An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Root system of singular perturbations of the harmonic oscillator type operators

We analyze perturbations of the harmonic oscillator type operators in a Hilbert space H, i.e. of the self-adjoint operator with simple positive eigenvalues μ k satisfying μ k+1 − μ k ≥ Δ > 0. Perturbations are considered in the sense of quadratic forms. Under a local subordination assumption, the eigenvalues of the perturbed operator become eventually simple and the root system contains a Riesz basis.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Identification of maltreatment type in children with disabilities using the National Child Abuse and Neglect Data System (NCANDS)

This study was a retrospective design and used secondary data from the National Child Abuse and Neglect Data System (NCANDS), provided by the National Data Archive on Child Abuse and Neglect Family Life Development Center administered by Cornell University. The dataset contained information for the year 2005 on children from birth to 18 years of age. Child abuse and neglect for disabled children, was evaluated in-depth in the present study. Descriptive and statistical analysis was performed using the children with and without disabilities. It was found that children with disabilities have a lower rate of substantiation that likely indicates the interference of reporting due to their handicap. The results of this research demonstrate the important need to teach professionals and laypersons alike on how to recognize and substantiate abuse among disabled children.^

Changes in 911 call volume and type during Hurricane Ike and the implementation and usefulness of the TeleHealth Nurse system for the Houston Fire Department

This study examined both changing call volume and type with resulting effect of TeleHealth Nurse, the Houston Fire Department's (HFD) telephone nurse line, on call burden during Hurricane Ike. On September 13, 2008, Hurricane Ike made landfall in the Galveston area and continued north through Houston resulting in catastrophic damages in infrastructure and posing a public health threat. The overall goal of this study looked at data from Houston Fire Department to obtain a better understanding of the needs of citizens before, during, and after a hurricane. This study looked at four aspects of emergency response from HFD. The first section looked at call volumes surrounding the time of Hurricane Ike in 2008 compared to the same time period in 2007. The data showed a 12% increase in calls surrounding Hurricane Ike compared to previous years with a p value <.001. Next, the study evaluated the types of calls prevalent during Hurricane Ike compared to the same time period in 2007. The data showed a statistically significant increase in chronic health problems such as diabetes and cardiac events, Obstetric calls and an increase in breathing problems, falls, and lacerations during the days following Hurricane Ike. There was also a statistically significant increase in auto med alerts and check patients surrounding Hurricane Ike's landfall. The third section analyzed the change in call volume sent to HFD's Telephone Nurse Line during Hurricane Ike and compares this to earlier time periods while the fourth and final section looks at the types of calls sent to the nurse line during Hurricane Ike. The data showed limited use of the TeleHealth Nurse line before Hurricane Ike, but when the winds were at their strongest and ambulances were unable to leave the station, the nurse line was the only functioning medical help some people were able to receive. These studies bring a better understanding to the number and types of calls that a city might experience during a natural disaster, such as a hurricane. This study also shows the usefulness of an EMS Telephone Nurse Line during a natural disaster.^

Ascorbic acid effects on the immune system and type -1 /type -2 cytokine balance in humans

Vitamin C (ascorbic acid--AA) can have a substantial impact on human health by reducing the incidence and/or severity of coryza. Studies also suggest it has immunomodulatory functions in humans. Immune function is controlled by cytokines, such as type-1 cytokines (IFNγ) that promote antiviral immunity and type-2 cytokines (IL-4, IL-10) that promote humoral immunity. Knowing the mechanisms responsible for both antiviral immunity and type-1/type-2 cytokine balance, we sought to identify AA-induced alterations of human peripheral blood mononuclear cells (PBMC) in vivo and in vitro . We hypothesized that AA modulates the immune system, altering both number and function of PBMC. We first described the effect of 14 days of oral (1 gram) AA in healthy subjects. AA increased circulating natural killer (NK) cells, CD25+ and HLA-DR+ T cells, and PMA/ionomycin-stimulated intracellular IFNγ. We subsequently developed models for in vitro use. We determined that AA was toxic in vitro to T cells when used at doses found intracellularly but doses found in plasma from individuals taking 1gm/day AA were nontoxic. The model that most fully reproduced our in vivo intracellular cytokine findings used dehydroascorbic acid and buffers to deliver AA intracellularly. This model generated the largest increase in IFNγ at physiologic plasma concentrations. Previous studies demonstrate that chronic psychological stress is associated with a type-2 cytokine response. We hypothesized that vitamin C could prevent the type-2 cytokine shift associated with stress. In a study of medical students taking 1 g AA or placebo, a significant increase in IFNγ was seen intracellularly in CD4+ and CD8+ cells and in tetanus-stimulated cultures in the AA group only. We also observed increases in IFNγ/IL-4 and IFNγ/IL-10 ratios with AA supplementation, indicating a type-1 shift. Furthermore, we noted increased numbers of NK cells and activated T cells in the peripheral blood in the AA treated group only. Lastly, we investigated the role of the CD40L/CD40 and CD28/B7 costimulatory pathway in these cytokine alterations. AA did not have any effect on either pathway studied. Thus costimulatory pathways are not contributing to AA induced modulation of the type-1/type-2 immune balance. ^

Gini coefficient, dissimilarity index and Lorenz curve for the spanish port system by type of goods

This paper shows the Gini Coefficient, the dissimilarity Index and the Lorenz Curve for the Spanish Port System by type of goods from 1960 to the year 2010 for business units: Total traffic, Liquid bulk cargo, Solid bulk cargo, General Merchandise and Container (TEUs) with the aim of carcaterizar the Spanish port systems in these periods and propose future strategies.

Transient behavior of a system composed of conductive thin wire structures excited by harmonic and lightning type signals

The transient response of a system of independent electrodes buried in a semi-infinite conducting medium is studied. Using a simple and versatile numerical scheme written by the authors and based on the Electric Field Integral Equation (EFIE), the effect caused by harmonic signals ranging on frequency from Hz to hundred of MHz, and also by lightning type driving signal striking at a remote point far from the conductors, is extensively studied. The value of the scalar potential appearing on the electrodes as a function of the frequency of the applied signal is one of the variables investigated. Other features such as the input impedance at the injection point of the signal and the Ground Potential Rise (GPR) over the electrode system are also discussed

Transcriptional coupling between the divergent promoters of a prototypic LysR-type regulatory system, the ilvYC operon of Escherichia coli

The twin-domain model [Liu, L. F. & Wang, J. C. (1987) Proc. Natl. Acad. Sci. USA 84, 7024–7027] suggests that closely spaced, divergent, superhelically sensitive promoters can affect the transcriptional activity of one another by transcriptionally induced negative DNA supercoiling generated in the divergent promoter region. This gene arrangement is observed for many LysR-type-regulated operons in bacteria. We have examined the effects of divergent transcription in the prototypic LysR-type system, the ilvYC operon of Escherichia coli. Double-reporter constructs with the lacZ gene under transcriptional control of the ilvC promoter and the galK gene under control of the divergent ilvY promoter were used to demonstrate that a down-promoter mutation in the ilvY promoter severely decreases in vivo transcription from the ilvC promoter. However, a down-promoter mutation in the ilvC promoter only slightly affects transcription from the ilvY promoter. In vitro transcription assays with DNA topoisomers showed that transcription from the ilvC promoter increases over the entire range of physiological superhelical densities, whereas transcription initiation from the ilvY promoter exhibits a broad optimum at a midphysiological superhelical density. Evidence that this promoter coupling is DNA supercoiling-dependent is provided by the observation that a novobiocin-induced decrease in global negative superhelicity results in an increase in ilvY promoter activity and a decrease in ilvC promoter activity predicted by the in vitro data. We suggest that this transcriptional coupling is important for coordinating basal level expression of the ilvYC operon with the nutritional and environmental conditions of cell growth.