ALBERT

Description: We present a formalized medical knowledge system using a linguistic approach combined with a semantic net.

Description: Background: Non-adherence to Antiretroviral Treatment (ART) is strongly associated with virologic rebound and drug resistance. Studies have shown that the most frequently mentioned reason for missing ART doses is the forgetfulness of patients to take their medications on time. Therefore using communication devices as reminder tools, for example alarms, pagers, text messages and telephone calls could improve adherence to ART. The aim of this study is to measure access to cellphones, willingness to receive text message medication reminders and to identify associated factors of ART patients at the University of Gondar Hospital, in North West Ethiopia. Methods: An institution based cross sectional quantitative study was conducted among 423 patients on ART during April 2014. Data were collected using structured interviewer-administered questionnaires. Data entry and analysis were done using Epi-Info version 7 and SPSS version 20 respectively. Descriptive statistics and multivariable logistic regression analysis were used to describe the characteristic of the sample and identify factors associated with the willingness to receive text message medication reminders. Results: A total of 415 (98 % response rate) respondents participated in the interview. The majority of respondents 316 (76.1 %) owned a cellphone, and 161(50.9 %) were willing to receive text message medication reminders. Positively associated factors to the willingness were the following: Younger age group (AOR = 5.18, 95 % CI: [1.69, 15.94]), having secondary or higher education (AOR = 4.61, 95 % CI: [1.33, 16.01]), using internet (AOR = 3.94, 95 % CI: [1.67, 9.31]), not disclosing HIV status to anyone other than HCP (Health Care Provider) (AOR = 3.03, 95 % CI: [1.20, 7.61]), availability of radio in dwelling (AOR = 2.74 95 % CI: [1.27, 5.88]), not answering unknown calls (AOR = 2.67, 95 % CI: [1.34, 5.32]), use of cellphone alarm as medication reminder (AOR = 2.22, 95%CI [1.09, 4.52]), and forgetting to take medications (AOR = 2.13, 95 % CI: [1.14, 3.96]). Conclusions: A high proportion of respondents have a cell phone and are willing to use it as medication reminders. Age, educational status and using internet were the main factors that are significantly associated with the willingness of patients to receive text message medication reminders.

Description: Background: Identification of marker genes associated with a specific tissue/cell type is a fundamental challenge in genetic and cell research. Marker genes are of great importance for determining cell identity, and for understanding tissue specific gene function and the molecular mechanisms underlying complex diseases. Results: We have developed a new bioinformatics tool called MGFM (Marker Gene Finder in Microarray data) to predict marker genes from microarray gene expression data. Marker genes are identified through the grouping of samples of the same type with similar marker gene expression levels. We verified our approach using two microarray data sets from the NCBI’s Gene Expression Omnibus public repository encompassing samples for similar sets of five human tissues (brain, heart, kidney, liver, and lung). Comparison with another tool for tissue-specific gene identification and validation with literature-derived established tissue markers established functionality, accuracy and simplicity of our tool. Furthermore, top ranked marker genes were experimentally validated by reverse transcriptase-polymerase chain reaction (RT-PCR). The sets of predicted marker genes associated with the five selected tissues comprised well-known genes of particular importance in these tissues. The tool is freely available from the Bioconductor web site, and it is also provided as an online application integrated into the CellFinder platform (http://cellfinder.org/analysis/marker). Conclusions: MGFM is a useful tool to predict tissue/cell type marker genes using microarray gene expression data. The implementation of the tool as an R-package as well as an application within CellFinder facilitates its use.

Description: Background: Different species and strains of probiotic bacteria confer distinct immunological responses on immune cells. Lactobacillus rhamnosus GR-1 (GR-1) is a probiotic bacterial strain found in both the intestinal and urogenital tracts, and has immunomodulatory effects on several cell types including macrophages. However, detailed immunological responses and the signaling mechanism involved in the response are largely unknown. Results: We examined the production of GR-1-induced cytokines/chemokines and signaling events in macrophages. Among 84 cytokines and chemokines examined, GR-1 discretely induced granulocyte colony-stimulating factor (G-CSF) mRNA at highest levels (〉60-fold) without inducing other cytokines such as IL-1α, IL-1β, IL-6 and TNF-α ( 50-fold). The TLR2 ligand lipoteichoic acid activated all mitogen-activated kinases, Akt and NF-κB; whereas, GR-1 selectively activated extracellular regulated kinases and p38, NF-κB and Akt, but not c-Jun N-terminal kinases (JNKs) in a TLR2-dependent manner. Using specific inhibitors, we demonstrated that lack of JNKs activation by GR-1 caused inefficient production of pro-inflammatory cytokines but not G-CSF production. A secreted heat-labile protein-like molecule, 30–100 kDa in size, induced the preferential production of G-CSF. Conclusion: This study elucidated unique signaling events triggered by GR-1, resulting in selective production of the immunomodulatory cytokine G-CSF in macrophages.

Description: Background: CGGBP1 is a repetitive DNA-binding transcription regulator with target sites at CpG-rich sequences such as CGG repeats and Alu-SINEs and L1-LINEs. The role of CGGBP1 as a possible mediator of CpG methylation however remains unknown. At CpG-rich sequences cytosine methylation is a major mechanism of transcriptional repression. Concordantly, gene-rich regions typically carry lower levels of CpG methylation than the repetitive elements. It is well known that at interspersed repeats Alu-SINEs and L1-LINEs high levels of CpG methylation constitute a transcriptional silencing and retrotransposon inactivating mechanism. Results: Here, we have studied genome-wide CpG methylation with or without CGGBP1-depletion. By high throughput sequencing of bisulfite-treated genomic DNA we have identified CGGBP1 to be a negative regulator of CpG methylation at repetitive DNA sequences. In addition, we have studied CpG methylation alterations on Alu and L1 retrotransposons in CGGBP1-depleted cells using a novel bisulfite-treatment and high throughput sequencing approach. Conclusions: The results clearly show that CGGBP1 is a possible bidirectional regulator of CpG methylation at Alus, and acts as a repressor of methylation at L1 retrotransposons.

Description: The minimally invasive, balloon-assisted reduction and cement-augmented internal fixation of the tibial plateau is an innovative surgical procedure for tibial plateau fractures. The close proximity of balloons...

Description: Background: Point mutations can have a strong impact on protein stability. A change in stability may subsequently lead to dysfunction and finally cause diseases. Moreover, protein engineering approaches aim to deliberately modify protein properties, where stability is a major constraint. In order to support basic research and protein design tasks, several computational tools for predicting the change in stability upon mutations have been developed. Comparative studies have shown the usefulness but also limitations of such programs. Results: We aim to contribute a novel method for predicting changes in stability upon point mutation in proteins called MAESTRO. MAESTRO is structure based and distinguishes itself from similar approaches in the following points: (i) MAESTRO implements a multi-agent machine learning system. (ii) It also provides predicted free energy change (Δ ΔG) values and a corresponding prediction confidence estimation. (iii) It provides high throughput scanning for multi-point mutations where sites and types of mutation can be comprehensively controlled. (iv) Finally, the software provides a specific mode for the prediction of stabilizing disulfide bonds. The predictive power of MAESTRO for single point mutations and stabilizing disulfide bonds is comparable to similar methods. Conclusions: MAESTRO is versatile tool in the field of stability change prediction upon point mutations. Executables for the Linux and Windows operating systems are freely available to non-commercial users from http://biwww.che.sbg.ac.at/MAESTRO.

Description: Background: Previously, we identified a major quantitative trait locus (QTL) for host response to Porcine Respiratory and Reproductive Syndrome virus (PRRSV) infection in high linkage disequilibrium (LD) with SNP rs80800372 on Sus scrofa chromosome 4 (SSC4). Results: Within this QTL, guanylate binding protein 5 (GBP5) was differentially expressed (DE) (p 

Description: Background: The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60 K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so the effect of the WUR10000125 (WUR) genotype on expression in whole blood was also examined. Results: Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4dpi contrasted with 0dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. Conclusion: There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups.