Effect of carrier size on the dispersion of salmeterol xinafoate from interactive mixtures

The objective of this study was to determine the influence of lactose carrier size on drug dispersion of salmeterol xinafoate (SX) from interactive mixtures. SX dispersion was measured by using the fine particle fractions determined by a twin stage impinger attached to a Rotahaler1. The particle size of the lactose carrier in the SX interactive mixtures was varied using a range of commercial inhalation-grade lactoses. In addition, differing size fractions of individual lactose samples were achieved by dry sieving. The dispersion ofSXappeared to increase as the particle size of the lactose carrier decreased for the mixtures prepared from different particle size commercial samples of lactose and from different sieve fractions of the same lactose. Fine particles of lactose (<5 mm) associated with the lactose carrier were removed from the carrier surface by a wet decantation process to produce lactose samples with low but similar concentrations of fine lactose particles. The fine particle fractions of SX in mixtures prepared with the decanted lactose decreased significantly (analysis of variance, p<0.001) and the degree of dispersion became independent of the volume mean diameter of the carriers (analysis of variance, p<0.05). The dispersion behavior is therefore associated with the presence of fine adhered particles associated with the carriers and the inherent size of the carrier itself has little influence on dispersion.

Stress-state permeability relationships for clays with coarse fraction

In standard laboratory consolidation tests, only the fraction of soil passing through a particular size of the sieve, called the matrix material, is used. This size is usually restricted to 1/10 of the height of the consolidation ring. Particles larger than this size that are removed before the test may consist of gravel, fragments of rock, or other coarse materials. Hence, it is not possible to estimate the compressibility and permeability of the total material based on the compressibility and permeability behavior obtained from laboratory consolidation tests on the matrix material. In the present investigation an attempt has been made to estimate the compressibility and permeability behavior of the total material based on the compressibility and permeability behavior of the matrix material. The results indicate that the presence of coarse particles will reduce the compressibility of the soil in proportion to the coarse fraction present in the whole soil and will not affect the permeability of the soil for the range investigated. If the coarse fraction exceeds the Limiting percentage, the void ratio-vertical effective stress path will also start to deviate from the predicted path. An expression has been developed to estimate approximately the deviating pressure, and it is found to depend on the soil type as well as the percent clay fraction.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Efficient estimation for rank-based regression with clustered data

Rank-based inference is widely used because of its robustness. This article provides optimal rank-based estimating functions in analysis of clustered data with random cluster effects. The extensive simulation studies carried out to evaluate the performance of the proposed method demonstrate that it is robust to outliers and is highly efficient given the existence of strong cluster correlations. The performance of the proposed method is satisfactory even when the correlation structure is misspecified, or when heteroscedasticity in variance is present. Finally, a real dataset is analyzed for illustration.

Load estimation with uncertainties from opportunistic sampling data: A semiparametric approach

We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Rank-based regression for analysis of repeated measures

We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then introduced to generate bootstrap replicates of the estimating functions and the parameter estimates. This provides a convenient way for combining the corresponding two types of estimating function for more efficient estimation.

Closed-form solutions for low-rank non-rigid reconstruction

Recovering the motion of a non-rigid body from a set of monocular images permits the analysis of dynamic scenes in uncontrolled environments. However, the extension of factorisation algorithms for rigid structure from motion to the low-rank non-rigid case has proved challenging. This stems from the comparatively hard problem of finding a linear “corrective transform” which recovers the projection and structure matrices from an ambiguous factorisation. We elucidate that this greater difficulty is due to the need to find multiple solutions to a non-trivial problem, casting a number of previous approaches as alleviating this issue by either a) introducing constraints on the basis, making the problems nonidentical, or b) incorporating heuristics to encourage a diverse set of solutions, making the problems inter-dependent. While it has previously been recognised that finding a single solution to this problem is sufficient to estimate cameras, we show that it is possible to bootstrap this partial solution to find the complete transform in closed-form. However, we acknowledge that our method minimises an algebraic error and is thus inherently sensitive to deviation from the low-rank model. We compare our closed-form solution for non-rigid structure with known cameras to the closed-form solution of Dai et al. [1], which we find to produce only coplanar reconstructions. We therefore make the recommendation that 3D reconstruction error always be measured relative to a trivial reconstruction such as a planar one.

Three new Lasiodiplodia spp. from the tropics, recognized based on DNA sequence comparisons and morphology

Botryosphaeria rhodina (anamorph Lasiodiplodia theobromae) is a common endophyte and opportunistic pathogen on more than 500 tree species in the tropics and subtropics. During routine disease surveys of plantations in Australia and Venezuela several isolates differing from L. theobromae were identified and subsequently characterized based upon morphology and ITS and EF1-a nucleotide sequences. These isolates grouped into three strongly supported clades related to but different from the known taxa, B. rhodina and L. gonubiensis, These have been described here as three new species L. venezuelensis sp. nov., L. crassispora sp. nov. and L. rubropurpurea sp. nov. The three could be distinguished easily from each other and the two described species of Lasiodiplodia, thus confirming phylogenetic separations. Furthermore all five Lasiodiplodia spp. now recognized separated from Diplodia spp. and Dothiorella spp. with 100% bootstrap support.

Hardness Methods for Testing Maize Kernels

Maize is a highly important crop to many countries around the world, through the sale of the maize crop to domestic processors and subsequent production of maize products and also provides a staple food to subsistance farms in undeveloped countries. In many countries, there have been long-term research efforts to develop a suitable hardness method that could assist the maize industry in improving efficiency in processing as well as possibly providing a quality specification for maize growers, which could attract a premium. This paper focuses specifically on hardness and reviews a number of methodologies as well as important biochemical aspects of maize that contribute to maize hardness used internationally. Numerous foods are produced from maize, and hardness has been described as having an impact on food quality. However, the basis of hardness and measurement of hardness are very general and would apply to any use of maize from any country. From the published literature, it would appear that one of the simpler methods used to measure hardness is a grinding step followed by a sieving step, using multiple sieve sizes. This would allow the range in hardness within a sample as well as average particle size and/or coarse/fine ratio to be calculated. Any of these parameters could easily be used as reference values for the development of near-infrared (NIR) spectroscopy calibrations. The development of precise NIR calibrations will provide an excellent tool for breeders, handlers, and processors to deliver specific cultivars in the case of growers and bulk loads in the case of handlers, thereby ensuring the most efficient use of maize by domestic and international processors. This paper also considers previous research describing the biochemical aspects of maize that have been related to maize hardness. Both starch and protein affect hardness, with most research focusing on the storage proteins (zeins). Both the content and composition of the zein fractions affect hardness. Genotypes and growing environment influence the final protein and starch content and. to a lesser extent, composition. However, hardness is a highly heritable trait and, hence, when a desirable level of hardness is finally agreed upon, the breeders will quickly be able to produce material with the hardness levels required by the industry.

Phylogenetic relationships of unclassified, satellitic Pasteurellaceae obtained from different species of birds as demonstrated by 16S rRNA gene sequence comparison

Avian haemophili demonstrating in vitro satellitic growth, also referred to as the V-factor or NAD requirement, have mainly been classified with Avibacterium paragallinarum (Haemophilus paragallinarum), Avibacterium avium (Pasteurella avium), Avibacterium volantium (Pasteurella volantium) and Avibacterium sp. A (Pasteurella species A). The aim of the present study was to assess the taxonomic position of 18 V-factor-requiring isolates of unclassified Haemophilus-like organisms isolated from galliforme, anseriforme, columbiforme and gruiforme birds as well as kestrels and psittacine birds including budgerigars by conventional phenotypic tests and 16S rRNA gene sequencing. All isolates shared phenotypical characteristics which allowed classification with Pasteurellaceae. Haemolysis of bovine red blood cells was negative. Haemin (X-factor) was not required for growth. Maximum-likelihood phylogenetic analysis including bootstrap analysis showed that six isolates were related to the avian 16S rRNA group and were classified as Avibacterium according to 16S rRNA sequence analysis. Surprisingly, the other 12 isolates were unrelated to Avibacterium. Two isolates were unrelated to any of the known 16S rRNA groups of Pasteurellaceae. Two isolates were related to Volucribacter of the avian 16S rRNA group. Seven isolates belonged to the Testudinis 16S rRNA group and out of these, two isolates were closely related to taxa 14 and 32 of Bisgaard, whereas four other isolates were found to form a genus-like group distantly related to taxon 40 and one isolated remained distantly related to other members of the Testudinis group. One isolate was closely related to taxon 26 (a member of Actinobacillus sensu stricto). The study documented major genetic diversity among V-factor-requiring avian isolates beyond the traditional interpretation that they only belong to Avibacterium, underlining the limited value of satellitic growth for identification of avian members of Pasteurellaceae. Our study also emphasized that these organisms will never be isolated without the use of special media satisfying the V-factor requirement.

Podocyte molecules in the pancreas and lymphoid tissues and their association to autoimmunity of diabetes

Type 1 diabetes is a disease where the insulin-producing beta cells of the pancreas are destroyed by an autoimmune mechanism. The incidence of type 1 diabetes, as well as the incidence of the diabetic kidney complication, diabetic nephropathy, are increasing worldwide. Nephrin is a crucial molecule for the filtration function of the kidney. It localises in the podocyte foot processes partially forming the interpodocyte final sieve of the filtration barrier, the slit diaphragm. The expression of nephrin is altered in diabetic nephropathy. Recently, nephrin was found from the beta cells of the pancreas as well, which makes this molecule interesting in the context of type 1 diabetes and especially in diabetic nephropathy. In this thesis work, the expression of other podocyte molecules in the beta cells of the pancreas, in addition to nephrin, were deciphered. It was also hypothesised that patients with type 1 diabetes may develop autoantibodies against novel beta cell molecules comparably to the formation of autoantibodies to GAD, IA-2 and insulin. The possible association of such novel autoantibodies with the pathogenesis of diabetic nephropathy was also assessed. Furthermore, expression of nephrin in lymphoid tissues has been suggested, and this issue was more thoroughly deciphered here. The expression of nephrin in the human lymphoid tissues, and a set of podocyte molecules in the human, mouse and rat pancreas at the gene and protein level were studied by polymerase chain reaction (PCR) -based methods and immunochemical methods. To detect autoantibodies to novel beta cell molecules, specific radioimmunoprecipitation assays were developed. These assays were used to screen a follow-up material of 66 patients with type 1 diabetes and a patient material of 150 diabetic patients with signs of diabetic nephropathy. Nephrin expression was detected in the lymphoid follicle germinal centres, specifically in the follicular dendritic cells. In addition to the previously reported expression of nephrin in the pancreas, expression of the podocyte molecules, densin, filtrin, FAT and alpha-actinin-4 were detected in the beta cells. Circulating antibodies to nephrin, densin and filtrin were discovered in a subset of patients with type 1 diabetes. However, no association of these autoantibodies with the pathogenesis of diabetic nephropathy was detected. In conclusion, the expression of five podocyte molecules in the beta cells of the pancreas suggests some molecular similarities between the two cell types. The novel autoantibodies against shared molecules of the kidney podocytes and the pancreatic beta cells appear to be part of the common autoimmune mechanism in patients with type 1 diabetes. No data suggested that the autoantibodies would be active participants of the kidney injury detected in diabetic nephropathy.

The impact of a streamlined funding application process on application time: Two cross-sectional surveys of Australian researchers

Objective: To examine if streamlining a medical research funding application process saved time for applicants. Design: Cross-sectional surveys before and after the streamlining. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant applications in 2012 or 2014. Main outcome measures: Average researcher time spent preparing an application and the total time for all applications in working days. Results: The average time per application increased from 34 working days before streamlining (95% CI 33 to 35) to 38 working days after streamlining (95% CI 37 to 39; mean difference 4 days, bootstrap p value <0.001). The estimated total time spent by all researchers on applications after streamlining was 614 working years, a 67-year increase from before streamlining. Conclusions: Streamlined applications were shorter but took longer to prepare on average. Researchers may be allocating a fixed amount of time to preparing funding applications based on their expected return, or may be increasing their time in response to increased competition. Many potentially productive years of researcher time are still being lost to preparing failed applications.

Biological management of the invasive Vachellia nilotica ssp. indica (Benth.) Kyal. & Boatwr. (Fabales: Mimosoideae) in tropical Australia: stress-inducing potential of Anomalococcus indicus Ramakrishna (Insecta: Hemiptera: Coccoidea: Lecanodiaspididae), an agent of promise

Vachellia nilotica ssp. indica (hereafter, V. n. indica) is an important tree weed in Australia. Its dense populations induce undesirable changes in the vast areas of northern Australia. Because chemical and mechanical management options appear unviable for various reasons, biological management of this tree is considered a better option. Among the many trialled arthropods in Australian context, Anomalococcus indicus, a lecanodiaspid native to India, has been identified as a potent-candidate, since in India, its native terrain, it is the most widespread and occurs throughout the year. Severe infestations of A. indicus cause defoliation, wilting and death of branches, and occasionally the tree. Populations of A. indicus have been brought into Australia and are being tested for its host specificity under quarantine conditions. This article reports the physiological damage and stress it inflicts in the shoots of V. n. indica. Younger-nymphal instars of A. indicus feed on cortical-parenchyma cells of young stems, whereas the older instars and adults feed from the phloem of old stems. Two conspicuous responses of V. n. indica arising in response to the feeding action of A. indicus are changes in the cell-wall dynamics and irregular cell divisions. The feeding action of A. indicus elicits a sequence of reactions in the stem tissues of V. n. indica such as differentiation of thick-walled elements in the outer cortical parenchyma, differential thickening of cells with supernumerary layers of either suberin or lignin, proliferations of parenchyma and phloem, wall thickening and obliteration of inner lumen of phloem cells, and the sieve plates plugged with callosic deposits. The responses are the culminations of interaction between the virulence factor (one or more of the salivary proteins?) from A. indicus and the resistance factor in V. n. indica. We have analysed structural changes in the context of their functions, by comparing the feeding action of A. indicus with that of other hemipteroids. From the level of stress it induces, this study confirms that A. indicus has the potential to be an effective biological management of V. n. indica in Australia. © 2014 © 2014 Taylor & Francis and Aboricultural Association.

Effect of the method of preparation and pretreatment on the texture of alumina and related catalysts

The effect of the method of preparation and pretreatment on catalyst texture was investigated in the case of alumina, silica-alumina, 10 × molecular sieve and thoria catalysts. All the catalysts were characterised with respect to their specific surface area, surface acidity, pore size distribution and pore volume. The above properties were found to reflect the textural changes that might have been undergone by the catalyst surface as a result of the method of preparation and pretreatment. The method of preparation was found to influence markedly the acidity of the surface and to a lesser extent the surface area and pore size distribution. Acid-treatment was found to increase selectively the acidity of the catalyst while heat-treatment was found to decrease proportionally the acidity as well as surface area of the catalyst.