What is the best test to diagnose urinary tract stones?

Over the past 3 years, helical (or spiral) computerized tomography (CT) has proved the best method of testing for urinary tract stones. All reviewed studies published since mid-1998 found helical CT scan to be the safest and most accurate test. (Grade of recommendation: A, based on independent blind comparison of an appropriate spectrum of patients.

Optogenetics in primates: monkey see monkey look

Optogenetics has emerged as a powerful tool for studying the neural basis of simple behaviors in rodents and small animals. In the primate model, however, optogenetics has had limited utility because optical methods have not been able to drive behavior. Here, we report that monkeys reliably shift their gaze toward the receptive field of optically driven channelrhodopsin-2-expressing V1 neurons. This result establishes optogenetics as a viable means for the causal analysis of behavior in the primate model

When should patients with asymptomatic aortic stenosis be evaluated for valve replacement?

For patients whose echocardiograms show advanced calcification of the aortic valves, a jet velocity of > 4.0 m/s, or a progression in jet velocity of 0.3m/s/year; and for patients who have an abnormal exercise response or an impaired functional status, consider referral for valve replacement prior to the onset of symptoms (Grade of Recommendation: C)

Colour displays for categorical images

We propose a method for identifying a set of colours for displaying 2-D and 3-D categorical images when the categories are unordered labels. The principle is to find maximally distinct sets of colours. We either generate colours sequentially, to maximise the dissimilarity or distance between a new colour and the set of colours already chosen, or use a simulated annealing algorithm to find a set of colours of specified size. In both cases, we use a Euclidean metric on the perceptual colour space, CIE-LAB, to specify distances

Cloning and characterization of feline islet glucokinase

Background: Glucokinase (GK) is a metabolic enzyme encoded by the GCK gene and expressed in glucose-sensitive tissues, principally pancreatic islets cell and hepatocytes. The GK protein acts in pancreatic islets as a “glucose sensor” that couples fluctuations in the blood glucose concentration to changes in cellular function and insulin secretion. GCK and GK have proposed importance in the development and progression of diabetes mellitus and are potential therapeutic targets for diabetes treatment. The study was undertaken to determine the nucleotide sequence of feline pancreatic GK cDNA, predict the amino acid sequence and structure of the feline GK protein, and perform comparative bioinformatic analysis of feline cDNA and protein. Routine PCR techniques were used with cDNA from feline pancreas. Clones were assembled to obtain the full length cDNA. Protein prediction and modeling were performed using bioinformatic tools. Results: Full-length feline pancreatic GK cDNA contains a 1398 nucleotide coding sequence with high identity to other pancreatic GK cDNAs. The deduced 465 amino acid feline protein has 15 amino acid substitutions not found in other mammalian GK proteins but maintains high structural homology with human GK. Feline pancreatic GK is highly conserved at nucleotide and protein levels. Residues crucial for substrate binding and catalysis are completely conserved in the feline protein. Conclusion: Molecular analysis predicts that feline pancreatic GK functions similarly to other mammalian GK proteins

Squeezed States and Helmholtz Spectra

The 'classical interpretation' of the wave function psi(x) reveals an interesting operational aspect of the Helmholtz spectra. It is shown that the traditional Sturm-Liouville problem contains the simplest key to predict the squeezing effect for charged particle states.Comment: 10 pages, Latex, 3 gzip-compressed figures in figh.tar.g

An Exploratory Analysis on the Lived Experiences of First-Year Students Participating in Living Learning Communities on a College Campus

Living learning communities in higher education involve students living in a shared residence space and a faculty or staff member leading various activities. These communities have been shown to help students transition to and retain in higher education, promote higher grade point averages, and provide peer support. However, only a limited number of published studies have shown the benefits for students who may have adverse experiences because they come from diverse backgrounds. The purpose of this study was to explore the perceived social support received and the benefits of the support across a sample of first-semester living learning community students with and without risk factors who lived in different learning communities at a large four-year public university. This study used a behavior systems analysis tool to capture perceived living learning community social support. The behavior systems analysis tool allowed the researcher to explore the supports at the system level and to focus on social support which has been determined to be a predictive variable for higher education retention. Students gave reports suggesting programming had, at times, aligned with recommended practices, yet differences were found across different disciplines of living learning communities. Findings are discussed in relation to diversity of the participant and recommendations for future research is provided

An Exploratory Analysis on the Lived Experiences of First-Year Students Participating in Living Learning Communities on a College Campus

Living learning communities in higher education involve students living in a shared residence space and a faculty or staff member leading various activities. These communities have been shown to help students transition to and retain in higher education, promote higher grade point averages, and provide peer support. However, only a limited number of published studies have shown the benefits for students who may have adverse experiences because they come from diverse backgrounds. The purpose of this study was to explore the perceived social support received and the benefits of the support across a sample of first-semester living learning community students with and without risk factors who lived in different learning communities at a large four-year public university. This study used a behavior systems analysis tool to capture perceived living learning community social support. The behavior systems analysis tool allowed the researcher to explore the supports at the system level and to focus on social support which has been determined to be a predictive variable for higher education retention. Students gave reports suggesting programming had, at times, aligned with recommended practices, yet differences were found across different disciplines of living learning communities. Findings are discussed in relation to diversity of the participant and recommendations for future research is provided