Prediction-Coherent LSTM-based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People

In the context of time-series forecasting, we propose a LSTM-based recurrent neural network architecture and loss function that enhance the stability of the predictions. In particular, the loss function penalizes the model, not only on the prediction error (mean-squared error), but also on the predicted variation error. We apply this idea to the prediction of future glucose values in diabetes, which is a delicate task as unstable predictions can leave the patient in doubt and make him/her take the wrong action, threatening his/her life. The study is conducted on type 1 and type 2 diabetic people, with a focus on predictions made 30-minutes ahead of time. First, we confirm the superiority, in the context of glucose prediction, of the LSTM model by comparing it to other state-of-the-art models (Extreme Learning Machine, Gaussian Process regressor, Support Vector Regressor). Then, we show the importance of making stable predictions by smoothing the predictions made by the models, resulting in an overall improvement of the clinical acceptability of the models at the cost in a slight loss in prediction accuracy. Finally, we show that the proposed approach, outperforms all baseline results. More precisely, it trades a loss of 4.3\% in the prediction accuracy for an improvement of the clinical acceptability of 27.1\%. When compared to the moving average post-processing method, we show that the trade-off is more efficient with our approach

Baby Business: a randomised controlled trial of a universal parenting program that aims to prevent early infant sleep and cry problems and associated parental depression

<p>Abstract</p> <p>Background</p> <p>Infant crying and sleep problems (e.g. frequent night waking, difficulties settling to sleep) each affect up to 30% of infants and often co-exist. They are costly to manage and associated with adverse outcomes including postnatal depression symptoms, early weaning from breast milk, and later child behaviour problems. Preventing such problems could improve these adverse outcomes and reduce costs to families and the health care system. Anticipatory guidance-i.e. providing parents with information about normal infant sleep and cry patterns, ways to encourage self-settling in infants, and ways to develop feeding and settling routines <it>before </it>the onset of problems-could prevent such problems. This paper outlines the protocol for our study which aims to test an anticipatory guidance approach.</p> <p>Methods/Design</p> <p>750 families from four Local Government Areas in Melbourne, Australia have been randomised to receive the <it>Baby Business </it>program (intervention group) or usual care (control group) offered by health services. The <it>Baby Business </it>program provides parents with information about infant sleep and crying via a DVD and booklet (mailed soon after birth), telephone consultation (at infant age 6-8 weeks) and parent group session (at infant age 12 weeks). All English speaking parents of healthy newborn infants born at > 32 weeks gestation and referred by their maternal and child health nurse at their first post partum home visit (day 7-10 postpartum), are eligible. The primary outcome is parent report of infant night time sleep as a problem at four months of age and secondary outcomes include parent report of infant daytime sleep or crying as a problem, mean duration of infant sleep and crying/24 hours, parental depression symptoms, parent sleep quality and quantity and health service use. Data will be collected at two weeks (baseline), four months and six months of age. An economic evaluation using a cost-consequences approach will, from a societal perspective, compare costs and health outcomes between the intervention and control groups.</p> <p>Discussion</p> <p>To our knowledge this is the first randomised controlled trial of a program which aims to prevent both infant sleeping and crying problems and associated postnatal depression symptoms. If effective, it could offer an important public health prevention approach to these common, distressing problems.</p> <p>Trial registration number</p> <p>ISRCTN: <a href="http://www.controlled-trials.com/ISRCTN63834603">ISRCTN63834603</a></p

The National Lung Matrix Trial: translating the biology of stratification in advanced non-small-cell lung cancer

© The Author 2015.Background: The management of NSCLC has been transformed by stratified medicine. The National Lung Matrix Trial (NLMT) is a UK-wide study exploring the activity of rationally selected biomarker/targeted therapy combinations. Patients and methods: The Cancer Research UK (CRUK) Stratified Medicine Programme 2 is undertaking the large volume national molecular pre-screening which integrates with the NLMT. At study initiation, there are eight drugs being used to target 18 molecular cohorts. The aim is to determine whether there is sufficient signal of activity in any drug-biomarker combination to warrant further investigation. A Bayesian adaptive design that gives a more realistic approach to decision making and flexibility to make conclusions without fixing the sample size was chosen. The screening platform is an adaptable 28-gene Nextera next-generation sequencing platform designed by Illumina, covering the range of molecular abnormalities being targeted. The adaptive design allows new biomarker-drug combination cohorts to be incorporated by substantial amendment. The pre-clinical justification for each biomarker-drug combination has been rigorously assessed creating molecular exclusion rules and a trumping strategy in patients harbouring concomitant actionable genetic abnormalities. Discrete routes of pathway activation or inactivation determined by cancer genome aberrations are treated as separate cohorts. Key translational analyses include the deep genomic analysis of pre- and post-treatment biopsies, the establishment of patient-derived xenograft models and longitudinal ctDNA collection, in order to define predictive biomarkers, mechanisms of resistance and early markers of response and relapse. Conclusion: The SMP2 platform will provide large scale genetic screening to inform entry into the NLMT, a trial explicitly aimed at discovering novel actionable cohorts in NSCLC

Mosquitoes Put the Brake on Arbovirus Evolution: Experimental Evolution Reveals Slower Mutation Accumulation in Mosquito Than Vertebrate Cells

Like other arthropod-borne viruses (arboviruses), mosquito-borne dengue virus (DENV) is maintained in an alternating cycle of replication in arthropod and vertebrate hosts. The trade-off hypothesis suggests that this alternation constrains DENV evolution because a fitness increase in one host usually diminishes fitness in the other. Moreover, the hypothesis predicts that releasing DENV from host alternation should facilitate adaptation. To test this prediction, DENV was serially passaged in either a single human cell line (Huh-7), a single mosquito cell line (C6/36), or in alternating passages between Huh-7 and C6/36 cells. After 10 passages, consensus mutations were identified and fitness was assayed by evaluating replication kinetics in both cell types as well as in a novel cell type (Vero) that was not utilized in any of the passage series. Viruses allowed to specialize in single host cell types exhibited fitness gains in the cell type in which they were passaged, but fitness losses in the bypassed cell type, and most alternating passages, exhibited fitness gains in both cell types. Interestingly, fitness gains were observed in the alternately passaged, cloned viruses, an observation that may be attributed to the acquisition of both host cell–specific and amphi-cell-specific adaptations or to recovery from the fitness losses due to the genetic bottleneck of biological cloning. Amino acid changes common to both passage series suggested convergent evolution to replication in cell culture via positive selection. However, intriguingly, mutations accumulated more rapidly in viruses passed in Huh-7 cells than in those passed in C6/36 cells or in alternation. These results support the hypothesis that releasing DENV from host alternation facilitates adaptation, but there is limited support for the hypothesis that such alternation necessitates a fitness trade-off. Moreover, these findings suggest that patterns of genetic evolution may differ between viruses replicating in mammalian and mosquito cells

The Human Sweet Tooth

Humans love the taste of sugar and the word "sweet" is used to describe not only this basic taste quality but also something that is desirable or pleasurable, e.g., la dolce vita. Although sugar or sweetened foods are generally among the most preferred choices, not everyone likes sugar, especially at high concentrations. The focus of my group's research is to understand why some people have a sweet tooth and others do not. We have used genetic and molecular techniques in humans, rats, mice, cats and primates to understand the origins of sweet taste perception. Our studies demonstrate that there are two sweet receptor genes (TAS1R2 and TAS1R3), and alleles of one of the two genes predict the avidity with which some mammals drink sweet solutions. We also find a relationship between sweet and bitter perception. Children who are genetically more sensitive to bitter compounds report that very sweet solutions are more pleasant and they prefer sweet carbonated beverages more than milk, relative to less bitter-sensitive peers. Overall, people differ in their ability to perceive the basic tastes, and particular constellations of genes and experience may drive some people, but not others, toward a caries-inducing sweet diet. Future studies will be designed to understand how a genetic preference for sweet food and drink might contribute to the development of dental caries

Quantifying the impact of deprivation on preterm births:a retrospective cohort study

Background: Social deprivation is associated with higher rates of preterm birth and subsequent infant mortality. Our objective was to identify risk factors for preterm birth in the UK's largest maternity unit, with a particular focus on social deprivation, and related factors. Methodology/Principal Findings: Retrospective cohort study of 39,873 women in Liverpool, UK, from 2002-2008. Singleton pregnancies were stratified into uncomplicated low risk pregnancies and a high risk group complicated by medical problems. Multiple logistic regression, and generalized additive models were used to explore the effect of covariates including area deprivation, smoking status, BMI, parity and ethnicity on the risk of preterm birth (34(+0) weeks). In the low risk group, preterm birth rates increased with deprivation, reaching 1.6% (CI95 1.4 to 1.8) in the most deprived quintile; the unadjusted odds ratio comparing an individual in the most deprived quintile, to one in the least deprived quintile was 1.5 (CI95 1.2 to 1.9). Being underweight and smoking were both independently associated with preterm birth in the low risk group, and adjusting for these factors explained the association between deprivation and preterm birth. Preterm birth was five times more likely in the high risk group (RR 4.8 CI95 4.3 to 5.4), and there was no significant relationship with deprivation. Conclusions: Deprivation has significant impact on preterm birth rates in low risk women. The relationship between low socio-economic status and preterm births appears to be related to low maternal weight and smoking in more deprived groups