Singlet Portal to the Hidden Sector

Ultraviolet physics typically induces a kinetic mixing between gauge singlets which is marginal and hence non-decoupling in the infrared. In singlet extensions of the minimal supersymmetric standard model, e.g. the next-to-minimal supersymmetric standard model, this furnishes a well motivated and distinctive portal connecting the visible sector to any hidden sector which contains a singlet chiral superfield. In the presence of singlet kinetic mixing, the hidden sector automatically acquires a light mass scale in the range 0.1 - 100 GeV induced by electroweak symmetry breaking. In theories with R-parity conservation, superparticles produced at the LHC invariably cascade decay into hidden sector particles. Since the hidden sector singlet couples to the visible sector via the Higgs sector, these cascades necessarily produce a Higgs boson in an order 0.01 - 1 fraction of events. Furthermore, supersymmetric cascades typically produce highly boosted, low-mass hidden sector singlets decaying visibly, albeit with displacement, into the heaviest standard model particles which are kinematically accessible. We study experimental constraints on this broad class of theories, as well as the role of singlet kinetic mixing in direct detection of hidden sector dark matter. We also present related theories in which a hidden sector singlet interacts with the visible sector through kinetic mixing with right-handed neutrinos.Comment: 12 pages, 5 figure

A Definitive Signal of Multiple Supersymmetry Breaking

If the lightest observable-sector supersymmetric particle (LOSP) is charged and long-lived, then it may be possible to indirectly measure the Planck mass at the LHC and provide a spectacular confirmation of supergravity as a symmetry of nature. Unfortunately, this proposal is only feasible if the gravitino is heavy enough to be measured at colliders, and this condition is in direct conflict with constraints from big bang nucleosynthesis (BBN). In this work, we show that the BBN bound can be naturally evaded in the presence of multiple sectors which independently break supersymmetry, since there is a new decay channel of the LOSP to a goldstino. Certain regions of parameter space allow for a direct measurement of LOSP decays into both the goldstino and the gravitino at the LHC. If the goldstino/gravitino mass ratio is measured to be 2, as suggested by theory, then this would provide dramatic verification of the existence of multiple supersymmetry breaking and sequestering. A variety of consistent cosmological scenarios are obtained within this framework. In particular, if an R symmetry is imposed, then the gauge-gaugino-goldstino interaction vertices can be forbidden. In this case, there is no bound on the reheating temperature from goldstino overproduction, and thermal leptogenesis can be accommodated consistently with gravitino dark matter.Comment: 10 pages, 5 figures, title changed to match the version published in JHE

The Impact of HAART on the Respiratory Complications of HIV Infection: Longitudinal Trends in the MACS and WIHS Cohorts

Objective: To review the incidence of respiratory conditions and their effect on mortality in HIV-infected and uninfected individuals prior to and during the era of highly active antiretroviral therapy (HAART). Design: Two large observational cohorts of HIV-infected and HIV-uninfected men (Multicenter AIDS Cohort Study [MACS]) and women (Women's Interagency HIV Study [WIHS]), followed since 1984 and 1994, respectively. Methods: Adjusted odds or hazards ratios for incident respiratory infections or non-infectious respiratory diagnoses, respectively, in HIV-infected compared to HIV-uninfected individuals in both the pre-HAART (MACS only) and HAART eras; and adjusted Cox proportional hazard ratios for mortality in HIV-infected persons with lung disease during the HAART era. Results: Compared to HIV-uninfected participants, HIV-infected individuals had more incident respiratory infections both pre-HAART (MACS, odds ratio [adjusted-OR], 2.4; 95% confidence interval [CI], 2.2-2.7; p<0.001) and after HAART availability (MACS, adjusted-OR, 1.5; 95%CI 1.3-1.7; p<0.001; WIHS adjusted-OR, 2.2; 95%CI 1.8-2.7; p<0.001). Chronic obstructive pulmonary disease was more common in MACS HIV-infected vs. HIV-uninfected participants pre-HAART (hazard ratio [adjusted-HR] 2.9; 95%CI, 1.02-8.4; p = 0.046). After HAART availability, non-infectious lung diseases were not significantly more common in HIV-infected participants in either MACS or WIHS participants. HIV-infected participants in the HAART era with respiratory infections had an increased risk of death compared to those without infections (MACS adjusted-HR, 1.5; 95%CI, 1.3-1.7; p<0.001; WIHS adjusted-HR, 1.9; 95%CI, 1.5-2.4; p<0.001). Conclusion: HIV infection remained a significant risk for infectious respiratory diseases after the introduction of HAART, and infectious respiratory diseases were associated with an increased risk of mortality. © 2013 Gingo et al

Bayesian fusion of physiological measurements using a signal quality extension

Objective: The fusion of multiple noisy labels for biomedical data (such as ECG annotations, which may be obtained from human experts or from automated systems) into a single robust annotation has many applications in physiologic monitoring. Directly modelling the difficulty of the task has the potential to improve the fusion of such labels. This paper proposes a means for the incorporation of task difficulty, as quantified by ‘signal quality’, into the fusion process. Approach: We propose a Bayesian fusion model to infer a consensus through aggregating labels, where the labels are provided by multiple imperfect automated algorithms (or ‘annotators’). Our model incorporates the signal quality of the underlying recording when fusing labels. We compare our proposed model with previously published approaches. Two publicly available datasets were used to demonstrate the feasibility of our proposed model: one focused on QT interval estimation in the ECG and the other focused on respiratory rate (RR) estimation from the photoplethysmogram (PPG). We inferred the hyperparameters of our model using maximum- a posteriori inference and Gibbs sampling. Main results: For the QT dataset, our model significantly outperformed the previously published models (root-mean-square error of 25.61 ± 8.68 ms for our model versus 30.79 ± 13.16 ms from the best existing model) when fusing labels from only three annotators. For the RR dataset, no improvement was observed compared to the same model without signal quality modelling, where our model outperformed existing models (mean-absolute error of 1.89 ± 0.36 bpm for our model versus 2.22 ± 0.41 bpm from the best existing model). We conclude that our approach demonstrates the feasibility of using a signal quality metric as a confidence measure to improve label fusion. Significance: Our Bayesian learning model provides an extension over existing work to incorporate signal quality as a confidence measure to improve the reliability of fusing labels from biomedical datasets

Doppler-based fetal heart rate analysis markers for the detection of early intrauterine growth restriction

IntroductionOne indicator for fetal risk of mortality is intrauterine growth restriction (IUGR). Whether markers reflecting the impact of growth restriction on the cardiovascular system, computed from a Doppler-derived heart rate signal, would be suitable for its detection antenatally was studied. Material and methodsWe used a cardiotocography archive of 1163 IUGR cases and 1163 healthy controls, matched for gestation and gender. We assessed the discriminative power of short-term variability and long-term variability of the fetal heart rate, computed over episodes of high and low variation aiming to separate growth-restricted fetuses from controls. Metrics characterizing the sleep state distribution within a trace were also considered for inclusion into an IUGR detection model. ResultsSignificant differences in the risk markers comparing growth-restricted with healthy fetuses were found. When used in a logistic regression classifier, their performance for identifying IUGR was considerably superior before 34 weeks of gestation. Long-term variability in active sleep was superior to short-term variability [area under the receiver operator curve (AUC) of 72% compared with 71%]. Most predictive was the number of minutes in high variation per hour (AUC of 75%). A multivariate IUGR prediction model improved the AUC to 76%. ConclusionWe suggest that heart rate variability markers together with surrogate information on sleep states can contribute to the detection of early-onset IUGR

A multifaceted strategy using mobile technology to assist rural primary healthcare doctors and frontline health workers in cardiovascular disease risk management: protocol for the SMARTHealth India cluster randomised controlled trial

BACKGROUND: Blood Pressure related disease affected 118 million people in India in the year 2000; this figure will double by 2025. Around one in four adults in rural India have hypertension, and of those, only a minority are accessing appropriate care. Health systems in India face substantial challenges to meet these gaps in care, and innovative solutions are needed. METHODS: We hypothesise that a multifaceted intervention involving capacity strengthening of primary healthcare doctors and non-physician healthcare workers through use of a mobile device-based clinical decision support system will result in improved blood pressure control for individuals at high risk of a cardiovascular disease event when compared with usual healthcare. This intervention will be implemented as a stepped wedge, cluster randomised controlled trial in 18 primary health centres and 54 villages in rural Andhra Pradesh involving adults aged ≥40 years at high cardiovascular disease event risk (approximately 15,000 people). Cardiovascular disease event risk will be calculated based on World Health Organisation/International Society of Hypertension's region-specific risk charts. Cluster randomisation will occur at the level of the primary health centres. Outcome analyses will be conducted blinded to intervention allocation. EXPECTED OUTCOMES: The primary study outcome is the difference in the proportion of people meeting guideline-recommended blood pressure targets in the intervention period vs. the control period. Secondary outcomes include mean reduction in blood pressure levels; change in other cardiovascular disease risk factors, including body mass index, current smoking, reported healthy eating habits, and reported physical activity levels; self-reported use of blood pressure and other cardiovascular medicines; quality of life (using the EQ-5D); and cardiovascular disease events (using hospitalisation data). Trial outcomes will be accompanied by detailed process and economic evaluations. SIGNIFICANCE: The findings are likely to inform policy on a scalable strategy to overcome entrenched inequities in access to effective healthcare for under-served populations in low and middle income country settings. TRIAL REGISTRATION: Clinical Trial Registry India CTRI/2013/06/003753

Evaluation of the fetal QT interval using non-invasive fetal ECG technology

Non-invasive fetal electrocardiography (NI-FECG) is a promising alternative continuous fetal monitoring method that has the potential to allow morphological analysis of the FECG. However, there are a number of challenges associated with the evaluation of morphological parameters from the NI-FECG, including low signal to noise ratio of the NI-FECG and methodological challenges for getting reference annotations and evaluating the accuracy of segmentation algorithms. This work aims to validate the measurement of the fetal QT interval in term laboring women using a NI-FECG electrocardiogram monitor. Fetal electrocardiogram data were recorded from 22 laboring women at term using the NI-FECG and an invasive fetal scalp electrode simultaneously. A total of 105 one-minute epochs were selected for analysis. Three pediatric electrophysiologists independently annotated individual waveforms and averaged waveforms from each epoch. The intervals measured on the averaged cycles taken from the NI-FECG and the fetal scalp electrode showed a close agreement; the root mean square error between all corresponding averaged NI-FECG and fetal scalp electrode beats was 13.6 ms, which is lower than the lowest adult root mean square error of 16.1 ms observed in related adult QT studies. These results provide evidence that NI-FECG technology enables accurate extraction of the fetal QT interval

Preferential risk of HPV16 for squamous cell carcinoma and of HPV18 for adenocarcinoma of the cervix compared to women with normal cytology in The Netherlands

We present the type-distribution of high-risk human papillomavirus (HPV) types in women with normal cytology (n=1467), adenocarcinoma in situ (ACIS) (n=61), adenocarcinoma (n=70), and squamous cell carcinoma (SCC) (n=83). Cervical adenocarcinoma and ACIS were significantly more frequently associated with HPV18 (ORMH 15.0; 95% CI 8.6–26.1 and 21.8; 95% CI 11.9–39.8, respectively) than normal cytology. Human papillomavirus16 was only associated with adenocarcinoma and ACIS after exclusion of HPV18-positive cases (ORMH 6.6; 95% CI 2.8–16.0 and 9.4; 95% CI 2.8–31.2, respectively). For SCC, HPV16 prevalence was elevated (ORMH 7.0; 95% CI 3.9–12.4) compared to cases with normal cytology, and HPV18 prevalence was only increased after exclusion of HPV16-positive cases (ORMH 4.3; 95% CI 1.6–11.6). These results suggest that HPV18 is mainly a risk factor for the development of adenocarcinoma whereas HPV16 is associated with both SCC and adenocarcinoma

ADARRI:a novel method to detect spurious R-peaks in the electrocardiogram for heart rate variability analysis in the intensive care unit

We developed a simple and fully automated method for detecting artifacts in the R-R interval (RRI) time series of the ECG that is tailored to the intensive care unit (ICU) setting. From ECG recordings of 50 adult ICU-subjects we selected 60 epochs with valid R-peak detections and 60 epochs containing artifacts leading to missed or false positive R-peak detections. Next, we calculated the absolute value of the difference between two adjacent RRIs (adRRI), and obtained the empirical probability distributions of adRRI values for valid R-peaks and artifacts. From these, we calculated an optimal threshold for separating adRRI values arising from artifact versus non-artefactual data. We compared the performance of our method with the methods of Berntson and Clifford on the same data. We identified 257,458 R-peak detections, of which 235,644 (91.5%) were true detections and 21,814 (8.5%) arose from artifacts. Our method showed superior performance for detecting artifacts with sensitivity 100%, specificity 99%, precision 99%, positive likelihood ratio of 100 and negative likelihood ratio <0.001 compared to Berntson’s and Clifford’s method with a sensitivity, specificity, precision and positive and negative likelihood ratio of 99%, 78%, 82%, 4.5, 0.013 for Berntson’s method and 55%, 98%, 96%, 27.5, 0.460 for Clifford’s method, respectively. A novel algorithm using a patient-independent threshold derived from the distribution of adRRI values in ICU ECG data identifies artifacts accurately, and outperforms two other methods in common use. Furthermore, the threshold was calculated based on real data from critically ill patients and the algorithm is easy to implement

Can Research Assessments Themselves Cause Bias in Behaviour Change Trials? A Systematic Review of Evidence from Solomon 4-Group Studies

BACKGROUND: The possible effects of research assessments on participant behaviour have attracted research interest, especially in studies with behavioural interventions and/or outcomes. Assessments may introduce bias in randomised controlled trials by altering receptivity to intervention in experimental groups and differentially impacting on the behaviour of control groups. In a Solomon 4-group design, participants are randomly allocated to one of four arms: (1) assessed experimental group; (2) unassessed experimental group (3) assessed control group; or (4) unassessed control group. This design provides a test of the internal validity of effect sizes obtained in conventional two-group trials by controlling for the effects of baseline assessment, and assessing interactions between the intervention and baseline assessment. The aim of this systematic review is to evaluate evidence from Solomon 4-group studies with behavioural outcomes that baseline research assessments themselves can introduce bias into trials. METHODOLOGY/PRINCIPAL FINDINGS: Electronic databases were searched, supplemented by citation searching. Studies were eligible if they reported appropriately analysed results in peer-reviewed journals and used Solomon 4-group designs in non-laboratory settings with behavioural outcome measures and sample sizes of 20 per group or greater. Ten studies from a range of applied areas were included. There was inconsistent evidence of main effects of assessment, sparse evidence of interactions with behavioural interventions, and a lack of convincing data in relation to the research question for this review. CONCLUSIONS/SIGNIFICANCE: There were too few high quality completed studies to infer conclusively that biases stemming from baseline research assessments do or do not exist. There is, therefore a need for new rigorous Solomon 4-group studies that are purposively designed to evaluate the potential for research assessments to cause bias in behaviour change trials