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.

Natural selection and quantitative genetics of life-history traits in Western women: A twin study

Whether contemporary human populations are still evolving as a result of natural selection has been hotly debated. For natural selection to cause evolutionary change in a trait, variation in the trait must be correlated with fitness and be genetically heritable and there must be no genetic constraints to evolution. These conditions have rarely been tested in human populations. In this study, data from a large twin cohort were used to assess whether selection Will cause a change among women in contemporary Western population for three life-history traits: age at menarche, age at first reproduction, and age at menopause. We control for temporal variation in fecundity (the baby boom phenomenon) and differences between women in educational background and religious affiliation. University-educated women have 35% lower fitness than those with less than seven years education, and Roman Catholic women have about 20% higher fitness than those of other religions. Although these differences were significant, education and religion only accounted for 2% and 1% of variance in fitness, respectively. Using structural equation modeling, we reveal significant genetic influences for all three life-history traits, with heritability estimates of 0.50, 0.23, and 0.45, respectively. However, strong genetic covariation with reproductive fitness could only be demonstrated for age at first reproduction, with much weaker covariation for age at menopause and no significant covariation for age at menarche. Selection may, therefore, lead to the evolution of earlier age at first reproduction in this population. We also estimate substantial heritable variation in fitness itself, with approximately 39% of the variance attributable to additive genetic effects, the remainder consisting of unique environmental effects and small effects from education and religion. We discuss mechanisms that could be maintaining such a high heritability for fitness. Most likely is that selection is now acting on different traits from which it did in pre-industrial human populations.

Age changes in personality traits and their heritabilities during the adult years: evidence from Australian Twin Registry samples

Short versions of four Eysenck personality scales had been included in questionnaires given to several adult samples from the Australian Twin Registry, comprising altogether some 5400 pairs. Means and regressions with age are compared for three samples at average ages of 23, 37, and 61 years, and for two samples of retested individuals, one tested twice at average ages of 29 and 37 years, and one tested three times at average ages of 45, 56, and 62 years, For both males and females the trends for Psychoticism (P), Extraversion (E), and Neuroticism (N) were generally downward with age, and for Lie (L), upward. However, in the longitudinal sample between ages 56 and 62 the trends for P, E, and I stopped or reversed, although N continued downward. Heritabilities were reasonably stable across age for P, E, and N, and the effects of shared environments negligible, but L showed some influence of shared environment as well as genes in all but the oldest age group. (C) 2001 Elsevier Science Ltd. All rights reserved.

Host preference and host suitability in an egg-pupal fruit fly parasitoid, Fopius arisanus (Sonan) (Hym., Braconidae)

The relative oviposition rate of the parasitoid Fopius arisanus (Sonan) was investigated across three frugivorous tephritid species, Bactrocera tryoni Froggart, Bactrocera jarvisi (Tryon) and Bactrocera cucumis French. Choice and no-choice tests were both used. The suitability of these three species for sustaining larval development and survival to the adult stage was also assessed. Fopius arisanus parasitized all three tephritid species. regardless of the method of exposure, but showed stronger preference for B. tryoni and B. jarvisi over B. cucumis. Superparasitism was extremely rare. Successful development of F. arisanus varied across host species. Bactrocera tryoni yielded significantly more parasitoids than B. jarvisi, but no wasps emerged from B. cucumis puparia. Tests were set up in replicated trials. but results were not homogeneous across trials. We discuss the host relationships of F. arisanus with reference to this variation and in relation to host suitability for larval development.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

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.

Quantifying stresses and support requirements in the undercut and production level drifts of block and panel caving mines

A numerical modelling strategy has been developed in order to quantify the magnitude of induced stresses at the boundaries of production level and undercut level drifts for various in situ stress environments and undercut scenarios. The results of the stress modelling were in line with qualitative experiential guidelines and a limited number of induced stress measurements documented from caving sites. A number of stress charts were developed which quantify the maximum boundary stresses in drift roofs for varying in situ stress regimes, depths and undercut scenarios. This enabled many of the experiential guidelines to be quantified and bounded. A limited number of case histories of support and support performance in cave mine drifts were compared to support recommendations using the NGI classification system, The stress charts were used to estimate the Stress Reduction Factor for this system. The back-analyses suggested that the NGI classification system might be able to give preliminary estimates of support requirements in caving mines with modifications relating to rock bolt length and the support of production level intersections. (C) 2002 Elsevier Science Ltd. All rights reserved.