SecA interacts with ribosomes in order to facilitate posttranslational translocation in bacteria

In Escherichia coli, translocation of exported proteins across the cytoplasmic membrane is dependent on the motor protein SecA and typically begins only after synthesis of the substrate has already been completed (i.e., posttranslationally). Thus, it has generally been assumed that the translocation machinery also recognizes its protein substrates posttranslationally. Here we report a specific interaction between SecA and the ribosome at a site near the polypeptide exit channel. This interaction is mediated by conserved motifs in SecA and ribosomal protein L23, and partial disruption of this interaction in?vivo by introducing mutations into the genes encoding SecA or L23 affects the efficiency of translocation by the posttranslational pathway. Based on these findings, we propose that SecA could interact with its nascent substrates during translation in order to efficiently channel them into the "posttranslational" translocation pathway.     

Revision of the pseudo-orbweavers of the genus Fecenia Simon, 1887 (Araneae, Psechridae), with emphasis on their pre-epigyne

The present paper provides a taxonomic revision of the genus Fecenia with emphasis on the characteristics of the pre-epigynes which are integrated for the first time into an identification key. As a result, one species is revalidated, Fecenia protensa Thorell, 1891, stat. n., and two new junior synonyms for Fecenia protensa are recognised: Fecenia sumatrana Kulczyński, 1908, syn. n. and Fecenia nicobarensis (Tikader, 1977), syn. n. New records are reported: Fecenia ochracea (Doleschall, 1859)from Malaysian Borneo, Fecenia macilenta (Simon, 1885) from Sumatra, Indonesia, Fecenia protensa from Thailand and Malaysia, Fecenia travancoria Pocock, 1899 from Sri Lanka and Thailand, and Fecenia cylindrata Thorell, 1895 from Thailand and Laos. Additional information on the biology of Fecenia is provided and the validity of characters for identifying Fecenia species is discussed.     

Prevalence of the most frequent BRCA1 mutations in Polish population

The purpose of our study was to establish the frequency and distribution of the four most common BRCA1 mutations in Polish general population and in a series of breast cancer patients. Analysis of the population frequency of 5382insC (c.5266dupC), 300T >G (p.181T >G), 185delAG (c.68_69delAG) and 3819del5 (c.3700_3704del5) mutations of the BRCA1 gene were performed on a group of respectively 16,849, 13,462, 12,485 and 3923 anonymous samples collected at birth in seven Polish provinces. The patient group consisted of 1845 consecutive female breast cancer cases. The most frequent BRCA1 mutation in the general population was 5382insC found in 29 out of 16,849 samples (0.17%). 300T >G and 3819del5 mutations were found in respectively 11 of 13,462 (0.08%) and four of 3923 (0.1%) samples. The population prevalence for combined Polish founder 5382insC and 300T >G mutations was 0.25% (1/400). The frequencies of 5382insC and 300T >G carriers among consecutive breast cancer cases were, respectively, 1.9% (35/1845) and 1.2% (18/1486). Comparing these data with the population frequency, we calculated the relative risk of breast cancer for 5382insC mutation at OR = 17 and for 300T >G mutation at OR = 26. Our results, based on large population studies, show high frequencies of founder 5382insC and 300T >G BRCA1 mutations in Polish general population. Carriage of one of these mutations is connected with a very high relative risk of breast cancer.     

The caBIG® Life Science Business Architecture Model

MOTIVATION: Business Architecture Models (BAMs) describe what a business does, who performs the activities, where and when activities are performed, how activities are accomplished and which data are present. The purpose of a BAM is to provide a common resource for understanding business functions and requirements and to guide software development. The cancer Biomedical Informatics Grid (caBIG?) Life Science BAM (LS BAM) provides a shared understanding of the vocabulary, goals and processes that are common in the business of LS research. RESULTS: LS BAM 1.1 includes 90 goals and 61 people and groups within Use Case and Activity Unified Modeling Language (UML) Diagrams. Here we report on the model's current release, LS BAM 1.1, its utility and usage, and plans for future use and continuing development for future releases. Availability and Implementation: The LS BAM is freely available as UML, PDF and HTML (https://wiki.nci.nih.gov/x/OFNyAQ).     

Generation of a predictive melphalan resistance index by drug screen of B-cell cancer cell lines

Background

Recent reports indicate that in vitro drug screens combined with gene expression profiles (GEP) of cancer cell lines may generate informative signatures predicting the clinical outcome of chemotherapy. In multiple myeloma (MM) a range of new drugs have been introduced and now challenge conventional therapy including high dose melphalan. Consequently, the generation of predictive signatures for response to melphalan may have a clinical impact. The hypothesis is that melphalan screens and GEPs of B-cell cancer cell lines combined with multivariate statistics may provide predictive clinical information.

Materials and Methods

Microarray based GEPs and a melphalan growth inhibition screen of 59 cancer cell lines were downloaded from the National Cancer Institute database. Equivalent data were generated for 18 B-cell cancer cell lines. Linear discriminant analyses (LDA), sparse partial least squares (SPLS) and pairwise comparisons of cell line data were used to build resistance signatures from both cell line panels. A melphalan resistance index was defined and estimated for each MM patient in a publicly available clinical data set and evaluated retrospectively by Cox proportional hazards and Kaplan-Meier survival analysis.

Principal Findings

Both cell line panels performed well with respect to internal validation of the SPLS approach but only the B-cell panel was able to predict a significantly higher risk of relapse and death with increasing resistance index in the clinical data sets. The most sensitive and resistant cell lines, MOLP-2 and RPMI-8226 LR5, respectively, had high leverage, which suggests their differentially expressed genes to possess important predictive value.

Conclusion

The present study presents a melphalan resistance index generated by analysis of a B-cell panel of cancer cell lines. However, the resistance index needs to be functionally validated and correlated to known MM biomarkers in independent data sets in order to better understand the mechanism underlying the preparedness to melphalan resistance.     

Food composition of the diet in relation to changes in waist circumference adjusted for body mass index

Background

Dietary factors such as low energy density and low glycemic index were associated with a lower gain in abdominal adiposity. A better understanding of which food groups/items contribute to these associations is necessary.

Objective

To ascertain the association of food groups/items consumption on prospective annual changes in “waist circumference for a given BMI” (WC_BMI), a proxy for abdominal adiposity.

Design

We analyzed data from 48,631 men and women from 5 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Anthropometric measurements were obtained at baseline and after a median follow-up time of 5.5 years. WC_BMI was defined as the residuals of waist circumference regressed on BMI, and annual change in WC_BMI (ΔWC_BMI, cm/y) was defined as the difference between residuals at follow-up and baseline, divided by follow-up time. The association between food groups/items and ΔWC_BMI was modelled using centre-specific adjusted linear regression, and random-effects meta-analyses to obtain pooled estimates.

Results

Higher fruit and dairy products consumption was associated with a lower gain in WC_BMI whereas the consumption of white bread, processed meat, margarine, and soft drinks was positively associated with ΔWC_BMI. When these six food groups/items were analyzed in combination using a summary score, those in the highest quartile of the score – indicating a more favourable dietary pattern –showed a ΔWC_BMI of −0.11 (95% CI −0.09 to −0.14) cm/y compared to those in the lowest quartile.

Conclusion

A dietary pattern high in fruit and dairy and low in white bread, processed meat, margarine, and soft drinks may help to prevent abdominal fat accumulation.     

P25α / TPPP expression increases plasma membrane presentation of the dopamine transporter and enhances cellular sensitivity to dopamine toxicity

Parkinson's disease is characterized by preferential degeneration of the dopamine-producing neurons of the brain stem substantia nigra. Imbalances between mechanisms governing dopamine transport across the plasma membrane and cellular storage vesicles increase the level of toxic pro-oxidative cytosolic dopamine. The microtubule-stabilizing protein p25α accumulates in dopaminergic neurons in Parkinson's disease. We hypothesized that p25α modulates the subcellular localization of the dopamine transporter via effects on sorting vesicles, and thereby indirectly affects its cellular activity. Here we show that co-expression of the dopamine transporter with p25α in HEK-293-MSR cells increases dopamine uptake via increased plasma membrane presentation of the transporter. No direct interaction between p25α and the dopamine transporter was demonstrated, but they co-fractionated during subcellular fractionation of brain tissue from striatum, and direct binding of p25α peptides to brain vesicles was demonstrated. Truncations of the p25α peptide revealed that the requirement for stimulating dopamine uptake is located in the central core and were similar to those required for vesicle binding. Co-expression of p25α and the dopamine transporter in HEK-293-MSR cells sensitized them to the toxicity of extracellular dopamine. Neuronal expression of p25α thus holds the potential to sensitize the cells toward dopamine and toxins carried by the dopamine transporter.     

Large-scale network models of IL-1 and IL-6 signalling and their hepatocellular specification

The pro-inflammatory cytokines interleukin 1 (IL-1) and 6 (IL-6) are crucially involved in the regulation of a multitude of physiological processes, in particular coordinating the immune response upon bacterial infection and tissue injury. Both interleukins induce complex signalling cascades and trigger the production of mitogenic, pro-proliferative, anti-apoptotic, chemotactic, and pro-angiogenic factors thereby affecting the delicate balance between regeneration vs. invasive growth, tumourigenesis and metastasis. Moreover, several links to insulin resistance have been found within their associated signalling networks. Focusing on this from a systems biology perspective, we introduce comprehensive large-scale network models of IL-1 and IL-6 signalling which are based on a logical modelling approach and reflect the current biological knowledge. Theoretical network analysis enabled us to uncover general topological features and to make testable predictions on the stimulus-response behaviour of the networks. In this context, non-intuitive network-wide species dependencies as well as structures of regulatory feedback and feed-forward mechanisms could be characterised. By integrating high-throughput phosphoproteomic data from primary human hepatocytes we optimised the model structures to obtain models with high prediction accuracy for hepatocytes. Our model-based data analysis, for instance, suggested model modifications regarding (i) Akt contribution to IL-1-stimulated p38 MAPK activation and (ii) insignificant p38 MAPK activation in response to IL-6. In light of the presented results and in conjunction with the detailed model documentations, both models hold great potential for theoretical studies and practical applications.     

Caries-preventive effect of glass ionomer and resin-based fissure sealants on permanent teeth: An update of systematic review evidence

Background

The 1980s marked the occasion when Geographical Information System (GIS) technology was broadly introduced into the geo-spatial community through the establishment of a strong GIS industry. This technology quickly disseminated across many countries, and has now become established as an important research, planning and commercial tool for a wider community that includes organisations in the public and private health sectors. The broad acceptance of GIS technology and the nature of its functionality have meant that numerous datasets have been created over the past three decades. Most of these datasets have been created independently, and without any structured documentation systems in place. However, search and retrieval systems can only work if there is a mechanism for datasets existence to be discovered and this is where proper metadata creation and management can greatly help. This situation must be addressed through support mechanisms such as Web-based portal technologies, metadata editor tools, automation, metadata standards and guidelines and collaborative efforts with relevant individuals and organisations. Engagement with data developers or administrators should also include a strategy of identifying the benefits associated with metadata creation and publication.

Findings

The establishment of numerous Spatial Data Infrastructures (SDIs), and other Internet resources, is a testament to the recognition of the importance of supporting good data management and sharing practices across the geographic information community. These resources extend to health informatics in support of research, public services and teaching and learning. This paper identifies many of these resources available to the UK academic health informatics community. It also reveals the reluctance of many spatial data creators across the wider UK academic community to use these resources to create and publish metadata, or deposit their data in repositories for sharing. The Go-Geo! service is introduced as an SDI developed to provide UK academia with the necessary resources to address the concerns surrounding metadata creation and data sharing. The Go-Geo! portal, Geodoc metadata editor tool, ShareGeo spatial data repository, and a range of other support resources, are described in detail.

Conclusions

This paper describes a variety of resources available for the health research and public health sector to use for managing and sharing their data. The Go-Geo! service is one resource which offers an SDI for the eclectic range of disciplines using GIS in UK academia, including health informatics. The benefits of data management and sharing are immense, and in these times of cost restraints, these resources can be seen as solutions to find cost savings which can be reinvested in more research.