Pathogenicity and virulence

Invertebrate pathologists have multiple definitions for the terms pathogenicity and virulence, and these definitions vary across disciplines that focus on host-pathogen interactions. We surveyed various literatures, including plant pathology, invertebrate pathology, evolutionary biology, and medicine, and found most define pathogenicity as the broader term, which incorporates virulence. Virulence is seen as the severity of disease manifestation that can only be measured in infected individuals. These definitions readily apply to both lethal and non-lethal diseases. Invertebrate pathologists commonly use dose-response bioassays to estimate LD(50) or LC(50) (dose or concentration needed to kill 50% of hosts exposed). These bioassays measure pathogenicity if the bioassay includes a transmission component, and measure virulence if the bioassay is measured in infected individuals only. Another common bioassay estimate is LT(50) (median time to death of infected hosts), which is a measure of virulence as long as survivors are not included in its calculation.     

对“小鼠腹腔巨噬细胞吞噬作用的观察实验”的拓展探索

以"小鼠腹腔巨噬细胞吞噬作用的观察实验"为例,从发现疑问、确定拓展方向、设计拓展方案等方面拓展传统验证性实验项目,使其一般验证性实验具有了综合性和设计性的作用,让学生体会到在小实验中发现大问题的乐趣,进一步激发学生参与实验的积极性。     

Proposed minimum reporting standards for chemical analysis

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at or . Further, community input related to this document can also be provided via this electronic forum. The contents of this paper do not necessarily reflect any position of the Government or the opinion of the Food and Drug Administration Sponsor: Metabolomics Society http://www.metabolomicssociety.org/ Reference: http://msi-workgroups.sourceforge.net/bio-metadata/reporting/pbc/ http://msi-workgroups.sourceforge.net/chemical-analysis/ Version: Revision: 5.1 Date: 09 January, 2007     

Dynamic modeling of Listeria monocytogenes growth in pasteurized milk

AIMS: The development and validation of a dynamic model for predicting Listeria monocytogenes growth in pasteurized milk stored at both static and dynamic temperature conditions. METHODS AND RESULTS: Growth of inoculated L. monocytogenes in a commercial pasteurized whole milk product was monitored at various isothermal conditions from 1.5 to 16 degrees C. The kinetic parameters of the pathogen were modelled as a function of temperature using a square root type model, which was further validated using data from 92 published growth curves from eight different milk products. Compared to four published models for L. monocytogenes growth, the model developed in this study performed better, with a per cent discrepancy and bias of 49.1 and -1.01%, respectively. The performance of the model in predicting growth at dynamic temperature conditions was evaluated at four different fluctuating temperature scenarios with periodic temperature changes from -2 to 16 degrees C. The prediction of growth at dynamic storage temperature was based on the square root model in conjunction with the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. The per cent relative errors between the observed and the predicted growth of L. monocytogenes were less than 10% for all temperature scenarios tested. CONCLUSIONS: Available models from experiments conducted in laboratory media may result in significant overestimation of L. monocytogenes growth in pasteurized milk because they do not take into account factors such as milk composition (e.g. natural antimicrobial compounds present in milk) and the interactions of the pathogen with the natural microflora. The product-targeted model developed in the present study showed a high performance in predicting growth of L. monocytogenes in pasteurized milk under both static and dynamic temperature conditions. SIGNIFICANCE AND IMPACT OF THE STUDY: Temperature fluctuations often occur during the transportation and storage of pasteurized milk. A high performance, dynamic model for the growth of L. monocytogenes can be a useful tool for effective management and optimization of product safety and can lead to more realistic estimations of pasteurized-milk related safety risks.     

Modeling analysis on sporulation capacity,storage and infectivity of the aphid-specific pathogen Conidiobolus obscurus (Entomophthoromycota: Entomophthorales)

Entomophthorales are important natural enemies against agroforestry pests. Conidiobolus obscurus in this order, a common obligate aphid pathogen, possesses features of rapid growth in vitro and ease to mass production. This study sought to evaluate the potential of C. obscurus in aphid biocontrol, by modeling analyzing on the sporulation capacity and storage of its alginate formulation and infectivity to Myzus persicae. The C. obscurus mycelia-entrapping alginate pellets discharges 0.12–18.26 × 10⁴ conidia per pellet at 4−32 °C. The optimal temperature for the fungal sporulation was computed as 23.3 °C. Each pellet could sporulated for 7 d, releasing 22.3-fold more conidia than a cadaver at 24 °C. Moreover, it had longevity of 8 mo at 4 °C, with half decline time of 2.3 mo. The infectivity of C. obscurus was assessed by multi-concentration bioassays at 10−28 °C and 8−16 h light per d. The median lethal concentration (LC₅₀) at each temperature-photoperiod regime was computed based on the morality-concentration trend. The LC₅₀ values reached the lowest one of 15 conidia per mm² at 28 °C and 16:8 L:D cycles. The total results suggest that C. obscurus mycelia-inclusive alginate pellets meet the requirement of aphid biocontrol in the high-temperature surroundings of 24–28 °C.     

Validation of Fecal Glucocorticoid Metabolite Assays for South African Herbivores

ABSTRACT Fecal glucocorticoid metabolite (FGM) assays are a popular means of monitoring adrenocortical activity (i.e., physiological stress response) in wildlife. Species-specific differences in glucocorticoid metabolism and excretion require assay validation, including both laboratory and biological components, before assay use in new species. We validated a commercially available radioimmunoassay (MP ¹²⁵I corticosterone RIA kit [MP Biomedicals, Solon, OH]) for measuring FGMs of several South African herbivores, including giraffe (Giraffa camelopardalis), impala (Aepyceros melampus), nyala (Tragelaphus buxtoni), kudu (Tragelaphus strepsiceros), wildebeest (Connochaetes taurinus), and zebra (Equus burchelli). These herbivores are important in South African parks and reserves for ecotourism and as a prey base for predators and serve an integral role in ecosystem processes. Standard biochemical validations (e.g., recovery of exogenous corticosterone, intra- and interassay variation, and parallelism) demonstrated that the assay accurately and precisely measured FGMs of all 6 herbivore species. Our biological validations demonstrated that the assay was sensitive enough to detect changes in FGM production associated with season. Samples collected during the dry season (Jun-Aug) contained higher FGM concentrations than those from the wet season (Dec-Feb) in all species. We established optimal sample dilutions and reference FGM levels for these 6 herbivores, which can now be used to monitor the effects of management and ecotourism activities on the stress responses of these herbivores.     

Neurogenomics of speech and language disorders: the road ahead

Next-generation sequencing is set to transform the discovery of genes underlying neurodevelopmental disorders, and so offer important insights into the biological bases of spoken language. Success will depend on functional assessments in neuronal cell lines, animal models and humans themselves.     

Prediction of herbage yield in grassland: How well do Ellenberg N‐values perform?

Question: How useful are Ellenberg N‐values for predicting the herbage yield of Central European grasslands in comparison to approaches based on ordination scores of plant species composition or on soil parameters? Location: Central Germany (11°00′‐11°37’E, 50°21‐50°34’N, 500–840 m a.s.l.). Methods: Based on data from a field survey in 2001, the following models were constructed for predicting herbage yield in montane Central European grasslands: (1) Linear regression of mean Ellenberg N‐, R‐ and F‐values; (2) Linear regression of ordination scores derived from Non‐metric Multidimensional Scaling (NMDS) of vegetation data; and (3) Multiple linear regression (MLR) of soil variables. Models were evaluated by cross‐validation and validation with additional data collected in 2002. Results: Best predictions were obtained with models based on species composition. Ellenberg N‐values and NMDS scores performed equally well and better than models based on Ellenberg R‐ or F‐values. Predictions based on soil variables were least accurate. When tested with data from 2002, models based on Ellenberg N‐values or on NMDS scores accurately predicted productivity rank order of sites, but not the actual herbage yield of particular sites. Conclusions: Mean Ellenberg N‐values, which are easy to calculate, are as accurate as ordination scores in predicting herbage yield from plant species composition. In contrast, models based on soil variables may be useful for generating hypotheses about the factors limiting herbage yield, but not for prediction. We support the view that Ellenberg N‐values should be called productivity values rather than nitrogen values.     

Influence of non-bonded parameters on the quality of NMR structures: A new force field for NMR structure calculation

The effects of different non-bonded parameters of force fields for NMR structure calculation on the quality of the resulting NMR solution structures were investigated using Interleukin 4 as a model system. NMR structure ensembles were calculated with an ab initio protocol using torsion angle dynamics. The calculations were repeated with five different non-bonded energy functions and parameters. The resulting ensembles were compared with the available X-ray structures, and their quality was assessed with common structure validation programs. In addition, the impact of torsion angle restraints and dihedral energy terms for the sidechains and the backbone was studied. The further improvement of the quality by refinement in explicit solvent was demonstrated. The optimal parameters, including those necessary for water refinement, are available in the new version of the PARALLHDG force field.     

Preliminary validation of an activation assay for ex vivo activated T cells utilized in cancer immunotherapy

An in vitro assay that measures the activation level of ex vivo activated (EVA) T cells currently being used in the adoptive immunotherapy of metastatic renal cell carcinoma has been developed. This assay is based on the ability of activated, but not resting. T cells to proliferate in response to the protein kinase C activator, phorbol myristate (PMA). To utilize this assay for in-process monitoring and control, we have begun an initial validation of the overall reproducibility of this assay. The proliferation of activated T cells in response to PMA, as measured by the mean cpm values of (3)H-thymidine incorporated, was demonstrated to have intra-assay coefficients of variation (cv's) for individual analysts that were typically less than 10% and rarely exceeded 20%. Activated T cells could be frozen and stored for at least 6 weeks with little or no deterioration in their ability to proliferate in response to PMA. Using these cells, inter-assay cv's that were typically less than 15% were obtained by individual analysts, and overall cv's of 10% to 25% were obtained for different samples assayed by different analysts at different times. This level of variability is very reasonable for a cellular assay. Furhter validation of this assay will address the issues of sensitivity, linearity and selectivity. To date, this assay has been used to analyze over 90 patient EVA cell samples and has revealed a broad range of proliferative responses to PMA. Taken together, these results suggest that this assay may be useful in defining the potency of the activated T cell used therapeutically.