41 research outputs found

    Potential pitfalls of modelling ribosomal RNA data in phylogenetic tree reconstruction: Evidence from case studies in the Metazoa

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    <p>Abstract</p> <p>Background</p> <p>Failure to account for covariation patterns in helical regions of ribosomal RNA (rRNA) genes has the potential to misdirect the estimation of the phylogenetic signal of the data. Furthermore, the extremes of length variation among taxa, combined with regional substitution rate variation can mislead the alignment of rRNA sequences and thus distort subsequent tree reconstructions. However, recent developments in phylogenetic methodology now allow a comprehensive integration of secondary structures in alignment and tree reconstruction analyses based on rRNA sequences, which has been shown to correct some of these problems. Here, we explore the potentials of RNA substitution models and the interactions of specific model setups with the inherent pattern of covariation in rRNA stems and substitution rate variation among loop regions.</p> <p>Results</p> <p>We found an explicit impact of RNA substitution models on tree reconstruction analyses. The application of specific RNA models in tree reconstructions is hampered by interaction between the appropriate modelling of covarying sites in stem regions, and excessive homoplasy in some loop regions. RNA models often failed to recover reasonable trees when single-stranded regions are excessively homoplastic, because these regions contribute a greater proportion of the data when covarying sites are essentially downweighted. In this context, the RNA6A model outperformed all other models, including the more parametrized RNA7 and RNA16 models.</p> <p>Conclusions</p> <p>Our results depict a trade-off between increased accuracy in estimation of interdependencies in helical regions with the risk of magnifying positions lacking phylogenetic signal. We can therefore conclude that caution is warranted when applying rRNA covariation models, and suggest that loop regions be independently screened for phylogenetic signal, and eliminated when they are indistinguishable from random noise. In addition to covariation and homoplasy, other factors, like non-stationarity of substitution rates and base compositional heterogeneity, can disrupt the signal of ribosomal RNA data. All these factors dictate sophisticated estimation of evolutionary pattern in rRNA data, just as other molecular data require similarly complicated (but different) corrections.</p

    Proteomics in India: the clinical aspect

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    Evaluation of Prescription Pattern and Medication Adherence in Patients with Alcoholic Liver Disease

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    Background: ALD is the most common cause of morbidity and mortality among patients. A patient’s Medication Non-Adherence may also interfere with the progression of Disease. Analysis of Prescription pattern in ALD helps to ensure the safety of the Patient by assessing the signs and symptoms of disease and its appropriate therapy. &nbsp;Thus, educating the patients regarding their clinical condition will have a significant role in reducing the severity of the disease. Aim: To assess the Prescription pattern, Medication Adherence and to identify the correlation between the medication adherence and the educational status in ALD patients. Materials and Methods: The Study was a Prospective Observational study carried out for a duration of Six months. Morisky Green Levine scale was the tool used to assess the medication adherence. Data was collected using a self-designed data collection form. Results: A Total of 160 Alcoholic subjects were assessed during the study period among which 65.62% of them were illiterate. Out of total cases 76.87 % of hepatoprotective drugs, 50.62% antiemetics, 38% vitamins and 11% of anti-ulcer drugs were prescribed among patients. &nbsp;It was found that there exist a relationship between educational status and medication adherence (P-value: 0.0021). Conclusion: The study helped to assess the &nbsp;different class of drugs, drugs used in different comorbid conditions and also to evaluate, identify and solve the problems associated with the Medication Non-Adherence of the patients. Keywords: Medication Adherence, Alcoholic Liver Disease, Rational Drug Therapy
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