Conservation of soil water by gravel mulches

September 1968.Includes bibliographical references (page 23)

Performance of Centargo:A Novel Piston-Based Injection System for High Throughput in CE CT

PURPOSE: To compare an investigational device (MEDRAD(®) Centargo CT Injection System, “Centargo”) to the currently available MEDRAD(®) Stellant CT Injection System (“Stellant”), in terms of efficiency, injector performance, and user satisfaction. PATIENTS AND METHODS: A total of 425 patients at two sites were enrolled; 198 patients in phase one, a randomized study (98 Stellant and 100 Centargo). The second observational phase included 227 patients who were injected with Centargo. Phase one recorded times for setup, disassembly, and patient changeovers. Demographic data, subjective image quality, and injection parameters were collected. Phase two assessed usability via a questionnaire provided to all end-users of both systems (radiographers). RESULTS: Patient changeover times were statistically significantly faster with Centargo (15.4s ± 8.7s vs 53.7s ± 19.6s, p < 0.001). Centargo day-setup times were similar to Stellant (138.1s ± 92s vs 151.8s ± 30.6s, p = 0.33) and end-of-day-disassembly times were significantly slower (60.6s ± 27s vs 17.1s ± 12.9s, p < 0.001). Based on four different scenarios modelling patient throughput, the projected time savings with Centargo over Stellant was 40–63%, with the highest efficiency improvements for higher throughputs and the use of larger contrast medium bottles. Both Centargo and Stellant usability averaged between “Very Easy” and “Easy” in all responses to the questionnaire. There were no instances of interrupted injections due to communication loss or detected air and no insufficient images due to injector performance. No safety issues were identified. CONCLUSION: Centargo was able to demonstrate improved efficiency as compared to Stellant while maintaining injector performance and high usability scores

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

International audienceCellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program

Abstract Capturing intraoperative deformations: research experience at Brigham and WomenÕs hospital

During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patientÕs brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and WomenÕs Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy. Ó 2004 Elsevier B.V. All rights reserved