Regulation and consequences of differential gene expression in diabetic kidney disease

DIN (diabetic nephropathy) is the leading cause of end-stage renal disease worldwide and develops in 25-40% of patients with Type 1 or Type 2 diabetes mellitus. Elevated blood glucose over long periods together with glomerular hypertension leads to progressive glomerulosclerosis and tubulointerstitial fibrosis in susceptible individuals. Central to the pathology of DIN are cytokines and growth factors such as TGF-beta (transforming growth factor beta) superfamily members, including BMPs (bone morphogenetic protein) and TGF-beta 1, which play key roles in fibrogenic responses of the kidney, including podocyte loss, mesangial cell hypertrophy, matrix accumulation and tubulointerstitial fibrosis. Many of these responses can be mimicked in in vitro models of cells cultured in high glucose. We have applied differential gene expression technologies to identify novel genes expressed in in vitro and in vivo models of DN and, importantly, in human renal tissue. By mining these datasets and probing the regulation of expression and actions of specific molecules, we have identified novel roles for molecules such as Gremlin, IHG-1 (induced in high glucose-1) and CTGF (connective tissue growth factor) in DIN and potential regulators of their bioactions.

Filling Ability and Plastic Settlement of Self-Compacting Concrete

The use of self-compacting concrete (SCC) facilitates the placing of concrete by eliminating the need for compaction by vibration. Given the highly flowable nature of such concrete, care is required to ensure excellent filling ability and adequate stability. This is especially important in deep structural members and wall elements where concrete can block the flow, segregate and exhibit bleeding and settlement which can result in local defects that can reduce mechanical properties, durability and quality of surface finish. This paper shows results of an investigation of fresh properties of self-compacting concrete, such as filling ability measured by slump flow and flow time (measured by Orimet) and plastic fresh settlement measured in a column. The SCC mixes incorporated various combinations of fine inorganic powders and admixtures. The slump flow of all SCCs was greater than 580 mm and the time in which the slumping concrete reached 500 rnm was less than 3 s. The flow time was less than 5 s. The results on SCCs were compared to a control mix. The compressive strength and splitting tensile strength of SCCs were also measured. The effects of water/powder ratio, slump and nature of the sand on the fresh settlement were also evaluated. The volume of coarse aggregate and the dosage of superphsticizer were kept constant. It can be concluded that the settlement of fresh self-compacting concrete increased with the increase in water/powder ratio and slump. The nature of sand influenced the maximum settlement.

A statistical framework for the design of microarray experiments and effective detection of differential gene expression

Motivation: Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment.