Encapsulation and sedimentation of nanomaterials through complex coacervation

Altres ajuts: the ICN2 is funded by the CERCA programme/Generalitat de Catalunya.Hypothesis: Nanoparticles removal from seawage water is a health and environmental challenge, due to the increasing use of these materials of excellent colloidal stability. Herein we hypothesize to reach this objective through complex coacervation, a straightforward, low-cost process, normally accomplished with non-toxic and biodegradable macromolecules. Highly dense polymer-rich colloidal droplets (the coacervates) obtained from a reversible charge-driven phase separation, entrap suspended nanomaterials, allowing their settling and potential recovery. Experiments: In this work we apply this process to highly stable aqueous colloidal dispersions of different surface charge, size, type and state (solid or liquid). We systematically investigate the effects of the biopolymers excess and the nanomaterials concentration and charge on the encapsulation and sedimentation efficiency and rate. This strategy is also applied to real laboratory water-based wastes. Findings: Long-lasting colloidal suspensions are succesfully destabilized through coacervate formation, which ensures high nanomaterials encapsulation efficiencies (~85%), payloads and highly tranparent supernatants (%T ~90%), within two hours. Lower polymer excess induces faster clearance and less sediments, while preserving effective nanomaterials removal. Preliminary experiments also validate the method for the clearance of real water residuals, making complex coacervation a promising scalable, low-cost and ecofriendly alternative to concentrate, separate or recover suspended micro/nanomaterials from aqueous sludges

Segmenting white matter hyperintensities on isotropic three-dimensional Fluid Attenuated Inversion Recovery magnetic resonance images: Assessing deep learning tools on a Norwegian imaging database

An important step in the analysis of magnetic resonance imaging (MRI) data for neuroimaging is the automated segmentation of white matter hyperintensities (WMHs). Fluid Attenuated Inversion Recovery (FLAIR-weighted) is an MRI contrast that is particularly useful to visualize and quantify WMHs, a hallmark of cerebral small vessel disease and Alzheimer's disease (AD). In order to achieve high spatial resolution in each of the three voxel dimensions, clinical MRI protocols are evolving to a three-dimensional (3D) FLAIR-weighted acquisition. The current study details the deployment of deep learning tools to enable automated WMH segmentation and characterization from 3D FLAIR-weighted images acquired as part of a national AD imaging initiative. Based on data from the ongoing Norwegian Disease Dementia Initiation (DDI) multicenter study, two 3D models-one off-the-shelf from the NVIDIA nnU-Net framework and the other internally developed-were trained, validated, and tested. A third cutting-edge Deep Bayesian network model (HyperMapp3r) was implemented without any de-novo tuning to serve as a comparison architecture. The 2.5D in-house developed and 3D nnU-Net models were trained and validated in-house across five national collection sites among 441 participants from the DDI study, of whom 194 were men and whose average age was (64.91 +/- 9.32) years. Both an external dataset with 29 cases from a global collaborator and a held-out subset of the internal data from the 441 participants were used to test all three models. These test sets were evaluated independently. The ground truth human-in-the-loop segmentation was compared against five established WMH performance metrics. The 3D nnU-Net had the highest performance out of the three tested networks, outperforming both the internally developed 2.5D model and the SOTA Deep Bayesian network with an average dice similarity coefficient score of 0.76 +/- 0.16. Our findings demonstrate that WMH segmentation models can achieve high performance when trained exclusively on FLAIR input volumes that are 3D volumetric acquisitions. Single image input models are desirable for ease of deployment, as reflected in the current embedded clinical research project. The 3D nnU-Net had the highest performance, which suggests a way forward for our need to automate WMH segmentation while also evaluating performance metrics during on-going data collection and model retraining

ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice

"I did not intend to stop. I just could not stand cigarettes any more." A qualitative interview study of smoking cessation among the elderly

<p>Abstract</p> <p>Background</p> <p>Every year, more than 650,000 Europeans die because they smoke. Smoking is considered to be the single most preventable factor influencing health. General practitioners (GP) are encouraged to advise on smoking cessation at all suitable consultations. Unsolicited advice from GPs results in one of 40-60 smokers stopping smoking. Smoking cessation advice has traditionally been given on an individual basis. Our aim was to gain insights that may help general practitioners understand why people smoke, and why smokers stop and then remain quitting and, from this, to find fruitful approaches to the dialogue about stopping smoking.</p> <p>Methods</p> <p>Interviews with 18 elderly smokers and ex-smokers about their smoking and decisions to smoke or quit were analysed with qualitative content analysis across narratives. A narrative perspective was applied.</p> <p>Results</p> <p>Six stages in the smoking story emerged, from the start of smoking, where friends had a huge influence, until maintenance of the possible cessation. The informants were influenced by "all the others" at all stages. Spouses had vital influence in stopping, relapses and continued smoking. The majority of quitters had stopped by themselves without medication, and had kept the tobacco handy for 3-6 months. Often smoking cessation seemed to happen unplanned, though sometimes it was planned. With an increasingly negative social attitude towards smoking, the informants became more aware of the risks of smoking.</p> <p>Conclusion</p> <p>"All the others" is a clue in the smoking story. For smoking cessation, it is essential to be aware of the influence of friends and family members, especially a spouse. People may stop smoking unplanned, even when motivation is not obvious. Information from the community and from doctors on the negative aspects of smoking should continue. Eliciting life-long smoking narratives may open up for a fruitful dialogue, as well as prompting reflection about smoking and adding to the motivation to stop.</p

Variable, but not free-weight, resistance back squat exercise potentiates jump performance following a comprehensive task-specific warm-up

Studies examining acute, high-speed movement performance enhancement following intense muscular contractions (frequently called "post-activation potentiation"; PAP) often impose a limited warm-up, compromizing external validity. In the present study, the effects on countermovement vertical jump (CMJ) performance of back squat exercises performed with or without elastic bands during warm-up were compared. After familiarization, fifteen active men visited the laboratory on two occasions under randomized, counterbalanced experimental squat warm-up conditions: (a) free-weight resistance (FWR) and (b) variable resistance (VR). After completing a comprehensive task-specific warm-up, three maximal CMJs were performed followed by three back squat repetitions completed at 85% of 1-RM using either FWR or VR Three CMJs were then performed 30 seconds, 4 minutes, 8 minutes, and 12 minutes later. During CMJ trials, hip, knee, and ankle joint kinematics, ground reaction force data and vastus medialis, vastus lateralis, and gluteus maximus electromyograms (EMG) were recorded simultaneously using 3D motion analysis, force platform, and EMG techniques, respectively. No change in any variable occurred after FWR (P > 0.05). Significant increases (P < 0.05) were detected at all time points following VR in CMJ height (5.3%-6.5%), peak power (4.4%-5.9%), rate of force development (12.9%-19.1%), peak concentric knee angular velocity (3.1%-4.1%), and mean concentric vastus lateralis EMG activity (27.5%-33.4%). The lack of effect of the free-weight conditioning contractions suggests that the comprehensive task-specific warm-up routine mitigated any further performance augmentation. However, the improved CMJ performance following the use of elastic bands is indicative that specific alterations in force-time properties of warm-up exercises may further improve performance

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Historical total ozone radiative forcing derived from CMIP6 simulations

Radiative forcing (RF) time series for total ozone from 1850 up to the present day are calculated based on historical simulations of ozone from 10 climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, RF is calculated for ozone fields prepared as an input for CMIP6 models without chemistry schemes and from a chemical transport model simulation. A radiative kernel for ozone is constructed and used to derive the RF. The ozone RF in 2010 (2005–2014) relative to 1850 is 0.35 W m−2 [0.08–0.61] (5–95% uncertainty range) based on models with both tropospheric and stratospheric chemistry. One of these models has a negative present-day total ozone RF. Excluding this model, the present-day ozone RF increases to 0.39 W m−2 [0.27–0.51] (5–95% uncertainty range). The rest of the models have RF close to or stronger than the RF time series assessed by the Intergovernmental Panel on Climate Change in the fifth assessment report with the primary driver likely being the new precursor emissions used in CMIP6. The rapid adjustments beyond stratospheric temperature are estimated to be weak and thus the RF is a good measure of effective radiative forcing

Comparison of arterial spin labeling registration strategies in the multi-center GENetic frontotemporal dementia initiative (GENFI)

PURPOSE: To compare registration strategies to align arterial spin labeling (ASL) with 3D T1-weighted (T1w) images, with the goal of reducing the between-subject variability of cerebral blood flow (CBF) images. MATERIALS AND METHODS: Multi-center 3T ASL data were collected at eight sites with four different sequences in the multi-center GENetic Frontotemporal dementia Initiative (GENFI) study. In a total of 48 healthy controls, we compared the following image registration options: (I) which images to use for registration (perfusion-weighted images [PWI] to the segmented gray matter (GM) probability map (pGM) (CBF-pGM) or M0 to T1w (M0-T1w); (II) which transformation to use (rigid-body or non-rigid); and (III) whether to mask or not (no masking, M0-based FMRIB software library Brain Extraction Tool [BET] masking). In addition to visual comparison, we quantified image similarity using the Pearson correlation coefficient (CC), and used the Mann-Whitney U rank sum test. RESULTS: CBF-pGM outperformed M0-T1w (CC improvement 47.2% ± 22.0%; P < 0.001), and the non-rigid transformation outperformed rigid-body (20.6% ± 5.3%; P < 0.001). Masking only improved the M0-T1w rigid-body registration (14.5% ± 15.5%; P = 0.007). CONCLUSION: The choice of image registration strategy impacts ASL group analyses. The non-rigid transformation is promising but requires validation. CBF-pGM rigid-body registration without masking can be used as a default strategy. In patients with expansive perfusion deficits, M0-T1w may outperform CBF-pGM in sequences with high effective spatial resolution. BET-masking only improves M0-T1w registration when the M0 image has sufficient contrast. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017

A systematic review of patient reported factors associated with uptake and completion of cardiovascular lifestyle behaviour change

Background: Healthy lifestyles are an important facet of cardiovascular risk management. Unfortunately many individuals fail to engage with lifestyle change programmes. There are many factors that patients report as influencing their decisions about initiating lifestyle change. This is challenging for health care professionals who may lack the skills and time to address a broad range of barriers to lifestyle behaviour. Guidance on which factors to focus on during lifestyle consultations may assist healthcare professionals to hone their skills and knowledge leading to more productive patient interactions with ultimately better uptake of lifestyle behaviour change support. The aim of our study was to clarify which influences reported by patients predict uptake and completion of formal lifestyle change programmes. Methods: A systematic narrative review of quantitative observational studies reporting factors (influences) associated with uptake and completion of lifestyle behaviour change programmes. Quantitative observational studies involving patients at high risk of cardiovascular events were identified through electronic searching and screened against pre-defined selection criteria. Factors were extracted and organised into an existing qualitative framework. Results: 374 factors were extracted from 32 studies. Factors most consistently associated with uptake of lifestyle change related to support from family and friends, transport and other costs, and beliefs about the causes of illness and lifestyle change. Depression and anxiety also appear to influence uptake as well as completion. Many factors show inconsistent patterns with respect to uptake and completion of lifestyle change programmes. Conclusion: There are a small number of factors that consistently appear to influence uptake and completion of cardiovascular lifestyle behaviour change. These factors could be considered during patient consultations to promote a tailored approach to decision making about the most suitable type and level lifestyle behaviour change support