Docosahexaenoic acid increases permeability of lipid vesicles and tumor cells

Docosahexaenoic acid (DHA), a long-chain polyunsaturated ω3 fatty acid, is tested to determine its mode of action as an anti-cancer agent. We demonstrate that DHA can increase the permeability of phospholipid vesicles, as monitored by vesicle swelling in isomolar erythritol and leakage of sequestered carboxylfluorescein, and T27A tumor cells, as monitored by swelling in isomolar erythritol and release of sequestered⁵¹Cr. DHA was incorporated into lipid vesicles as either the free fatty acid or as 1-stearoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine. DHA was incorporated into the tumor cells by fusion with vesicles made from the mixed-chain phosphatidylcholines. DHA is demonstrated here to be much more effective in increasing permeability than is oleic acid, the major unsaturated fatty acid normally found in tumor plasma membranes. It is proposed that incorporation of DHA makes tumor plasma membranes substantially more permeable, which may explain, in part, its anti-tumor properties.     

Effect of a patient management system on outcomes of total hip and knee arthroplasty

Five hundred fifty-three patients undergoing hip and knee reconstructive procedures in one institution that used a patient management system were compared with a retrospective group of 340 patients undergoing similar procedures in the same institution. All procedures were performed by one surgeon and the same patient management team. Measures of length of stay, discharge disposition, and hospital charges were recorded for all patients in each subgroup of total hip arthroplasty, revision total hip arthroplasty, total knee arthroplasty, revision total knee arthroplasty, unicompartmental knee arthroplasty, and bilateral procedures. The length of stay and hospital charges were reduced significantly in all groups, whereas the percentage of patients discharged to home was unchanged. There was no significant difference in complication rates between the two groups.     

Caries prevention

It is apparent that the use of fluoride in multiple measures has a significant impact upon the prevention of dental caries. These measures involve public health benefits of water fluoridation, professional fluoride treatments in the dental office, and the home use of effective fluoridated dentifrices, with the use of fluoride rinses and gels as adjuncts when needed. In many clinical situations, professional judgment is required to identify the most appropriate treatment measures to address the needs of individual patients.     

Single-nucleotide polymorphism in the human mu opioid receptor gene alters beta-endorphin binding and activity: possible implications for opiate addiction

Opioid drugs play important roles in the clinical management of pain, as well as in the development and treatment of drug abuse. The mu opioid receptor is the primary site of action for the most commonly used opioids, including morphine, heroin, fentanyl, and methadone. By sequencing DNA from 113 former heroin addicts in methadone maintenance and 39 individuals with no history of drug or alcohol abuse or dependence, we have identified five different single-nucleotide polymorphisms (SNPs) in the coding region of the mu opioid receptor gene. The most prevalent SNP is a nucleotide substitution at position 118 (A118G), predicting an amino acid change at a putative N-glycosylation site. This SNP displays an allelic frequency of approximately 10% in our study population. Significant differences in allele distribution were observed among ethnic groups studied. The variant receptor resulting from the A118G SNP did not show altered binding affinities for most opioid peptides and alkaloids tested. However, the A118G variant receptor binds beta-endorphin, an endogenous opioid that activates the mu opioid receptor, approximately three times more tightly than the most common allelic form of the receptor. Furthermore, beta-endorphin is approximately three times more potent at the A118G variant receptor than at the most common allelic form in agonist-induced activation of G protein-coupled potassium channels. These results show that SNPs in the mu opioid receptor gene can alter binding and signal transduction in the resulting receptor and may have implications for normal physiology, therapeutics, and vulnerability to develop or protection from diverse diseases including the addictive diseases.     

Three-dimensional stress analysis of two-ply cord-rubber composite laminates

A three-dimensional finite element model was developed to predict the structural response of two-ply cord-rubber composite laminates. The present model treats a two-ply composite as an equivalent six-ply system with rubber and cord-rubber elements using 20-node isoparametric finite elements. The accuracy of the present model is demonstrated by comparing the results to the existing alternative solutions for linear analysis. The effects of different analyses, cord orientations, rubber material models and interply rubber thickness on interply stresses are presented for ± steel cord-rubber composite laminates. The presented results of interface and interply stresses, and interply strains across the width as well as through the thickness illustrate behavior of two-ply cord-rubber composites.     

Selective Antifolates for Chemically Labeling Proteins in Mammalian Cells

Antifolate labels : Molecules that bind specifically and with high affinity to proteins can be developed into powerful tools for chemical biology. The interaction between substituted 5‐benzyl pyrimidines and dihydrofolate reductase can be exploited for chemically labeling fusion proteins in mammalian cells.

     

Small-Molecule Inhibition of the uPAR ⋅ uPA Interaction by Conformational Selection

The urokinase receptor (uPAR) is a cell surface receptor that binds to the serine protease urokinase-type plasminogen activator (uPA) with high affinity. This interaction is beneficial for extravascular fibrin clearance, but it has also been associated with a broad range of pathological conditions including cancer, atherosclerosis, and kidney disease. Here, starting with a small molecule that we previously discovered by virtual screening and cheminformatics analysis, we design and synthesize several derivatives that were tested for binding and inhibition of the uPAR ⋅ uPA interaction. To confirm the binding site and establish a binding mode of the compounds, we carried out biophysical studies using uPAR mutants, among them uPAR^H47C−N259C, a mutant previously developed to mimic the structure of uPA-bound uPAR. Remarkably, a substantial increase in potency is observed for inhibition of uPAR^H47C−N259C binding to uPA compared to wild-type uPAR, consistent with our use of the structure of uPAR in its uPA-bound state to design small-molecule uPAR ⋅ uPA antagonists. Combined with the biophysical studies, molecular docking followed by extensive explicit-solvent molecular dynamics simulations and MM-GBSA free energy calculations yielded the most favorable binding pose of the compound. Collectively, these results suggest that potent inhibition of uPAR binding to uPA with small molecules will likely only be achieved by developing small molecules that exhibit high-affinity to solution apo structures of uPAR, rather than uPA-bound structures of the receptor.     

Position computation models for high-speed train based on support vector machine approach

High-accuracy positioning is not only an essential issue for efficient running of high-speed train (HST), but also an important guarantee for the safe operation of high-speed train. Positioning error is zero when the train is passing through a balise. However, positioning error between adjacent balises is going up as the train is moving away from the previous balise. Although average speed method (ASM) is commonly used to compute the position of train in engineering, its positioning error is somewhat large by analyzing the field data. In this paper, we firstly establish a mathematical model for computing position of HST after analyzing wireless message from the train control system. Then, we propose three position computation models based on least square method (LSM), support vector machine (SVM) and least square support vector machine (LSSVM). Finally, the proposed models are trained and tested by the field data collected in Wuhan-Guangzhou high-speed railway. The results show that: (1) compared with ASM, the three models proposed are capable of reducing positioning error; (2) compared with ASM, the percentage error of LSM model is reduced by 50.2% in training and 53.9% in testing; (3) compared with LSM model, the percentage error of SVM model is further reduced by 38.8% in training and 14.3% in testing; (4) although LSSVM model performs almost the same with SVM model, LSSVM model has advantages over SVM model in terms of running time. We also put forward some online learning methods to update the parameters in the three models and better positioning accuracy is obtained. With the three position computation models we proposed, we can improve the positioning accuracy for HST and potentially reduce the number of balises to achieve the same positioning accuracy.