Correction: CD95 maintains stem cell-like and non-classical EMT programs in primary human glioblastoma cells.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Regulation of Adult CNS Axonal Regeneration by the Post-transcriptional Regulator Cpeb1.

Adult mammalian central nervous system (CNS) neurons are unable to regenerate following axonal injury, leading to permanent functional impairments. Yet, the reasons underlying this regeneration failure are not fully understood. Here, we studied the transcriptome and translatome shortly after spinal cord injury. Profiling of the total and ribosome-bound RNA in injured and naïve spinal cords identified a substantial post-transcriptional regulation of gene expression. In particular, transcripts associated with nervous system development were down-regulated in the total RNA fraction while remaining stably loaded onto ribosomes. Interestingly, motif association analysis of post-transcriptionally regulated transcripts identified the cytoplasmic polyadenylation element (CPE) as enriched in a subset of these transcripts that was more resistant to injury-induced reduction at the transcriptome level. Modulation of these transcripts by overexpression of the CPE binding protein, Cpeb1, in mouse and Drosophila CNS neurons promoted axonal regeneration following injury. Our study uncovered a global evolutionarily conserved post-transcriptional mechanism enhancing regeneration of injured CNS axons.

Loss of Dickkopf-1 restores neurogenesis in old age and counteracts cognitive decline.

Memory impairment has been associated with age-related decline in adult hippocampal neurogenesis. Although Notch, bone morphogenetic protein, and Wnt signaling pathways are known to regulate multiple aspects of adult neural stem cell function, the molecular basis of declining neurogenesis in the aging hippocampus remains unknown. Here, we show that expression of the Wnt antagonist Dickkopf-1 (Dkk1) increases with age and that its loss enhances neurogenesis in the hippocampus. Neural progenitors with inducible loss of Dkk1 increase their Wnt activity, which leads to enhanced self-renewal and increased generation of immature neurons. This Wnt-expanded progeny subsequently matures into glutamatergic granule neurons with increased dendritic complexity. As a result, mice deficient in Dkk1 exhibit enhanced spatial working memory and memory consolidation and also show improvements in affective behavior. Taken together, our findings show that upregulating Wnt signaling by reducing Dkk1 expression can counteract age-related decrease in neurogenesis and its associated cognitive decline.

Genome-wide RNAi screening identifies human proteins with a regulatory function in the early secretory pathway.

The secretory pathway in mammalian cells has evolved to facilitate the transfer of cargo molecules to internal and cell surface membranes. Use of automated microscopy-based genome-wide RNA interference screens in cultured human cells allowed us to identify 554 proteins influencing secretion. Cloning, fluorescent-tagging and subcellular localization analysis of 179 of these proteins revealed that more than two-thirds localize to either the cytoplasm or membranes of the secretory and endocytic pathways. The depletion of 143 of them resulted in perturbations in the organization of the COPII and/or COPI vesicular coat complexes of the early secretory pathway, or the morphology of the Golgi complex. Network analyses revealed a so far unappreciated link between early secretory pathway function, small GTP-binding protein regulation, actin cytoskeleton organization and EGF-receptor-mediated signalling. This work provides an important resource for an integrative understanding of global cellular organization and regulation of the secretory pathway in mammalian cells.

[Down syndrome: another cause of immunosuppression associated with multiple eruptive dermatofibromas?]. / Síndrome de Down: ¿otra causa de inmunosupresión asociada con dermatofibromas eruptivos múltiples?

The term "multiple eruptive dermatofibromas" usually refers to a clinical situation characterized by the development of between five and eight dermatofibromas during a period of up to four months. It is usually linked to immunodeficiency associated conditions as autoimmune disorders, hematologic malignancies, HIV infection, and transplants. We report three patients with Down syndrome. One patient had psoriatic arthritis under treatment with methotrexate, one had Graves-Basedow disease, and one had hypercholesterolemia. All three patients developed multiple eruptive dermatofibromas. We suggest that the immunologic disturbances associated with Down syndrome, together with other underlying conditions present in these patients, could trigger the development of cutaneous lesions.

Biocompatibility of agarose gel as a dermal filler: histologic evaluation of subcutaneous implants.

BACKGROUND: The search for safe and effective tissue fillers has been an ongoing effort in plastic and cosmetic surgery over recent decades. Biocompatibility is a prerequisite for any substance to be used as an implant material, and potential biomaterials need to be characterized by histologic evaluation of tissue responses. Collagen is a well-known tissue filler. Agarose gel is widely used in bioengineering. Both products are considered biocompatible. The purpose of this study was to evaluate the bioactivity of agarose gel as a dermal filler compared with collagen. METHODS: Tissue responses to agarose gel and collagen were evaluated in a rat in vivo model (n = 96). Four groups were evaluated: group 1 (n = 24), rats with agarose gel implants; group 2 (n = 24), rats with collagen implants; group 3, a placebo group (n = 24); and group 4, a control group (n = 24). Responses and biocompatibility were assessed by histopathologic and histomorphometric evaluation at 1 week to 8 months after implantation. RESULTS: Agarose gel showed marked bioactivity and biodegradation, although the implants integrated well into tissues: newly formed collagen bands were observed inside the implants and no granulomas were detected. Collagen implants showed low cell infiltration and a significant loss of product over time. CONCLUSIONS: Agarose gel is a biocompatible product that can be considered for use as a tissue filler. Further investigation is required to assess its long-term efficacy and safety.

Maturation of the mammalian secretome.

A recent use of quantitative proteomics to determine the constituents of the endoplasmic reticulum and Golgi complex is discussed in the light of other available methodologies for cataloging the proteins associated with the mammalian secretory pathway.

Blepharophimosis-ptosis-epicanthus inversus syndrome (BPES).

Blepharophimosis-ptosis-epicanthus inversus syndrome (BPES) is a rare inherited condition that includes characteristic eyelid malformations and sometimes reduced fertility in females. Genetic studies have implicated mutations in the forkhead transcription factor FOXL2 as responsible for BPES. We report a female and her father with BPES type I, who presented the 1092-1108dup17 mutation in the FOXL2 gene. Molecular studies and the typical clinical features of BPES should allow the dermatologist to reach an early diagnosis and permit the treatment of eyelid alterations and the investigation of infertility.

Reticular erythematous mucinosis (REM) with telangiectasias associated with essential thrombocytosis and lung carcinoma.

The cutaneous mucinoses are a heterogeneous group of diseases in which mucin accumulates in the skin. Reticular erythematous mucinosis (REM) is an infrequent variant. We present a 48-year-old man with essential thrombocytosis and REM lesions with atypical telangiectasias on his chest, who developed a non-small cell lung carcinoma. We discuss the unusual clinical finding of telangiectasias over REM lesions and the association with essential thrombocytosis and lung carcinoma.

New challenges in gene expression data analysis and the extended GEPAS.

Since the first papers published in the late nineties, including, for the first time, a comprehensive analysis of microarray data, the number of questions that have been addressed through this technique have both increased and diversified. Initially, interest focussed on genes coexpressing across sets of experimental conditions, implying, essentially, the use of clustering techniques. Recently, however, interest has focussed more on finding genes differentially expressed among distinct classes of experiments, or correlated to diverse clinical outcomes, as well as in building predictors. In addition to this, the availability of accurate genomic data and the recent implementation of CGH arrays has made mapping expression and genomic data on the chromosomes possible. There is also a clear demand for methods that allow the automatic transfer of biological information to the results of microarray experiments. Different initiatives, such as the Gene Ontology (GO) consortium, pathways databases, protein functional motifs, etc., provide curated annotations for genes. Whereas many resources on the web focus mainly on clustering methods, GEPAS has evolved to cope with the aforementioned new challenges that have recently arisen in the field of microarray data analysis. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://gepas.bioinfo.cnio.es.

GEPAS: A web-based resource for microarray gene expression data analysis.

We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es).

Comparing bacterial genomes through conservation profiles.

We constructed two-dimensional representations of profiles of gene conservation across different genomes using the genome of Escherichia coli as a model. These profiles permit both the visualization at the genome level of different traits in the organism studied and, at the same time, reveal features related to the genomes analyzed (such as defective genomes or genomes that lack a particular system). Conserved genes are not uniformly distributed along the E. coli genome but tend to cluster together. The study of gene distribution patterns across genomes is important for the understanding of how sets of genes seem to be dependent on each other, probably having some functional link. This provides additional evidence that can be used for the elucidation of the function of unannotated genes. Clustering these patterns produces families of genes which can be arranged in a hierarchy of closeness. In this way, functions can be defined at different levels of generality depending on the level of the hierarchy that is studied. The combined study of conservation and phenotypic traits opens up the possibility of defining phenotype/genotype associations, and ultimately inferring the gene or genes responsible for a particular trait.

Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons.

Recent advances in microarray technology have opened new ways for functional annotation of previously uncharacterised genes on a genomic scale. This has been demonstrated by unsupervised clustering of co-expressed genes and, more importantly, by supervised learning algorithms. Using prior knowledge, these algorithms can assign functional annotations based on more complex expression signatures found in existing functional classes. Previously, support vector machines (SVMs) and other machine-learning methods have been applied to a limited number of functional classes for this purpose. Here we present, for the first time, the comprehensive application of supervised neural networks (SNNs) for functional annotation. Our study is novel in that we report systematic results for ~100 classes in the Munich Information Center for Protein Sequences (MIPS) functional catalog. We found that only ~10% of these are learnable (based on the rate of false negatives). A closer analysis reveals that false positives (and negatives) in a machine-learning context are not necessarily "false" in a biological sense. We show that the high degree of interconnections among functional classes confounds the signatures that ought to be learned for a unique class. We term this the "Borges effect" and introduce two new numerical indices for its quantification. Our analysis indicates that classification systems with a lower Borges effect are better suitable for machine learning. Furthermore, we introduce a learning procedure for combining false positives with the original class. We show that in a few iterations this process converges to a gene set that is learnable with considerably low rates of false positives and negatives and contains genes that are biologically related to the original class, allowing for a coarse reconstruction of the interactions between associated biological pathways. We exemplify this methodology using the well-studied tricarboxylic acid cycle.