Management of multiple, late onset complications in a 33-year-old female, with a ventriculoperitoneal shunt and crohn\u27s disease

Numerous complications can occur after the placement of a venticuloperitoneal shunt. The late onset of an autoimmune disease such as Crohn\u27s disease can be the disruptive factor for a previously well functioning shunt. A 33-year-old female with a ventriculo-peritoneal shunt since the age of 7, as well as Crohn\u27s disease since the age of 25, presented in the ER with dysuria, long-lasting fever and intermittent severe headache. The patient underwent a CT scan of the chest, abdomen and brain. An enlargement of the ventricular system was revealed, suggesting malfunction of the shunt. Simultaneously, the abdominal scan revealed an abnormal course of the peritoneal catheter of the shunt in the lower abdomen, inside the bladder. The existence of the catheter inside the bladder was confirmed and filmed during a cystoscopy and was attributed to the several inflammations and surgeries performed for the treatment of Crohn\u27s disease.The absence of an obvious stenosis of the aqueduct, the early immunodeficiency due to Azathioprine and the multiple abdominal surgeries made the treatment selection a complex algorithm for the neurosurgeon

HGCA και ACT: Εργαλεία για τη μελέτη της γονιδιακής συνέκφρασης στον άνθρωπο και το πρότυπο φυτό Arabidopsis thaliana

Γονίδια με παρόμοια πρότυπα έκφρασης τείνουν να συμμετέχουν σε σχετικές βιολογικές διεργασίες. Ο πιο αποτελεσματικός τρόπος για την μελέτη της γονιδιακής συνέκφρασης βασίζεται στην ανάλυση μεταγραφωμικών δεδομένων του συνόλου των πιο αντιπροσωπευτικών δειγμάτων από κάθε ιστό ή είδος κυττάρου. Η συνέκφραση γονιδίων που αποκαλύπτεται από μία ποικιλία πειραμάτων μεταγραφωμικής, που υπάρχουν διαθέσιμα σε δημόσια καταθετήρια, μπορεί να περιέχει πληροφορίες που υπερβαίνουν τον αρχικό σκοπό του κάθε πειράματος και αυτό μπορεί να αποτελέσει ένα πολύτιμο εργαλείο πρόβλεψης για τη λειτουργία γονιδίων και τη συμμετοχή τους σε βιολογικά μονοπάτια. Δημιουργήθηκαν 3 εργαλεία συνέκφρασης: το Arabidopsis Coexpression Tool (ACT) που μελετάει τη γονιδιακή συνέκφραση στο πρότυπο φυτό Arabidopsis thaliana και είναι βασισμένο σε 3500 δείγματα μικροσυστοιχιών από 3 διαφορετικές βάσεις δεδομένων, το Human Gene Coexpression Analysis (HGCA) 1.5 που μελετάει τη γονιδιακή συνέκφραση στον άνθρωπο και είναι βασισμένο σε 1959 δείγματα μικροσυστοιχιών από την GEO και το HGCA2, πάλι για τον άνθρωπο, που είναι βασισμένο σε 3500 δείγματα RNA-seq από την GTEx. Η επιλογή των δειγμάτων σε κάθε περίπτωση έγινε με λεπτομερή τρόπο, χρησιμοποιήθηκαν καινοτόμοι αλγόριθμοι επεξεργασίας των δεδομένων και η ομαδοποίηση των γονιδίων έγινε με ιεραρχική ομαδοποίηση. Η ανάπτυξη των ιστοτόπων έγινε χρησιμοποιώντας μοντέρνες τεχνολογίες. Εισάγοντας ένα γονίδιο-οδηγό, τα εργαλεία παρουσιάζουν ένα φυλογενετικό υποδέντρο του οποίου τα φύλλα αποτελούν γονίδια συνεκφρασμένα με το γονίδιο εισόδου. Ο χρήστης μπορεί επιπλέον να πραγματοποιήσει ποικίλες αναλύσεις εμπλουτισμού βιολογικών όρων πάνω στα γονίδια του υποδέντρου. Μελετώντας τη λίστα συνεκφρασμένων γονιδίων και τα αποτελέσματα υπερεκπροσώπησης ανακαλύπτονται λειτουργικοί συνεργάτες ή προσδίδονται ρόλοι σε μη χαρακτηρισμένα γονίδια, κοιτώντας τους γείτονές τους στο υποδέντρο συνέκφρασης.Genes with similar expression patterns tend to participate in related biological processes. The most efficient way to study gene coexpression is based on the transcriptomic data analysis of the subset of samples which contain the best representatives of each tissue or cell type. The coexpression of genes revealed from a variety of transcriptomic experiments stored in public repositories, may contain information far beyond the original scope of each constituent experiment, and can be a valuable predictive tool for gene function and pathway membership. Three tools were developed: Arabidopsis Coexpression Tool (ACT) studies gene coexpression in model plant Arabidopsis thaliana, which is based on 3500 microarray samples from three different public repositories, Human Gene Coexpression Analysis (HGCA) 1.5 studies gene coexpression in human, which is based on 1959 microarray samples from GEO and HGCA2, again for human, based on 3500 RNA-seq samples from GTEx. Meticulous sample selection was performed in each case, novel data processing algorithms were used and genes were grouped using hierarchical clustering. The websites were developed using modern libraries. By typing a driver-gene, the tools output a coexpression subtree whose leaves contain genes coexpressed with the input gene. The user can perform a variety of biological term enrichment analyses upon the list of gene of the coexpression subtree. By studying the list of coexpressed genes and the enrichment analysis results, gene functional partners to the gene of interest can be discovered or a function can be assigned to a gene of unknown role by examining its coexpressed genes in neighbouring leaves

Quality development in education

The article suggests that people involved in quality development need a specific competence, called quality literacy, in order to successfully improve learning processes. Quality literacy is viewed as a set of competencies that are needed for professional quality development. Quality literacy emphasizes the importance of professionalism as a necessary component for quality development, in addition to structural quality management models. Quality development is a co-production between learners and their learning environment. This means that the educational process can only be influenced and optimized through participation and not steered externally. Quality strategies cannot, therefore, guarantee a high quality of learning processes but rather aim at professionalisation of the educational process. This article suggests participation and negotiation between educational participants (clients and providers) as a main condition for quality development. © 2009 Springer Berlin Heidelberg

Arabidopsis Coexpression Tool:a tool for gene coexpression analysis in Arabidopsis thaliana

Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Arabidopsis Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis thaliana, identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint

Copy number variations and risk for schizophrenia in 22q11.2 deletion syndrome

22q11.2 Deletion Syndrome (22q11.2DS) is a common microdeletion syndrome with congenital and late-onset features. Testing for the genomic content of copy number variations (CNVs) may help elucidate the 22q11.2 deletion mechanism and the variable clinical expression of the syndrome including the high (25%) risk for schizophrenia. We used genome-wide microarrays to assess CNV content and the parental origin of 22q11.2 deletions in a cohort of 100 adults with 22q11.2DS (44 with schizophrenia) and controls. 22q11.2DS subjects with schizophrenia failed to exhibit de novo CNVs or any excess of novel inherited CNVs outside the 22q11.2 region. There were no significant effects of parental origin of the 22q11.2 deletion, deletion length, parental age or family history on expression of schizophrenia. There was no evidence for a general increase of de novo CNVs in 22q11.2DS. A novel finding was the relative paucity of males with de novo 22q11.2 deletions of paternal origin (P = 0.019). The Y chromosome may play a mediating role in the mechanism of 22q11.2 deletion events during spermatogenesis, resulting in the previously observed excess of maternal de novo 22q11.2 deletions. Hemizygosity of the 22q11.2 region appears to be the major CNV-related risk factor for schizophrenia in 22q11.2DS. The results reinforce the need for further efforts to identify specific molecular mechanisms underlying this expression and to identify the 1% of patients with schizophrenia who carry 22q11.2 deletions

Germline EPHB2 Receptor Variants in Familial Colorectal Cancer

Familial clustering of colorectal cancer occurs in 15–20% of cases, however recognized cancer syndromes explain only a small fraction of this disease. Thus, the genetic basis for the majority of hereditary colorectal cancer remains unknown. EPHB2 has recently been implicated as a candidate tumor suppressor gene in colorectal cancer. The aim of this study was to evaluate the contribution of EPHB2 to hereditary colorectal cancer. We screened for germline EPHB2 sequence variants in 116 population-based familial colorectal cancer cases by DNA sequencing. We then estimated the population frequencies and characterized the biological activities of the EPHB2 variants identified. Three novel nonsynonymous missense alterations were detected. Two of these variants (A438T and G787R) result in significant residue changes, while the third leads to a conservative substitution in the carboxy-terminal SAM domain (V945I). The former two variants were found once in the 116 cases, while the V945I variant was present in 2 cases. Genotyping of additional patients with colorectal cancer and control subjects revealed that A438T and G787R represent rare EPHB2 alleles. In vitro functional studies show that the G787R substitution, located in the kinase domain, causes impaired receptor kinase activity and is therefore pathogenic, whereas the A438T variant retains its receptor function and likely represents a neutral polymorphism. Tumor tissue from the G787R variant case manifested loss of heterozygosity, with loss of the wild-type allele, supporting a tumor suppressor role for EPHB2 in rare colorectal cancer cases. Rare germline EPHB2 variants may contribute to a small fraction of hereditary colorectal cancer