Uptake of regular chlamydia testing by U.S. women: a longitudinal study

Background Routine chlamydia screening is a recommended preventive intervention for sexually active women aged ≤25 years in the U.S. but rates of regular uptake are not known. Purpose This study aimed to examine rates of annual chlamydia testing and factors associated with repeat testing in a population of U.S. women. Methods Women aged 15–25 years at any time from January 1, 2002, to December 31, 2006 who were enrolled in 130 commercial health plans were included. Data relating to chlamydia tests were analyzed in 2009. Chlamydia testing rates (per 100 woman-years) by age and rates of repeated annual testing were estimated. Poisson regression was used to examine the effects of age and previous testing on further chlamydia testing within the observation period. Results In total, 2,632,365 women were included. The chlamydia testing rate over the whole study period was 13.6 per 100 woman years after adjusting for age-specific sexual activity; 8.5 (95% CI=6.0, 12.3) per 100 woman-years in those aged 15 years; and 17.7 (95% CI=17.1, 18.9) in those aged 25 years. Among women enrolled for the entire 5-year study period, 25.9% had at least one test but only 0.1% had a chlamydia test every year. Women tested more than once and older women were more likely to be tested again in the observation period. Conclusions The low rates of regular annual chlamydia testing do not comply with national recommendations and would not be expected to have a major impact on the control of chlamydia infection at the population level.

Regular physical activity moderates cardiometabolic risk in Alzheimer's caregivers

Dementia caregivers have an increased risk of cardiovascular disease, and it is possible that metabolic disturbances contribute to this risk. Regular physical exercise reduces cardiometabolic risk, but caregivers may have less opportunity to engage in such activity. We hypothesized that regular physical activity would moderate cardiometabolic risk in dementia caregivers.

Genome-wide association study identifies new HLA class II haplotypes strongly protective against narcolepsy

Narcolepsy is a rare sleep disorder with the strongest human leukocyte antigen (HLA) association ever reported. Since the associated HLA-DRB1*1501-DQB1*0602 haplotype is common in the general population (15-25%), it has been suggested that it is almost necessary but not sufficient for developing narcolepsy. To further define the genetic basis of narcolepsy risk, we performed a genome-wide association study (GWAS) in 562 European individuals with narcolepsy (cases) and 702 ethnically matched controls, with independent replication in 370 cases and 495 controls, all heterozygous for DRB1*1501-DQB1*0602. We found association with a protective variant near HLA-DQA2 (rs2858884; P < 3 x 10(-8)). Further analysis revealed that rs2858884 is strongly linked to DRB1*03-DQB1*02 (P < 4 x 10(-43)) and DRB1*1301-DQB1*0603 (P < 3 x 10(-7)). Cases almost never carried a trans DRB1*1301-DQB1*0603 haplotype (odds ratio = 0.02; P < 6 x 10(-14)). This unexpected protective HLA haplotype suggests a virtually causal involvement of the HLA region in narcolepsy susceptibility.

A Flow Trace Generator using Graph-based Traffic Classification Techniques

We propose a novel methodology to generate realistic network flow traces to enable systematic evaluation of network monitoring systems in various traffic conditions. Our technique uses a graph-based approach to model the communication structure observed in real-world traces and to extract traffic templates. By combining extracted and user-defined traffic templates, realistic network flow traces that comprise normal traffic and customized conditions are generated in a scalable manner. A proof-of-concept implementation demonstrates the utility and simplicity of our method to produce a variety of evaluation scenarios. We show that the extraction of templates from real-world traffic leads to a manageable number of templates that still enable accurate re-creation of the original communication properties on the network flow level.

Natural variations at position 93 of the invariant Vα24-Jα18 α chain of human iNKT-cell TCRs strongly impact on CD1d binding

Human invariant natural killer T (NKT) cell TCRs bind to CD1d via an "invariant" Vα24-Jα18 chain (iNKTα) paired to semi-invariant Vβ11 chains (iNKTβ). Single-amino acid variations at position 93 (p93) of iNKTα, immediately upstream of the "invariant" CDR3α region, have been reported in a substantial proportion of human iNKT-cell clones (4-30%). Although p93, a serine in most human iNKT-cell TCRs, makes no contact with CD1d, it could affect CD1d binding by altering the conformation of the crucial CDR3α loop. By generating recombinant refolded iNKT-cell TCRs, we show that natural single-nucleotide variations in iNKTα, translating to serine, threonine, asparagine or isoleucine at p93, exert a powerful effect on CD1d binding, with up to 28-fold differences in affinity between these variants. This effect was observed with CD1d loaded with either the artificial α-galactosylceramide antigens KRN7000 or OCH, or the endogenous glycolipid β-galactosylceramide, and its importance for autoreactive recognition of endogenous lipids was demonstrated by the binding of variant iNKT-cell TCR tetramers to cell surface expressed CD1d. The serine-containing variant showed the strongest CD1d binding, offering an explanation for its predominance in vivo. Complementary molecular dynamics modeling studies were consistent with an impact of p93 on the conformation of the CDR3α loop.

High expression of octamer-binding transcription factor 4A, prominin-1 and aldehyde dehydrogenase strongly indicates involvement in the initiation of lung adenocarcinoma resulting in shorter disease-free intervals

The increasing relevance of the cancer stem cell (CSC) hypothesis and the impact of CSC-associated markers in the carcinogenesis of solid tumours may provide potential prognostic implications in lung cancer. We propose that a collective genetic analysis of established CSC-related markers will generate data to better define the role of putative CSCs in lung adenocarcinoma (LAC).

Graph-Based Multi-Surface Segmentation of OCT Data Using Trained Hard and Soft Constraints

Optical coherence tomography (OCT) is a well-established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graph-based multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ±0.54 μm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.