Challenges posed by non-standard neutrino interactions in the determination of δCP\delta_{CP} at DUNE

One of the primary objectives of Deep Underground Neutrino Experiment (DUNE) is to discover the leptonic CP violation and to identify it's source. In this context, we study the impact of non-standard neutrino interactions (NSIs) on observing the CP violation signal at DUNE. We explore the impact of various parameter degeneracies introduced by non-zero NSI and identify which of these can influence the CP violation sensitivity and CP precision of DUNE, by considering NSI both in data and in theory. In particular, we study how the CP sensitivity of DUNE is affected because of the intrinsic hierarchy degeneracy which occurs when the diagonal NSI parameter $\epsilon_{ee}=-1$ and $\delta_{CP}= \pm 90^{\circ}$

Comparison of the Adherence to the American Diabetes Association Guidelines of Diabetes Care in Primary Care and Subspecialty Clinics

Abstract Background Diabetes mellitus is a major public health problem with significant morbidity and mortality. Evidence based guidelines have been proposed to reduce the micro and macrovascular complications, but studies have shown that these goals are not being met. We sought to compare the adherence to the American Diabetes Association guidelines for measurement and control of glycohemoglobin (A1c), blood pressure (BP), lipids (LDL) and microalbuminuria (MA) by subspecialty and primary care clinics in an academic medical center. Methods 390 random charts of patients with diabetes from Family Practice (FP), Internal Medicine (IM) and Diabetes (DM) clinics at Michigan State University were reviewed. Results We reviewed 131, 134 and 125 charts from the FP, IM and DM clinics, respectively. DM clinic had a higher percentage of patients with type 1 diabetes 43/125 (34.4%) compared with 7/131 (5.3%) in FP and 7/134 (5.2%) in IM clinics. A1c was measured in 99%, 97.8% and 100% subjects in FP, IM and DM clinics respectively. B.P. was measured in all subjects in all three clinics. Lipids were checked in 97.7%, 95.5% and 92% patients in FP, IM and DM clinics respectively. MA was measured at least once during the year preceding the office visit in 85.5%, 82.8% and 76.8% patients in FP, IM and DM clinics respectively. A1C was controlled (<7%) in 38.9, 43.3, 28.8% of patients in the FP, IM and DM clinics, respectively (p = 0.034). LDL was controlled (<100 mg/dl or 2.586 mmol/l) in 71.8, 64.9, 64% of patients in the FP, IM and DM clinics, respectively. MA was controlled (<30 mg/gm creatinine) in 60.3%, 51.5% and 60% patients in FP, IM and DM clinics respectively (P = 0.032). BP was controlled (<130/80) in 59.5, 67.2 and 52.8% patients in the FP, IM and DM clinics, respectively. Conclusion Testing rates for A1C, LDL, and MA were high, in both subspecialty and primary care clinics. However, the degree of control was not optimal. Significantly fewer patients in the DM clinic had A1c <7%, the cause of which may be multifactorial.http://deepblue.lib.umich.edu/bitstream/2027.42/111055/1/40200_2015_Article_158.pd

Donor demographic and laboratory predictors of single donor platelet yield

Background: Platelet transfusions are essential to prevent morbidity and mortality in patients who are severely thrombocytopenic and are at risk of spontaneous bleeding. Platelets are currently obtained either by fractionation of whole blood or by platelet apheresis. The quality of single donor platelets (SDP) in terms of yield influences platelet recovery in the recipient and allows prolonging intervals between transfusions. Material and Methods: Donor demographic and laboratory data were analyzed prior to performing plateletpheresis to identify donor factors that influence platelet yield. The study was conducted on 130 healthy, first-time plateletpheresis donors over a period of 4 years. The plateletpheresis procedures were performed using Fresenius Kabi COM.TEC and Hemonetics MCS plus separator. A relationship between pre-donation donor variables and yield of platelets was studied using the Pearson correlation. Results: The mean platelet yield was 3.160.62x1011 per unit. A positive correlation was observed between platelet yield and pre-donation platelet count, body mass index (BMI; Kg/m2) of the donor, while a negative correlation was observed between age and the platelet yield. Conclusion: Donor pre-donation platelet count, BMI and donor age influence platelet yield. Young healthy donors with a high platelet count and better BMI can give a better platelet yield in the SDP