Improving supply chain performance: Real-time demand information and flexible deliveries

In some supply chains, materials are ordered periodically according to local information. This paper investigates how to improve the performance of such a supply chain. Specifically, we consider a serial inventory system in which each stage implements a local reorder interval policy; i.e., each stage orders up to a local basestock level according to a fixed-interval schedule. A fixed cost is incurred for placing an order. Two improvement strategies are considered: (1) expanding the information flow by acquiring real-time demand information and (2) accelerating the material flow via flexible deliveries. The first strategy leads to a reorder interval policy with full information; the second strategy leads to a reorder point policy with local information. Both policies have been studied in the literature. Thus, to assess the benefit of these strategies, we analyze the local reorder interval policy. We develop a bottom-up recursion to evaluate the system cost and provide a method to obtain the optimal policy. A numerical study shows the following: Increasing the flexibility of deliveries lowers costs more than does expanding information flow; the fixed order costs and the system lead times are key drivers that determine the effectiveness of these improvement strategies. In addition, we find that using optimal batch sizes in the reorder point policy and demand rate to infer reorder intervals may lead to significant cost inefficiency. © 2010 INFORMS.

Patient-derived endothelial progenitor cells improve vascular graft patency in a rodent model.

Late outgrowth endothelial progenitor cells (EPCs) derived from the peripheral blood of patients with significant coronary artery disease were sodded into the lumens of small diameter expanded polytetrafluoroethylene (ePTFE) vascular grafts. Grafts (1mm inner diameter) were denucleated and sodded either with native EPCs or with EPCs transfected with an adenoviral vector containing the gene for human thrombomodulin (EPC+AdTM). EPC+AdTM was shown to increase the in vitro rate of graft activated protein C (APC) production 4-fold over grafts sodded with untransfected EPCs (p<0.05). Unsodded control and EPC-sodded and EPC+AdTM-sodded grafts were implanted bilaterally into the femoral arteries of athymic rats for 7 or 28 days. Unsodded control grafts, both with and without denucleation treatment, each exhibited 7 day patency rates of 25%. Unsodded grafts showed extensive thrombosis and were not tested for patency over 28 days. In contrast, grafts sodded with untransfected EPCs or EPC+AdTM both had 7 day patency rates of 88-89% and 28 day patency rates of 75-88%. Intimal hyperplasia was observed near both the proximal and distal anastomoses in all sodded graft conditions but did not appear to be the primary occlusive failure event. This in vivo study suggests autologous EPCs derived from the peripheral blood of patients with coronary artery disease may improve the performance of synthetic vascular grafts, although no differences were observed between untransfected EPCs and TM transfected EPCs.

Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.

Restoration of beta-adrenergic signaling in failing cardiac ventricular myocytes via adenoviral-mediated gene transfer.

Cardiovascular gene therapy is a novel approach to the treatment of diseases such as congestive heart failure (CHF). Gene transfer to the heart would allow for the replacement of defective or missing cellular proteins that may improve cardiac performance. Our laboratory has been focusing on the feasibility of restoring beta-adrenergic signaling deficiencies that are a characteristic of chronic CHF. We have now studied isolated ventricular myocytes from rabbits that have been chronically paced to produce hemodynamic failure. We document molecular beta-adrenergic signaling defects including down-regulation of myocardial beta-adrenergic receptors (beta-ARs), functional beta-AR uncoupling, and an up-regulation of the beta-AR kinase (betaARK1). Adenoviral-mediated gene transfer of the human beta2-AR or an inhibitor of betaARK1 to these failing myocytes led to the restoration of beta-AR signaling. These results demonstrate that defects present in this critical myocardial signaling pathway can be corrected in vitro using genetic modification and raise the possibility of novel inotropic therapies for CHF including the inhibition of betaARK1 activity in the heart.