Delayed union of femoral fractures in older rats:decreased gene expression

BACKGROUND: Fracture healing slows with age. While 6-week-old rats regain normal bone biomechanics at 4 weeks after fracture, one-year-old rats require more than 26 weeks. The possible role of altered mRNA gene expression in this delayed union was studied. Closed mid-shaft femoral fractures were induced followed by euthanasia at 0 time (unfractured) or at 1, 2, 4 or 6 weeks after fracture in 6-week-old and 12-15-month-old Sprague-Dawley female rats. mRNA levels were measured for osteocalcin, type I collagen α1, type II collagen, bone morphogenetic protein (BMP)-2, BMP-4 and the type IA BMP receptor. RESULTS: For all of the genes studied, the mRNA levels increased in both age groups to a peak at one to two weeks after fracture. All gene expression levels decreased to very low or undetectable levels at four and six weeks after fracture for both age groups. At four weeks after fracture, the younger rats were healed radiographically, but not the older rats. CONCLUSIONS: (1) All genes studied were up-regulated by fracture in both age groups. Thus, the failure of the older rats to heal promptly was not due to the lack of expression of any of the studied genes. (2) The return of the mRNA gene expression to baseline values in the older rats prior to healing may contribute to their delayed union. (3) No genes were overly up-regulated in the older rats. The slower healing response of the older rats did not stimulate a negative-feedback increase in the mRNA expression of stimulatory cytokines

Nonlinear ion-acoustic (IA) waves driven in a cylindrically symmetric flow

By employing a self-similar, two-fluid MHD model in a cylindrical geometry, we study the features of nonlinear ion-acoustic (IA) waves which propagate in the direction of external magnetic field lines in space plasmas. Numerical calculations not only expose the well-known three shapes of nonlinear structures (sinusoidal, sawtooth, and spiky or bipolar) which are observed by numerous satellites and simulated by models in a Cartesian geometry, but also illustrate new results, such as, two reversely propagating nonlinear waves, density dips and humps, diverging and converging electric shocks, etc. A case study on Cluster satellite data is also introduced.Comment: accepted by AS

Update of TTD: Therapeutic Target Database

Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds of which are targets of approved and clinical trial drugs. Knowledge of these targets and corresponding drugs, particularly those in clinical uses and trials, is highly useful for facilitating drug discovery. Therapeutic Target Database (TTD) has been developed to provide information about therapeutic targets and corresponding drugs. In order to accommodate increasing demand for comprehensive knowledge about the primary targets of the approved, clinical trial and experimental drugs, numerous improvements and updates have been made to TTD. These updates include information about 348 successful, 292 clinical trial and 1254 research targets, 1514 approved, 1212 clinical trial and 2302 experimental drugs linked to their primary targets (3382 small molecule and 649 antisense drugs with available structure and sequence), new ways to access data by drug mode of action, recursive search of related targets or drugs, similarity target and drug searching, customized and whole data download, standardized target ID, and significant increase of data (1894 targets, 560 diseases and 5028 drugs compared with the 433 targets, 125 diseases and 809 drugs in the original release described in previous paper). This database can be accessed at http://bidd.nus.edu.sg/group/cjttd/TTD.asp

An ACACB Variant Implicated in Diabetic Nephropathy Associates with Body Mass Index and Gene Expression in Obese Subjects

published_or_final_versio

Association of Adiponectin Gene Polymorphisms With Type 2 Diabetes in an African American Population Enriched for Nephropathy

OBJECTIVE—Polymorphisms in the adiponectin gene (ADIPOQ) have been associated with type 2 diabetes and diabetic nephropathy in type 1 diabetes, in mostly European-derived populations

Quantitative Analysis of Lipid Droplet Fusion: Inefficient Steady State Fusion but Rapid Stimulation by Chemical Fusogens

Lipid droplets (LDs) are dynamic cytoplasmic organelles containing neutral lipids and bounded by a phospholipid monolayer. Previous studies have suggested that LDs can undergo constitutive homotypic fusion, a process linked to the inhibitory effects of fatty acids on glucose transporter trafficking. Using strict quantitative criteria for LD fusion together with refined light microscopic methods and real-time analysis, we now show that LDs in diverse cell types show low constitutive fusogenic activity under normal growth conditions. To investigate the possible modulation of LD fusion, we screened for agents that can trigger fusion. A number of pharmacological agents caused homotypic fusion of lipid droplets in a variety of cell types. This provided a novel cell system to study rapid regulated fusion between homotypic phospholipid monolayers. LD fusion involved an initial step in which the two adjacent membranes became continuous (<10 s), followed by the slower merging (100 s) of the neutral lipid cores to produce a single spherical LD. These fusion events were accompanied by changes to the LD surface organization. Measurements of LDs undergoing homotypic fusion showed that fused LDs maintained their initial volume, with a corresponding decrease in surface area suggesting rapid removal of membrane from the fused LD. This study provides estimates for the level of constitutive LD fusion in cells and questions the role of LD fusion in vivo. In addition, it highlights the extent of LD restructuring which occurs when homotypic LD fusion is triggered in a variety of cell types

Bidirectional lipid droplet velocities are controlled by differential binding strengths of HCV Core DII protein

Host cell lipid droplets (LD) are essential in the hepatitis C virus (HCV) life cycle and are targeted by the viral capsid core protein. Core-coated LDs accumulate in the perinuclear region and facilitate viral particle assembly, but it is unclear how mobility of these LDs is directed by core. Herein we used two-photon fluorescence, differential interference contrast imaging, and coherent anti-Stokes Raman scattering microscopies, to reveal novel core-mediated changes to LD dynamics. Expression of core protein’s lipid binding domain II (DII-core) induced slower LD speeds, but did not affect directionality of movement on microtubules. Modulating the LD binding strength of DII-core further impacted LD mobility, revealing the temporal effects of LD-bound DII-core. These results for DII-core coated LDs support a model for core-mediated LD localization that involves core slowing down the rate of movement of LDs until localization at the perinuclear region is accomplished where LD movement ceases. The guided localization of LDs by HCV core protein not only is essential to the viral life cycle but also poses an interesting target for the development of antiviral strategies against HCV

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

Estimates of array and pool-construction variance for planning efficient DNA-pooling genome wide association studies

<p>Abstract</p> <p>Background</p> <p>Until recently, genome-wide association studies (GWAS) have been restricted to research groups with the budget necessary to genotype hundreds, if not thousands, of samples. Replacing individual genotyping with genotyping of DNA pools in Phase I of a GWAS has proven successful, and dramatically altered the financial feasibility of this approach. When conducting a pool-based GWAS, how well SNP allele frequency is estimated from a DNA pool will influence a study's power to detect associations. Here we address how to control the variance in allele frequency estimation when DNAs are pooled, and how to plan and conduct the most efficient well-powered pool-based GWAS.</p> <p>Methods</p> <p>By examining the variation in allele frequency estimation on SNP arrays between and within DNA pools we determine how array variance [var(e_array)] and pool-construction variance [var(e_construction)] contribute to the total variance of allele frequency estimation. This information is useful in deciding whether replicate arrays or replicate pools are most useful in reducing variance. Our analysis is based on 27 DNA pools ranging in size from 74 to 446 individual samples, genotyped on a collective total of 128 Illumina beadarrays: 24 1M-Single, 32 1M-Duo, and 72 660-Quad.</p> <p>Results</p> <p>For all three Illumina SNP array types our estimates of var(e_array) were similar, between 3-4 × 10^-4for normalized data. Var(e_construction) accounted for between 20-40% of pooling variance across 27 pools in normalized data.</p> <p>Conclusions</p> <p>We conclude that relative to var(e_array), var(e_construction) is of less importance in reducing the variance in allele frequency estimation from DNA pools; however, our data suggests that on average it may be more important than previously thought. We have prepared a simple online tool, PoolingPlanner (available at <url>http://www.kchew.ca/PoolingPlanner/</url>), which calculates the effective sample size (ESS) of a DNA pool given a range of replicate array values. ESS can be used in a power calculator to perform pool-adjusted calculations. This allows one to quickly calculate the loss of power associated with a pooling experiment to make an informed decision on whether a pool-based GWAS is worth pursuing.</p