PTEN loss defines a TGF-β-induced tubule phenotype of failed differentiation and JNK signaling during renal fibrosis

We investigated the signaling basis for tubule pathology during fibrosis after renal injury. Numerous signaling pathways are activated physiologically to direct tubule regeneration after acute kidney injury (AKI) but several persist pathologically after repair. Among these, transforming growth factor (TGF)-β is particularly important because it controls epithelial differentiation and profibrotic cytokine production. We found that increased TGF-β signaling after AKI is accompanied by PTEN loss from proximal tubules (PT). With time, subpopulations of regenerating PT with persistent loss of PTEN (phosphate and tension homolog) failed to differentiate, became growth arrested, expressed vimentin, displayed profibrotic JNK activation, and produced PDGF-B. These tubules were surrounded by fibrosis. In contrast, PTEN recovery was associated with epithelial differentiation, normal tubule repair, and less fibrosis. This beneficial outcome was promoted by TGF-β antagonism. Tubule-specific induction of TGF-β led to PTEN loss, JNK activation, and fibrosis even without prior AKI. In PT culture, high TGF-β depleted PTEN, inhibited differentiation, and activated JNK. Conversely, TGF-β antagonism increased PTEN, promoted differentiation, and decreased JNK activity. Cre-Lox PTEN deletion suppressed differentiation, induced growth arrest, and activated JNK. The low-PTEN state with JNK signaling and fibrosis was ameliorated by contralateral nephrectomy done 2 wk after unilateral ischemia, suggesting reversibility of the low-PTEN dysfunctional tubule phenotype. Vimentin-expressing tubules with low-PTEN and JNK activation were associated with fibrosis also after tubule-selective AKI, and with human chronic kidney diseases of diverse etiology. By preventing tubule differentiation, the low-PTEN state may provide a platform for signals initiated physiologically to persist pathologically and cause fibrosis after injury.     

Using pooled exposure assessment to improve efficiency in case-control studies

Assays can be so expensive that interesting hypotheses become impractical to study epidemiologically. One need not, however, perform an assay for everyone providing a biological specimen. We propose pooling equal-volume aliquots from randomly grouped sets of cases and randomly grouped sets of controls, and then assaying the smaller number of pooled samples. If an effect modifier is of concern, the pooling can be done within strata defined by that variable. For covariates assessed on individuals (e.g., questionnaire data), set-based counterparts are calculated by adding the values for the individuals in each set. The pooling set then becomes the unit of statistical analysis. We show that, with appropriate specification of a set-based logistic model, standard software yields a valid estimated exposure odds ratio, provided the multiplicative formulation is correct. Pooling minimizes the depletion of irreplaceable biological specimens and can enable additional exposures to be studied economically. Statistical power suffers very little compared with the usual, individual-based analysis. In settings where high assay costs constrain the number of people an investigator can afford to study, specimen pooling can make it possible to study more people and hence improve the study's statistical power with no increase in cost.     

Effect of fluid mechanical stresses and plasma constituents on aggregation of LDL

LDL aggregates when exposed to even moderate fluid mechanical stresses in the laboratory, yet its half-life in the circulation is 2-3 days, implying that little aggregation occurs. LDL may be protected from aggregation in vivo by components of plasma, or by a qualitative difference in flows. Previous studies have shown that HDL and albumin inhibit the aggregation induced by vortexing. Using a more reproducible method of inducing aggregation and assessing aggregation both spectrophotometrically and by sedimentation techniques, we showed that at physiological concentrations, albumin is the more effective inhibitor, and that aggregation is substantially but not completely inhibited in plasma. Heat denatured and fatty-acid-stripped albumin were more effective inhibitors than normal albumin, supporting the idea that hydrophobic interactions are involved. Aggregation of LDL in a model reproducing several aspects of flow in the circulation was 200-fold slower, but was still inhibited by HDL and albumin, suggesting similar mechanisms are involved. Within the sensitivity of our technique, LDL aggregation did not occur in plasma exposed to these flows. Thus, as a result of the characteristics of blood flow and the inhibitory effects of plasma components, particularly albumin, LDL aggregation is unlikely to occur within the circulation.     

Ski/Sno and TGF-beta signaling

Transforming growth factor-beta is a potent inhibitor of epithelial cell proliferation. Proteins involved in TGF-beta signaling are bona fide tumor suppressors and many tumor cells acquire the ability to escape TGF-beta growth inhibition through the loss of key signaling transducers in the pathway or through the activation of oncogenes. Recent studies indicate that there is a specific connection between the TGF-beta signaling pathway and the Ski/SnoN family of oncoproteins. We summarize evidence that Ski and SnoN directly associate with Smad proteins and block the ability of the Smads to activate expression of many if not all TGF-beta-responsive genes. This appears to cause abrogation of TGF-beta growth inhibition in epithelial cells.     

Disease patterns at arterial branches and their relation to flow

The distribution of lesions around arterial branch points is complex and changes with age. Four distinct patterns - here termed the arrowhead pattern, the lateral pattern, the upstream streak and the volcano - have been reported around the origins of intercostal arteries in the human aorta at different ages. The first two patterns also occur in young and old rabbits, the third in minipigs, and the fourth in apolipoprotein E/LDL receptor knockout mice. It is unclear how all four patterns can depend solely on flow; a particular problem is that the prevalence of lipid deposition remains highly nonuniform for several branch diameters upstream of the ostium. Variations in the prevalence of fatty streaks may originate near the branch and then spread by the migration of activated endothelial cells towards the heart. The pattern of raised lesions may reflect a different aetiology.     

Gene selection and clustering for time-course and dose-response microarray experiments using order-restricted inference

We propose an algorithm for selecting and clustering genes according to their time-course or dose-response profiles using gene expression data. The proposed algorithm is based on the order-restricted inference methodology developed in statistics. We describe the methodology for time-course experiments although it is applicable to any ordered set of treatments. Candidate temporal profiles are defined in terms of inequalities among mean expression levels at the time points. The proposed algorithm selects genes when they meet a bootstrap-based criterion for statistical significance and assigns each selected gene to the best fitting candidate profile. We illustrate the methodology using data from a cDNA microarray experiment in which a breast cancer cell line was stimulated with estrogen for different time intervals. In this example, our method was able to identify several biologically interesting genes that previous analyses failed to reveal.     

High-throughput approaches to catalyst discovery

High-throughput synthesis and screening approaches to catalyst discovery and optimization are systematically changing the way in which catalyst research is conducted. Increased rates of innovation, cost effectiveness, improved intellectual property, reduced time to market and an improved probability of success are some of the attractive features that demand consideration. Advances made over the past few years reveal that any initial skepticism is waning, and high-throughput approaches to catalyst discovery are now being implemented broadly in industrial and academic laboratories.