Six-Minute Walk Test: Reference Values and Prediction Equation in Healthy Boys Aged 5 to12 Years

OBJECTIVE

This study aimed to (1) generate normative data in healthy boys aged 5–12 years for the six-minute walk test (6MWT), an outcome measure currently used in clinical trials in Duchenne muscular dystrophy (DMD), (2) to describe the relation with anthropometric variables and myometry, and (3) to compare our data with published equations.

METHODS

The 6MWT was conducted in 442 boys according to a standardized protocol, as currently used in clinical trials in DMD. Maximal voluntary isometric contractions for knee flexion and extension were recorded with a hand-held myometer.

RESULTS

The 6MWD increased significantly with age, from 478.0±44.1 m at age 5, to 650.0±76.8 m at age 12, with the steepest increase between 5 and 8 years. Age- and height related percentile curves of the 6MWD were developed. Correlations with anthropometric variables were fair to good (age r = 0.60, height r = 0.57, weight r = 0.44). Myometric variables (knee flexors and extensors) showed correlations of 0.46 and 0.50 respectively. When dividing into two age categories (5–8 years, 9–12 years), these magnitudes of correlations only applied to the younger age group. Additionally, predicted values were calculated according to available reference equations (Geiger and Ben Saad), indicating an overestimation by those equations. Finally, the Geiger equation was refitted to our population.

CONCLUSION

The percentile curves according to age and height provide a useful tool in the assessment of ambulatory capacity in boys aged 5 to 12 years. Significant correlations with anthropometric variables and myometry were only found in the 5–8 years age group. The Geiger prediction equation, currently used to assess ambulatory capacity in DMD was refitted to obtain a more accurate prediction model based on a large sample with a homogenous distribution across the age categories 5 to 12 years and applying the methodology as currently used in clinical trials in DMD.     

SHUGOSHINs and PATRONUS protect meiotic centromere cohesion in Arabidopsis thaliana

In meiosis, chromosome cohesion is maintained by the cohesin complex, which is released in a two‐step manner. At meiosis I, the meiosis‐specific cohesin subunit Rec8 is cleaved by the protease Separase along chromosome arms, allowing homologous chromosome segregation. Next, in meiosis II, cleavage of the remaining centromere cohesin results in separation of the sister chromatids. In eukaryotes, protection of centromeric cohesion in meiosis I is mediated by SHUGOSHINs (SGOs). The Arabidopsis genome contains two SGO homologs. Here we demonstrate that Atsgo1 mutants show a premature loss of cohesion of sister chromatid centromeres at anaphase I and that AtSGO2 partially rescues this loss of cohesion. In addition to SGOs, we characterize PATRONUS which is specifically required for the maintenance of cohesion of sister chromatid centromeres in meiosis II. In contrast to the Atsgo1 Atsgo2 double mutant, patronus T‐DNA insertion mutants only display loss of sister chromatid cohesion after meiosis I, and additionally show disorganized spindles, resulting in defects in chromosome segregation in meiosis. This leads to reduced fertility and aneuploid offspring. Furthermore, we detect aneuploidy in sporophytic tissue, indicating a role for PATRONUS in chromosome segregation in somatic cells. Thus, ploidy stability is preserved in Arabidopsis by PATRONUS during both meiosis and mitosis.     

A structured overview of simultaneous component based data integration

Background  

Data integration is currently one of the main challenges in the biomedical sciences. Often different pieces of information are gathered on the same set of entities (e.g., tissues, culture samples, biomolecules) with the different pieces stemming, for example, from different measurement techniques. This implies that more and more data appear that consist of two or more data arrays that have a shared mode. An integrative analysis of such coupled data should be based on a simultaneous analysis of all data arrays. In this respect, the family of simultaneous component methods (e.g., SUM-PCA, unrestricted PCovR, MFA, STATIS, and SCA-P) is a natural choice. Yet, different simultaneous component methods may lead to quite different results.     

A novel strategy for the comprehensive analysis of the biomolecular composition of isolated plasma membranes

We manufactured a novel type of lipid‐coated superparamagnetic nanoparticles that allow for a rapid isolation of plasma membranes (PMs), enabling high‐resolution proteomic, glycomic and lipidomic analyses of the cell surface. We used this technology to characterize the effects of presenilin knockout on the PM composition of mouse embryonic fibroblasts. We found that many proteins are selectively downregulated at the cell surface of presenilin knockout cells concomitant with lowered surface levels of cholesterol and certain sphingomyelin species, indicating defects in specific endosomal transport routes to and/or from the cell surface. Snapshots of N‐glycoproteomics and cell surface glycan profiling further underscored the power and versatility of this novel methodology. Since PM proteins provide many pathologically relevant biomarkers representing two‐thirds of the currently used drug targets, this novel technology has great potential for biomedical and pharmaceutical applications.     

CHARACTERIZATION OF A RABE (RAS GENE FROM RAT BRAIN E) GTPASE EXPRESSED DURING MORPHOGENESIS IN THE UNICELLULAR GREEN ALGA MICRASTERIAS DENTICULATA (ZYGNEMATOPHYCEAE,STREPTOPHYTA)1

Rab GTPases are central regulators of cell shape in land plants by coordinating vesicle trafficking during morphogenesis. To date, relatively little is known about the role of these ubiquitous signaling proteins during cell growth in microalgae, in particular in the related charophyte algae. This article identifies the first charophyte Rab GTPase, MdRABE1, in Micrasterias denticulata Bréb., a convenient model organism for studying morphogenesis. Its expression correlated with the onset of morphogenesis, and structural analysis indicated that it belongs to the RABE (Ras gene from rat brain E) subclass. Confocal fluorescence and immunoelectron microscopy (IEM) of transiently GFP‐MdRABE1 overexpressing interphase cells demonstrated that the GFP‐MdRABE1 protein was localized to the endoplasmic reticulum, dictyosomes, exocytotic vesicles, the cell margin, the membranes of cell organelles, and in the isthmus zone around the nucleus. Although overexpression phenotyping of both N‐ and C‐terminal green fluorescent protein (GFP) fusions failed to indicate additional functional evidence of the MdRABE1 protein due to mortality of those transgenic cells, its expression profile, bioinformatics, and intracellular localization suggest a role in vesicle trafficking during morphogenesis.     

Lysosomal calcium homeostasis defects, not proton pump defects, cause endo-lysosomal dysfunction in PSEN-deficient cells

Presenilin (PSEN) deficiency is accompanied by accumulation of endosomes and autophagosomes, likely caused by impaired endo-lysosomal fusion. Recently, Lee et al. (2010. Cell. doi: http://dx.doi.org/10.1016/j.cell.2010.05.008) attributed this phenomenon to PSEN1 enabling the transport of mature V0a1 subunits of the vacuolar ATPase (V-ATPase) to lysosomes. In their view, PSEN1 mediates the N-glycosylation of V0a1 in the endoplasmic reticulum (ER); consequently, PSEN deficiency prevents V0a1 glycosylation, compromising the delivery of unglycosylated V0a1 to lysosomes, ultimately impairing V-ATPase function and lysosomal acidification. We show here that N-glycosylation is not a prerequisite for proper targeting and function of this V-ATPase subunit both in vitro and in vivo in Drosophila melanogaster. We conclude that endo-lysosomal dysfunction in PSEN(-/-) cells is not a consequence of failed N-glycosylation of V0a1, or compromised lysosomal acidification. Instead, lysosomal calcium storage/release is significantly altered in PSEN(-/-) cells and neurons, thus providing an alternative hypothesis that accounts for the impaired lysosomal fusion capacity and accumulation of endomembranes that accompanies PSEN deficiency.     

Joint mapping of genes and conditions via multidimensional unfolding analysis

Background  

Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding.     

Using ribosomal protein genes as reference: a tale of caution

Background

Housekeeping genes are needed in every tissue as their expression is required for survival, integrity or duplication of every cell. Housekeeping genes commonly have been used as reference genes to normalize gene expression data, the underlying assumption being that they are expressed in every cell type at approximately the same level. Often, the terms “reference genes” and “housekeeping genes” are used interchangeably. In this paper, we would like to distinguish between these terms. Consensus is growing that housekeeping genes which have traditionally been used to normalize gene expression data are not good reference genes. Recently, ribosomal protein genes have been suggested as reference genes based on a meta-analysis of publicly available microarray data.

Methodology/Principal Findings

We have applied several statistical tools on a dataset of 70 microarrays representing 22 different tissues, to assess and visualize expression stability of ribosomal protein genes. We confirmed the housekeeping status of these genes, but further estimated expression stability across tissues in order to assess their potential as reference genes. One- and two-way ANOVA revealed that all ribosomal protein genes have significant expression variation across tissues and exhibit tissue-dependent expression behavior as a group. Via multidimensional unfolding analysis, we visualized this tissue-dependency. In addition, we explored mechanisms that may cause tissue dependent effects of individual ribosomal protein genes.

Conclusions/Significance

Here we provide statistical and biological evidence that ribosomal protein genes exhibit important tissue-dependent variation in mRNA expression. Though these genes are most stably expressed of all investigated genes in a meta-analysis they cannot be considered true reference genes.