The UK Consumer's Attitudes to, and Willingness to Pay for, imported Foods

We report results from an investigation into consumer preferences for locally produced foods. Using a choice experiment we estimate willingness to pay for foods of a designated origin together with certification for Organic and GM free status. Our results indicate that there is a preference for locally produced food which is GM free, Organic and produced in the traditional season.imported food, seasonality, willingness-to-pay, choice experiment, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, International Relations/Trade,

Exosomes: key mediators of metastasis and pre-metastatic niche formation

While tumour cells are classically known to communicate via direct cell-to-cell contact and the secretion of soluble protein-based factors such as cytokines and growth factors, alternative novel mechanisms that promote tumour progression have recently emerged. Now, new critical components of the secretome thought to be involved in tumour progression are exosomes, small vesicles of endocytic origin that carry a variety of bioactive molecules, including proteins, lipids, RNA, as well as DNA molecules. Cancer cell-derived exosomes have been shown to participate in crucial steps of metastatic spread of a primary tumour, ranging from oncogenic reprogramming of malignant cells to formation of pre-metastatic niches. These effects are achieved through the mediation of intercellular cross-talk and subsequent modification of both local and distant microenvironments in an autocrine and paracrine fashion. Here, we summarise the recent findings that implicate this non-canonical signalling within the tumour as a critical driver of metastatic disease progression, and discuss how understanding the molecular mechanisms involved in exosome-mediated metastasis is of great value for the development of new therapeutic strategies to prevent cancer progression

Mitochondrial Protein Lipoylation and the 2-Oxoglutarate Dehydrogenase Complex Controls HIF1α Stability in Aerobic Conditions.

Hypoxia-inducible transcription factors (HIFs) control adaptation to low oxygen environments by activating genes involved in metabolism, angiogenesis, and redox homeostasis. The finding that HIFs are also regulated by small molecule metabolites highlights the need to understand the complexity of their cellular regulation. Here we use a forward genetic screen in near-haploid human cells to identify genes that stabilize HIFs under aerobic conditions. We identify two mitochondrial genes, oxoglutarate dehydrogenase (OGDH) and lipoic acid synthase (LIAS), which when mutated stabilize HIF1α in a non-hydroxylated form. Disruption of OGDH complex activity in OGDH or LIAS mutants promotes L-2-hydroxyglutarate formation, which inhibits the activity of the HIFα prolyl hydroxylases (PHDs) and TET 2-oxoglutarate dependent dioxygenases. We also find that PHD activity is decreased in patients with homozygous germline mutations in lipoic acid synthesis, leading to HIF1 activation. Thus, mutations affecting OGDHC activity may have broad implications for epigenetic regulation and tumorigenesis.This work was supported by a Wellcome Trust Senior Clinical Research Fellowship to J.A.N. (102770/Z/13/Z), Wellcome Trust Principal Research Fellowship to P.J.L. (084957/Z/08/Z), and the Medical Research Council (A.S.H.C. and C.F.). The Cambridge Institute for Medical Research is in receipt of a Wellcome Trust Strategic Award (100140).This is the final version of the article. It first appeared from Elsevier (Cell Press) via https://doi.org/10.1016/j.cmet.2016.09.01

Gene expression and in situ protein profiling of candidate SARS-CoV-2 receptors in human airway epithelial cells and lung tissue

In December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)emerged, causing the coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV, the agent responsible for the 2003 SARS outbreak, utilises angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) host molecules for viral entry. ACE2 and TMPRSS2 have recently been implicated in SARS-CoV-2 viral infection. Additional host molecules including ADAM17, cathepsin L, CD147 and GRP78 may also function as receptors for SARS-CoV-2.To determine the expression and in situ localisation of candidate SARS-CoV-2 receptors in the respiratory mucosa, we analysed gene expression datasets from airway epithelial cells of 515 healthy subjects, gene promoter activity analysis using the FANTOM5 dataset containing 120 distinct sample types, single cell RNA sequencing (scRNAseq) of 10 healthy subjects, proteomic datasets, immunoblots on multiple airway epithelial cell types, and immunohistochemistry on 98 human lung samples.We demonstrate absent to lowACE2promoter activity in a variety of lung epithelial cell samples andlowACE2gene expression in both microarray and scRNAseq datasets of epithelial cell populations.Consistent with gene expression, rare ACE2 protein expression was observed in the airway epithelium and alveoli of human lung, confirmed with proteomics. We present confirmatory evidence for the presence ofTMPRSS2, CD147 and GRP78 protein in vitro in airway epithelial cells and confirm broad in situ protein expression of CD147 and GRP78 in the respiratory mucosa. Collectively, our data suggest the presence of a mechanism dynamically regulating ACE2 expression inhuman lung, perhaps in periods of SARS-CoV-2 infection, and also suggest that alternative receptors forSARS-CoV-2 exist to facilitate initial host cell infection

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Genetic identification of fish

Our report shows that the straightforward extraction of DNA and amplification of appropriate genes can identify fish that are difficult to identify unequivocally from morphology alone. Three examples show that these techniques can be extended to identify fish from other regions or countries and could be useful for the surveillance of illegal or unregulated transfers of fish, and for identifying species from a conservation perspective

The evolving translational potential of small extracellular vesicles in cancer

Cancer-derived extracellular vesicles (EVs) are regarded as having promising potential to be used as therapeutics and disease biomarkers. Mechanistically, EVs have been shown to function in most, if not all, steps of cancer progression. Cancer EVs, including small EVs (sEVs), contain unique biomolecular cargo, consisting of protein, nucleic acid and lipids. Through progress in the identification of this specific cargo, cancer biomarkers have been identified and developed, opening up novel and interesting opportunities for cancer diagnosis and prognosis. Intriguingly, we still lack a comprehensive understanding of the cancer-specific pathways that govern EV biogenesis in cancer cells. Filling this knowledge gap will rapidly improve cancer EV biomarkers, as it will also allow discrimination of the procancer and anticancer actions of those EVs. Even more promising is uncovering therapeutically targetable, tumour-specific EV pathways and content, which will generate novel classes of cancer therapies. This Review highlights the progress the cancer sEV field has made in the areas of biomarker discovery and validation as well as sEV-based therapeutics, highlights the challenges we are facing and identifies gaps in our knowledge, which currently prevent us from developing the full potential of sEVs in cancer diagnostic and therapy

An Evaluation of Reconstruction Filters for Volume Rendering

To render images from a three-dimensional array of sample values, it is necessary to interpolate between the samples. This paper is concerned with interpolation methods that are equivalent to convolving the samples with a reconstruction filter; this covers all commonly used schemes, including trilinear and cubic interpolation. We first outline the formal basis of interpolation in three-dimensional signal processing theory. We then propose numerical metrics that can be used to measure filter characteristics that are relevant to the appearance of images generated using that filter. We apply those metrics to several previously used filters and relate the results to isosurface images of the interpolations. We show that the choice of interpolation scheme can have a dramatic effect on image quality, and we discuss the cost/benefit tradeoff inherent in choosing a filter.