Supports Used by Aboriginal and Torres Strait Islander Women for Their Health, including Smoking Cessation, and a Baby's Health: A Cross-Sectional Survey in New South Wales, Australia

Supports Used by Aboriginal and Torres Strait Islander Women for Their Health, including Smoking Cessation, and a Baby's Health: A Cross-Sectional Survey in New South Wales, Australi

Segmentation characteristics of models selected by Procedure 2.

<p>Length: number of alignment columns in the component; Nfixed: number of fixed change-points, corresponding to the boundaries of alignment blocks; <i>k</i>: posterior average number of change-points; <i>L</i>: posterior average length of segments. Note the length of the coding sequence is equal to that of the 3′ UTRs for the same species pair, once the number of fixed change-points (corresponding to the ends of alignment blocks) is added to the length.</p

Motifs identified by MEME.

<p>Sequence LOGOs for four of the motifs identified by MEME in the 15-class model for the <i>D. melanogaster</i> versus <i>D. simulans</i> 3′ UTR alignment: A) a polyA motif identified in Class 1, B) a CAG repeat motif identified in Class 9, C) a CA repeat motif identified in Class 12, D) a TCC repeat motif identified in Class 9.</p

Models selected using two procedures.

<p>Dme: <i>D. melanogaster</i>; Dsi: <i>D. simulans</i>; Dya: <i>D. yakuba</i>; Procedure 1: Models selected based on DICV values; Procedure 2: Models selected by investigating stability of classes; Coding 1, 2, 3: three different coding sequences.</p

DICV values for segmentation of binary sequences.

<p>DICV values versus the number of classes (1–10) for segmentation of: A) the binary representation of GC content in <i>D. melanogaster</i> 3′ UTRs, and B) the binary representation of conservation in the <i>D. melanogaster</i> versus <i>D. simulans</i> 3′ UTR alignment.</p

GC content versus conservation level for models selected by Procedure 2.

<p>GC content (in the first named species of each pair) versus the proportion of alignment matches, for each model selected by Procedure 2. The different colours represent different classes, and each class is plotted for the post burn-in samples; A) 15-class model for the <i>D. melanogaster</i> versus <i>D. simulans</i> 3′ UTR alignment, B) 12-class model for the <i>D. melanogaster</i> versus <i>D. simulans</i> first coding sequence (Coding 1) alignment, C) 16-class model for the <i>D. melanogaster</i> versus <i>D. yakuba</i> 3′ UTR alignment and D) 15-class model for the <i>D. simulans</i> versus <i>D. yakuba</i> 3′ UTR alignment.</p

Stress increases the risk of type 2 diabetes onset in women: A 12-year longitudinal study using causal modelling

<div><p>Background</p><p>Type 2 diabetes is associated with significant morbidity and mortality. Modifiable risk factors have been found to contribute up to 60% of type 2 diabetes risk. However, type 2 diabetes continues to rise despite implementation of interventions based on traditional risk factors. There is a clear need to identify additional risk factors for chronic disease prevention. The aim of this study was to examine the relationship between perceived stress and type 2 diabetes onset, and partition the estimates into direct and indirect effects.</p><p>Methods and findings</p><p>Women born in 1946–1951 (n = 12,844) completed surveys for the Australian Longitudinal Study on Women’s Health in 1998, 2001, 2004, 2007 and 2010. The total causal effect was estimated using logistic regression and marginal structural modelling. Controlled direct effects were estimated through conditioning in the regression model. A graded association was found between perceived stress and all mediators in the multivariate time lag analyses. A significant association was found between hypertension, as well as physical activity and body mass index, and diabetes, but not smoking or diet quality. Moderate/high stress levels were associated with a 2.3-fold increase in the odds of diabetes three years later, for the total estimated effect. Results were only slightly attenuated when the direct and indirect effects of perceived stress on diabetes were partitioned, with the mediators only explaining 10–20% of the excess variation in diabetes.</p><p>Conclusions</p><p>Perceived stress is a strong risk factor for type 2 diabetes. The majority of the effect estimate of stress on diabetes risk is not mediated by the traditional risk factors of hypertension, physical activity, smoking, diet quality, and body mass index. This gives a new pathway for diabetes prevention trials and clinical practice.</p></div

Supplementary_Figure_1 - Proteomic Analysis Identifies Tenascin-C Expression Is Upregulated in Uterine Fibroids

<p>Supplementary_Figure_1 for Proteomic Analysis Identifies Tenascin-C Expression Is Upregulated in Uterine Fibroids by M. Fairuz B. Jamaluddin, Prathima B. Nagendra, Pravin Nahar, Christopher Oldmeadow, and Pradeep S. Tanwar in Reproductive Sciences</p

Longitudinal associations between the hypothesised mediators and type 2 diabetes, using a time lag approach.

<p>Each analysis is adjusted for the potential confounders of SES (measured by educational attainment) and age, as well as secular trends (time by survey). The aim here is to identify the relationship between each mediator and the outcome of type 2 diabetes. The combined effect of all the mediators is modelled in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172126#pone.0172126.t004" target="_blank">Table 4</a>.</p

Total causal effects of perceived stress on type 2 diabetes using a time lag approach (assuming physical activity as a time varying mediator).^a^,^b

<p>Total causal effects of perceived stress on type 2 diabetes using a time lag approach (assuming physical activity as a time varying mediator).<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172126#t004fn001" target="_blank">^a</a>^,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172126#t004fn002" target="_blank">^b</a></p