Development of a potent and selective cell penetrant Legumain inhibitor

This Letter describes the continued SAR exploration of small molecule Legumain inhibitors with the aim of developing a potent and selective in vitro tool compound. Work continued in this Letter explores the use of alternative P2-P3 linker units and the P3 group SAR which led to the identification of 10t, a potent, selective and cellularly active Legumain inhibitor. We also demonstrate that 10t has activity in both cancer cell viability and colony formation assays.

A HuGE Review and Meta-Analyses of Genetic Associations in New Onset Diabetes after Kidney Transplantation

PURPOSE: New onset diabetes after transplantation (NODAT) is a serious complication following solid organ transplantation. There is a genetic contribution to NODAT and we have conducted comprehensive meta-analysis of available genetic data in kidney transplant populations.

METHODS: Relevant articles investigating the association between genetic markers and NODAT were identified by searching PubMed, Web of Science and Google Scholar. SNPs described in a minimum of three studies were included for analysis using a random effects model. The association between identified variants and NODAT was calculated at the per-study level to generate overall significance values and effect sizes.

RESULTS: Searching the literature returned 4,147 citations. Within the 36 eligible articles identified, 18 genetic variants from 12 genes were considered for analysis. Of these, three were significantly associated with NODAT by meta-analysis at the 5% level of significance; CDKAL1 rs10946398 p = 0.006 OR = 1.43, 95% CI = 1.11-1.85 (n = 696 individuals), KCNQ1 rs2237892 p = 0.007 OR = 1.43, 95% CI = 1.10-1.86 (n = 1,270 individuals), and TCF7L2 rs7903146 p = 0.01 OR = 1.41, 95% CI = 1.07-1.85 (n = 2,967 individuals).

CONCLUSION: Evaluating cumulative evidence for SNPs associated with NODAT in kidney transplant recipients has revealed three SNPs associated with NODAT. An adequately powered, dense genome-wide association study will provide more information using a carefully defined NODAT phenotype.

Endoscopic tri-modal imaging improves detection of gastric intestinal metaplasia among a high-risk patient population in Singapore

BACKGROUND: Detection of pre-neoplastic gastric mucosal changes and early gastric cancer (EGC) by white-light endoscopy (WLE) is often difficult. In this study we investigated whether combined autofluorescence imaging (AFI) and narrow band imaging (NBI) can improve detection of pre-neoplastic lesions and early gastric cancer in high-risk patients.

PATIENTS AND METHODS: Chinese patients who were 50-years-old or above with dyspepsia were examined by both high-resolution WLE and combined AFI followed by NBI (AFI-NBI), consecutively in a prospective randomized cross-over setting, by two experienced endoscopists. The primary outcome was diagnostic ability of the two methods for patients with pre-neoplastic lesions such as intestinal metaplasia (IM) and mucosal atrophy.

RESULTS: Sixty-five patients were recruited. One patient with large advanced gastric cancer was found and excluded from the analysis. Among the remaining 64 patients, 38 (59%) had IM; of these, 26 (68%) were correctly identified by AFI-NBI (sensitivity 68%, specificity 23%) and only 13 (34%) by WLE (sensitivity 34%, specificity 65%). AFI-NBI detected more patients with IM than did WLE (p=0.011). Thirty-one patients (48%) had mucosal atrophy. Ten patients (32%) were identified by AFI-NBI (sensitivity 32%, specificity 79%) and four patients (13%) by WLE (sensitivity 13%, specificity 88%) (p=0.100). No dysplasia or EGC was found.

CONCLUSION: AFI-NBI identified significantly more patients with IM than did WLE. Our result warrants further studies to define the role of combined AFI-NBI endoscopy for detection of precancerous conditions.

Lewis Superacidic Ionic Liquids with Tricoordinate Borenium Cations

The first examples of ionic liquids based on borenium cations, [BCl2L](+), are reported. These compounds form highly Lewis acidic liquids under solvent-free conditions. Their acidity was quantified by determining the Gutmann acceptor number (AN). Extremely high ANs were recorded (up to AN=182, delta(31P)=120 ppm), demonstrating that these borenium ionic liquids are the strongest Lewis superacids reported to date, with the acidity enhanced by the ionic liquid environment.

Can publicly available webcameras and mechanical Turks be used to evaluate physical activity policy and built environment change?

Introduction: Fewer than 50% of adults and 40% of youth meet US CDC guidelines for physical activity (PA) with the built environment (BE) a culprit for limited PA. A challenge in evaluating policy and BE change is the forethought to capture a priori PA behaviors and the ability to eliminate bias in post-change environments. The present objective was to analyze existing public data feeds to quantify effectiveness of BE interventions. The Archive of Many Outdoor Scenes (AMOS) has collected 135 million images of outdoor environments from 12,000 webcams since 2006. Many of these environments have experienced BE change. Methods: One example of BE change is the addition of protected bike lanes and a bike share program in Washington, DC.Weselected an AMOS webcam that captured this change. AMOS captures a photograph from eachwebcamevery half hour.AMOScaptured the 120 webcam photographs between 0700 and 1900 during the first work week of June 2009 and the 120 photographs from the same week in 2010. We used the Amazon Mechanical Turk (MTurk) website to crowd-source the image annotation. MTurk workers were paid US$0.01 to mark each pedestrian, cyclist and vehicle in a photograph. Each image was coded 5 unique times (n=1200). The data, counts of transportation mode, was downloaded to SPSS for analysis. Results: The number of cyclists per scene increased four-fold between 2009 and 2010 (F=36.72, p=0.002). There was no significant increase in pedestrians between the two years, however there was a significant increase in number of vehicles per scene (F=16.81, p

Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments

Abstract
Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.
This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.

Evaluation of biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes mellitus: A systematic review.

BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal morbidity and mortality. Women with type 1 diabetes are considered a high-risk group for developing pre-eclampsia. Much research has focused on biomarkers as a means of screening for pre-eclampsia in the general maternal population; however, there is a lack of evidence for women with type 1 diabetes.
OBJECTIVES: To undertake a systematic review to identify potential biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes.
SEARCH STRATEGY: We searched Medline, EMBASE, Maternity and Infant Care, Scopus, Web of Science and CINAHL SELECTION CRITERIA: Studies were included if they measured biomarkers in blood or urine of women who developed pre-eclampsia and had pre-gestational type 1 diabetes mellitus Data collection and analysis A narrative synthesis was adopted as a meta-analysis could not be performed, due to high study heterogeneity.
MAIN RESULTS: A total of 72 records were screened, with 21 eligible studies being included in the review. A wide range of biomarkers was investigated and study size varied from 34 to 1258 participants. No single biomarker appeared to be effective in predicting pre-eclampsia; however, glycaemic control was associated with an increased risk while a combination of angiogenic and anti-angiogenic factors seemed to be potentially useful.
CONCLUSIONS: Limited evidence suggests that combinations of biomarkers may be more effective in predicting pre-eclampsia than single biomarkers. Further research is needed to verify the predictive potential of biomarkers that have been measured in the general maternal population, as many studies exclude women with diabetes preceding pregnancy.

Quantifying Submerged Fluvial Topography Using Hyperspatial Resolution UAS Imagery and Structure From Motion Photogrammetry.

Quantifying the topography of rivers and their associated bedforms has been a fundamental concern of fluvial geomorphology for decades. Such data, acquired at high temporal and spatial resolutions, are increasingly in demand for process-oriented investigations of flow hydraulics, sediment dynamics and in-stream habitat. In these riverine environments, the most challenging region for topographic measurement is the wetted, submerged channel. Generally, dry bed topography and submerged bathymetry are measured using different methods and technology. This adds to the costs, logistical challenges and data processing requirements of comprehensive river surveys. However, some technologies are capable of measuring the submerged topography. Through-water photogrammetry and bathymetric LiDAR are capable of reasonably accurate measurements of channel beds in clear water. Whilst the cost of bathymetric LiDAR remains high and its resolution relatively coarse, the recent developments in photogrammetry using Structure from Motion (SfM) algorithms promise a fundamental shift in the accessibility of topographic data for a wide range of settings. Here we present results demonstrating the potential of so called SfM-photogrammetry for quantifying both exposed and submerged fluvial topography at the mesohabitat scale. We show that imagery acquired from a rotary-winged Unmanned Aerial System (UAS) can be processed in order to produce digital elevation models (DEMs) with hyperspatial resolutions (c. 0.02 m) for two different river systems over channel lengths of 50-100 m. Errors in submerged areas range from 0.016 m to 0.089 m, which can be reduced to between 0.008 m and 0.053 m with the application of a simple refraction correction. This work therefore demonstrates the potential of UAS platforms and SfM-photogrammetry as a single technique for surveying fluvial topography at the mesoscale (defined as lengths of channel from c.10 m to a few hundred metres). This article is protected by copyright. All rights reserved.

Affective Instability, Childhood Trauma and Major Affective Disorders

BACKGROUND: Affective instability (AI), childhood trauma, and mental illness are linked, but evidence in affective disorders is limited, despite both AI and childhood trauma being associated with poorer outcomes. Aims were to compare AI levels in bipolar disorder I (BPI) and II (BPII), and major depressive disorder recurrent (MDDR), and to examine the association of AI and childhood trauma within each diagnostic group. METHODS: AI, measured using the Affective Lability Scale (ALS), was compared between people with DSM-IV BPI (n=923), BPII (n=363) and MDDR (n=207) accounting for confounders and current mood. Regression modelling was used to examine the association between AI and childhood traumas in each diagnostic group. RESULTS: ALS scores in descending order were BPII, BPI, MDDR, and differences between groups were significant (p<0.05). Within the BPI group any childhood abuse (p=0.021), childhood physical abuse (p=0.003) and the death of a close friend in childhood (p=0.002) were significantly associated with higher ALS score but no association was found between childhood trauma and AI in BPII and MDDR. LIMITATIONS: The ALS is a self-report scale and is subject to retrospective recall bias. CONCLUSIONS: AI is an important dimension in bipolar disorder independent of current mood state. There is a strong link between childhood traumatic events and AI levels in BPI and this may be one way in which exposure and disorder are linked. Clinical interventions targeting AI in people who have suffered significant childhood trauma could potentially change the clinical course of bipolar disorder.

Stravinsky Festival, May 10, 1972

Concert program for Stravinsky Festival, May 10, 1972

Faculty Recital, September 30, 2008

Concert program for Faculty Recital, September 30, 2008