Globally, there is a huge unmet need for effective treatments for neurodegenerative diseases. The complexity of the molecular mechanisms underlying neuronal degeneration and the heterogeneity of the patient population present massive challenges to the development of early diagnostic tools and effective treatments for these diseases. Machine learning, a subfield of artificial intelligence, is enabling scientists, clinicians and patients to address some of these challenges. In this Review, we discuss how machine learning can aid early diagnosis and interpretation of medical images as well as the discovery and development of new therapies. A unifying theme of the different applications of machine learning is the integration of multiple high-dimensional sources of data, which all provide a different view on disease, and the automated derivation of actionable insights.

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Applications of machine learning to diagnosis and treatment of neurodegenerative diseases

Toxicological interactions of microplastics/nanoplastics and environmental contaminants: Current knowledge and future perspectives.

Polymeric micelles for the delivery of poorly soluble drugs: From nanoformulation to clinical approval.

On the linkage between urban heat island and urban pollution island: Three-decade literature review towards a conceptual framework.

The worldwide contamination of waters by microplastics is an emerging health and environmental issue. Despite being relatively inert, microplastics may adsorb and carry other aquatic pollutants such as heavy metals. Adsorption of heavy metals onto microplastics is a spontaneous process controlled by the microplastic surface. Marine microplastics have been well discussed, yet there are actually a few reviews on microplastics in freshwater. Here, we review microplastic contamination in freshwater systems with focus on adsorption of heavy metals. We present microplastic abundance, distribution, impact of microplastic size, affinity for heavy metals and combined toxic effects of the co-occurrence of microplastic and heavy metals. Remarkably, the concentration of metals on polystyrene and polyvinyl chloride was 800 times higher than in the surrounding environment. Combined toxic effects include endocrine disrupting and reduced predatory behavior of aquatic carnivores.

Interaction of freshwater microplastics with biota and heavy metals: a review

We identify the physical mechanism through which newly developed quaternary ammonium salt (QAS) deposit control additives (DCAs) affect the rheological properties of cavitating turbulent flows, resulting in an increase in the volumetric efficiency of clean injectors fuelled with diesel or biodiesel fuels. Quaternary ammonium surfactants with appropriate counterions can be very effective in reducing the turbulent drag in aqueous solutions, however, less is known about the effect of such surfactants in oil-based solvents or in cavitating flow conditions. Small-angle neutron scattering (SANS) investigations show that in traditional DCA fuel compositions only reverse spherical micelles form, whereas reverse cylindrical micelles are detected by blending the fuel with the QAS additive. Moreover, experiments utilising X-ray micro computed tomography (micro-CT) in nozzle replicas, quantify that in cavitation regions the liquid fraction is increased in the presence of the QAS additive. Furthermore, high-flux X-ray phase contrast imaging (XPCI) measurements identify a flow stabilization effect in the region of vortex cavitation by the QAS additive. The effect of the formation of cylindrical micelles is reproduced with computational fluid dynamics (CFD) simulations by including viscoelastic characteristics for the flow. It is demonstrated that viscoelasticity can reduce turbulence and suppress cavitation, and subsequently increase the injector’s volumetric efficiency.

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Dale Diamond

Papers

Turbulence and Cavitation Suppression by Quaternary Ammonium Salt Additives.