Effect of lipopolysaccharide from periodontal pathogens on the production of tissue plasminogen activator and plasminogen activator inhibitor 2 by human gingival fibroblasts

Both tissue plasminogen activator (t-PA) and plasminogen activator inhibitor 2 (PAI-2) are important proteolysis factors present in inflamed human periodontal tissues. The aim of the present study was to investigate the effect of lipopolysaccharide (LPS) on the synthesis: of t-PA and PAI-2 by human gingival fibroblasts (HGF). LPS from different periodontal pathogens including Actinobacillus actinomycetemcomitans, Porphyromonas gingivalis and Fusobacterium nucleatum were extracted by the hot phenol water method. The levels of t-PA and PAI-2 secreted into the cell culture media were measured by enzyme-linked immunosorbent assays (ELISA). The mRNA for t-PA and PAI-2 were measured by RT-PCR. The results showed t-PA synthesis was increased in response to all types of LPS studied and PAI-2 level was increased by LPS from A. actinomycetemcomitans and F. nucleatum, but not P. gingivalis. When comparing the effects of LPS from non-periodontal bacteria (Escherichia coli and Salmonella enteritidis) with the LPS from periodontal pathogens, we found that the ratio of t-PA to PAI-2 was greater following exposure of the cells to LPS from periodontal pathogens. The highest ratio of t-PA to PAI-2 was found in those cells exposed to LPS from P. gingivalis. These results indicate that LPS derived from periodontal pathogens may cause unbalanced regulation of plasminogen activator and plasminogen activator inhibitor by HGF and such an effect may, in part, contribute to the destruction of periodontal connective tissue through dysregulated pericellular proteolysis.

Large-N solutions of the Heisenberg and Hubbard-Heisenberg models on the anisotropic triangular lattice: application to Cs2CuCl4 and to the layered organic superconductors kappa-(BEDT-TTF)(2)X (BEDT-TTF bis(ethylene-dithio)tetrathiafulvalene); X anion)

We solve the Sp(N) Heisenberg and SU(N) Hubbard-Heisenberg models on the anisotropic triangular lattice in the large-N limit. These two models may describe respectively the magnetic and electronic properties of the family of layered organic materials K-(BEDT-TTF)(2)X, The Heisenberg model is also relevant to the frustrated antiferromagnet, Cs2CuCl4. We find rich phase diagrams for each model. The Sp(N) :antiferromagnet is shown to have five different phases as a function of the size of the spin and the degree of anisotropy of the triangular lattice. The effects of fluctuations at finite N are also discussed. For parameters relevant to Cs2CuCl4 the ground state either exhibits incommensurate spin order, or is in a quantum disordered phase with deconfined spin-1/2 excitations and topological order. The SU(N) Hubbard-Heisenberg model exhibits an insulating dimer phase, an insulating box phase, a semi-metallic staggered flux phase (SFP), and a metallic uniform phase. The uniform and SFP phases exhibit a pseudogap, A metal-insulator transition occurs at intermediate values of the interaction strength.

Accumulation of manganese in Neisseria gonorrhoeae correlates with resistance to oxidative killing by superoxide anion and is independent of superoxide dismutase activity

As a facultative aerobe with a high iron requirement and a highly active aerobic respiratory chain, Neisseria gonorrhoeae requires defence systems to respond to toxic oxygen species such as superoxide. It has been shown that supplementation of media with 100 muM Mn(II) considerably enhanced the resistance of this bacterium to oxidative killing by superoxide. This protection was not associated with the superoxide dismutase enzymes of N. gonorrhoeae. In contrast to previous studies, which suggested that some strains of N. gonorrhoeae might not contain a superoxide dismutase, we identified a sodB gene by genome analysis and confirmed its presence in all strains examined by Southern blotting, but found no evidence for sodA or sodC. A sodB mutant showed very similar susceptibility to superoxide killing to that of wild-type cells, indicating that the Fe-dependent SOD B did not have a major role in resistance to oxidative killing under the conditions tested. The absence of a sodA gene indicated that the Mn-dependent protection against oxidative killing was independent of Mn-dependent SOD A. As a sodB mutant also showed Mn-dependent resistance to oxidative killing, then it is concluded that this resistance is independent of superoxide dismutase enzymes. Resistance to oxidative killing was correlated with accumulation of Mn(II) by the bacterium. We hypothesize that this bacterium uses Mn(II) as a chemical quenching agent in a similar way to the already established process in Lactobacillus plantarum. A search for putative Mn(II) uptake systems identified an ABC cassette-type system (MntABC) with a periplasmic-binding protein (MntC). An mntC mutant was shown to have lowered accumulation of Mn(II) and was also highly susceptible to oxidative killing, even in the presence of added Mn(II). Taken together, these data show that N. gonorrhoeae possesses a Mn(II) uptake system that is critical for resistance to oxidative stress.

Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.