Publications by authors named "C S Manno"

The incidence and prevalence of muscular disorders and of type 2 diabetes (T2D) is increasing and both represent highly significant healthcare problems, both economically and compromising quality of life. Interestingly, skeletal muscle dysfunction and T2D share some commonalities including dysregulated glucose homeostasis, increased oxidative stress, dyslipidemia, and cytokine alterations. Several lines of evidence have hinted to a relationship between skeletal muscle dysfunction and T2D.

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Marine microplastic is pervasive, polluting the remotest ecosystems including the Southern Ocean. Since this region is already undergoing climatic changes, the additional stress of microplastic pollution on the ecosystem should not be considered in isolation. We identify potential hotspot areas of ecological impact from a spatial overlap analysis of multiple data sets to understand where marine biota are likely to interact with local microplastic emissions (from ship traffic and human populations associated with scientific research and tourism).

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The Antarctic krill (Euphausia superba) play a critical role in promoting the so-called "blue carbon pathway" by producing a large amount of fast-sinking faecal pellets (FPs) which facilitate the transport of CO through the water column. Here we assess how exposure to negatively (PS-COOH) and positively (PS-NH) charged polystyrene nanoparticles, impacts degradation of krill FPs (i.e.

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The aim of this paper is to characterize the plastic and to study a potential relationship between plastic debris characteristics and the presence of fouling biota in an Antarctic Specially Protected Area Robert Island, on the Antarctic peninsula region. A combination of lab-based sorting, advanced spectral analysis and general linear modelling was used to assess the abundance and type of plastic debris washed up on the shore. Observations recorded 730 debris items, with 85 % being plastic.

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Skeletal muscle, the major processor of dietary glucose, stores it in myriad glycogen granules. Their numbers vary with cellular location and physiological and pathophysiological states. AI models were developed to derive granular glycogen content from electron-microscopic images of human muscle.

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