Is medical research informing professional practice more highly cited? Evidence from AHFS DI Essentials in drugs.com

Scientometrics - Citation-based indicators are often used to help evaluate the impact of published medical studies, even though the research has the ultimate goal of improving human wellbeing. One...     

Exploring a Local Linear Model Tree Approach to Car‐Following

Because car‐following (CF) models are fundamental to replicating traffic flow they have received considerable attention over the last 50 years. They are in a continuous state of improvement due to their significant role in traffic microsimulations, intelligent transportation systems, and safety engineering models. This article uses the local linear model tree (LOLIMOT) approach to model driver's CF behavior to incorporate human perceptual imperfections into a CF model. This model defines some localities in the input space. These localities are fuzzy and have overlaps with each other. Specific models for each of the localities are then defined and combined in a fuzzy manner to predict the final output. The model was developed using real world dynamic data sets. Three different data sets were used for training, testing, and validating the model. The performance of the model was compared to a number of existing CF models. The results showed very close agreement between the real data and the LOLIMOT outputs.     

Recurrence of steroid-resistant nephrotic syndrome in kidney transplants is associated with increased acute renal failure and acute rejection

We performed 73 kidney transplants in 51 patients with steroid-resistant nephrotic syndrome (SRNS) with focal segmental glomerular sclerosis (FSG) ages 18.4 +/- 12.8 (mean +/- SD) years. Recurrence of SRNS, defined by rapid onset of proteinuria, hypoalbuminemia and/or > 95% epithelial cell foot process effacement with or without the presence of FSG, occurred in 26 grafts in 16 patients. Acute renal failure (ARF) occurred in 16 of 26 (61.5%) grafts with recurrence versus 7 of 47 (14.9%) grafts without recurrence (P < 0.0001). ARF occurred in 4 of 9 (44.4%) living-related donor (LRD) recipients with recurrence and 3 of 21 (12.5%) LRD recipients without recurrence (NS). ARF in cadaver donor (CAD) recipients with recurrence was 12 of 17 (70.5%) versus 4 of 23 (17.4%) without recurrence (P < 0.0001). ARF was also higher in LRD or CAD with recurrence than in a control group of non-SRNS patients matched for age, sex and time of transplantation. Graft survival at one year was lower in patients with recurrence and ARF [4 of 16 (25%)] compared to patients with recurrence and no ARF [9 of 11 (82%), P < 0.01]. There was no difference in graft survival in patients without recurrence who did or did not have ARF. One or more acute rejection episodes occurred in all 16 patients with ARF and recurrence, in all 7 patients with ARF without recurrence, and in 7 of 10 patients with recurrence without ARF compared with only 11 of 40 (28%) of patients with neither recurrence nor ARF (P < 0.0001, < 0.001 and < 0.04, respectively).(ABSTRACT TRUNCATED AT 250 WORDS)     

Effect of early cyclosporine levels on kidney allograft rejection

Experiments were performed on strips of mouse stomach and urinary bladder to characterize the receptors involved in the contractile responses of these tissues to neurokinins (substance P (SP), neurokinin A (NKA), neurokinin B (NKB), and neuropeptide gamma (NP gamma). The neurokinin receptors were characterized by using assays with selective agonists as well as peptide and nonpeptide antagonists and by applying the two Schild criteria for receptor classification, namely, the order of potency of agonists and the apparent affinity of competitive antagonists. The mouse stomach contains primarily NK1 and NK2 functional sites and possibly some NK3 receptors, whereas the urinary bladder possesses only the NK2 receptor. The rank order of potency of agonists in the stomach is Ac[Arg6,Sar9,Met(O2)11]SP-(6-11) > NKA > SP > [beta-Ala8]NKA-(4-10) > NKB > [MePhe7]NKB. Among the selective agonists, Ac[Arg6,Sar9,Met(O2)11]SP-(6-11) is more active than SP and [Sar9,Met(O2)11]SP on the NK1 receptor, whereas the order of potency on the NK2 receptor is NKA > NP gamma > or = [beta-Ala8]NKA-(4-10) > [Nle10]NKA-(4-10). The order of potency of agonists in the bladder is NP gamma > NKA > [beta-Ala8]NKA-(4-10). The myotropic responses mediated by NK1 selective agonists are blocked by SR 140333 (pA2 8.57) and those mediated by the NK2 selective agonists are inhibited by SR 48968 (pA2 9.05). RP 67580 (pA2 8.41) is more active than CP 99994 (pA2 6.06) on the mouse NK1 receptor. The NK1 receptor of the mouse shows, therefore, a pharmacological profile similar to that of the NK1 receptor of the rat. Similarly, MEN 10627 (pA2 9.20) is more active than R 396 (pA2 6.21), suggesting that the mouse NK2 receptor is similar to that of the rabbit. The mouse NK2 receptor of the urinary bladder shows similarity with that of the stomach, but is less sensitive to [beta-Ala8]NKA-(4-10).     

Surface wavelength content based clustering using neural networks for manufacturing process mapping

Manufacturing processes produce a unique texture on the surface that serves as a fingerprint of the process. It is possible to provide feedback to the process by studying the surfaces carefully. Analytical techniques such as Fourier analysis and digital filters are commonly used to characterize surface profiles. Parameters extracted from filtered profiles are monitored to detect variations in the process. This requires the development of an inference engine to map metrology parameters to manufacturing process parameters. This paper presents an artificial neural network (ANN) based inference engine for providing process feedback with surface finish input. Parameters such as R_a and W_a as well as advanced wavelet based features are extracted from surface finish data collected from a crankshaft manufacturing line and fed as input to the neural network. This input is then clustered using a competitive neural network trained in unsupervised mode. The resulting clusters are analyzed and discussed. The network is then tested with new data to evaluate the quality of the clusters previously generated and to demonstrate the applicability of this technique for detecting process variations.     

Development of a Simple Phosphorus Model for a Large Urban Watershed: A Case Study

Often, the initiation of a total maximum daily load (TMDL) program is delayed until intensive monitoring data can be collected—even in watersheds where large historical data sets exist. This paper provides a case study of a modeling effort that utilizes available historical data to fulfill an intermediate goal of a TMDL program for the Passaic River Basin. The subject model is developed to simulate total phosphorus concentrations (and loads) within the basin’s effluent-dominated streams. The model is based on the assumption that the primary process controlling in-stream total phosphorus concentrations is the dilution of the cumulative upstream effluent load—which was computed on a continuous (daily) basis. Model comparisons indicate a generally good fit to long-term river-monitoring data at several key sites. Model results, and data analyses, suggest that secondary processes have a relatively minor impact on total phosphorus (TP) concentrations in this relatively large, urbanized system. This finding is consistent with a previous QUAL2E model study of the system, and consistent with the relatively conservative behavior of TP reported in many medium-to-large river systems throughout the United States. Model results are used to facilitate TMDL planning efforts for a major water supply reservoir in the basin.     

Accessing Video Contents through Key Objects over IP

In order to support content-based video database access over the Internet Protocol (IP), achieving the following objectives are important: (i) video query by a representative object (key object) or some statistical characterization of the target contents, (ii) bandwidth-efficient browsing over IP, and (iii) scalable and user-centric video transmission over a heterogeneous and variable-bandwidth network. We present a video object extraction and scalable coding system designed to meet the above objectives. In our system, key objects of meaning to video database users are generated via a human-computer-interaction procedure, and are tracked across frames. Given a key object, an algorithm classifies a subset of its VOPs as key VOPs. This subset forms the basis of a highly bandwidth-efficient base layer for supporting activities such as browsing and refining queries. Over the base layer, a number of enhancement layers can be defined to progressively increase the spatial and temporal resolutions of retrieved video. It is expected that heterogeneous users can subscribe to different numbers of the enhancement layers according to their own conditions, such as access authorization, available connection bandwidth, and quality preference.     

A Fixed-Distribution PAC Learning Theory for Neural FIR Models

The PAC learning theory creates a framework to assess the learning properties of static models. This theory has been extended to include learning of modeling tasks with m-dependent data given that the data are distributed according to a uniform distribution. The extended theory can be applied for learning of nonlinear FIR models with the restriction that the data are unformly distributed. In this paper, The PAC learning scheme is extended to deal with any FIR model regardless of the distribution of the data. This fixed-distribution m-dependent extension of the PAC learning theory is then applied to the learning of FIR three-layer feedforward sigmoid neural networks.     

Cover Picture: Functionalized Gold Nanoparticles Mimic Catalytic Activity of a Polysiloxane‐Synthesizing Enzyme (Adv. Mater. 10/2005)

A system that acts as a biomimetic of the silica‐synthesizing enzyme found in a marine sponge is reported by Morse and co‐workers on p. 1234. Gold nanoparticles (GNPs) are functionalized with the same organic moieties that are found in the enzyme's catalytic site. Interaction between the nucleophilic (OH‐terminated) and hydrogen‐bonding (imidazole‐terminated) GNPs, as shown on the cover, is required for the hydrolysis of a silicon alkoxide precursor and subsequent polycondensation to form silica at a low temperature and near‐neutral pH. Replacement of either of the required functional groups by a non‐reactive methyl group abolishes catalysis in this synthetic system, as it does in the biological enzyme. Cover art provided by Peter Allen.