5 resultados para 2nd degree equation
em Duke University
Resumo:
Co-occurrence of HIV and substance abuse is associated with poor outcomes for HIV-related health and substance use. Integration of substance use and medical care holds promise for HIV patients, yet few integrated treatment models have been reported. Most of the reported models lack data on treatment outcomes in diverse settings. This study examined the substance use outcomes of an integrated treatment model for patients with both HIV and substance use at three different clinics. Sites differed by type and degree of integration, with one integrated academic medical center, one co-located academic medical center, and one co-located community health center. Participants (n=286) received integrated substance use and HIV treatment for 12 months and were interviewed at 6-month intervals. We used linear generalized estimating equation regression analysis to examine changes in Addiction Severity Index (ASI) alcohol and drug severity scores. To test whether our treatment was differentially effective across sites, we compared a full model including site by time point interaction terms to a reduced model including only site fixed effects. Alcohol severity scores decreased significantly at 6 and 12 months. Drug severity scores decreased significantly at 12 months. Once baseline severity variation was incorporated into the model, there was no evidence of variation in alcohol or drug score changes by site. Substance use outcomes did not differ by age, gender, income, or race. This integrated treatment model offers an option for treating diverse patients with HIV and substance use in a variety of clinic settings. Studies with control groups are needed to confirm these findings.
Resumo:
BACKGROUND: Heart failure is characterized by abnormalities in beta-adrenergic receptor (betaAR) signaling, including increased level of myocardial betaAR kinase 1 (betaARK1). Our previous studies have shown that inhibition of betaARK1 with the use of the Gbetagamma sequestering peptide of betaARK1 (betaARKct) can prevent cardiac dysfunction in models of heart failure. Because inhibition of betaARK activity is pivotal for amelioration of cardiac dysfunction, we investigated whether the level of betaARK1 inhibition correlates with the degree of heart failure. METHODS AND RESULTS: Transgenic (TG) mice with varying degrees of cardiac-specific expression of betaARKct peptide underwent transverse aortic constriction (TAC) for 12 weeks. Cardiac function was assessed by serial echocardiography in conscious mice, and the level of myocardial betaARKct protein was quantified at termination of the study. TG mice showed a positive linear relationship between the level of betaARKct protein expression and fractional shortening at 12 weeks after TAC. TG mice with low betaARKct expression developed severe heart failure, whereas mice with high betaARKct expression showed significantly less cardiac deterioration than wild-type (WT) mice. Importantly, mice with a high level of betaARKct expression had preserved isoproterenol-stimulated adenylyl cyclase activity and normal betaAR densities in the cardiac membranes. In contrast, mice with low expression of the transgene had marked abnormalities in betaAR function, similar to the WT mice. CONCLUSIONS: These data show that the level of betaARK1 inhibition determines the degree to which cardiac function can be preserved in response to pressure overload and has important therapeutic implications when betaARK1 inhibition is considered as a molecular target.
Resumo:
A shearing quotient (SQ) is a way of quantitatively representing the Phase I shearing edges on a molar tooth. Ordinary or phylogenetic least squares regression is fit to data on log molar length (independent variable) and log sum of measured shearing crests (dependent variable). The derived linear equation is used to generate an 'expected' shearing crest length from molar length of included individuals or taxa. Following conversion of all variables to real space, the expected value is subtracted from the observed value for each individual or taxon. The result is then divided by the expected value and multiplied by 100. SQs have long been the metric of choice for assessing dietary adaptations in fossil primates. Not all studies using SQ have used the same tooth position or crests, nor have all computed regression equations using the same approach. Here we focus on re-analyzing the data of one recent study to investigate the magnitude of effects of variation in 1) shearing crest inclusion, and 2) details of the regression setup. We assess the significance of these effects by the degree to which they improve or degrade the association between computed SQs and diet categories. Though altering regression parameters for SQ calculation has a visible effect on plots, numerous iterations of statistical analyses vary surprisingly little in the success of the resulting variables for assigning taxa to dietary preference. This is promising for the comparability of patterns (if not casewise values) in SQ between studies. We suggest that differences in apparent dietary fidelity of recent studies are attributable principally to tooth position examined.