Interventional tool tracking using discrete optimization.

This work presents a novel scheme for tracking of motion and deformation of interventional tools such as guide-wires and catheters in fluoroscopic X-ray sequences. Being able to track and thus to estimate the correct positions of these tools is crucial in order to offer guidance enhancement during interventions. The task of estimating the apparent motion is particularly challenging due to the low signal-to-noise ratio (SNR) of fluoroscopic images and due to combined motion components originating from patient breathing and tool interactions performed by the physician. The presented approach is based on modeling interventional tools with B-splines whose optimal configuration of control points is determined through efficient discrete optimization. Each control point corresponds to a discrete random variable in a Markov random field (MRF) formulation where a set of labels represents the deformation space. In this context, the optimal curve corresponds to the maximum a posteriori (MAP) estimate of the MRF energy. The main motivation for employing a discrete approach is the possibility to incorporate a multi-directional search space which is robust to local minima. This is of particular interest for curve tracking under large deformation. This work analyzes feasibility of employing efficient first-order MRFs for tracking. In particular it shows how to achieve a good compromise between energy approximations and computational efficiency. Experimental results suggest to define both the external and internal energy in terms of pairwise potential functions. The method was successfully applied to the tracking of guide-wires in fluoroscopic X-ray sequences of several hundred frames which requires extremely robust techniques. Comparisons with state-of-the-art guide-wire tracking algorithms confirm the effectiveness of the proposed method. © 1982-2012 IEEE

Transcriptional Regulation of N-Acetylglutamate Synthase

The urea cycle converts toxic ammonia to urea within the liver of mammals. At least 6 enzymes are required for ureagenesis, which correlates with dietary protein intake. The transcription of urea cycle genes is, at least in part, regulated by glucocorticoid and glucagon hormone signaling pathways. N-acetylglutamate synthase (NAGS) produces a unique cofactor, N-acetylglutamate (NAG), that is essential for the catalytic function of the first and rate-limiting enzyme of ureagenesis, carbamyl phosphate synthetase 1 (CPS1). However, despite the important role of NAGS in ammonia removal, little is known about the mechanisms of its regulation. We identified two regions of high conservation upstream of the translation start of the NAGS gene. Reporter assays confirmed that these regions represent promoter and enhancer and that the enhancer is tissue specific. Within the promoter, we identified multiple transcription start sites that differed between liver and small intestine. Several transcription factor binding motifs were conserved within the promoter and enhancer regions while a TATA-box motif was absent. DNA-protein pull-down assays and chromatin immunoprecipitation confirmed binding of Sp1 and CREB, but not C/EBP in the promoter and HNF-1 and NF-Y, but not SMAD3 or AP-2 in the enhancer. The functional importance of these motifs was demonstrated by decreased transcription of reporter constructs following mutagenesis of each motif. The presented data strongly suggest that Sp1, CREB, HNF-1, and NF-Y, that are known to be responsive to hormones and diet, regulate NAGS transcription. This provides molecular mechanism of regulation of ureagenesis in response to hormonal and dietary changes

A Prospective Study of Return to Work Across Health Conditions: Perceived Work Attitude, Self-efficacy and Perceived Social Support

Background The aim of the present study was to conduct subgroup-analyses in a prospective cohort of workers on long-term sickness absence to investigate whether associations between perceived work attitude, self-efficacy and perceived social support and time to RTW differ across different health conditions. Methods The study was based on a sample of 926 workers on sickness absence (6–12 weeks). The participants filled out a baseline questionnaire and were subsequently followed until the tenth month after listing sick. Perceived work attitude was measured with a Dutch language version of the Work Involvement Scale. Perceived social support was measured with a self-constructed standardized scale reflecting a person’s perception of social support regarding RTW. Self-efficacy was measured with the standardised Dutch version of the General self-efficacy scale, assessing the subjects’ expectations of their general capacities. The sample was divided into three subgroups: musculoskeletal health conditions, other physical health conditions and mental health conditions. Anova analyses and Cox proportional hazards regression analyses were used to identify differences in association between the three factors and the time to RTW between different subgroups. Results The associations between the perceived work attitude, self-efficacy and perceived social support and the time to RTW vary across different health condition subgroups, not only with regard to the strength of the association but also for the type of factor. In the multivariate model, hazard ratios (HRs) of 1.33 (95% CI 1.01–1.75) in the musculoskeletal subgroup, and 1.26 (95% CI 0.89–1.78) in the other physical subgroup were found in perceived work attitude. With regard to perceived social support HRs of 1.39 (95% CI 1.12–1.99) respectively 1.51 (1.05–2.17) in the same subgroups were found. Only self-efficacy remained in the multivariate model in all subgroups with HRs of 1.49 (95% CI 1.12–1.99) in the musculoskeletal subgroup, 1.53 (95% CI 1.07–2.18) in the other physical subgroup and 1.60 (1.07–2.40) in the mental subgroup. Conclusions The results of this study show that perceived work attitude, self-efficacy and perceived social support are relevant predictors with regard to the time to RTW in all types of health conditions, but that important differences are observed in type of factor and strengths of the relationships between physical and mental health conditions