Rational design of the inlet configuration of flow systems for enhanced mixing

Funder: Chinese Government Scholarship; doi: http://dx.doi.org/10.13039/501100010890Funder: Cambridge Overseas Trust; doi: http://dx.doi.org/10.13039/501100003341AbstractHigh mass transfer rate is a key advantage of microreactors however, under their characteristic laminar flow, it is dominated by slow diffusion rather than fast convection. In this paper, we demonstrate how the configuration of the inlet, i.e. mixers, can promote different flow patterns to greatly enhance mixing efficiency downstream. A systematic evaluation and comparison of different widely adopted mixers as well as advanced designs is presented using a combination of computational fluid dynamics (CFD) and backward particle tracking to accurately calculate diffusion, in the absence of numerical diffusion (false diffusion). In the method, the convection contributed concentration profile is obtained by tracking sampling points from a cross-sectional plane to the inlet point, and diffusion is estimated subsequently. In conventional T- and Y-mixers, the shape of channel, circular or square, is key with only the latter promoting engulfment flow. In cyclone mixers, the resulting average inlet velocity, independent of Reynolds number or geometry, is the dominating design parameter to predict mixing efficiency. This work will serve as a guideline for the design of efficient flow systems with predicted mixing as a way of maximising selectivity and product quality.</jats:p

Comparison of Sentiment Analysis and User Ratings in Venue Recommendation

Venue recommendation aims to provide users with venues to visit, taking into account historical visits to venues. Many venue recommendation approaches make use of the provided users’ ratings to elicit the users’ preferences on the venues when making recommendations. In fact, many also consider the users’ ratings as the ground truth for assessing their recommendation performance. However, users are often reported to exhibit inconsistent rating behaviour, leading to less accurate preferences information being collected for the recommendation task. To alleviate this problem, we consider instead the use of the sentiment information collected from comments posted by the users on the venues as a surrogate to the users’ ratings. We experiment with various sentiment analysis classifiers, including the recent neural networks-based sentiment analysers, to examine the effectiveness of replacing users’ ratings with sentiment information. We integrate the sentiment information into the widely used matrix factorization and GeoSoCa multi feature-based venue recommendation models, thereby replacing the users’ ratings with the obtained sentiment scores. Our results, using three Yelp Challenge-based datasets, show that it is indeed possible to effectively replace users’ ratings with sentiment scores when state-of-the-art sentiment classifiers are used. Our findings show that the sentiment scores can provide accurate user preferences information, thereby increasing the prediction accuracy. In addition, our results suggest that a simple binary rating with ‘like’ and ‘dislike’ is a sufficient substitute of the current used multi-rating scales for venue recommendation in location-based social networks

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Seatbelt use and risk of major injuries sustained by vehicle occupants during motor-vehicle crashes: A systematic review and meta-analysis of cohort studies

BackgroundIn 2004, a World Health Report on road safety called for enforcement of measures such as seatbelt use, effective at minimizing morbidity and mortality caused by road traffic accidents. However, injuries caused by seatbelt use have also been described. Over a decade after publication of the World Health Report on road safety, this study sought to investigate the relationship between seatbelt use and major injuries in belted compared to unbelted passengers.MethodsCohort studies published in English language from 2005 to 2018 were retrieved from seven databases. Critical appraisal of studies was carried out using the Scottish Intercollegiate Guidelines Network (SIGN) checklist. Pooled risk of major injuries was assessed using the random effects meta-analytic model. Heterogeneity was quantified using I-squared and Tau-squared statistics. Funnel plots and Egger's test were used to investigate publication bias. This review is registered in PROSPERO (CRD42015020309).ResultsEleven studies, all carried out in developed countries were included. Overall, the risk of any major injury was significantly lower in belted passengers compared to unbelted passengers (RR 0.47; 95%CI, 0.29 to 0.80; I-2=99.7; P=0.000). When analysed by crash types, belt use significantly reduced the risk of any injury (RR 0.35; 95%CI, 0.24 to 0.52). Seatbelt use reduces the risk of facial injuries (RR=0.56, 95% CI=0.37 to 0.84), abdominal injuries (RR=0.87; 95% CI=0.78 to 0.98) and, spinal injuries (RR=0.56, 95% CI=0.37 to 0.84). However, we found no statistically significant difference in risk of head injuries (RR=0.49; 95% CI=0.22 to 1.08), neck injuries (RR=0.69: 95%CI 0.07 to 6.44), thoracic injuries (RR 0.96, 95%CI, 0.74 to 1.24), upper limb injuries (RR=1.05, 95%CI 0.83 to 1.34) and lower limb injuries (RR=0.77, 95%CI 0.58 to 1.04) between belted and non-belted passengers.ConclusionIn sum, the risk of most major road traffic injuries is lower in seatbelt users. Findings were inconclusive regarding seatbelt use and susceptibility to thoracic, head and neck injuries during road traffic accidents. Awareness should be raised about the dangers of inadequate seatbelt use. Future research should aim to assess the effects of seatbelt use on major injuries by crash type

Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential

BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control

Anthropometric measures in relation to Basal Cell Carcinoma: a longitudinal study

BACKGROUND: The relationship between anthropometric indices and risk of basal cell carcinoma (BCC) is largely unknown. We aimed to examine the association between anthropometric measures and development of BCC and to demonstrate whether adherence to World Health Organisation guidelines for body mass index, waist circumference, and waist/hip ratio was associated with risk of BCC, independent of sun exposure. METHODS: Study participants were participants in a community-based skin cancer prevention trial in Nambour, a town in southeast Queensland (latitude 26°S). In 1992, height, weight, and waist and hip circumferences were measured for all 1621 participants and weight was remeasured at the end of the trial in 1996. Prevalence proportion ratios were calculated using a log-binomial model to estimate the risk of BCC prior to or prevalent in 1992, while Poisson regression with robust error variances was used to estimate the relative risk of BCC during the follow-up period. RESULTS: At baseline, 94 participants had a current BCC, and 202 had a history of BCC. During the 5-year follow-up period, 179 participants developed one or more new BCCs. We found no significant association between any of the anthropometric measures or indices and risk of BCC after controlling for potential confounding factors including sun exposure. There was a suggestion that short-term weight gain may increase the risk of developing BCC for women only. CONCLUSION: Adherence to World Health Organisation guidelines for body mass index, waist circumference and waist/hip ratio is not significantly associated with occurrence of basal cell carcinomas of the skin

LRP16 Integrates into NF-κB Transcriptional Complex and Is Required for Its Functional Activation

BACKGROUND: Nuclear factor κB (NF-κB)-mediated pathways have been widely implicated in cell survival, development and tumor progression. Although the molecular events of determining NF-κB translocation from cytoplasm to nucleus have been extensively documented, the regulatory mechanisms of NF-κB activity inside the nucleus are still poorly understood. Being a special member of macro domain proteins, LRP16 was previously identified as a coactivator of both estrogen receptor and androgen receptor, and as an interactor of NF-κB coactivator UXT. Here, we investigated the regulatory role of LRP16 on NF-κB activation. METHODOLOGY: GST pull-down and coimmunoprecipitation (CoIP) assays assessed protein-protein interactions. The functional activity of NF-κB was assessed by luciferase assays, changes in expression of its target genes, and its DNA binding ability. Annexin V staining and flow cytometry analysis were used to evaluate cell apoptosis. Immunohistochemical staining of LRP16 and enzyme-linked immunosorbent assay-based evaluation of active NF-κB were performed on primary human gastric carcinoma samples. RESULTS: We demonstrate that LRP16 integrates into NF-κB transcriptional complex through associating with its p65 component. RNA interference knockdown of the endogenous LRP16 in cells leads to impaired NF-κB activity and significantly attenuated NF-κB-dependent gene expression. Mechanistic analysis revealed that knockdown of LRP16 did not affect tumor necrosis factor α (TNF-α)-induced nuclear translocation of NF-κB, but blunted the formation or stabilization of functional NF-κB/p300/CREB-binding protein transcription complex in the nucleus. In addition, knockdown of LRP16 also sensitizes cells to apoptosis induced by TNF-α. Finally, a positive link between LRP16 expression intensity in nuclei of tumor cells and NF-κB activity was preliminarily established in human gastric carcinoma specimens. CONCLUSIONS: Our findings not only indicate that LRP16 is a crucial regulator for NF-κB activation inside the nucleus, but also suggest that LRP16 may be an important contributor to the aberrant activation of NF-κB in tumors

The virtual supermarket: An innovative research tool to study consumer food purchasing behaviour

<p>Abstract</p> <p>Background</p> <p>Economic interventions in the food environment are expected to effectively promote healthier food choices. However, before introducing them on a large scale, it is important to gain insight into the effectiveness of economic interventions and peoples' genuine reactions to price changes. Nonetheless, because of complex implementation issues, studies on price interventions are virtually non-existent. This is especially true for experiments undertaken in a retail setting. We have developed a research tool to study the effects of retail price interventions in a virtual-reality setting: the Virtual Supermarket. This paper aims to inform researchers about the features and utilization of this new software application.</p> <p>Results</p> <p>The Virtual Supermarket is a Dutch-developed three-dimensional software application in which study participants can shop in a manner comparable to a real supermarket. The tool can be used to study several food pricing and labelling strategies. The application base can be used to build future extensions and could be translated into, for example, an English-language version. The Virtual Supermarket contains a front-end which is seen by the participants, and a back-end that enables researchers to easily manipulate research conditions. The application keeps track of time spent shopping, number of products purchased, shopping budget, total expenditures and answers on configurable questionnaires. All data is digitally stored and automatically sent to a web server. A pilot study among Dutch consumers (n = 66) revealed that the application accurately collected and stored all data. Results from participant feedback revealed that 83% of the respondents considered the Virtual Supermarket easy to understand and 79% found that their virtual grocery purchases resembled their regular groceries.</p> <p>Conclusions</p> <p>The Virtual Supermarket is an innovative research tool with a great potential to assist in gaining insight into food purchasing behaviour. The application can be obtained via an URL and is freely available for academic use. The unique features of the tool include the fact that it enables researchers to easily modify research conditions and in this way study different types of interventions in a retail environment without a complex implementation process. Finally, it also maintains researcher independence and avoids conflicts of interest that may arise from industry collaboration.</p