Bilinear Models of Parts and Appearances in Generative Adversarial Networks.

Recent advances in the understanding of Generative Adversarial Networks (GANs) have led to remarkable progress in visual editing and synthesis tasks, capitalizing on the rich semantics that are embedded in the latent spaces of pre-trained GANs. However, existing methods are often tailored to specific GAN architectures and are limited to either discovering global semantic directions that do not facilitate localized control, or require some form of supervision through manually provided regions or segmentation masks. In this light, we present an architecture-agnostic approach that jointly discovers factors representing spatial parts and their appearances in an entirely unsupervised fashion. These factors are obtained by applying a semi-nonnegative tensor factorization on the feature maps, which in turn enables context-aware local image editing with pixel-level control. In addition, we show that the discovered appearance factors correspond to saliency maps that localize concepts of interest, without using any labels. Experiments on a wide range of GAN architectures and datasets show that, in comparison to the state of the art, our method is far more efficient in terms of training time and, most importantly, provides much more accurate localized control

Cyclooxygenase activity mediates colorectal cancer cell resistance to the omega-3 polyunsaturated fatty acid eicosapentaenoic acid

Purpose The naturally-occurring omega-3 polyunsaturated fatty acid eicosapentaenoic acid (EPA) is safe, well-tolerated and inexpensive, making it an attractive anti-cancer intervention. However, EPA has only modest anti-colorectal cancer (CRC) activity, when used alone. Both cyclooxygenase (COX) isoforms metabolise EPA and are over-expressed in CRC cells. We investigated whether COX inhibition increases the sensitivity of CRC cells to growth inhibition by EPA. Methods A panel of 18 human and mouse CRC cell lines was used to characterize the differential sensitivity of CRC cells to the growth inhibitory effects of EPA. The effect of CRISPR-Cas9 genetic deletion and pharmacological inhibition of COX-1 and COX-2 on the anti-cancer activity of EPA was determined using in vitro and in vivo models. Results Genetic ablation of both COX isoforms increased sensitivity of CT26 mouse CRC cells to growth inhibition by EPA in vitro and in vivo. The non-selective COX inhibitor aspirin and the selective COX-2 inhibitor celecoxib increased sensitivity of several human and mouse CRC cell lines to EPA in vitro. However, in a MC38 mouse CRC cell tumour model, with dosing that mirrored low-dose aspirin use in humans, thereby producing significant platelet COX-1 inhibition, there was ineffective intra-tumoral COX-2 inhibition by aspirin and no effect on EPA sensitivity of MC38 cell tumours. Conclusion Cyclooxygenase inhibition by non-steroidal anti-inflammatory drugs represents a therapeutic opportunity to augment the modest anti-CRC activity of EPA. However, intra-tumoral COX inhibition is likely to be critical for this drug-nutrient interaction and careful tissue pharmacodynamic profiling is required in subsequent pre-clinical and human studies

Highly efficient synthesis of the tricyclic core of Taxol by cascade metathesis

An efficient enantioselective synthesis of the ABC tricyclic core of the anticancer drug Taxol is reported. The key step of this synthesis is a cascade metathesis reaction, which leads in one operation to the required tricycle if appropriate fine-tuning of the dienyne precursor is performed

Dynamic behavior analysis via structured rank minimization

Human behavior and affect is inherently a dynamic phenomenon involving temporal evolution of patterns manifested through a multiplicity of non-verbal behavioral cues including facial expressions, body postures and gestures, and vocal outbursts. A natural assumption for human behavior modeling is that a continuous-time characterization of behavior is the output of a linear time-invariant system when behavioral cues act as the input (e.g., continuous rather than discrete annotations of dimensional affect). Here we study the learning of such dynamical system under real-world conditions, namely in the presence of noisy behavioral cues descriptors and possibly unreliable annotations by employing structured rank minimization. To this end, a novel structured rank minimization method and its scalable variant are proposed. The generalizability of the proposed framework is demonstrated by conducting experiments on 3 distinct dynamic behavior analysis tasks, namely (i) conflict intensity prediction, (ii) prediction of valence and arousal, and (iii) tracklet matching. The attained results outperform those achieved by other state-of-the-art methods for these tasks and, hence, evidence the robustness and effectiveness of the proposed approach

Metabolic Engineering for Biocatalyst Robustness to Organic Inhibitors

Microbial production of biorenewable fuels and chemicals is often limited by inhibition of the biocatalyst, either by increasing concentrations of the product compound or by contaminant compounds in the biomass‐derived sugars. This inhibition can interfere with economically viable production. Here we discuss typical mechanisms of inhibition and methods for improving biocatalyst robustness. Inhibition often takes the form of inhibition of enzyme activity, depletion of cofactor pools, and membrane damage; methods are discussed for mitigating each of these types of inhibition. Various evolutionary schemes have been developed and implemented on a variety of inhibitory compounds, including butanol, acetic acid, furfural, and ethanol. Reverse engineering of these improved strains can provide insight into new metabolic engineering strategies

ARPES: A probe of electronic correlations

Angle-resolved photoemission spectroscopy (ARPES) is one of the most direct methods of studying the electronic structure of solids. By measuring the kinetic energy and angular distribution of the electrons photoemitted from a sample illuminated with sufficiently high-energy radiation, one can gain information on both the energy and momentum of the electrons propagating inside a material. This is of vital importance in elucidating the connection between electronic, magnetic, and chemical structure of solids, in particular for those complex systems which cannot be appropriately described within the independent-particle picture. Among the various classes of complex systems, of great interest are the transition metal oxides, which have been at the center stage in condensed matter physics for the last four decades. Following a general introduction to the topic, we will lay the theoretical basis needed to understand the pivotal role of ARPES in the study of such systems. After a brief overview on the state-of-the-art capabilities of the technique, we will review some of the most interesting and relevant case studies of the novel physics revealed by ARPES in 3d-, 4d- and 5d-based oxides.Comment: Chapter to appear in "Strongly Correlated Systems: Experimental Techniques", edited by A. Avella and F. Mancini, Springer Series in Solid-State Sciences (2013). A high-resolution version can be found at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Reviews/ARPES_Springer.pdf. arXiv admin note: text overlap with arXiv:cond-mat/0307085, arXiv:cond-mat/020850

A prospective cohort study of dietary patterns of non-western migrants in the Netherlands in relation to risk factors for cardiovascular diseases: HELIUS-Dietary Patterns

<p>Abstract</p> <p>Background</p> <p>In Western countries the prevalence of cardiovascular disease (CVD) is often higher in non-Western migrants as compared to the host population. Diet is an important modifiable determinant of CVD. Increasingly, dietary patterns rather than single nutrients are the focus of research in an attempt to account for the complexity of nutrient interactions in foods. Research on dietary patterns in non-Western migrants is limited and may be hampered by a lack of validated instruments that can be used to assess the habitual diet of non-western migrants in large scale epidemiological studies. The ultimate aims of this study are to (1) understand whether differences in dietary patterns explain differences in CVD risk between ethnic groups, by developing and validating ethnic-specific Food Frequency Questionnaires (FFQs), and (2) to investigate the determinants of these dietary patterns. This paper outlines the design and methods used in the HELIUS-Dietary Patterns study and describes a systematic approach to overcome difficulties in the assessment and analysis of dietary intake data in ethnically diverse populations.</p> <p>Methods/Design</p> <p>The HELIUS-Dietary Patterns study is embedded in the HELIUS study, a Dutch multi-ethnic cohort study. After developing ethnic-specific FFQs, we will gather data on the habitual intake of 5000 participants (18-70 years old) of ethnic Dutch, Surinamese of African and of South Asian origin, Turkish or Moroccan origin. Dietary patterns will be derived using factor analysis, but we will also evaluate diet quality using hypothesis-driven approaches. The relation between dietary patterns and CVD risk factors will be analysed using multiple linear regression analysis. Potential underlying determinants of dietary patterns like migration history, acculturation, socio-economic factors and lifestyle, will be considered.</p> <p>Discussion</p> <p>This study will allow us to investigate the contribution of the dietary patterns on CVD risk factors in a multi-ethnic population. Inclusion of five ethnic groups residing in one setting makes this study highly innovative as confounding by local environment characteristics is limited. Heterogeneity in the study population will provide variance in dietary patterns which is a great advantage when studying the link between diet and disease.</p