Preservation of myocardial beta-adrenergic receptor signaling delays the development of heart failure after myocardial infarction.

When the heart fails, there is often a constellation of biochemical alterations of the beta-adrenergic receptor (betaAR) signaling system, leading to the loss of cardiac inotropic reserve. betaAR down-regulation and functional uncoupling are mediated through enhanced activity of the betaAR kinase (betaARK1), the expression of which is increased in ischemic and failing myocardium. These changes are widely viewed as representing an adaptive mechanism, which protects the heart against chronic activation. In this study, we demonstrate, using in vivo intracoronary adenoviral-mediated gene delivery of a peptide inhibitor of betaARK1 (betaARKct), that the desensitization and down-regulation of betaARs seen in the failing heart may actually be maladaptive. In a rabbit model of heart failure induced by myocardial infarction, which recapitulates the biochemical betaAR abnormalities seen in human heart failure, delivery of the betaARKct transgene at the time of myocardial infarction prevents the rise in betaARK1 activity and expression and thereby maintains betaAR density and signaling at normal levels. Rather than leading to deleterious effects, cardiac function is improved, and the development of heart failure is delayed. These results appear to challenge the notion that dampening of betaAR signaling in the failing heart is protective, and they may lead to novel therapeutic strategies to treat heart disease via inhibition of betaARK1 and preservation of myocardial betaAR function.

Dunn County and Watford City, North Dakota: A case study of the fiscal effects of Bakken shale development

The Bakken region of North Dakota and Montana has experienced perhaps the greatest effects of increased oil and gas development in the United States, with major implications for local governments. Though development of the Bakken began in the early 2000s, large-scale drilling and population growth dramatically affected the region from roughly 2008 through today. This case study examines the local government fiscal benefits and challenges experienced by Dunn County and Watford City, which lie near the heart of the producing region. For both local governments, the initial growth phase presented major fiscal challenges due to rapidly expanding service demands and insufficient revenue. In the following years, these challenges eased as demand for services slowed due to declining industry activity and state tax policies redirected more funds to localities. Looking forward, both local governments describe their fiscal health as stronger because of the Bakken boom, though higher debt loads and an economy heavily dependent on the volatile oil and gas industry each pose challenges for future fiscal stability.

Development and Testing of An Automatic Lung IMRT Planning Algorithm

Knowledge-based radiation treatment is an emerging concept in radiotherapy. It

mainly refers to the technique that can guide or automate treatment planning in

clinic by learning from prior knowledge. Dierent models are developed to realize

it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This

model can automatically determine both beam conguration and optimization ob-

jectives with non-coplanar beams based on patient-specic anatomical information.

Although plans automatically generated by this model demonstrate equivalent or

better dosimetric quality compared to clinical approved plans, its validity and gener-

ality are limited due to the empirical assignment to a coecient called angle spread

constraint dened in the beam eciency index used for beam ranking. To eliminate

these limitations, a systematic study on this coecient is needed to acquire evidences

for its optimal value.

To achieve this purpose, eleven lung cancer patients with complex tumor shape

with non-coplanar beams adopted in clinical approved plans were retrospectively

studied in the frame of the automatic lung IMRT treatment algorithm. The primary

and boost plans used in three patients were treated as dierent cases due to the

dierent target size and shape. A total of 14 lung cases, thus, were re-planned using

the knowledge-based automatic lung IMRT planning algorithm by varying angle

spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency

index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good

as possible. Important dosimetric parameters for PTV and OARs, quantitatively

re

ecting the plan quality, were extracted from the DVHs and analyzed as a function

of angle spread constraint for each case. Comparisons of these parameters between

clinical plans and model-based plans were evaluated by two-sampled Students t-tests,

and regression analysis on a composite index built on the percentage errors between

dosimetric parameters in the model-based plans and those in the clinical plans as a

function of angle spread constraint was performed.

Results show that model-based plans generally have equivalent or better quality

than clinical approved plans, qualitatively and quantitatively. All dosimetric param-

eters except those for lungs in the automatically generated plans are statistically

better or comparable to those in the clinical plans. On average, more than 15% re-

duction on conformity index and homogeneity index for PTV and V40, V60 for heart

while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The

intra-plan comparison among model-based plans demonstrates that plan quality does

not change much with angle spread constraint larger than 0.4. Further examination

on the variation curve of the composite index as a function of angle spread constraint

shows that 0.6 is the optimal value that can result in statistically the best achievable

plans.