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Will, S.

Publications and source records attributed to Will, S..

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Bi-Alignments as Models of Incongruent Evolution of RNA Sequence and Structure

RNA molecules may experience independent selection pressures on their sequence and (secondary) structure. Structural features then may be preserved without maintaining their exact position along the sequence. In such cases, corresponding base pairs are no longer formed by homologous bases, leading to the incongruent evolutionary conservation of sequence and structure. In order to model this phenomenon, we introduce bi-alignments as a superposition of two alignments: one modeling sequence homology; the other, structural homology. We show that under natural assumptions on the scoring functions, bi-alignments form a special case of 4-way alignments, in which the incongruencies are measured as indels in the pairwise alignment of the two alignment copies. A preliminary survey of the Rfam database suggests that incongruent evolution of RNAs is not a very rare phenomenon.\n\nAvailabilityOur software is freely available at https://github.com/s-will/BiAlign

bioinformatics

Renal and Renal Sinus Fat Volumes as Quantified by Magnetic Resonance Imaging in Subjects with Prediabetes, Diabetes, and Normal Glucose Tolerance.

PurposeThe aim of this study was to assess the volume of the respective kidney compartments with particular interest in renal sinus fat as an early biomarker and to compare the distribution between individuals with normal glucose levels and individuals with prediabetes and diabetes.\n\nMaterial and MethodsThe sample comprised N = 366 participants who were either normoglycemic (N = 230), had prediabetes (N = 87) or diabetes (N =49), as determined by Oral Glucose Tolerance Test. Other covariates were obtained by standardized measurements and interviews. Whole-body MR measurements were performed on a 3 Tesla scanner. For assessment of the kidneys, a coronal T1w dual-echo Dixon and a coronal T2w single shot fast spin echo sequence were employed. Stepwise semi-automated segmentation of the kidneys on the Dixon-sequences was based on thresholding and geometric assumptions generating volumes for the kidneys and sinus fat. Inter- and intra-reader variability were determined on a subset of 40 subjects. Associations between glycemic status and renal volumes were evaluated by linear regression models, adjusted for other potential confounding variables. Furthermore, the association of renal volumes with visceral adipose tissue was assessed by linear regression models and Pearsons correlation coefficient.\n\nResultsRenal volume, renal sinus volume and renal sinus fat increased gradually from normoglycemic controls to individuals with prediabetes to individuals with diabetes (renal volume: 280.3{+/-}64.7 ml vs 303.7{+/-}67.4 ml vs 320.6{+/-}77.7ml, respectively, p < 0.001). After adjustment for age and sex, prediabetes and diabetes were significantly associated to increased renal volume, sinus volume (e.g. {beta}prediabetes = 10.1, 95% CI: [6.5, 13.7]; p<0.01, {beta}Diabetes = 11.86, 95% CI: [7.2, 16.5]; p<0.01) and sinus fat (e.g. {beta}prediabetes = 7.13, 95% CI: [4.5, 9.8]; p<0.001, {beta}Diabetes = 7.34, 95% CI: [4.0, 10.7]; p<0.001). Associations attenuated after adjustment for additional confounders were only significant for prediabetes and sinus volume ({beta} =4.0 95% CI [0.4, 7.6]; p<0.05). Hypertension was significantly associated with increased sinus volume ({beta} = 3.7, 95% CI: [0.4, 6.9; p<0.05]) and absolute sinus fat volume ({beta} = 3.0, 95%CI: [0.7, 5.2]; p<0.05). GFR and all renal volumes were significantly associated as well as urine albumin levels and renal sinus volume ({beta} = 1.6, 95% CI: [0.2, 3.0]; p<0.05). There was a highly significant association between VAT and the absolute sinus fat volume ({beta} = 2.75, 95% CI: [2.3, 3.2]; p<0.01).\n\nConclusionRenal volume and particularly renal sinus fat volume already increases significantly in prediabetic subjects. There is a significant association between VAT and renal sinus fat, suggesting that there are metabolic interactions between these perivascular fat compartments.

epidemiology