Implementation of routine first trimester combined screening for pre-eclampsia: a clinical effectiveness study.

OBJECTIVE: Evaluate clinical effectiveness of the first trimester combined (FMF) pre-eclampsia screening programme when implemented in a public healthcare setting. DESIGN: Retrospective cohort study. SETTING: London tertiary hospital from January 2017 to March 2019. METHODS: 7720 women screened for pre-eclampsia according to National Institute for Health and Care Excellence (NICE) risk-based guidance and 4841 by the Fetal Medical Foundation (FMF) algorithm which combined maternal risk factors, blood pressure, PAPP-A and uterine artery Doppler indices in the first trimester. High risk was defined by standard NICE criteria in the pre-intervention cohort (prescribed 75 mg aspirin) or a risk of ≥1:50 for preterm pre-eclampsia from the FMF algorithm in the post-intervention cohort (prescribed 150 mg aspirin). MAIN OUTCOME MEASURES: Screening effectiveness, rates of pre-eclampsia. RESULTS: The FMF screening programme resulted in a significant reduction in the screen-positive rate (16.1 versus 8.2%, odds ratio [OR] 0.50, 95% confidence interval [CI] 0.41-0.53) with a concurrent increase in targeted aspirin use in women classified as high risk for pre-eclampsia (28.9 versus 99.0%, OR 241.6, 95% CI 89.6-652.0). Screening indices were uniformly improved for the FMF algorithm with receiver operating characteristic (ROC) analysis demonstrating excellent discrimination for preterm pre-eclampsia (area under the curve [AUC] = 0.846, 95% CI 0.778-0.915, P value <.001). Interrupted time series analysis showed that the FMF screening programme resulted in a significant 21-month relative effect reduction of 80% (P = .025) and 89% (P = .017), for preterm and early pre-eclampsia, respectively. CONCLUSIONS: First trimester combined screening for pre-eclampsia is both feasible and effective in a public healthcare setting. Such an approach results in a two-fold de-escalation of risk, doubling of pre-eclampsia detection, near total physician compliance of aspirin use and a significant reduction in the prevalence of preterm pre-eclampsia. TWEETABLE ABSTRACT: Implementation of 1st trimester combined pre-eclampsia screening effectively reduces prevalence of the disorder

A CD36 ectodomain mediates insect pheromone detection via a putative tunnelling mechanism.

CD36 transmembrane proteins have diverse roles in lipid uptake, cell adhesion and pathogen sensing. Despite numerous in vitro studies, how they act in native cellular contexts is poorly understood. A Drosophila CD36 homologue, sensory neuron membrane protein 1 (SNMP1), was previously shown to facilitate detection of lipid-derived pheromones by their cognate receptors in olfactory cilia. Here we investigate how SNMP1 functions in vivo. Structure-activity dissection demonstrates that SNMP1's ectodomain is essential, but intracellular and transmembrane domains dispensable, for cilia localization and pheromone-evoked responses. SNMP1 can be substituted by mammalian CD36, whose ectodomain can interact with insect pheromones. Homology modelling, using the mammalian LIMP-2 structure as template, reveals a putative tunnel in the SNMP1 ectodomain that is sufficiently large to accommodate pheromone molecules. Amino-acid substitutions predicted to block this tunnel diminish pheromone sensitivity. We propose a model in which SNMP1 funnels hydrophobic pheromones from the extracellular fluid to integral membrane receptors

Genome-wide DNA methylation pattern in visceral adipose tissue differentiates insulin-resistant from insulin-sensitive obese subject

Elucidating the potential mechanisms involved in the detrimental effect of excess body weight on insulin action is an important priority in counteracting obesity-associated diseases. The present study aimed to disentangle the epigenetic basis of insulin resistance by performing a genome-wide epigenetic analysis in visceral adipose tissue (VAT) from morbidly obese patients depending on the insulin sensitivity evaluated by the clamp technique. The global human methylome screening performed in VAT from 7 insulin-resistant (IR) and 5 insulin-sensitive (IS) morbidly obese patients (discovery cohort) analyzed using the Infinium HumanMethylation450 BeadChip array identified 982 CpG sites able to perfectly separate the IR and IS samples. The identified sites represented 538 unique genes, 10% of which were diabetes-associated genes. The current work identified novel IR-related genes epigenetically regulated in VAT, such as COL9A1, COL11A2, CD44, MUC4, ADAM2, IGF2BP1, GATA4, TET1, ZNF714, ADCY9, TBX5, and HDACM. The gene with the largest methylation fold-change and mapped by 5 differentially methylated CpG sites located in island/shore and promoter region was ZNF714. This gene presented lower methylation levels in IR than in IS patients in association with increased transcription levels, as further reflected in a validation cohort (n = 24; 11 IR and 13 IS). This study reveals, for the first time, a potential epigenetic regulation involved in the dysregulation of VAT that could predispose patients to insulin resistance and future type 2 diabetes in morbid obesity, providing a potential therapeutic target and biomarkers for counteracting this process

Charged lepton Flavor Violation in Supersymmetry with Bilinear R-Parity Violation

The simplest unified extension of the Minimal Supersymmetric Standard Model with bi-linear R-parity violation naturally predicts a hierarchical neutrino mass spectrum, suitable to explain atmospheric and solar neutrino fluxes. We study whether the individual violation of the lepton numbers L_{e,mu,tau} in the charged sector can lead to measurable rates for BR(mu->e gamma)and $BR(tau-> mu gamma). We find that some of the R-parity violating terms that are compatible with the observed atmospheric neutrino oscillations could lead to rates for mu->e gamma measurable in projected experiments. However, the Delta m^2_{12} obtained for those parameters is too high to be compatible with the solar neutrino data, excluding therefore the possibility of having measurable rates for mu->e gamma in the model.Comment: 29 pages, 8 figures. Constraint from solar neutrino data included, conclusions changed respect v

Non-invasive ventilation in obesity hypoventilation syndrome without severe obstructive sleep apnoea

Background Non-invasive ventilation (NIV) is an effective form of treatment in patients with obesity hypoventilation syndrome (OHS) who have concomitant severe obstructive sleep apnoea (OSA). However, there is a paucity of evidence on the efficacy of NIV in patients with OHS without severe OSA. We performed a multicentre randomised clinical trial to determine the comparative efficacy of NIV versus lifestyle modification (control group) using daytime arterial carbon dioxide tension (PaCO2) as the main outcome measure. Methods Between May 2009 and December 2014 we sequentially screened patients with OHS without severe OSA. Participants were randomised to NIV versus lifestyle modification and were followed for 2 months. Arterial blood gas parameters, clinical symptoms, health-related quality of life assessments, polysomnography, spirometry, 6-min walk distance test, blood pressure measurements and healthcare resource utilisation were evaluated. Statistical analysis was performed using intention-to-treat analysis. Results A total of 365 patients were screened of whom 58 were excluded. Severe OSA was present in 221 and the remaining 86 patients without severe OSA were randomised. NIV led to a significantly larger improvement in PaCO2 of -6 (95% CI -7.7 to -4.2) mm Hg versus -2.8 (95% CI -4.3 to -1.3) mm Hg, (p<0.001) and serum bicarbonate of -3.4 (95% CI -4.5 to -2.3) versus -1 (95% CI -1.7 to -0.2 95% CI) mmol/L (p<0.001). PaCO2 change adjusted for NIV compliance did not further improve the inter-group statistical significance. Sleepiness, some health-related quality of life assessments and polysomnographic parameters improved significantly more with NIV than with lifestyle modification. Additionally, there was a tendency towards lower healthcare resource utilisation in the NIV group. Conclusions NIV is more effective than lifestyle modification in improving daytime PaCO2, sleepiness and polysomnographic parameters. Long-term prospective studies are necessary to determine whether NIV reduces healthcare resource utilisation, cardiovascular events and mortality

The synovial and blood monocyte DNA methylomes mirror prognosis, evolution and treatment in early arthritis

Identifying predictive biomarkers at early stages of early inflammatory arthritis is crucial for starting appropriate therapies to avoid poor outcomes. Monocytes and macrophages, largely associated with arthritis, are contributors and sensors of inflammation through epigenetic modifications. In this study, we investigated associations between clinical features and DNA methylation in blood and synovial fluid (SF) monocytes in a prospective cohort of early inflammatory arthritis patients. Undifferentiated arthritis (UA) blood monocyte DNA methylation profiles exhibited significant alterations in comparison with those from healthy donors. We identified additional differences both in blood and SF monocytes after comparing UA patients grouped by their future outcomes, good versus poor. Patient profiles in subsequent visits revealed a reversion towards a healthy level in both groups, those requiring disease-modifying antirheumatic drugs (DMARDs) and those that remitted spontaneously. Changes in disease activity between visits also impacted DNA methylation, partially concomitant in the SF of UA and in blood monocytes of rheumatoid arthritis patients. Epigenetic similarities between arthritis types allow a common prediction of disease activity. Our results constitute a resource of DNA methylation-based biomarkers of poor prognosis, disease activity and treatment efficacy in early untreated UA patients for the personalized clinical management of early inflammatory arthritis patients

Can we identify non-stationary dynamics of trial-to-trial variability?"

Identifying sources of the apparent variability in non-stationary scenarios is a fundamental problem in many biological data analysis settings. For instance, neurophysiological responses to the same task often vary from each repetition of the same experiment (trial) to the next. The origin and functional role of this observed variability is one of the fundamental questions in neuroscience. The nature of such trial-to-trial dynamics however remains largely elusive to current data analysis approaches. A range of strategies have been proposed in modalities such as electro-encephalography but gaining a fundamental insight into latent sources of trial-to-trial variability in neural recordings is still a major challenge. In this paper, we present a proof-of-concept study to the analysis of trial-to-trial variability dynamics founded on non-autonomous dynamical systems. At this initial stage, we evaluate the capacity of a simple statistic based on the behaviour of trajectories in classification settings, the trajectory coherence, in order to identify trial-to-trial dynamics. First, we derive the conditions leading to observable changes in datasets generated by a compact dynamical system (the Duffing equation). This canonical system plays the role of a ubiquitous model of non-stationary supervised classification problems. Second, we estimate the coherence of class-trajectories in empirically reconstructed space of system states. We show how this analysis can discern variations attributable to non-autonomous deterministic processes from stochastic fluctuations. The analyses are benchmarked using simulated and two different real datasets which have been shown to exhibit attractor dynamics. As an illustrative example, we focused on the analysis of the rat's frontal cortex ensemble dynamics during a decision-making task. Results suggest that, in line with recent hypotheses, rather than internal noise, it is the deterministic trend which most likely underlies the observed trial-to-trial variability. Thus, the empirical tool developed within this study potentially allows us to infer the source of variability in in-vivo neural recordings