Developmental Pathways in Microcerotermes turneri (Termitidae: Termitinae): Biometric Descriptors of Worker Caste and Instar

The foraging process of location and exploitation of food in complex termite societies is in part reliant upon unequal division of specific tasks amongst its members (polyethism). To conduct studies assessing the role of individuals in foraging activities it is necessary to have descriptors of worker caste and instar. Here we provide biometric descriptors of specific caste and instar for worker caste and instars of Microcerotermes turneri (Froggatt) (Termitidae: Termitinae) for the worker castes (male and female) for the identification of individuals in laboratory assays applicable across multiple nests. The use of head width for determining sex of workers was successful across multiple nests. The length of the first three flagellum segments of the antenna and tibia three could be used to determine worker instar.

Classifying client goals in community-based ABI rehabilitation: a taxonomy for profiling service delivery and conceptualizing outcomes

Purpose: To develop, confirm and trial a framework for analysing the content of goals set within community-based rehabilitation. This framework (taxonomy) is proposed as a tool to assist in service evaluation and outcome exploration. Method: Qualitative thematic analysis and categorization of 1765 rehabilitation goal statements in a four phase process of synthesis, refinement, verification and application. Results: A taxonomy of goal content was developed comprising 21 categories within five domains, utilizing 125 descriptors. The taxonomy demonstrated good inter-rater consistency and was able to discriminate between similar but related data sets comprising goal statements. Conclusion: Structured analysis of the content of goal setting (particularly in community rehabilitation) utilizing a framework such as the proposed taxonomy has considerable potential as a 'window' into service delivery to broaden the parameters of existing service evaluation and to more clearly link outcome exploration to intervention.

What is the best size descriptor to use for pharmacokinetic studies in the obese?

The prevalence of obesity in the western world is dramatically rising, with many of these individuals requiring therapeutic intervention for a variety of disease states. Despite the growing prevalence of obesity there is a paucity of information describing how doses should be adjusted, or indeed whether they need to be adjusted, in the clinical setting. This review is aimed at identifying which descriptors of body size provide the most information about the relationship between dose and concentration in the obese. The size descriptors, weight, lean body weight, ideal body weight, body surface area, body mass index, fat-free mass, percent ideal body weight, adjusted body weight and predicted normal body weight were considered as potential size descriptors. We conducted an extensive review of the literature to identify studies that have assessed the quantitative relationship between the parameters clearance (CL) and volume of distribution (V) and these descriptors of body size. Surprisingly few studies have addressed the relationship between obesity and CL or V in a quantitative manner. Despite the lack of studies there were consistent findings: (i) most studies found total body weight to be the best descriptor of V. A further analysis of the studies that have addressed V found that total body weight or another descriptor that incorporated fat mass was the preferred descriptor for drugs that have high lipophilicity; (ii) in contrast, CL was best described by lean body mass and no apparent relationship between lipophilicity or clearance mechanism and preference for body size descriptor was found. In conclusion, no single descriptor described the influence of body size on both CL and V equally well. For drugs that are dosed chronically, and therefore CL is of primary concern, dosing for obese patients should not be based on their total weight. If a weight-based dose individualization is required then we would suggest that chronic drug dosing in the obese subject should be based on lean body weight, at least until a more robust size descriptor becomes available.

Seasonal variations of phenolic compounds in Australia-grown tea (Camellia sinensis)

Seasonal variations of phenolic compounds in fresh tea shoots grown in Australia were studied using an HPLC method. Three principal tea flavanols [epigallocatechin gallate (EGCG), epicatechin gallate (ECG), and epigallocatechin (EGC)] and four grouped phenolics [total catechins (Cs), total catechin gallates (CGs), total flavanols (Fla), and total polyphenols (PPs)] in fresh tea shoots were analyzed and compared during the commercial harvest seasons from April 2000 to May 2001. The levels of EGCG, ECG, and CGs in the fresh tea shoots were higher in the warm months of April 2000 (120.52, 34.50, and 163.75 mg/g, respectively) and May 2000 (128.63, 44.26, and 183.83 mg/g, respectively) and lower during the cool months of July 2000 (91.39, 35.16, and 132.30 mg/g, respectively), August 2000 (91.31, 31.56, and 128.64 mg/g, respectively), and September 2000 (96.12, 33.51, and 136.90 mg/g, respectively). Thereafter, the levels increased throughout the warmer months from October to December 2000 and remained high until May 2001. In the warmer months, the levels of EGCG, ECG, and CGs were in most cases significantly higher (P < 0.05) than those in the samples harvested in the cooler months. In contrast, the levels of EGC and Cs were high and consistent in the cooler months and low in the warmer months. The seasonal variations of the individual and grouped catechins were significant (P < 0.05) between the cooler and warmer months. This study revealed that EGCG and ECG could be used as quality descriptors for monitoring the seasonal variations of phenolics in Australia-grown tea leaves, and the ratio (EGCG + ECG)/EGC has been suggested as a quality index for measuring the differences in flavanol levels in fresh tea shoots across the growing seasons. Mechanisms that induce seasonal variations in tea shoots may include one or all three of the following environmental conditions: day length, sunlight, and/or temperature, which vary markedly across seasons. Therefore, further studies under controlled conditions such as in a greenhouse may be required to direct correlate flavonoid profiles of green tea leaves with their yields and also to with conditions such as rainfall and humidity.

CandiVF - Candida albicans virulence factor database

Candida albicans is a pathogen commonly infecting patients who receive immunosuppressive drug therapy, long-term catheterization, or those who suffer from acquired immune deficiency syndrome (AIDS). The major factor accountable for pathogenicity of C. albicans is host immune status. Various virulence molecules, or factors, of are also responsible for the disease progression. Virulence proteins are published in public databases but they normally lack detailed functional annotations. We have developed CandiVF, a specialized database of C. albicans virulence factors (http://antigen.i2r.a-star.edu.sg/Templar/DB/CandiVF/) to facilitate efficient extraction and analysis of data aimed to assist research on immune responses, pathogenesis, prevention, and control of candidiasis. CandiVF contains a large number of annotated virulence proteins, including secretory, cell wall-associated, membrane, cytoplasmic, and nuclear proteins. This database has in-built bioinformatics tools including keyword and BLAST search, visualization of 3D-structures, HLA-DR epitope prediction, virulence descriptors, and virulence factors ontology.

Topological side-chain classification of beta-turns: Ideal motifs for peptidomimetic development

beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi 2, psi 2, phi 3 and psi 3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C-alpha-C-beta vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C-alpha-C-beta vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

Artificial neural network modeling of phytoestrogen binding to estrogen receptors

Differential pathophysiological roles of estrogen receptors alpha (ERα) and beta (ERβ) are of particular interest for phytochemical screening. A QSAR incorporating theoretical descriptors was developed in the present study utilizing sequential multiple-output artificial neural networks. Significant steric, constitutional, topological and electronic descriptors were identified enabling ER affinity differentiation.

Benthic metabolism as an indicator of stream ecosystem health

We tested direct and indirect measures of benthic metabolism as indicators of stream ecosystem health across a known agricultural land-use disturbance gradient in southeast Queensland, Australia. Gross primary production (GPP) and respiration (R-24) in benthic chambers in cobble and sediment habitats, algal biomass (as chlorophyll a) from cobbles and sediment cores, algal biomass accrual on artificial substrates and stable carbon isotope ratios of aquatic plants and benthic sediments were measured at 53 stream sites, ranging from undisturbed subtropical rainforest to catchments where improved pasture and intensive cropping are major land-uses. Rates of benthic GPP and R-24 varied by more than two orders of magnitude across the study gradient. Generalised linear regression modelling explained 80% or more of the variation in these two indicators when sediment and cobble substrate dominated sites were considered separately, and both catchment and reach scale descriptors of the disturbance gradient were important in explaining this variation. Model fits were poor for net daily benthic metabolism (NDM) and production to respiration ratio (P/R). Algal biomass accrual on artificial substrate and stable carbon isotope ratios of aquatic plants and benthic sediment were the best of the indirect indicators, with regression model R-2 values of 50% or greater. Model fits were poor for algal biomass on natural substrates for cobble sites and all sites. None of these indirect measures of benthic metabolism was a good surrogate for measured GPP. Direct measures of benthic metabolism, GPP and R-24, and several indirect measures were good indicators of stream ecosystem health and are recommended in assessing process-related responses to riparian and catchment land use change and the success of ecosystem rehabilitation actions.

Utility of signs and symptoms of chronic cough in predicting specific cause in children

Background: Paediatricians rely on cough descriptors to direct them to the level of investigations needed for a child presenting with chronic cough, yet there is a lack of published data to support this approach. A study was undertaken to evaluate ( 1) whether historical cough pointers can predict which children have a specific cause for their cough and ( 2) the usefulness of chest radiography and spirometry as standard investigations in children with chronic cough. Methods: This was a prospective cohort study of children referred to a tertiary hospital with a cough lasting 3 weeks between June 2002 and July 2004. All included children completed a detailed history and examination using a standardised data collection sheet and followed a pathway of investigation until a diagnosis was made. Results: In 100 consecutively recruited children of median age 2.8 years, the best predictor of specific cough observed was a moist cough at the time of consultation with an odds ratio ( OR) of 9.34 (95% CI 3.49 to 25.03). Chest examination or chest radiographic abnormalities were also predictive with OR 3.60 ( 95% CI 1.31 to 9.90) and 3.16 (95% CI 1.32 to 7.62), respectively. The most significant historical pointer for predicting a specific cause of the cough was a parental history of moist cough ( sensitivity 96%, specificity 26%, positive predictive value 74%). Conclusions: The most useful clinical marker in predicting specific cough is the presence of a daily moist cough. Both chest examination and chest radiographic abnormalities are also useful in predicting whether children have a specific cause of their cough.

Measurement of strain and strain rate by echocardiography - Ready for prime time?

Strain and strain rate (SR) are measures of deformation that are basic descriptors of both the nature and the function of cardiac tissue. These properties may now be measured using either Doppler or two-dimensional ultrasound techniques. Although these measurements are feasible in routine clinical echocardiography, their acquisition and analysis nonetheless presents a number of technical challenges and complexities. Echocardiographic strain and SR imaging has been applied to the assessment of resting ventricular function, the assessment of myocardial viability using low-dose dobutamine infusion, and stress testing for ischemia. Resting function assessment has been applied in both the left and the fight ventricles, and may prove particularly valuable for identifying myocardial diseases and following up the treatment response. Although the evidence base is limited, SR imaging seems to be feasible and effective for the assessment of myocardial viability. The use of the technique for the detection of ischemia during stress echocardiography is technically challenging and likely to evolve further. The clinical availability of strain and SR measurement may offer a solution to the ongoing need for quantification of regional and global cardiac function. Nonetheless, these techniques are susceptible to artifact, and further technical development is necessary.

Blast fragmentation modelling for a green field open cut gold deposit

This paper outlines the methodology of blast fragmentation modeling undertaken for a green field feasibility study at the Riska gold deposit in Indonesia. The favoured milling process for the feasibility study was dump leaching,with no crushing of the ore material extracted from the pit. For this reason,blast fragmentation was a critical issue to be addressed by the study. A range of blast designs were considered with bench heights and blasthole diameters ranging from 4 m to 7 m and 76 mm to 102 mm respectively. Rock mass data was obtained from 19 diamond drill cores across the deposit (total drill length approximately 2200 m). Intact rock strength was estimated from qualitative strength descriptors,while the in situ block size distribution of the rock mass was estimated from the Rock Quality Designation (RQD) of the core.

A fuzzy approach to texture segmentation

The texture segmentation techniques are diversified by the existence of several approaches. In this paper, we propose fuzzy features for the segmentation of texture image. For this purpose, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window. Using these membership function values, we find a feature by weighted average method for the current pixel. This is repeated for all pixels in the window treating each time one pixel as the current pixel. Using these fuzzy based features, we derive three descriptors such as maximum, entropy, and energy for each window. To segment the texture image, the modified mountain clustering that is unsupervised and fuzzy c-means clustering have been used. The performance of the proposed features is compared with that of fractal features.