Iranian Dietary Patterns and Risk of Colorectal Cancer

Background: Role of diet on colorectal cancer (CRC) has been considered in terms of single foods and nutrients, but less frequently in terms of dietary patterns in Iran. The objective of this study was to determine the association between Iranian dietary patterns and CRC. Methods: This case-control study was conducted in four hospitals in Tabriz City of Iran including 414 participants aged 35-75 years: 207 cases with CRC confirmed by pathology and colonoscopy findings were selected and 207 controls free of neoplastic conditions and diet-related chronic diseases (from the same hospital at the same period for the cases). Dietary data were assessed using a 123-item semi-quantitative food frequency questionnaire. Two dietary patterns were found by using of Principal Component Analysis (PCA) method;"Healthy pattern" and "Iranian pattern". Multivariate logistic regression analysis was used to estimate adjusted odds ratios (OR) for relationship between dietary patterns and colorectal cancer. Results: After adjusting for confounding factors, the Iranian dietary pattern was significantly associated with an increased odds of colorectal cancer (OR=1.46; 95 Confidenec Interval (CI)=1.05-2.19) while a reduced odds of colorectal cancer was observed with the Healthy dietary pattern (OR=0.18; 95 CI=0.091-0.47). Conclusion: Iranian dietary pattern (IDP) seems to increase the odds of colorectal cancer and protective effect of Healthy dietary pattern

The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario

Conducting data analysis tasks rarely occur in isolation. Especially in intelligence analysis scenarios where different experts contribute knowledge to a shared understanding, members must communicate how insights develop to establish common ground among collaborators. The use of provenance to communicate analytic sensemaking carries promise by describing the interactions and summarizing the steps taken to reach insights. Yet, no universal guidelines exist for communicating provenance in different settings. Our work focuses on the presentation of provenance information and the resulting conclusions reached and strategies used by new analysts. In an open-ended, 30-minute, textual exploration scenario, we qualitatively compare how adding different types of provenance information (specifically data coverage and interaction history) affects analysts' confidence in conclusions developed, propensity to repeat work, filtering of data, identification of relevant information, and typical investigation strategies. We see that data coverage (i.e., what was interacted with) provides provenance information without limiting individual investigation freedom. On the other hand, while interaction history (i.e., when something was interacted with) does not significantly encourage more mimicry, it does take more time to comfortably understand, as represented by less confident conclusions and less relevant information-gathering behaviors. Our results contribute empirical data towards understanding how provenance summarizations can influence analysis behaviors.Comment: to be published in IEEE Vis 202

Prevalence of legionella species in water resources of Iran: A systematic review and meta-analysis

Background: Legionella species are ubiquitous and naturally found in lakes, rivers, streams and hot springs, and other water resources. The present study aimed to investigate the prevalence of Legionella species in water resources of Iran by a systematic review and meta-analysis. Methods: In search of papers relevant to the prevalence of Legionella in water resources of Iran, the scientific information database in both English and Persian languages was used. The search was limited to studies between the year 2000 and end of July 2016. Each cohort and cross-sectional study that reported the contamination of water with Legionella was included in the present study. For data analysis, comprehensive meta-analysis software with Cochran�s Q and I2 tests were used. P values less than 0.05 were considered statistically significant. Results: The prevalence of Legionella species in water resources of Iran was 27.3 (95 CI: 25.3-29.3). The prevalence of Legionella spp. in hospital water, dental settings water, and other water resources were 28.8 (95 CI: 26.4-31.2), 23.6 (95 CI: 16.1-33.2), and 29.6 (95 CI: 25.6-33.8), respectively. The most common Legionella species was L. pneumophila with a prevalence of 60.5 (95 CI: 53.3-67.2) and the prevalence of all other species was 52.5 (95 CI: 44.7-60.2). The highest prevalence was reported in Isfahan with 55.7 (95 CI: 48.0-63.0). Conclusion: Based on the results, the prevalence rate of Legionella species in water resources of Iran was high and the most common Legionella species was L. pneumophila. © 2018, Shiraz University of Medical Sciences. All rights reserved

A Review and Analysis of the Effects of Colors of Light On the Performance of Solar Photovoltaic Panels

Peer reviewedPublisher PD

Improving the hyperpolarization of (31)p nuclei by synthetic design

Traditional (31)P NMR or MRI measurements suffer from low sensitivity relative to (1)H detection and consequently require longer scan times. We show here that hyperpolarization of (31)P nuclei through reversible interactions with parahydrogen can deliver substantial signal enhancements in a range of regioisomeric phosphonate esters containing a heteroaromatic motif which were synthesized in order to identify the optimum molecular scaffold for polarization transfer. A 3588-fold (31)P signal enhancement (2.34% polarization) was returned for a partially deuterated pyridyl substituted phosphonate ester. This hyperpolarization level is sufficient to allow single scan (31)P MR images of a phantom to be recorded at a 9.4 T observation field in seconds that have signal-to-noise ratios of up to 94.4 when the analyte concentration is 10 mM. In contrast, a 12 h 2048 scan measurement under standard conditions yields a signal-to-noise ratio of just 11.4. (31)P-hyperpolarized images are also reported from a 7 T preclinical scanner

Surface plasticity: theory and computation

Surfaces of solids behave differently from the bulk due to different atomic rearrangements and processes such as oxidation or aging. Such behavior can become markedly dominant at the nanoscale due to the large ratio of surface area to bulk volume. The surface elasticity theory (Gurtin and Murdoch in Arch Ration Mech Anal 57(4):291–323, 1975) has proven to be a powerful strategy to capture the size-dependent response of nano-materials. While the surface elasticity theory is well-established to date, surface plasticity still remains elusive and poorly understood. The objective of this contribution is to establish a thermodynamically consistent surface elastoplasticity theory for finite deformations. A phenomenological isotropic plasticity model for the surface is developed based on the postulated elastoplastic multiplicative decomposition of the surface superficial deformation gradient. The non-linear governing equations and the weak forms thereof are derived. The numerical implementation is carried out using the finite element method and the consistent elastoplastic tangent of the surface contribution is derived. Finally, a series of numerical examples provide further insight into the problem and elucidate the key features of the proposed theory. © 2017 Springer-Verlag GmbH Germany, part of Springer Natur

CFTR interactome mapping using the mammalian membrane two-hybrid high-throughput screening system

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride and bicarbonate channel in secretory epithelia with a critical role in maintaining fluid homeostasis. Mutations in CFTR are associated with Cystic Fibrosis (CF), the most common lethal autosomal recessive disorder in Caucasians. While remarkable treatment advances have been made recently in the form of modulator drugs directly rescuing CFTR dysfunction, there is still considerable scope for improvement of therapeutic effectiveness. Here, we report the application of a high-throughput screening variant of the Mammalian Membrane Two-Hybrid (MaMTH-HTS) to map the protein-protein interactions of wild-type (wt) and mutant CFTR (F508del), in an effort to better understand CF cellular effects and identify new drug targets for patient-specific treatments. Combined with functional validation in multiple disease models, we have uncovered candidate proteins with potential roles in CFTR function/CF pathophysiology, including Fibrinogen Like 2 (FGL2), which we demonstrate in patient-derived intestinal organoids has a significant effect on CFTR functional expression

Fluorescence-based high-throughput functional profiling of ligand-gated ion channels at the level of single cells

Ion channels are involved in many physiological processes and are attractive targets for therapeutic intervention. Their functional properties vary according to their subunit composition, which in turn varies in a developmental and tissue-specific manner and as a consequence of pathophysiological events. Understanding this diversity requires functional analysis of ion channel properties in large numbers of individual cells. Functional characterisation of ligand-gated channels involves quantitating agonist and drug dose-response relationships using electrophysiological or fluorescence-based techniques. Electrophysiology is limited by low throughput and high-throughput fluorescence-based functional evaluation generally does not enable the characterization of the functional properties of each individual cell. Here we describe a fluorescence-based assay that characterizes functional channel properties at single cell resolution in high throughput mode. It is based on progressive receptor activation and iterative fluorescence imaging and delivers >100 dose-responses in a single well of a 384-well plate, using α1-3 homomeric and αβ heteromeric glycine receptor (GlyR) chloride channels as a model system. We applied this assay with transiently transfected HEK293 cells co-expressing halide-sensitive yellow fluorescent protein and different GlyR subunit combinations. Glycine EC values of different GlyR isoforms were highly correlated with published electrophysiological data and confirm previously reported pharmacological profiles for the GlyR inhibitors, picrotoxin, strychnine and lindane. We show that inter and intra well variability is low and that clustering of functional phenotypes permits identification of drugs with subunit-specific pharmacological profiles. As this method dramatically improves the efficiency with which ion channel populations can be characterized in the context of cellular heterogeneity, it should facilitate systems-level analysis of ion channel properties in health and disease and the discovery of therapeutics to reverse pathological alterations

A Multi-Label Predictor for Identifying the Subcellular Locations of Singleplex and Multiplex Eukaryotic Proteins

Subcellular locations of proteins are important functional attributes. An effective and efficient subcellular localization predictor is necessary for rapidly and reliably annotating subcellular locations of proteins. Most of existing subcellular localization methods are only used to deal with single-location proteins. Actually, proteins may simultaneously exist at, or move between, two or more different subcellular locations. To better reflect characteristics of multiplex proteins, it is highly desired to develop new methods for dealing with them. In this paper, a new predictor, called Euk-ECC-mPLoc, by introducing a powerful multi-label learning approach which exploits correlations between subcellular locations and hybridizing gene ontology with dipeptide composition information, has been developed that can be used to deal with systems containing both singleplex and multiplex eukaryotic proteins. It can be utilized to identify eukaryotic proteins among the following 22 locations: (1) acrosome, (2) cell membrane, (3) cell wall, (4) centrosome, (5) chloroplast, (6) cyanelle, (7) cytoplasm, (8) cytoskeleton, (9) endoplasmic reticulum, (10) endosome, (11) extracellular, (12) Golgi apparatus, (13) hydrogenosome, (14) lysosome, (15) melanosome, (16) microsome, (17) mitochondrion, (18) nucleus, (19) peroxisome, (20) spindle pole body, (21) synapse, and (22) vacuole. Experimental results on a stringent benchmark dataset of eukaryotic proteins by jackknife cross validation test show that the average success rate and overall success rate obtained by Euk-ECC-mPLoc were 69.70% and 81.54%, respectively, indicating that our approach is quite promising. Particularly, the success rates achieved by Euk-ECC-mPLoc for small subsets were remarkably improved, indicating that it holds a high potential for simulating the development of the area. As a user-friendly web-server, Euk-ECC-mPLoc is freely accessible to the public at the website http://levis.tongji.edu.cn:8080/bioinfo/Euk-ECC-mPLoc/. We believe that Euk-ECC-mPLoc may become a useful high-throughput tool, or at least play a complementary role to the existing predictors in identifying subcellular locations of eukaryotic proteins