Set optimization - a rather short introduction

Recent developments in set optimization are surveyed and extended including various set relations as well as fundamental constructions of a convex analysis for set- and vector-valued functions, and duality for set optimization problems. Extensive sections with bibliographical comments summarize the state of the art. Applications to vector optimization and financial risk measures are discussed along with algorithmic approaches to set optimization problems

Acyl-Protein Thioesterase 2 Catalizes the Deacylation of Peripheral Membrane-Associated GAP-43

An acylation/deacylation cycle is necessary to maintain the steady-state subcellular distribution and biological activity of S-acylated peripheral proteins. Despite the progress that has been made in identifying and characterizing palmitoyltransferases (PATs), much less is known about the thioesterases involved in protein deacylation. In this work, we investigated the deacylation of growth-associated protein-43 (GAP-43), a dually acylated protein at cysteine residues 3 and 4. Using fluorescent fusion constructs, we measured in vivo the rate of deacylation of GAP-43 and its single acylated mutants in Chinese hamster ovary (CHO)-K1 and human HeLa cells. Biochemical and live cell imaging experiments demonstrated that single acylated mutants were completely deacylated with similar kinetic in both cell types. By RT-PCR we observed that acyl-protein thioesterase 1 (APT-1), the only bona fide thioesterase shown to mediate deacylation in vivo, is expressed in HeLa cells, but not in CHO-K1 cells. However, APT-1 overexpression neither increased the deacylation rate of single acylated GAP-43 nor affected the steady-state subcellular distribution of dually acylated GAP-43 both in CHO-K1 and HeLa cells, indicating that GAP-43 deacylation is not mediated by APT-1. Accordingly, we performed a bioinformatic search to identify putative candidates with acyl-protein thioesterase activity. Among several candidates, we found that APT-2 is expressed both in CHO-K1 and HeLa cells and its overexpression increased the deacylation rate of single acylated GAP-43 and affected the steady-state localization of diacylated GAP-43 and H-Ras. Thus, the results demonstrate that APT-2 is the protein thioesterase involved in the acylation/deacylation cycle operating in GAP-43 subcellular distribution

An emergent framework for supply chain risk management and performance measurement

Changes in the ‘shape’ of risk (ie sources, nature, triggers, scale, rapidity and severity of consequences) relating to supply chains pose challenges for risk management and the underpinning discipline domains such as Operations Research that have traditionally provided guidance and support. The aim is to evaluate these challenges, specifically in the context of supply chain risk management and to consider new approaches to support management. An overall Supply Chain Risk Management Framework is constructed, comprising five components—risk drivers, risk management influencers, decision maker characteristics, risk management responses and performance outcomes. The focus is towards the risk management influencers, recognizing that other components have been investigated elsewhere in the operations literature. Four elements are identified within this risk management component, two conventional elements, rewards and risks, and two new elements, timescale and portfolio effects. An empirical case example is employed to illustrate these issues of risk management in the manufacturing sector and to evaluate the approaches employed to manage risk and performance. The conclusion drawn is that the proposed Supply Chain Risk Management Framework with the inclusion of the risk management influencers component provides a more robust description of the factors that affect the nature of the risk management responses in particular situations. This also demonstrates the need for the Operations Research discipline to evolve a more diverse set of risk management tools and approaches (ie both quantitative and qualitative) to effectively address the diversity of issues and contexts

Structure and function of the initially transcribing RNA polymerase II–TFIIB complex

The general transcription factor (TF) IIB is required for RNA polymerase (Pol) II initiation and extends with its B-reader element into the Pol II active centre cleft. Low-resolution structures of the Pol II– TFIIB complex1,2 indicated how TFIIB functions in DNA recruitment, but they lacked nucleic acids and half of the B-reader, leaving other TFIIB functions3,4 enigmatic. Here we report crystal structures of the Pol II–TFIIB complex from the yeast Saccharomyces cerevisiae at 3.4A˚ resolution and of an initially transcribing complex that additionally contains theDNAtemplate and a 6-nucleotide RNAproduct.The structures reveal the entire B-reader and protein– nucleic acid interactions, and together with functional data lead to a more complete understanding of transcription initiation. TFIIB partially closes the polymerase cleft to position DNA and assist in its opening. The B-reader does not reach the active site but binds the DNA template strand upstream to assist in the recognition of the initiator sequence and in positioning the transcription start site. TFIIB rearranges active-site residues, induces binding of the catalytic metal ion B, and stimulates initial RNA synthesis allosterically. TFIIB then prevents the emergingDNA–RNAhybrid duplex from tilting, which would impair RNA synthesis. When the RNA grows beyond 6 nucleotides, it is separated from DNA and is directed to its exit tunnel by the B-reader loop. Once the RNA grows to 12–13 nucleotides, it clashes with TFIIB, triggering TFIIB displacement and elongation complex formation. Similar mechanisms may underlie all cellular transcription because all eukaryotic and archaeal RNA polymerases use TFIIB-like factors5, and the bacterial initiation factor sigma has TFIIB-like topology1,2 and contains the loop region 3.2 that resembles the B-reader loop in location, charge and function6–8. TFIIB and its counterparts may thus account for the two fundamental properties that distinguish RNA from DNA polymerases: primer-independent chain initiation and product separation from the template