Anti-Diabetic Drugs: Cure or Risk Factors for Cancer?

Anti-diabetic drugs are an important group of therapeutics used worldwide. Different anti-diabetic drugs lower blood glucose level by different mechanisms. In recent years, numerous investigations have been performed based on both comparative and cohort studies, in order to establish the relationship between anti-diabetic pharmacotherapy and cancer incidence as well as mortality due to cancer. Some anti-diabetic drugs have been found to exhibit anti-cancer activity while others might increase the risk for cancer. The underlying cause for this disparity is likely to be the varying mechanisms of action of these drugs in controlling blood glucose level. This review discusses the various carcinogenic and/or anti-cancer effects of commonly used anti-diabetic drugs. The information is vital in view of the fact that diabetes mellitus is a commonly occurring disease with a rising incidence rate.     

Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches

The degree of stenosis in the carotid artery can be predicted using automated carotid lumen diameter (LD) measured from B-mode ultrasound images. Systolic velocity-based methods for measurement of LD are subjective. With the advancement of high resolution imaging, image-based methods have started to emerge. However, they require robust image analysis for accurate LD measurement. This paper presents two different algorithms for automated segmentation of the lumen borders in carotid ultrasound images. Both algorithms are modeled as a two stage process. Stage one consists of a global-based model using scale-space framework for the extraction of the region of interest. This stage is common to both algorithms. Stage two is modeled using a local-based strategy that extracts the lumen interfaces. At this stage, the algorithm-1 is modeled as a region-based strategy using a classification framework, whereas the algorithm-2 is modeled as a boundary-based approach that uses the level set framework. Two sets of databases (DB), Japan DB (JDB) (202 patients, 404 images) and Hong Kong DB (HKDB) (50 patients, 300 images) were used in this study. Two trained neuroradiologists performed manual LD tracings. The mean automated LD measured was 6.35 ± 0.95 mm for JDB and 6.20 ± 1.35 mm for HKDB. The precision-of-merit was: 97.4 % and 98.0 % w.r.t to two manual tracings for JDB and 99.7 % and 97.9 % w.r.t to two manual tracings for HKDB. Statistical tests such as ANOVA, Chi-Squared, T-test, and Mann-Whitney test were conducted to show the stability and reliability of the automated techniques.     

Working sensitively with child sexual abuse survivors: what female child sexual abuse survivors want from health professionals

Adult survivors of child sexual abuse are high users of health and mental health services. Health professionals are well placed to improve health outcomes for them by delivering positive interventions post-abuse. The current study explored female child sexual abuse survivors' opinions on how health professionals could work better with child sexual abuse survivors. Sixty-one women, from 22-65 years old, who had been sexually abused before the age of 16 years, completed postal questionnaires in late 2004. A model was developed to guide the development of knowledge, skills, and practices for working more sensitively with child sexual abuse survivors. The model consisted of six chronological training steps: (1) knowledge on effects of child sexual abuse; (2) establishing the relationship with child sexual abuse survivors; (3) asking about child sexual abuse; (4) responding to disclosure; (5) sensitive provision of medical examinations; and (6) follow-up post examination. A systematic approach to training is proposed to assist with improving delivery of services sensitive to child sexual abuse survivor needs.     

Implementation of a universal cervical length screening program: identifying factors associated with decline rates

Purpose: Cervical length (CL) measurement is now accepted as a screening strategy for identifying women at risk for preterm birth (PTB). However, patient acceptability may limit its implementation. Our objective was to identify characteristics associated with women who decline this screening.

Materials and methods: This is a secondary analysis of a prospective cohort study of women offered UCL screening from January 2012 to June 2012. Women with a singleton gestation 18 0/7–23 6/7?weeks at the time of anatomy scan were included. Trained sonographers were instructed to perform UCL screening on all eligible patients using an “opt-out” approach. Chi square statistics and Wilcoxon rank sum tests were used to compare categorical and continuous data, where appropriate. Logistic regression was used to calculate odds ratio for factors associated with declining UCL screening

Results: 1348 women were offered CL screening; 131 (9.7%) declined. Overall, multiparous women were more than twice as likely to decline UCL screening compared to primiparous women [OR 2.4 (1.6–3.8)]. Patient acceptance of screening was significantly dependent on the sonographer (p?Conclusion: Multiparous women are less likely to accept this strategy of PTB prevention. A standardized counseling approach may improve patient acceptance and mitigate variability in acceptance rates observed amongst sonographers.     

Comprehensive framework for accurate diffusion MRI parameter estimation

During the last decade, many approaches have been proposed for improving the estimation of diffusion measures. These techniques have already shown an increase in accuracy based on theoretical considerations, such as incorporating prior knowledge of the data distribution. The increased accuracy of diffusion metric estimators is typically observed in well‐defined simulations, where the assumptions regarding properties of the data distribution are known to be valid. In practice, however, correcting for subject motion and geometric eddy current deformations alters the data distribution tremendously such that it can no longer be expressed in a closed form. The image processing steps that precede the model fitting will render several assumptions on the data distribution invalid, potentially nullifying the benefit of applying more advanced diffusion estimators. In this work, we present a generic diffusion model fitting framework that considers some statistics of diffusion MRI data. A central role in the framework is played by the conditional least squares estimator. We demonstrate that the accuracy of that particular estimator can generally be preserved, regardless the applied preprocessing steps, if the noise parameter is known a priori. To fulfill that condition, we also propose an approach for the estimation of spatially varying noise levels. Magn Reson Med, 70:972–984, 2013. © 2012 Wiley Periodicals, Inc.