Renal safety of a tenofovir-containing first line regimen: experience from an antiretroviral cohort in rural Lesotho

Introduction

Current guidelines contraindicate TDF use when creatinine clearance (CrCl) falls below 50 ml/min. We report prevalence of abnormal renal function at baseline and factors associated with abnormal renal function from a community cohort in Lesotho.

Methods

We calculated changes in CrCl from baseline for patients initiated on TDF at 6 and 12 months and the proportion of patients initiated on TDF who developed renal impairment. Screening algorithms were developed using risk factors determined by multivariate analysis.

Results

Among 933 adults for whom baseline creatinine was available, 176 (18.9%) presented with a baseline CrCl <50 ml/min. Renal function improved during follow-up. 19 patients who developed renal toxicity during follow up remained on TDF; renal function improved (CrCl≥50 ml/min) in all but 3 of these patients. Among 15 patients with a baseline CrCl <50 ml/min were started in error, none developed severe renal impairment.

Conclusion

In this setting TDF-associated renal toxicity is rare and mainly transient. Further studies to assess TDF safety at lower CrCl thresholds are warranted.     

The Shigella flexneri type three secretion system effector IpgD inhibits T cell migration by manipulating host phosphoinositide metabolism

Shigella, the Gram-negative enteroinvasive bacterium that causes shigellosis, relies on its type III secretion system (TTSS) and injected effectors to modulate host cell functions. However, consequences of the interaction between Shigella and lymphocytes have not been investigated. We show that Shigella invades activated human CD4(+) T lymphocytes. Invasion requires a functional TTSS and results in inhibition of chemokine-induced T cell migration, an effect mediated by the TTSS effector IpgD, a phosphoinositide 4-phosphatase. Remarkably, IpgD injection into bystander T cells can occur in the absence of cell invasion. Upon IpgD-mediated hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP(2)), the pool of PIP(2) at the plasma membrane is reduced, leading to dephosphorylation of the ERM proteins and their inability to relocalize at one T cell pole upon chemokine stimulus, likely affecting the formation of the polarized edge required for cell migration. These results reveal a bacterial TTSS effector-mediated strategy to impair T cell function.     

Vacuolar H(+)-ATPases: intra- and intermolecular interactions

V-ATPases in eukaryotes are heteromultimeric, H(+)-transporting proteins. They are localized in a multitude of different membranes and energize many different transport processes. Unique features of V-ATPases are, on the one hand, their ability to regulate enzymatic and ion transporting activity by the reversible dissociation of the catalytic V(1) complex from the membrane bound proton translocating V(0) complex and, on the other hand, their high sensitivity to specific macrolides such as bafilomycin and concanamycin from streptomycetes or archazolid and apicularen from myxomycetes. Both features require distinct intramolecular as well as intermolecular interactions. Here we will summarize our own results together with newer developments in both of these research areas.     

Quarnet Inference Rules for Level-1 Networks

An important problem in phylogenetics is the construction of phylogenetic trees. One way to approach this problem, known as the supertree method, involves inferring a phylogenetic tree with leaves consisting of a set X of species from a collection of trees, each having leaf-set some subset of X. In the 1980s, Colonius and Schulze gave certain inference rules for deciding when a collection of 4-leaved trees, one for each 4-element subset of X, can be simultaneously displayed by a single supertree with leaf-set X. Recently, it has become of interest to extend this and related results to phylogenetic networks. These are a generalization of phylogenetic trees which can be used to represent reticulate evolution (where species can come together to form a new species). It has recently been shown that a certain type of phylogenetic network, called a (unrooted) level-1 network, can essentially be constructed from 4-leaved trees. However, the problem of providing appropriate inference rules for such networks remains unresolved. Here, we show that by considering 4-leaved networks, called quarnets, as opposed to 4-leaved trees, it is possible to provide such rules. In particular, we show that these rules can be used to characterize when a collection of quarnets, one for each 4-element subset of X, can all be simultaneously displayed by a level-1 network with leaf-set X. The rules are an intriguing mixture of tree inference rules, and an inference rule for building up a cyclic ordering of X from orderings on subsets of X of size 4. This opens up several new directions of research for inferring phylogenetic networks from smaller ones, which could yield new algorithms for solving the supernetwork problem in phylogenetics.     

Some analytical results about a simple reaction-diffusion system for morphogenesis

Summary The reaction-diffusion system considered involves only one nonlinear term and is a gradient system. In a bifurcation analysis for the equilibrium states, the global existence of infinitely many solution branches can be shown by the method of Ljusternik-Schnirelmann. Their stability is studied. Using a Ljapunov functional it can be shown that the solutions of the time-dependent system converge to the equilibrium states.     

Update on <Emphasis Type="Italic">transparent testa</Emphasis> mutants from <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis>: characterisation of new alleles from an isogenic collection

Main conclusion

We present a comprehensive overview on flavonoid-related phenotypes of A. thaliana tt and tds mutants, provide tools for their characterisation, increase the number of available alleles and demonstrate that tds3 is allelic to tt12 and tds5 to aha10.Flavonoid biosynthesis is one of the best-studied secondary metabolite pathways in plants. In the model system Arabidopsis thaliana it leads to the synthesis of three phenolic compound classes: flavonol glycosides, anthocyanins and proanthocyanidins (PAs). PAs appear brown in their oxidised polymeric forms, and most A. thaliana mutants impaired in flavonoid accumulation were identified through screens for lack of this seed coat pigmentation. These mutants are referred to as transparent testa (tt) or tannin-deficient seed (tds). More than 20 mutants of these types have been published, probably representing most of the genes relevant for PA accumulation in A. thaliana. However, data about the genes involved in PA deposition or oxidation are still rather scarce. Also, for some of the known mutants it is unclear if they represent additional loci or if they are allelic to known genes. For the present study, we have performed a systematic phenotypic characterisation of almost all available tt and tds mutants and built a collection of mutants in the genetic background of the accession Columbia to minimise effects arising from ecotype variation. We have identified a novel tt6 allele from a forward genetic screen and demonstrated that tds3 is allelic to tt12 and tds5 to aha10.

     

Development,characterization, and application of a 2‐Compartment system to investigate the impact of pH inhomogeneities in large‐scale CHO‐based processes

Large‐scale bioreactors for the production of monoclonal antibodies reach volumes of up to 25 000 L. With increasing bioreactor size, mixing is however affected negatively, resulting in the formation of gradients throughout the reactor. These gradients can adversely affect process performance at large scale. Since mammalian cells are sensitive to changes in pH, this study investigated the effects of pH gradients on process performance. A 2‐Compartment System was established for this purpose to expose only a fraction of the cell population to pH excursions and thereby mimicking a large‐scale bioreactor. Cells were exposed to repeated pH amplitudes of 0.4 units (pH 7.3), which resulted in decreased viable cell counts, as well as the inhibition of the lactate metabolic shift. These effects were furthermore accompanied by increased absolute lactate levels. Continuous assessment of molecular attributes of the expressed target protein revealed that subunit assembly or N‐glycosylation patterns were only slightly influenced by the pH excursions. The exposure of more cells to the same pH amplitudes further impaired process performance, indicating this is an important factor, which influences the impact of pH inhomogeneity. This knowledge can aid in the design of pH control strategies to minimize the effects of pH inhomogeneity in large‐scale bioreactors.     

Robust Selection of Cancer Survival Signatures from High-Throughput Genomic Data Using Two-Fold Subsampling

Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature. The software is available as an R package rsig at CRAN (http://cran.r-project.org).