Anti-inflammatory Components from Functional Foods for Obesity

Obesity, defined as excessive fat accumulation that may impair health, has been described throughout human history, but it has now reached epidemic proportions with the WHO estimating that 39% of the world’s adults over 18 years of age were overweight or obese in 2016. Obesity is a chronic low-grade inflammatory state leading to organ damage with an increased risk of common diseases including cardiovascular and metabolic disease, non-alcoholic fatty liver disease, osteo-arthritis and some cancers. This inflammatory state may be influenced by adipose tissue hypoxia and changes in the gut microbiota. There has been an increasing focus on functional foods and nutraceuticals as treatment options for obesity as drug treatments are limited in efficacy. This chapter summarises the importance of anthocyanin-containing fruits and vegetables, coffee and its components, tropical fruit and food waste as sources of phytochemicals for obesity treatment. We emphasise that preclinical studies can form the basis for clinical trials to determine the effectiveness of these treatments in humans

Assessing the performance of methods for copy number aberration detection from single-cell DNA sequencing data.

Single-cell DNA sequencing technologies are enabling the study of mutations and their evolutionary trajectories in cancer. Somatic copy number aberrations (CNAs) have been implicated in the development and progression of various types of cancer. A wide array of methods for CNA detection has been either developed specifically for or adapted to single-cell DNA sequencing data. Understanding the strengths and limitations that are unique to each of these methods is very important for obtaining accurate copy number profiles from single-cell DNA sequencing data. We benchmarked three widely used methods-Ginkgo, HMMcopy, and CopyNumber-on simulated as well as real datasets. To facilitate this, we developed a novel simulator of single-cell genome evolution in the presence of CNAs. Furthermore, to assess performance on empirical data where the ground truth is unknown, we introduce a phylogeny-based measure for identifying potentially erroneous inferences. While single-cell DNA sequencing is very promising for elucidating and understanding CNAs, our findings show that even the best existing method does not exceed 80% accuracy. New methods that significantly improve upon the accuracy of these three methods are needed. Furthermore, with the large datasets being generated, the methods must be computationally efficient

Reducing EUV mask 3D effects by alternative metal absorbers

Over the recent years EUV lithography has demonstrated the patterning of ever shrinking feature sizes (enabling the N7 technology node and below), while the EUV mask has remained unaltered using a 70nm Ta-based absorber. This has led to experimentally observed Mask 3D (M3D) effects at wafer level, which are induced by the interaction between the oblique incident EUV light and the patterned absorber with typical thickness values in the order of several wavelengths. In this paper we exploit the optical properties of the absorber material of the EUV mask as M3D mitigation strategy. Using rigorous lithographic simulations, we screen potential single element absorber materials for their optical properties and their optimal thickness for minimum best focus variation through pitch at wafer level. In addition, the M3D mitigation by absorber material is evaluated by process window comparison of foundry N5 specific logic clips. In order to validate the rigorous simulation predict ions and to test the processing feasibility of the alternative absorber materials, we have selected the candidate single elements Nickel and Cobalt for an experimental evaluation on wafer substrates. In this work, we present the film characterization as well as first patterning tests of these single element candidate absorber materials