Physicians Infrequently Adhere to Hepatitis Vaccination Guidelines for Chronic Liver Disease

Background and Goals:Hepatitis A (HAV) and hepatitis B (HBV) vaccination in patients with chronic liver disease is an accepted standard of care. We determined HAV and HBV vaccination rates in a tertiary care referral hepatology clinic and the impact of electronic health record (EHR)-based reminders on adherence to vaccination guidelines.Methods:We reviewed the records of 705 patients with chronic liver disease referred to our liver clinic in 2008 with at least two follow-up visits during the subsequent year. Demographics, referral source, etiology, and hepatitis serology were recorded. We determined whether eligible patients were offered vaccination and whether patients received vaccination. Barriers to vaccination were determined by a follow-up telephone interview.Results:HAV and HBV serologic testing prior to referral and at the liver clinic were performed in 14.5% and 17.7%; and 76.7% and 74% patients, respectively. Hepatologists recommended vaccination for HAV in 63% and for HBV in 59.7% of eligible patients. Patient demographics or disease etiology did not influence recommendation rates. Significant variability was observed in vaccination recommendation amongst individual providers (30-98.6%), which did not correlate with the number of patients seen by each physician. Vaccination recommendation rates were not different for Medicare patients with hepatitis C infection for whom a vaccination reminder was automatically generated by the EHR. Most patients who failed to get vaccination after recommendation offered no specific reason for noncompliance; insurance was a barrier in a minority.Conclusions:Hepatitis vaccination rates were suboptimal even in an academic, sub-speciality setting, with wide-variability in provider adherence to vaccination guidelines. © 2013 Thudi et al

Molecular evolution of HoxA13 and the multiple origins of limbless morphologies in amphibians and reptiles

Developmental processes and their results, morphological characters, are inherited through transmission of genes regulating development. While there is ample evidence that cis-regulatory elements tend to be modular, with sequence segments dedicated to different roles, the situation for proteins is less clear, being particularly complex for transcription factors with multiple functions. Some motifs mediating protein-protein interactions may be exclusive to particular developmental roles, but it is also possible that motifs are mostly shared among different processes. Here we focus on HoxA13, a protein essential for limb development. We asked whether the HoxA13 amino acid sequence evolved similarly in three limbless clades: Gymnophiona, Amphisbaenia and Serpentes. We explored variation in ω (dN/dS) using a maximum-likelihood framework and HoxA13sequences from 47 species. Comparisons of evolutionary models provided low ω global values and no evidence that HoxA13 experienced relaxed selection in limbless clades. Branch-site models failed to detect evidence for positive selection acting on any site along branches of Amphisbaena and Gymnophiona, while three sites were identified in Serpentes. Examination of alignments did not reveal consistent sequence differences between limbed and limbless species. We conclude that HoxA13 has no modules exclusive to limb development, which may be explained by its involvement in multiple developmental processes

Effect of oat bran on time to exhaustion, glycogen content and serum cytokine profile following exhaustive exercise

The aim of this study was to evaluate the effect of oat bran supplementation on time to exhaustion, glycogen stores and cytokines in rats submitted to training. The animals were divided into 3 groups: sedentary control group (C), an exercise group that received a control chow (EX) and an exercise group that received a chow supplemented with oat bran (EX-O). Exercised groups were submitted to an eight weeks swimming training protocol. In the last training session, the animals performed exercise to exhaustion, (e.g. incapable to continue the exercise). After the euthanasia of the animals, blood, muscle and hepatic tissue were collected. Plasma cytokines and corticosterone were evaluated. Glycogen concentrations was measured in the soleus and gastrocnemius muscles, and liver. Glycogen synthetase-α gene expression was evaluated in the soleus muscle. Statistical analysis was performed using a factorial ANOVA. Time to exhaustion of the EX-O group was 20% higher (515 ± 3 minutes) when compared with EX group (425 ± 3 minutes) (p = 0.034). For hepatic glycogen, the EX-O group had a 67% higher concentrations when compared with EX (p = 0.022). In the soleus muscle, EX-O group presented a 59.4% higher glycogen concentrations when compared with EX group (p = 0.021). TNF-α was decreased, IL-6, IL-10 and corticosterone increased after exercise, and EX-O presented lower levels of IL-6, IL-10 and corticosterone levels in comparison with EX group. It was concluded that the chow rich in oat bran increase muscle and hepatic glycogen concentrations. The higher glycogen storage may improve endurance performance during training and competitions, and a lower post-exercise inflammatory response can accelerate recovery

Evidence of Genetic Instability in Tumors and Normal Nearby Tissues

We have analyzed the sequence heterogeneity of the transcripts of the human HPRT and G6PD single copy genes that are not considered tumor markers. Analyses have been performed on different colon cancers and on the nearby histologically normal tissues of two male patients. Several copies of each cDNA, which were produced by cloning the RT-PCR-amplified fragments of the specific mRNA, have been sequenced. Similar analyses have been performed on blood samples of two ostensibly healthy males as reference controls. The sequence heterogeneity of the HPRT and G6PD genes was also determined on DNA from tumor tissues. The employed analytical approach revealed the presence of low-frequency mutations not detectable by other procedures. The results show that genetic heterogeneity is detectable in HPRT and G6PD transcripts in both tumors and nearby healthy tissues of the two studied colon tumors. Similar frequencies of mutations are observed in patient genomic DNA, indicating that mutations have a somatic origin. HPRT transcripts show genetic heterogeneity also in healthy individuals, in agreement with previous results on human T-cells, while G6PD transcript heterogeneity is a characteristic of the patient tissues. Interestingly, data on TP53 show little, if any, heterogeneity in the same tissues. CONCLUSIONS/SIGNIFICANCE: These findings show that genetic heterogeneity is a peculiarity not only of cancer cells but also of the normal tissue where a tumor arises

Genotype V Japanese Encephalitis Virus Is Emerging

Japanese encephalitis (JE) is a global public health issue that has spread widely to more than 20 countries in Asia and has extended its geographic range to the south Pacific region including Australia. JE has become the most important cause of viral encephalitis in the world. Japanese encephalitis viruses (JEV) are divided into five genotypes, based on the nucleotide sequence of the envelope (E) gene. The Muar strain, isolated from patient in Malaya in 1952, is the sole example of genotype V JEV. Here, the XZ0934 strain of JEV was isolated from Culex tritaeniorhynchus, collected in China. The complete nucleotide and amino acid sequence of XZ0934 strain have been determined. The nucleotide divergence ranged from 20.3% to 21.4% and amino acid divergence ranged from 8.4% to 10.0% when compared with the 62 known JEV isolates that belong to genotype I–IV. It reveals low similarity between XZ0934 and genotype I–IV JEVs. Phylogenetic analysis using both complete genome and structural gene nucleotide sequences demonstrates that XZ0934 belongs to genotype V. This, in turn, suggests that genotype V JEV is emerging in JEV endemic areas. Thus, increased surveillance and diagnosis of viral encephalitis caused by genotype V JEV is an issue of great concern to nations in which JEV is endemic

Targeting HOX/PBX dimers in cancer

The HOX and PBX gene families encode transcription factors that have key roles in establishing the identity of cells and tissues in early development. Over the last 20 years it has become apparent that they are also dysregulated in a wide range of solid and haematological malignancies and have a predominantly pro-oncogenic function. A key mode of transcriptional regulation by HOX and PBX proteins is through their interaction as a heterodimer or larger complex that enhances their binding affinity and specificity for DNA, and there is growing evidence that this interaction is a potential therapeutic target in malignancies that include prostate, breast, renal, ovarian and lung cancer, melanoma, myeloma, and acute myeloid leukaemia. This review summarizes the roles of HOX and PBX genes in cancer and assesses the therapeutic potential of HOX/PBX dimer inhibition, including the availability of biomarkers for its application in precision medicine

How accurate and statistically robust are catalytic site predictions based on closeness centrality?

<p>Abstract</p> <p>Background</p> <p>We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex <it>i </it>and all other vertices.</p> <p>Results</p> <p>We benchmark the approach against 283 structurally unique proteins within the Catalytic Site Atlas. Our results, which are inline with previous investigations of smaller datasets, indicate closeness centrality predictions are statistically significant. However, unlike previous approaches, we specifically focus on residues with the very best scores. Over the top five closeness centrality scores, we observe an average true to false positive rate ratio of 6.8 to 1. As demonstrated previously, adding a solvent accessibility filter significantly improves predictive power; the average ratio is increased to 15.3 to 1. We also demonstrate (for the first time) that filtering the predictions by residue identity improves the results even more than accessibility filtering. Here, we simply eliminate residues with physiochemical properties unlikely to be compatible with catalytic requirements from consideration. Residue identity filtering improves the average true to false positive rate ratio to 26.3 to 1. Combining the two filters together has little affect on the results. Calculated p-values for the three prediction schemes range from 2.7E-9 to less than 8.8E-134. Finally, the sensitivity of the predictions to structure choice and slight perturbations is examined.</p> <p>Conclusion</p> <p>Our results resolutely confirm that closeness centrality is a viable prediction scheme whose predictions are statistically significant. Simple filtering schemes substantially improve the method's predicted power. Moreover, no clear effect on performance is observed when comparing ligated and unligated structures. Similarly, the CC prediction results are robust to slight structural perturbations from molecular dynamics simulation.</p

Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties

BACKGROUND: The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for functional prediction. Knowledge of catalytic sites provides a valuable insight into protein function. Although many computational methods have been developed to predict catalytic residues and active sites, their accuracy remains low, with a significant number of false positives. In this paper, we present a novel method for the prediction of catalytic sites, using a carefully selected, supervised machine learning algorithm coupled with an optimal discriminative set of protein sequence conservation and structural properties. RESULTS: To determine the best machine learning algorithm, 26 classifiers in the WEKA software package were compared using a benchmarking dataset of 79 enzymes with 254 catalytic residues in a 10-fold cross-validation analysis. Each residue of the dataset was represented by a set of 24 residue properties previously shown to be of functional relevance, as well as a label {+1/-1} to indicate catalytic/non-catalytic residue. The best-performing algorithm was the Sequential Minimal Optimization (SMO) algorithm, which is a Support Vector Machine (SVM). The Wrapper Subset Selection algorithm further selected seven of the 24 attributes as an optimal subset of residue properties, with sequence conservation, catalytic propensities of amino acids, and relative position on protein surface being the most important features. CONCLUSION: The SMO algorithm with 7 selected attributes correctly predicted 228 of the 254 catalytic residues, with an overall predictive accuracy of more than 86%. Missing only 10.2% of the catalytic residues, the method captures the fundamental features of catalytic residues and can be used as a "catalytic residue filter" to facilitate experimental identification of catalytic residues for proteins with known structure but unknown function