Cannabidiol protects against hepatic ischemia/reperfusion injury by attenuating inflammatory signaling and response, oxidative/nitrative stress, and cell death.

Ischemia/reperfusion (I/R) is a pivotal mechanism of liver damage after liver transplantation or hepatic surgery. We have investigated the effects of cannabidiol (CBD), the nonpsychotropic constituent of marijuana, in a mouse model of hepatic I/R injury. I/R triggered time-dependent increases/changes in markers of liver injury (serum transaminases), hepatic oxidative/nitrative stress (4-hydroxy-2-nonenal, nitrotyrosine content/staining, and gp91phox and inducible nitric oxide synthase mRNA), mitochondrial dysfunction (decreased complex I activity), inflammation (tumor necrosis factor α (TNF-α), cyclooxygenase 2, macrophage inflammatory protein-1α/2, intercellular adhesion molecule 1 mRNA levels; tissue neutrophil infiltration; nuclear factor κB (NF-κB) activation), stress signaling (p38MAPK and JNK), and cell death (DNA fragmentation, PARP activity, and TUNEL). CBD significantly reduced the extent of liver inflammation, oxidative/nitrative stress, and cell death and also attenuated the bacterial endotoxin-triggered NF-κB activation and TNF-α production in isolated Kupffer cells, likewise the adhesion molecule expression in primary human liver sinusoidal endothelial cells stimulated with TNF-α and attachment of human neutrophils to the activated endothelium. These protective effects were preserved in CB(2) knockout mice and were not prevented by CB(1/2) antagonists in vitro. Thus, CBD may represent a novel, protective strategy against I/R injury by attenuating key inflammatory pathways and oxidative/nitrative tissue injury, independent of classical CB(1/2) receptors.

Mutational screening of splicing factor genes in cases with autosomal dominant retinitis pigmentosa.

PURPOSE: Mutations in genes encoding proteins from the tri-snRNP complex of the spliceosome account for more than 12% of cases of autosomal dominant retinitis pigmentosa (adRP). Although the exact mechanism by which splicing factor defects trigger photoreceptor death is not completely clear, their role in retinitis pigmentosa has been demonstrated by several genetic and functional studies. To test for possible novel associations between splicing factors and adRP, we screened four tri-snRNP splicing factor genes (EFTUD2, PRPF4, NHP2L1, and AAR2) as candidate disease genes. METHODS: We screened up to 303 patients with adRP from Europe and North America who did not carry known RP mutations. Exon-PCR and Sanger methods were used to sequence the NHP2L1 and AAR2 genes, while the sequences of EFTUD2 and PRPF4 were obtained by using long-range PCRs spanning coding and non-coding regions followed by next-generation sequencing. RESULTS: We detected novel missense changes in individual patients in the sequence of the genes PRPF4 and EFTUD2, but the role of these changes in relationship to disease could not be verified. In one other patient we identified a novel nucleotide substitution in the 5' untranslated region (UTR) of NHP2L1, which did not segregate with the disease in the family. CONCLUSIONS: The absence of clearly pathogenic mutations in the candidate genes screened in our cohort suggests that EFTUD2, PRPF4, NHP2L1, and AAR2 are either not involved in adRP or are associated with the disease in rare instances, at least as observed in this study in patients of European and North American origin.

Quantitative modelling of transcription factor binding sites

Abstract One of the most important issues in molecular biology is to understand regulatory mechanisms that control gene expression. Gene expression is often regulated by proteins, called transcription factors which bind to short (5 to 20 base pairs),degenerate segments of DNA. Experimental efforts towards understanding the sequence specificity of transcription factors is laborious and expensive, but can be substantially accelerated with the use of computational predictions. This thesis describes the use of algorithms and resources for transcriptionfactor binding site analysis in addressing quantitative modelling, where probabilitic models are built to represent binding properties of a transcription factor and can be used to find new functional binding sites in genomes. Initially, an open-access database(HTPSELEX) was created, holding high quality binding sequences for two eukaryotic families of transcription factors namely CTF/NF1 and LEFT/TCF. The binding sequences were elucidated using a recently described experimental procedure called HTP-SELEX, that allows generation of large number (> 1000) of binding sites using mass sequencing technology. For each HTP-SELEX experiments we also provide accurate primary experimental information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, and assembled clone sequences of binding sequences. The database also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols.The database is available at http://wwwisrec.isb-sib.ch/htpselex/ and and ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex. The Expectation-Maximisation(EM) algorithm is one the frequently used methods to estimate probabilistic models to represent the sequence specificity of transcription factors. We present computer simulations in order to estimate the precision of EM estimated models as a function of data set parameters(like length of initial sequences, number of initial sequences, percentage of nonbinding sequences). We observed a remarkable robustness of the EM algorithm with regard to length of training sequences and the degree of contamination. The HTPSELEX database and the benchmarked results of the EM algorithm formed part of the foundation for the subsequent project, where a statistical framework called hidden Markov model has been developed to represent sequence specificity of the transcription factors CTF/NF1 and LEF1/TCF using the HTP-SELEX experiment data. The hidden Markov model framework is capable of both predicting and classifying CTF/NF1 and LEF1/TCF binding sites. A covariance analysis of the binding sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism. We next tested the LEF1/TCF model by computing binding scores for a set of LEF1/TCF binding sequences for which relative affinities were determined experimentally using non-linear regression. The predicted and experimentally determined binding affinities were in good correlation.

Measurement Properties of the Smartphone-Based B-B Score in Current Shoulder Pathologies.

NlmCategory="UNASSIGNED">This study is aimed at the determination of the measurement properties of the shoulder function B-B Score measured with a smartphone. This score measures the symmetry between sides of a power-related metric for two selected movements, with 100% representing perfect symmetry. Twenty healthy participants, 20 patients with rotator cuff conditions, 23 with fractures, 22 with capsulitis, and 23 with shoulder instabilities were measured twice across a six-month interval using the B-B Score and shoulder function questionnaires. The discriminative power, responsiveness, diagnostic power, concurrent validity, minimal detectable change (MDC), minimal clinically important improvement (MCII), and patient acceptable symptom state (PASS) were evaluated. Significant differences with the control group and significant baseline-six-month differences were found for the rotator cuff condition, fracture, and capsulitis patient groups. The B-B Score was responsive and demonstrated excellent diagnostic power, except for shoulder instability. The correlations with clinical scores were generally moderate to high, but lower for instability. The MDC was 18.1%, the MCII was 25.2%, and the PASS was 77.6. No floor effect was observed. The B-B Score demonstrated excellent measurement properties in populations with rotator cuff conditions, proximal humerus fractures, and capsulitis, and can thus be used as a routine test to evaluate those patients.

Host Genetics of Response to Hepatitis B Vaccine: A Systematic Review

Background. Hepatitis B virus (HBV) is an important cause of chronic viral disease worldwide and can be life threatening. While a safe and effective vaccine is widely available, 5 to 10% of healthy vaccinees fail to achieve a protective anti-hepatitis B surface antigen antibody (anti-HBs) titer (>10mIU/ml). A limited number of studies investigated host genetics of the response to HBV vaccine. To our knowledge, no comprehensive overview of genetic polymorphisms both within and outside the HLA system has been done so far. Aim. The aim of this study was to perform a systematic review of the literature of human genetics influencing immune response after hepatitis B vaccination. Methods. Literature searches using keywords were conducted in the electronic databases Medline, Embase and ISI Web of Science the cut-off date being March 2014. After selection of papers according to stringent inclusion criteria, relevant information was systematically collected from the remaining articles, including demographic data, number of patients, schedule and type of vaccine, phenotypes, genes and single nucleotide polymorphisms (SNPs) genotyping results and their association with immune response to hepatitis B vaccine. Results. The literature search produced a total of 1968 articles from which 46 studies were kept for further analyses. From these studies, data was extracted for 19 alleles from the human leukocyte antigen (HLA) region that were reported as significant at least twice. Among those alleles, 9 were firmly associated with vaccine response outcome (DQ2 [DQB1*02 and DQB1*0201], DR3 [DRB1*03 and DRB1*0301], DR7 [DRB1*07 and DRB1*0701], C4AQ0, DPB1*0401, DQ3, DQB1*06, DRB1*01 and DRB1*13 [DRB1*1301]). In addition, data was extracted for 55 different genes from which 13 extra-HLA genes had polymorphisms that were studied by different group of investigators or by the same group with a replication study. Among the 13 genes allowing comparison, 4 genes (IL-1B, IL-2, IL-4R and IL- 6) revealed no significant data, 6 genes (IL-4, IL-10, IL-12B, IL-13, TNFA, IFNG and TLR2) were explored with inconsistent results and 2 genes (CD3Z and ITGAL) yielded promising results as their association with vaccine response was confirmed by a replication approach. Furthermore, this review produced a list of 46 SNPs from 26 genes that were associated with immune response to vaccine only once, providing novel candidates to be tested in datasets from existing genome-wide association studies (GWAS). Conclusion. To the best of our knowledge, this is the first systematic review of immunogenetic studies of response to hepatitis B vaccine. While this work reassesses the role of several HLA alleles on vaccine response outcome, the associations with polymorphisms in genes outside the HLA region were rather inconsistent. Moreover, this work produced a list of 46 significant SNPs that were reported by a single group of investigators, opening up some interesting possibilities for further research.