The appended curve technique for deconvolutional analysis —method and validation

Deconvolutional analysis (DCA) is useful in correction of organ time activity curves (response function) for variations in blood activity (input function). Despite enthusiastic reports of applications of DCA in renal and cardiac scintigraphy, routine use has awaited an easily implemented algorithm which is insensitive to statistical noise. The matrix method suffers from the propagation of errors in early data points through the entire curve. Curve fitting or constraint methods require prior knowledge of the expected form of the results. DCA by Fourier transforms (FT) is less influenced by single data points but often suffers from high frequency artifacts which result from the abrupt termination of data acquisition at a nonzero value.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46829/1/259_2004_Article_BF00254393.pd

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science

Improving nutritional care quality in the orthopedic ward of a Septic Surgery Center by implementing a preventive nutritional policy using the Nutritional Risk Score: a pilot study.

Septic Surgery Center (SSC) patients are at a particularly high risk of protein-energy malnutrition (PEM), with a prevalence of 35-85% found in various studies. Previous collaboration between our hospital's SSC and its Clinical Nutrition Team (CNT) only focussed on patients with severe PEM. This study aimed to determine whether it was possible to improve the quality of nutritional care in septic surgery patients with help of a nutritional policy using the Nutritional Risk Score (NRS). Nutritional practices in the SSC were observed over three separate periods: in the 3 months leading up to the implementation baseline, 6 months after implementation of preventive nutritional practices, and at 3 years. The nutritional care quality indicator was the percentage of patients whose nutritional care, as prescribed by the SSC, was adapted to their specific requirements. We determined the septic surgery team's NRS completion rate and calculated the nutritional policy's impact on SSC length of stay. Data before (T <sub>0</sub> ) and after (T <sub>1</sub> + T <sub>2</sub> ) implementation of the nutritional policy were compared. Ninety-eight patients were included. The nutritional care-quality indicator improved from 26 to 81% between T <sub>0</sub> and T <sub>2</sub> . During the T <sub>1</sub> and T <sub>2</sub> audits, septic surgery nurses calculated NRS for 100% and 97% of patients, respectively. Excluding patients with severe PEM, SSC length of stay was significantly reduced by 23 days (p = 0.005). These findings showed that implementing a nutritional policy in an SSC is possible with the help of an algorithm including an easy-to-use tool like the NRS