fMRI evidence from auditory semantic processing

The role of the two hemispheres in the neurorehabilitation of language is still under dispute. This study explored the changes in language-evoked brain activation over a 2-week treatment interval with intensive constraint induced aphasia therapy (CIAT), which is also called intensive language action therapy (ILAT). Functional magnetic resonance imaging (fMRI) was used to assess brain activation in perilesional left hemispheric and in homotopic right hemispheric areas during passive listening to high and low-ambiguity sentences and non- speech control stimuli in chronic non-fluent aphasia patients. All patients demonstrated significant clinical improvements of language functions after therapy. In an event-related fMRI experiment, a significant increase of BOLD signal was manifest in right inferior frontal and temporal areas. This activation increase was stronger for highly ambiguous sentences than for unambiguous ones. These results suggest that the known language improvements brought about by intensive constraint-induced language action therapy at least in part relies on circuits within the right-hemispheric homologs of left- perisylvian language areas, which are most strongly activated in the processing of semantically complex language

Brain State-dependent Functional Hemispheric Specialization in Men but not in Women

Hemispheric specialization is reliably demonstrated in patients with unilateral lesions or disconnected hemispheres, but is inconsistent in healthy populations. The reason for this paradox is unclear. We propose that functional hemispheric specialization in healthy participants depends upon functional brain states at stimulus arrival (FBS). Brain activity was recorded from 123 surface electrodes while 22 participants (11 women) performed lateralized lexical decisions (left hemisphere processing) on neutral and emotional (right hemisphere processing) words. We determined two classes of stable FBS, one with right anterior-left posterior orientations (RA-LP maps) and one with left anterior-right posterior orientations (LA-RP maps). Results show that functional hemispheric specialization is dependent upon the class of FBS and gender. Of those with LA-RP maps, only men showed a strong emotional word advantage (EWA) after left visual field (right hemisphere) presentation, but no EWA after right visual field (left hemisphere) presentation. Subsequent to all other brain states, there was an almost equal EWA after presentation to either visual field. Only about half of the FBS in men led to the pattern of functional hemispheric specialization. We suggest that ‘split-brain' research may be marginally describable by a model, but only in exceptional situations, while in connected brains this functional hemispheric specialization is only one of many dynamic state

An integrative approach to ortholog prediction for disease-focused and other functional studies

Background Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. Results We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt webcite), for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM) and genes in genome-wide association study (GWAS) data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist webcite). Conclusions DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.Harvard CatalystNational Institutes of Health (U.S.) (NIH R01 GM067761)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (5K08DK78361)Dana-Farber/Harvard Cancer Cente

A novel approach to sequence validating protein expression clones with automated decision making

<p>Abstract</p> <p>Background</p> <p>Whereas the molecular assembly of protein expression clones is readily automated and routinely accomplished in high throughput, sequence verification of these clones is still largely performed manually, an arduous and time consuming process. The ultimate goal of validation is to determine if a given plasmid clone matches its reference sequence sufficiently to be "acceptable" for use in protein expression experiments. Given the accelerating increase in availability of tens of thousands of unverified clones, there is a strong demand for rapid, efficient and accurate software that automates clone validation.</p> <p>Results</p> <p>We have developed an Automated Clone Evaluation (ACE) system – the first comprehensive, multi-platform, web-based plasmid sequence verification software package. ACE automates the clone verification process by defining each clone sequence as a list of multidimensional discrepancy objects, each describing a difference between the clone and its expected sequence including the resulting polypeptide consequences. To evaluate clones automatically, this list can be compared against user acceptance criteria that specify the allowable number of discrepancies of each type. This strategy allows users to re-evaluate the same set of clones against different acceptance criteria as needed for use in other experiments. ACE manages the entire sequence validation process including contig management, identifying and annotating discrepancies, determining if discrepancies correspond to polymorphisms and clone finishing. Designed to manage thousands of clones simultaneously, ACE maintains a relational database to store information about clones at various completion stages, project processing parameters and acceptance criteria. In a direct comparison, the automated analysis by ACE took less time and was more accurate than a manual analysis of a 93 gene clone set.</p> <p>Conclusion</p> <p>ACE was designed to facilitate high throughput clone sequence verification projects. The software has been used successfully to evaluate more than 55,000 clones at the Harvard Institute of Proteomics. The software dramatically reduced the amount of time and labor required to evaluate clone sequences and decreased the number of missed sequence discrepancies, which commonly occur during manual evaluation. In addition, ACE helped to reduce the number of sequencing reads needed to achieve adequate coverage for making decisions on clones.</p

Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis

Background: RNA interference (RNAi) is an effective and important tool used to study gene function. For large-scale screens, RNAi is used to systematically down-regulate genes of interest and analyze their roles in a biological process. However, RNAi is associated with off-target effects (OTEs), including microRNA (miRNA)-like OTEs. The contribution of reagent-specific OTEs to RNAi screen data sets can be significant. In addition, the post-screen validation process is time and labor intensive. Thus, the availability of robust approaches to identify candidate off-targeted transcripts would be beneficial. Results: Significant efforts have been made to eliminate false positive results attributable to sequence-specific OTEs associated with RNAi. These approaches have included improved algorithms for RNAi reagent design, incorporation of chemical modifications into siRNAs, and the use of various bioinformatics strategies to identify possible OTEs in screen results. Genome-wide Enrichment of Seed Sequence matches (GESS) was developed to identify potential off-targeted transcripts in large-scale screen data by seed-region analysis. Here, we introduce a user-friendly web application that provides researchers a relatively quick and easy way to perform GESS analysis on data from human or mouse cell-based screens using short interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), as well as for Drosophila screens using shRNAs. Online GESS relies on up-to-date transcript sequence annotations for human and mouse genes extracted from NCBI Reference Sequence (RefSeq) and Drosophila genes from FlyBase. The tool also accommodates analysis with user-provided reference sequence files. Conclusion: Online GESS provides a straightforward user interface for genome-wide seed region analysis for human, mouse and Drosophila RNAi screen data. With the tool, users can either use a built-in database or provide a database of transcripts for analysis. This makes it possible to analyze RNAi data from any organism for which the user can provide transcript sequences

FlyPrimerBank: An Online Database for Drosophila melanogaster Gene Expression Analysis and Knockdown Evaluation of RNAi Reagents

The evaluation of specific endogenous transcript levels is important for understanding transcriptional regulation. More specifically, it is useful for independent confirmation of results obtained by the use of microarray analysis or RNA-seq and for evaluating RNA interference (RNAi)-mediated gene knockdown. Designing specific and effective primers for high-quality, moderate-throughput evaluation of transcript levels, i.e., quantitative, real-time PCR (qPCR), is nontrivial. To meet community needs, predefined qPCR primer pairs for mammalian genes have been designed and sequences made available, e.g., via PrimerBank. In this work, we adapted and refined the algorithms used for the mammalian PrimerBank to design 45,417 primer pairs for 13,860 Drosophila melanogaster genes, with three or more primer pairs per gene. We experimentally validated primer pairs for ~300 randomly selected genes expressed in early Drosophila embryos, using SYBR Green-based qPCR and sequence analysis of products derived from conventional PCR. All relevant information, including primer sequences, isoform specificity, spatial transcript targeting, and any available validation results and/or user feedback, is available from an online database (www.flyrnai.org/flyprimerbank). At FlyPrimerBank, researchers can retrieve primer information for fly genes either one gene at a time or in batch mode. Importantly, we included the overlap of each predicted amplified sequence with RNAi reagents from several public resources, making it possible for researchers to choose primers suitable for knockdown evaluation of RNAi reagents (i.e., to avoid amplification of the RNAi reagent itself). We demonstrate the utility of this resource for validation of RNAi reagents in vivo

Integrating protein-protein interaction networks with phenotypes reveals signs of interactions

A major objective of systems biology is to organize molecular interactions as networks and to characterize information-flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the “signs” of interactions (i.e. activation/inhibition relationships). We constructed a Drosophila melanogaster signed PPI network, consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes Enolase and Aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation/inhibition relationships between physically interacting proteins within signaling pathways will impact our understanding of many biological functions, including signal transduction and mechanisms of disease

Outcome and prognostic factors of desmoplastic medulloblastoma treated within a multidisciplinary treatment concept

<p>Abstract</p> <p>Background</p> <p>Desmoplasia in medulloblastoma is often diagnosed in adult patients and was repeatedly associated with improved results. Today, all medulloblastoma patients receive intensive multimodal treatment including surgery, radiotherapy and chemotherapy. This study was set up to investigate treatment outcome and prognostic factors after radiation therapy in patients with desmoplastic medulloblastomas.</p> <p>Methods</p> <p>Twenty patients treated for desmoplastic medulloblastoma in the Department of Radiation Oncology at the University of Heidelberg between 1984 and 2007 were included. Data were collected retrospectively. Tumor resection was performed in all patients. All patients underwent postsurgical radiotherapy (RT). Two patients underwent whole brain radiotherapy (WBRT), and 18 patients received craniospinal irradiation (CSI). In all patients, an additional boost was delivered to the posterior fossa. The median dose to the whole brain and the craniospinal axis was 35.2 Gray (Gy), and 54.4 Gy to the posterior fossa. Fourteen patients received chemotherapy, including seven who were treated with combined radiochemotherapy and twelve who received adjuvant chemotherapy. Statistical analysis was performed using the log-rank test and the Kaplan-Meier method.</p> <p>Results</p> <p>Median follow-up was 59 months. Overall (OS), local (LPFS) and distant progression-free survival (DPFS) was 80%, 71.2%, and 83.3% at 60 months. Patients who suffered from local or distant relapses had significantly worse outcome. Five patients died from recurrent medulloblastoma. Treatment-associated toxicity was acceptable.</p> <p>Conclusions</p> <p>Multimodal approaches with surgical resection followed by chemoirradiation achieved high response rates with long OS in desmoplastic medulloblastoma patients. Staging parameters expected to predict for poor prognosis did not significantly influence outcome. However, success of any first line regimen had strong impact on disease control, and remission was achieved in no patient with relapsing disease. Multimodal concepts must be evaluated in further clinical trials.</p

Ultra-rapid access to words in chronic aphasia: the effects of intensive language action therapy (ILAT).

Effects of intensive language action therapy (ILAT) on automatic language processing were assessed using Magnetoencephalography (MEG). Auditory magnetic mismatch negativity (MMNm) responses to words and pseudowords were recorded in twelve patients with chronic aphasia before and immediately after two weeks of ILAT. Following therapy, Patients showed significant clinical improvements of auditory comprehension as measured by the Token Test and in word retrieval and naming as measured by the Boston Naming Test. Neuromagnetic responses dissociated between meaningful words and meaningless word-like stimuli ultra-rapidly, approximately 50 ms after acoustic information first allowed for stimulus identification. Over treatment, there was a significant increase in the left-lateralisation of this early word-elicited activation, observed in perilesional fronto-temporal regions. No comparable change was seen for pseudowords. The results may reflect successful, therapy-induced, language restitution in the left hemisphere