupillary functions. The study aimed to evaluate the association between abnormal pupillary function, assessed by the Neurological Pupil Index (NPi), and long-term outcomes in patients with acute brain injury (ABI). The Outcome Prognostication of Acute Brain Injury using the Neurological Pupil Index study is a prospective, observational study including adult patients with ABI requiring admission at the intensive care unit. We aimed to recruit at least 420 patients including those suffering from traumatic brain injury or haemorrhagic strokes, over 12 months. The primary aim was to assess the relationship between NPi and 6-month mortality or poor neurological outcome, measured by the Extended Glasgow Outcome Score (GOS-E, poor outcome=GOS-E 1-4). Supervised and unsupervised methods and latent class mixed models will be used to identify patterns of NPi trajectories and Cox and logistic model to evaluate their association with outcome. The study has been approved by the institutional review board (Comitato Etico Brianza) on 16 July 2020. Approved protocol V.4.0 dated 10 March 2020. The results of this study will be published in peer-reviewed journals and presented at conferences. NCT04490005

Advanced magnetic resonance imaging of cortical laminar necrosis in patients with stroke

Purpose: The aim of this study was to assess the novel advanced magnetic resonance imaging findings of acute stage cortical laminar necrosis developing after complicated cardiovascular or abdominal surgery. Materials and methods: This institutional review board-approved study included patients with postoperative stroke due to cortical laminar necrosis imaged with magnetic resonance in the acute stage. Brain magnetic resonance imaging examinations were obtained on a 3T magnetic resonance scanner within 48 hours of the neurological symptoms, including diffusion-weighted images (b value, 1000 s/mm2) and arterial spin labelling using a pseudo-continuous arterial spin labelling method in four patients. Conventional and advanced magnetic resonance images were analysed to assess the imaging features in acute stage cortical laminar necrosis. Results: The final population consisted of 14 patients (seven men and seven women, mean age 61 years, range 32–79 years) diagnosed with stroke and acute phase cortical laminar necrosis. All the patients presented with cortical lesions showing restricted diffusion on diffusion-weighted images and hypointensity on the apparent diffusion coefficient map. Cortical hyperintensity on T2-weighted or fluid-attenuated inversion recovery images was found in three (21%) and six (43%) patients, respectively. Reduced perfusion was noted in three out of four patients imaged with arterial spin labelling, while in one case no corresponding perfusion abnormality was noted on the arterial spin labelling maps. Arterial spin labelling abnormalities were much more extensive than diffusion restriction in two patients, and they were associated with a poor outcome. Conclusion: Cortical hyperintense abnormalities on diffusion-weighted imaging may be the only sign of developing cortical laminar necrosis injury. The acquisition of arterial spin labelling helps to identify perfusion alterations and the extension of the ischaemic injury