Understanding food consumption lifecycles using wearable cameras

Application of design in HCI is a common approach to engendering behavioural change to address important challenges such as sustainability. Encouraging such change requires an understanding of current motivations and behaviours in the domain in question. In this paper, we describe use of wearable cameras to study motivations and behaviours around food consumption by focusing on two contrasting cultures, Malaysia and the UK. Our findings highlight the potential of wearable cameras to enhance knowledge of food consumption practices and identify where and how some digital interventions might be appropriate to change food behaviour. This includes appealing to people’s motivations behind food consumption and capitalising on existing practices such as gifting of food and social meals. We propose a food consumption lifecycle as a framework to understand and design human–food interaction. The use of wearable cameras enabled us to capture a high-level overview of spatially distributed food-related practices and understand food behaviours in greater depth.This work was co-funded by Horizon Digital Economy Research Institute, UK, and Crops for the Future, Malaysia.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s00779-015-0871-

Understanding food consumption lifecycles using wearable cameras

Application of design in HCI is a common approach to engendering behavioural change to address important challenges such as sustainability. Encouraging such change requires an understanding of current motivations and behaviours in the domain in question. In this paper, we describe use of wearable cameras to study motivations and behaviours around food consumption by focusing on two contrasting cultures, Malaysia and the UK. Our findings highlight the potential of wearable cameras to enhance knowledge of food consumption practices and identify where and how some digital interventions might be appropriate to change food behaviour. This includes appealing to people’s motivations behind food consumption and capitalising on existing practices such as gifting of food and social meals. We propose a food consumption lifecycle as a framework to understand and design human–food interaction. The use of wearable cameras enabled us to capture a high-level overview of spatially distributed food-related practices and understand food behaviours in greater depth.This work was co-funded by Horizon Digital Economy Research Institute, UK, and Crops for the Future, Malaysia.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s00779-015-0871-

Wearables or infrastructure: contrasting approaches to collecting behavioural data in the home

This paper examines and contrasts two approaches to collecting behavioural data within the home. The first of these involves filming from static video cameras combined with network logging to capture media consumption activities across multiple screens. The second utilises wearable cameras that passively collect still images to provide insights into food related behaviours. The paper compares the approaches from the perspective of the researchers and participants, and outlines the key benefits and challenges of each, with the aim of further mapping the space of possibilities now available when studying behaviour in the home

Wearables or infrastructure: contrasting approaches to collecting behavioural data in the home

This paper examines and contrasts two approaches to collecting behavioural data within the home. The first of these involves filming from static video cameras combined with network logging to capture media consumption activities across multiple screens. The second utilises wearable cameras that passively collect still images to provide insights into food related behaviours. The paper compares the approaches from the perspective of the researchers and participants,and outlines the key benefits and challenges of each, with the aim of further mapping the space of possibilities now available when studying behaviour in the home

The BRAF pseudogene functions as a competitive endogenous RNA and induces lymphoma in vivo

SummaryResearch over the past decade has suggested important roles for pseudogenes in physiology and disease. In vitro experiments demonstrated that pseudogenes contribute to cell transformation through several mechanisms. However, in vivo evidence for a causal role of pseudogenes in cancer development is lacking. Here, we report that mice engineered to overexpress either the full-length murine B-Raf pseudogene Braf-rs1 or its pseudo “CDS” or “3′ UTR” develop an aggressive malignancy resembling human diffuse large B cell lymphoma. We show that Braf-rs1 and its human ortholog, BRAFP1, elicit their oncogenic activity, at least in part, as competitive endogenous RNAs (ceRNAs) that elevate BRAF expression and MAPK activation in vitro and in vivo. Notably, we find that transcriptional or genomic aberrations of BRAFP1 occur frequently in multiple human cancers, including B cell lymphomas. Our engineered mouse models demonstrate the oncogenic potential of pseudogenes and indicate that ceRNA-mediated microRNA sequestration may contribute to the development of cancer

Ceftiofur Resistance in Salmonella enterica Serovar Heidelberg from Chicken Meat and Humans, Canada

Use of this drug in chickens may limit effectiveness of cephalosporins in treating human infections

A general co-expression network-based approach to gene expression analysis: comparison and applications

<p>Abstract</p> <p>Background</p> <p>Co-expression network-based approaches have become popular in analyzing microarray data, such as for detecting functional gene modules. However, co-expression networks are often constructed by ad hoc methods, and network-based analyses have not been shown to outperform the conventional cluster analyses, partially due to the lack of an unbiased evaluation metric.</p> <p>Results</p> <p>Here, we develop a general co-expression network-based approach for analyzing both genes and samples in microarray data. Our approach consists of a simple but robust rank-based network construction method, a parameter-free module discovery algorithm and a novel reference network-based metric for module evaluation. We report some interesting topological properties of rank-based co-expression networks that are very different from that of value-based networks in the literature. Using a large set of synthetic and real microarray data, we demonstrate the superior performance of our approach over several popular existing algorithms. Applications of our approach to yeast, Arabidopsis and human cancer microarray data reveal many interesting modules, including a fatal subtype of lymphoma and a gene module regulating yeast telomere integrity, which were missed by the existing methods.</p> <p>Conclusions</p> <p>We demonstrated that our novel approach is very effective in discovering the modular structures in microarray data, both for genes and for samples. As the method is essentially parameter-free, it may be applied to large data sets where the number of clusters is difficult to estimate. The method is also very general and can be applied to other types of data. A MATLAB implementation of our algorithm can be downloaded from <url>http://cs.utsa.edu/~jruan/Software.html</url>.</p

Gene expression profiling of primary cultures of ovarian epithelial cells identifies novel molecular classifiers of ovarian cancer

In order to elucidate the biological variance between normal ovarian surface epithelial (NOSE) and epithelial ovarian cancer (EOC) cells, and to build a molecular classifier to discover new markers distinguishing these cells, we analysed gene expression patterns of 65 primary cultures of these tissues by oligonucleotide microarray. Unsupervised clustering highlights three subgroups of tumours: low malignant potential tumours, invasive solid tumours and tumour cells derived from ascites. We selected 18 genes with expression profiles that enable the distinction of NOSE from these three groups of EOC with 92% accuracy. Validation using an independent published data set derived from tissues or primary cultures confirmed a high accuracy (87–96%). The distinctive expression pattern of a subset of genes was validated by quantitative reverse transcription–PCR. An ovarian-specific tissue array representing tissues from NOSE and EOC samples of various subtypes and grades was used to further assess the protein expression patterns of two differentially expressed genes (Msln and BMP-2) by immunohistochemistry. This study highlights the relevance of using primary cultures of epithelial ovarian cells as a model system for gene profiling studies and demonstrates that the statistical analysis of gene expression profiling is a useful approach for selecting novel molecular tumour markers

The Public Repository of Xenografts enables discovery and randomized phase II-like trials in mice

More than 90% of drugs with preclinical activity fail in human trials, largely due to insufficient efficacy. We hypothesized that adequately powered trials of patient-derived xenografts (PDX) in mice could efficiently define therapeutic activity across heterogeneous tumors. To address this hypothesis, we established a large, publicly available repository of well-characterized leukemia and lymphoma PDXs that undergo orthotopic engraftment, called the Public Repository of Xenografts (PRoXe). PRoXe includes all de-identified information relevant to the primary specimens and the PDXs derived from them. Using this repository, we demonstrate that large studies of acute leukemia PDXs that mimic human randomized clinical trials can characterize drug efficacy and generate transcriptional, functional, and proteomic biomarkers in both treatment-naive and relapsed/refractory disease

HYPOXIC STRESS, HEPATOCYTES AND CACO-2 VIABILITY AND SUSCEPTIBILITY TO Shigella flexneri INVASION

SUMMARY Inflammation due to Shigella flexneri can cause damage to the colonic mucosa and cell death by necrosis and apoptosis. This bacteria can reach the bloodstream in this way, and the liver through portal veins. Hypoxia is a condition present in many human diseases, and it may induce bacterial translocation from intestinal lumen. We studied the ability of S. flexneri to invade rat hepatocytes and Caco-2 cells both in normoxic and hypoxic microenvironments, as well as morphological and physiological alterations in these cells after infection under hypoxia. We used the primary culture of rat hepatocytes as a model of study. We analyzed the following parameters in normoxic and hypoxic conditions: morphology, cell viability, bacterial recovery and lactate dehydrogenase (LDH) released. The results showed that there were fewer bacteria within the Caco-2 cells than in hepatocytes in normoxic and hypoxic conditions. We observed that the higher the multiplicity of infection (MOI) the greater the bacterial recovery in hepatocytes. The hypoxic condition decreased the bacterial recovery in hepatocytes. The cytotoxicity evaluated by LDH released by cells was significantly higher in cells submitted to hypoxia than normoxia. Caco-2 cells in normoxia released 63% more LDH than hepatocytes. LDH increased 164% when hepatocytes were submitted to hypoxia and just 21% when Caco-2 cells were in the same condition. The apoptosis evaluated by Tunel was significantly higher in cells submitted to hypoxia than normoxia. When comparing hypoxic cells, we obtained more apoptotic hepatocytes than apoptotic Caco-2 cells. Concluding our results contribute to a better knowledge of interactions between studied cells and Shigella flexneri. These data may be useful in the future to define strategies to combat this virulent pathogen