Plasmid-Cured Chlamydia caviae Activates TLR2-Dependent Signaling and Retains Virulence in the Guinea Pig Model of Genital Tract Infection

Loss of the conserved “cryptic” plasmid from C. trachomatis and C. muridarum is pleiotropic, resulting in reduced innate inflammatory activation via TLR2, glycogen accumulation and infectivity. The more genetically distant C. caviae GPIC is a natural pathogen of guinea pigs and induces upper genital tract pathology when inoculated intravaginally, modeling human disease. To examine the contribution of pCpGP1 to C. caviae pathogenesis, a cured derivative of GPIC, strain CC13, was derived and evaluated in vitro and in vivo. Transcriptional profiling of CC13 revealed only partial conservation of previously identified plasmid-responsive chromosomal loci (PRCL) in C. caviae. However, 2-deoxyglucose (2DG) treatment of GPIC and CC13 resulted in reduced transcription of all identified PRCL, including glgA, indicating the presence of a plasmid-independent glucose response in this species. In contrast to plasmid-cured C. muridarum and C. trachomatis, plasmid-cured C. caviae strain CC13 signaled via TLR2 in vitro and elicited cytokine production in vivo similar to wild-type C. caviae. Furthermore, inflammatory pathology induced by infection of guinea pigs with CC13 was similar to that induced by GPIC, although we observed more rapid resolution of CC13 infection in estrogen-treated guinea pigs. These data indicate that either the plasmid is not involved in expression or regulation of virulence in C. caviae or that redundant effectors prevent these phenotypic changes from being observed in C. caviae plasmid-cured strains

The changing carbon cycle of the coastal ocean

The carbon cycle of the coastal ocean is a dynamic component of the global carbon budget. But the diverse sources and sinks of carbon and their complex interactions in these waters remain poorly understood. Here we discuss the sources, exchanges and fates of carbon in the coastal ocean and how anthropogenic activities have altered the carbon cycle. Recent evidence suggests that the coastal ocean may have become a net sink for atmospheric carbon dioxide during post-industrial times. Continued human pressures in coastal zones will probably have an important impact on the future evolution of the coastal ocean's carbon budget

HPLC purification of higher plant-dervied lignin phenols for compound specific radiocarbon analysis

The ability to measure the radiocarbon content of compounds isolated from complex mixtures has begun to revolutionize our understanding of carbon transformations on earth. Because samples are often small, each new compound isolation method must be tested for background carbon contamination (C ex). Here, we present a new method for compound-specific radiocarbon analysis (CSRA) of higher plant-derived lignin phenols. To test for C ex, we compared the Δ14C values of unprocessed lignin phenol containing standard materials (woods, leaves, natural vanillin, and synthetic vanillin) with those of lignin phenols liberated by CuO oxidation and purified by two-dimensional high-pressure liquid chromatography (HPLC) coupled to mass spectrometry (MS) and UV detection. We assessed Cex associated with (1) microwave assisted CuO oxidation of bulk samples to lignin phenol monomers, (2) HPLC purification, and (3) accelerator mass spectrometry (AMS) sample preparation. The Δ14C of purified compounds (corrected for Cex) agreed, within error, with those of bulk materials for samples that were >10 μg C. This method will allow routine analysis of the Δ14C of lignin phenols isolated from terrestrial, aquatic, and marine settings, revealing the time scale for the processing of one of the single largest components of active organic carbon reservoirs on earth. © 2010 American Chemical Society

HPLC purification of higher plant-dervied lignin phenols for compound specific radiocarbon analysis

The ability to measure the radiocarbon content of compounds isolated from complex mixtures has begun to revolutionize our understanding of carbon transformations on earth. Because samples are often small, each new compound isolation method must be tested for background carbon contamination (C ex). Here, we present a new method for compound-specific radiocarbon analysis (CSRA) of higher plant-derived lignin phenols. To test for C ex, we compared the Δ14C values of unprocessed lignin phenol containing standard materials (woods, leaves, natural vanillin, and synthetic vanillin) with those of lignin phenols liberated by CuO oxidation and purified by two-dimensional high-pressure liquid chromatography (HPLC) coupled to mass spectrometry (MS) and UV detection. We assessed Cex associated with (1) microwave assisted CuO oxidation of bulk samples to lignin phenol monomers, (2) HPLC purification, and (3) accelerator mass spectrometry (AMS) sample preparation. The Δ14C of purified compounds (corrected for Cex) agreed, within error, with those of bulk materials for samples that were >10 μg C. This method will allow routine analysis of the Δ14C of lignin phenols isolated from terrestrial, aquatic, and marine settings, revealing the time scale for the processing of one of the single largest components of active organic carbon reservoirs on earth. © 2010 American Chemical Society

Characterizing continuous (s, S) policy with supplier selection using Simulation Optimization

A real-world inventory control system, due to its nonlinear, stochastic, time-dependent nature, and the presence of complex interactions between supply chain members, can become quite challenging to optimize and requires a complex model. At this point, the Simulation Optimization (SO) model gains a better understanding of the complex and messy phenomenon of the inventory control of supply chain members. By creating SO models for Distribution Center (DC)s and Suppliers, we wish to present flexible and comprehensible research on the important decision of whether to minimize the differences between total overordering cost and total underordering cost (Model 1) or to minimize the total supply chain cost (Model 2). We also try to point out several important issues: the optimal value of the initial inventory, the reorder point, and the order-up-to level in continuous (s, S) policy for each DC and each Supplier; whether SO models can successfully integrate the supplier selection and continuous (s, S) policy for the supply chain environment; how to apply statistical analysis skills to compare these SO models with a greater level of detail. According to the cost analysis, the total supply chain cost of Model 1 is improved approximately 22% with Model 2. Also, Model 2 is the best one according to quantity-based analysis, order-based analysis, probability-based analysis, and lead-time-based analysis. Model 2 can be successfully applied for the actual situation of the supply chain inventory system and companies can obtain a remarkable amount of saving while increasing their competitive edge.Scientific and Technological Research Council of Turkey (TUBITAK) [2211]Ayse T Dosdogru gratefully acknowledges the Scientific and Technological Research Council of Turkey (TUBITAK) for the 2211 scholarship program