Differential display of mRNA was used to identify concordant changes in gene expression induced by two mood-stabilizing agents, lithium and valproate (VPA). Both treatments, on chronic administration, increased mRNA levels of the transcription factor polyomavirus enhancer-binding protein (PEBP) 2␤ in frontal cortex (FCx). Both treatments also increased the DNA binding activity of PEBP2␣␤ and robustly increased the levels of bcl-2 (known to be transcriptionally regulated by PEBP2) in FCx. Immunohistochemical studies revealed a marked increase in the number of bcl-2-immunoreactive cells in layers 2 and 3 of FCx. These novel findings represent the first report of medication-induced increases in CNS bcl-2 levels and may have implications not only for mood disorders, but also for long-term treatment of various neurodegenerative disorders. Key Words: Lithium-Valproate-Bcl-2-Manicdepressive illness-Transcription factors-Polyomavirus enhancer-binding protein 2-Differential display.

Using human heart fibroblasts (HHF), we studied the effect of basic fibroblast growth factor (bFGF) and transforming growth factor-beta (TGF-beta) on the gene expression of type I collagen, collagenase and tissue inhibitor of metalloproteinases (TIMP). Initially, treatment of HHF with bFGF alone (10 ng/ml) resulted in elevated secretion of collagenase into the culture medium. Subsequent treatment of HHF with TGF-beta in combination with bFGF suppressed collagenase secretion. Northern blot analysis reinforced this observation by revealing an enhancement of the steady-state mRNA level of collagenase in response to bFGF. In order to examine if the collagenase gene was affected by bFGF at the transcriptional level, transfection experiments were carried out with a plasmid containing collagenase promoter linked to chloramphenicol acetyltransferase gene (CAT). Basic FGF stimulated CAT activity by four-fold, indicating increased promoter activity whereas the combination of TGF-beta and bFGF resulted in decreased CAT activity. TGF-beta was shown to increase type I collagen and TIMP mRNA levels by 2.5- and 2.1-fold, respectively. These results suggest that TGF-beta and bFGF may play a pivotal role in regulating collagen metabolism in HHF.

The available-to-promise (ATP) function is becoming increasingly important in supply chain management since it directly links production resources with customer orders. In this paper, a mixed integer programming (MIP) ATP model is presented. This model can provide an order-promising and -fulfillment solution for a batch of orders that arrive within a predefined batching interval. A variety of constraints, such as raw material availability, production capacity, material compatibility, and customer preferences, are considered. Simulation experiments using the model investigate the sensitivity of supply chain performance to changes in certain parameters, such as batching interval size and customer order flexibility.• Customers are tightly linked with suppliers to form an integrated supply chain. More constraints, dynamics, and uncertainties from both the supplier side and the customer side have been introduced into the order management process. • Product life cycles are being reduced drastically. This further challenges order management practices and requires substantial flexibility. Advanced available-to-promise (ATP) is increasingly seen as the mechanism for addressing these issues and is becoming a differentiating tool to gain competitive advantages. As such it has become a strategic business tool that merits substantial corporate investment and thought along a variety of business dimensions including customer service, valuation of enterprise resources, e-commerce capability, supply chain collaboration, and crisis management.As its name suggests, an ATP system provides product availability information for orderpromising and order-fulfillment decision support. ATP is defined by the American Production and Inventory Control Society (APICS) in the APICS Dictionary (6th edition, 1987) as "the uncommitted portion of a company's inventory and planned production, maintained in the master schedule to support customer order promising."Under this conventional definition, ATP is based on a simple monitoring of the uncommitted portion of current and future available finished goods. In contrast, our model represents an advanced ATP that dynamically allocates and reallocates resources to promise and fulfill customer orders. It simultaneously considers supply-chain-wide resources, including raw materials, work-in-process (WIP), finished goods, and even production and distribution capacities. Advanced ATP is a decision-making mechanism that can dynamically handle the uncertainty and unanticipated changes related to suppliers and customers, as well as production processes. Its purpose is to mitigate the discrepancy between the forecast-driven push activities and order-driven pull activities across a supply chain system (see Simchi-Levi, Kaminsky, and Simchi-Levi 2000 for detailed discussions of pull and push systems). As a result, planning processes can match execution mechanisms on every push-pull boundary across a supply chain to improve supply chain performance. At the same time, advanced ATP takes into consideration various a...