Comparing Traditional Body Mass Index and Joslin Diabetes Center’s Asian Body Mass Index in Predicting Self-Report Type 2 Diabetes.

This study examined the predictability of traditional Body Mass Index standards and the Joslin Diabetes Center’s recommended BMI standards for Asian Americans. A sample of 2973 adult Asian Americans aged 45 and older from the 2009 California Health Interview Survey (CHIS) was used. This sample consists of 12.25% of respondents with type 2 diabetes and 87.75% that had neither type 2 or any types of diabetes. Logistic regression was used to estimate the predictability of two the BMI standards and to test for the interaction effect of BMI standards and sex in predicting type 2 diabetes. The results revealed that both traditional and Joslin Diabetes Center’s recommended standards had similar predictability of types 2 diabetes. Both BMI standards of overweight and obesity had a greater association with type 2 diabetes for men than for women. That is, given a similar level of BMI, men tend to report a greater prevalence of type 2 diabetes than women. These findings support caution in changing BMI cut-offs for Asian Americans, and highlight the potential limitations of using BMI as a measure of risk for diabetes in this population

Stochastic modelling of the correlation between transformer loading and distributed energy resources in LV distribution networks

The rapid growth of distributed energy resources (DERs) poses operational challenges for the low-voltage (LV) distribution networks, such as overloading of the transformer and/or voltage violation. Many smart strategies based on flexibility and coordinated control of DER have been developed to address these issues. To facilitate this implementation, this study presents a stochastic modelling technique, based on the Monte Carlo approach, to analyse the correlation between transformer loading and voltage magnitudes measured at the point of connection (POC) of DER in the network. A case study has been performed using IEEE European LV test feeder and smart meter measurement from the Netherlands to reflect the realistic aspects of operational conditions. Advanced statistical modelling techniques are applied to generate a set of scenarios, consisting of solar irradiation, and electric vehicle charging and load consumption profiles. Simulation results reveal a strong linear relationship between transformer loading and voltage magnitudes at the POC of DERs. Thus, these findings can aid in implementing flexibility and coordinated control DERs for congestion management in the LV distribution network.</p

Stochastic modelling of the correlation between transformer loading and distributed energy resources in LV distribution networks

The rapid growth of distributed energy resources (DERs) poses operational challenges for the low-voltage (LV) distribution networks, such as overloading of the transformer and/or voltage violation. Many smart strategies based on flexibility and coordinated control of DER have been developed to address these issues. To facilitate this implementation, this study presents a stochastic modelling technique, based on the Monte Carlo approach, to analyse the correlation between transformer loading and voltage magnitudes measured at the point of connection (POC) of DER in the network. A case study has been performed using IEEE European LV test feeder and smart meter measurement from the Netherlands to reflect the realistic aspects of operational conditions. Advanced statistical modelling techniques are applied to generate a set of scenarios, consisting of solar irradiation, and electric vehicle charging and load consumption profiles. Simulation results reveal a strong linear relationship between transformer loading and voltage magnitudes at the POC of DERs. Thus, these findings can aid in implementing flexibility and coordinated control DERs for congestion management in the LV distribution network.</p

Pharmacist-Led Intervention to Enhance Medication Adherence in Patients With Acute Coronary Syndrome in Vietnam:A Randomized Controlled Trial

Background: Patient adherence to cardioprotective medications improves outcomes of acute coronary syndrome (ACS), but few adherence-enhancing interventions have been tested in low-income and middle-income countries. Objectives: We aimed to assess whether a pharmacist-led intervention enhances medication adherence in patients with ACS and reduces mortality and hospital readmission. Methods: We conducted a randomized controlled trial in Vietnam. Patients with ACS were recruited, randomized to the intervention or usual care prior to discharge, and followed 3 months after discharge. Intervention patients received educational and behavioral interventions by a pharmacist. Primary outcome was the proportion of adherent patients 1 month after discharge. Adherence was a combined measure of self-reported adherence (the 8-item Morisky Medication Adherence Scale) and obtaining repeat prescriptions on time. Secondary outcomes were (1) the proportion of patients adherent to medication; (2) rates of mortality and hospital readmission; and (3) change in quality of life from baseline assessed with the European Quality of Life Questionnaire - 5 Dimensions - 3 Levels at 3 months after discharge. Logistic regression was used to analyze data. Registration: ClinicalTrials.gov (NCT02787941). Results: Overall, 166 patients (87 control, 79 intervention) were included (mean age 61.2 years, 73% male). In the analysis excluding patients from the intervention group who did not receive the intervention and excluding all patients who withdrew, were lost to follow-up, died or were readmitted to hospital, a greater proportion of patients were adherent in the intervention compared with the control at 1 month (90.0% vs. 76.5%; adjusted OR = 2.77; 95% CI, 1.01-7.62) and at 3 months after discharge (90.2% vs. 77.0%; adjusted OR = 3.68; 95% CI, 1.14-11.88). There was no significant difference in median change of EQ-5D-3L index values between intervention and control [0.000 (0.000; 0.275) vs. 0.234 (0.000; 0.379); p = 0.081]. Rates of mortality, readmission, or both were 0.8, 10.3, or 11.1%, respectively; with no significant differences between the 2 groups. Conclusion: Pharmacist-led interventions increased patient adherence to medication regimens by over 13% in the first 3 months after ACS hospital discharge, but not quality of life, mortality and readmission. These results are promising but should be tested in other settings prior to broader dissemination

An acto-myosin II constricting ring initiates the fission of activity-dependent bulk endosomes in neurosecretory cells

Activity-dependent bulk endocytosis allows neurons to internalize large portions of the plasma membrane in response to stimulation. However, whether this critical type of compensatory endocytosis is unique to neurons or also occurs in other excitable cells is currently unknown. Here we used fluorescent 70 kDa dextran to demonstrate that secretagogue-induced bulk endocytosis also occurs in bovine chromaffin cells. The relatively large size of the bulk endosomes found in this model allowed us to investigate how the neck of the budding endosomes constricts to allow efficient recruitment of the fission machinery. Using time-lapse imaging of Lifeact–GFP-transfected chromaffin cells in combination with fluorescent 70 kDa dextran, we detected acto-myosin II rings surrounding dextran-positive budding endosomes. Importantly, these rings were transient and contracted before disappearing, suggesting that they might be involved in restricting the size of the budding endosome neck. Based on the complete recovery of dextran fluorescence after photobleaching, we demonstrated that the actin ring-associated budding endosomes were still connected with the extracellular fluid. In contrast, no such recovery was observed following the constriction and disappearance of the actin rings, suggesting that these structures were pinched-off endosomes. Finally, we showed that the rings were initiated by a circular array of phosphatidylinositol(4,5)bisphosphate microdomains, and that their constriction was sensitive to both myosin II and dynamin inhibition. The acto-myosin II rings therefore play a key role in constricting the neck of budding bulk endosomes before dynamin-dependent fission from the plasma membrane of neurosecretory cells

Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation

Transit time distributions (TTDs) of streamflow are useful descriptors for understanding flow and solute transport in catchments. Catchment-scale TTDs can be modeled using tracer data (e.g. oxygen isotopes, such as δ18O) in inflow and outflows by employing StorAge Selection (SAS) functions. However, tracer data are often sparse in space and time, so they need to be interpolated to increase their spatiotemporal resolution. Moreover, SAS functions can be parameterized with different forms, but there is no general agreement on which one should be used. Both of these aspects induce uncertainty in the simulated TTDs, and the individual uncertainty sources as well as their combined effect have not been fully investigated. This study provides a comprehensive analysis of the TTD uncertainty resulting from 12 model setups obtained by combining different interpolation schemes for δ18O in precipitation and distinct SAS functions. For each model setup, we found behavioral solutions with satisfactory model performance for in-stream δ18O (KGEĝ€¯>ĝ€¯0.55, where KGE refers to the Kling-Gupta efficiency). Differences in KGE values were statistically significant, thereby showing the relevance of the chosen setup for simulating TTDs. We found a large uncertainty in the simulated TTDs, represented by a large range of variability in the 95ĝ€¯% confidence interval of the median transit time, varying at the most by between 259 and 1009ĝ€¯d across all tested setups. Uncertainty in TTDs was mainly associated with the temporal interpolation of δ18O in precipitation, the choice between time-variant and time-invariant SAS functions, flow conditions, and the use of nonspatially interpolated δ18O in precipitation. We discuss the implications of these results for the SAS framework, uncertainty characterization in TTD-based models, and the influence of the uncertainty for water quality and quantity studies

A randomized controlled trial of a pharmacist-led intervention to enhance knowledge of Vietnamese patients with type 2 diabetes mellitus

OBJECTIVES: We aimed to assess whether a pharmacist-led intervention enhances knowledge, medication adherence and glycemic control in patients with type 2 diabetes mellitus (T2DM). METHODS: We conducted a single-blinded randomized controlled trial in Vietnam. Individuals with T2DM were recruited from a general hospital and randomly allocated to intervention and routine care. The intervention group received routine care plus counselling intervention by a pharmacist, including providing drug information and answering individual patients' queries relating to T2DM and medications, which had not been done in routine care. We assessed the outcomes: knowledge score as measured by the Diabetes Knowledge Questionnaire, self-reported adherence and fasting blood glucose (FBG) at the 1-month follow-up. KEY FINDINGS: A total of 165 patients (83 intervention, 82 control) completed the study; their mean age was 63.33 years, and 49.1% were males. The baseline characteristics of the patients were similar between the groups. At 1-month follow-up, the pharmacist's intervention resulted in an improvement in all three outcomes: knowledge score [B = 5.527; 95% confidence intervals (CI): 3.982 to 7.072; P < 0.001], adherence [odds ratio (OR) = 9.813; 95% CI: 2.456 to 39.205; P = 0.001] and attainment of target FBG (OR = 1.979; 95% CI: 1.029 to 3.806; P = 0.041). CONCLUSIONS: The pharmacist-led intervention enhanced disease knowledge, medication adherence and glycemic control in patients with T2DM. This study provides evidence of the benefits of pharmacist counselling in addition to routine care for T2DM outpatients in a Vietnam population

Differentiation of Patients with Balance Insufficiency (Vestibular Hypofunction) versus Normal Subjects Using a Low-Cost Small Wireless Wearable Gait Sensor

Balance disorders present a significant healthcare burden due to the potential for hospitalization or complications for the patient, especially among the elderly population when considering intangible losses such as quality of life, morbidities, and mortalities. This work is a continuation of our earlier works where we now examine feature extraction methodology on Dynamic Gait Index (DGI) tests and machine learning classifiers to differentiate patients with balance problems versus normal subjects on an expanded cohort of 60 patients. All data was obtained using our custom designed low-cost wireless gait analysis sensor (WGAS) containing a basic inertial measurement unit (IMU) worn by each subject during the DGI tests. The raw gait data is wirelessly transmitted from the WGAS for real-time gait data collection and analysis. Here we demonstrate predictive classifiers that achieve high accuracy, sensitivity, and specificity in distinguishing abnormal from normal gaits. These results show that gait data collected from our very low-cost wearable wireless gait sensor can effectively differentiate patients with balance disorders from normal subjects in real-time using various classifiers. Our ultimate goal is to be able to use a remote sensor such as the WGAS to accurately stratify an individual’s risk for falls