Sampling with discrete contamination

The sampling variance for a process stream which carries fluctuating levels of the sought-after analyte and is subject to mass flow variation can be estimated from the covariance function of the analyte fluctuation and the covariance function of the mass flow when these covariance functions are well-defined and can be considered to be a stationary property of the process stream. However, in the case of sampling a flow of material (a one-dimensional lot) or from material removed from the hold of a ship (a three-dimensional lot) which does not possess a covariance function for the analyte of interest, a different approach must be taken. An important example of such a case is a shipment of grain that is contaminated by some component such as genetically modified organisms (GMOs) or by mycotoxins. Depending on the manner of contamination, the regions of the lot that carry contamination can be considered as randomly located distributions of concentration. The distributions themselves may be stochastic in that their mean concentrations and extents may be statistically defined rather than fixed. This paper develops the sampling variance for ‘slugs’ of contamination with a uniform concentration distribution and regular spacing of the sample increments, based on the assumption that the origins of the slugs are uniformly and randomly located (a Poisson point process)

Use of OC curves in quality control with an example of sampling for mycotoxins

An ‘operating characteristics’ (OC) curve is a simple tool that has been in use in quality control for many years but does not seem to be widely applied in the particulate sampling field. The OC curve provides the probability that a lot of material will be deemed to meet a specification (will be found to have an assay that falls above (or below) a specified level, given the true assay of the lot). In the application considered herein, it provides the probability that a grain shipment will be accepted, given the true value of the assay for the lot. It directly measures the probability of a type II error. To construct the OC curve for a given sampling protocol, it is necessary to know all the relevant components of variance and their distribution, as a function of the level of contamination in the shipment. This may be quite a challenge in many circumstances as the assumption of normality of distributions may be poor when dealing with substances such as mycotoxins. The paper introduces the method of OC curve construction and reviews the method developed by Whitaker for the construction of OC curves for mycotoxins in a wide range of commodities. It is shown that his method excludes a potentially critical component of uncertainty. Further, the discussion concludes that the estimation of the distribution of the missing component of uncertainty is potentially prohibitively expensive and logistically very difficult. The final conclusion is that more intensive sampling methods should be employed for mycotoxins

Modelling multi-scale microstructures with combined Boolean random sets: A practical contribution

Boolean random sets are versatile tools to match morphological and topological properties of real structures of materials and particulate systems. Moreover, they can be combined in any number of ways to produce an even wider range of structures that cover a range of scales of microstructures through intersection and union. Based on well-established theory of Boolean random sets, this work provides scientists and engineers with simple and readily applicable results for matching combinations of Boolean random sets to observed microstructures. Once calibrated, such models yield straightforward three-dimensional simulation of materials, a powerful aid for investigating microstructure property relationships. Application of the proposed results to a real case situation yield convincing realisations of the observed microstructure in two and three dimensions

Sampling, corporate governance and risk analysis

As the prices of metals slide, financial control of mineral processing operations becomes more and more important. Control of a mineral processing operation implies measurement of grades, recoveries and losses, with every effort being made to recover more product from the same feed. Shareholders become more concerned with the transparency of the operations and the corporate governance. There is only one way to achieve this and this is by sampling and making good use of the results of that sampling. Sampling systems that provide only 'rough' figures are not good enough. Similarly, a competitive position in the marketplace demands close control of product quality. Maximisation of product output demands that the product just meet the specification so that product yield is maximised. Decisions based on accurate and precise sampling results carry less risk that those based on imprecise and biased results. This paper reports some recent advances in sampling theory that permit full quantification of sampling distributions, not just the sampling variance as has been possible in the past. These advances can be used together with simulation methods to tie down sampling precisions and develop calculations that quantify decision making risk when using the sampling results. A number of examples illustrate the use of the new advances and a final example indicates the development of risk analysis curves in the coupling of sampling precision to sale of a commodit

Getting high added-value from sampling

Determination of the complete sampling distribution (Lyman, 2014), as opposed to estimation of the sampling variance, represents a significant advance in sampling theory. This is one link that has been missing for sampling results to be used to their full potential. In particular, access to the complete sampling distribution provides opportunities to bring all the concepts and risk assessment tools from statistical process control (SPC) into the production and trading of mineral commodities, giving sampling investments and results their full added-value. The paper focuses on the way by which sampling theory, via the complete sampling distribution, interfaces with production and statistical process control theory and practice. The paper evaluates specifically the effect of using the full sampling distribution on the Operating Characteristic curve and control charts’ Run Length distributions, two SPC cornerstones that are essential for quality assurance and quality control analysis and decision-making. It is shown that departure from normality of the sampling distribution has a strong effect on SPC analyses. Analysis of the Operating Characteristic curve for example shows that assumption of normality may lead to erroneous risk assessment of the conformity of commercial lots. It is concluded that the actual sampling distribution should be used for quality control and quality assurance in order to derive the highest value from sampling

Estimation of the sampling constants for grains contaminated by mycotoxins and the impact on sampling precision

Grains are subject to contamination by mycotoxins which are metabolic by-products of various fungi. The fungal infestations produce local concentrations of the mycotoxins thousands of times higher than the average. These facts make the sampling of the grain for assessment of the mean mycotoxin levels potentially very difficult. In the context of sampling theory, this morphology of the infestations creates a very high distributional and intrinsic heterogeneity of the grain shipment. The distributions of mycotoxin concentrations in seaborne shipments that exist at loading and the number and intensity of infestations that develop under shipping conditions are unknown. All grain shipments carry spores that may give rise to mycotoxin-producing colonies; moisture and temperature determine the final extent of the problem. This paper develops the value of the sampling constant with respect to intrinsic heterogeneity based on data on observed Ochratoxin A (OTA) concentrations in individual wheat kernels. A useful relationship between the distribution of mycotoxin concentrations on a kernel to kernel basis and the distribution of concentration over subsamples is developed

Phosphorylation of the HCN channel auxiliary subunit TRIP8b is altered in an animal model of temporal lobe epilepsy and modulates channel function

Temporal lobe epilepsy (TLE) is a prevalent neurological disorder with many patients experiencing poor seizure control with existing anti-epileptic drugs. Thus, novel insights into the mechanisms of epileptogenesis and identification of new drug targets can be transformative. Changes in ion channel function have been shown to play a role in generating the aberrant neuronal activity observed in TLE. Previous work demonstrates that hyperpolarization-activated cyclic nucleotide-gated (HCN) channels regulate neuronal excitability and are mislocalized within CA1 pyramidal cells in a rodent model of TLE. The subcellular distribution of HCN channels is regulated by an auxiliary subunit, tetratricopeptide repeat-containing Rab8b-interacting protein (TRIP8b), and disruption of this interaction correlates with channel mislocalization. However, the molecular mechanisms responsible for HCN channel dysregulation in TLE are unclear. Here we investigated whether changes in TRIP8b phosphorylation are sufficient to alter HCN channel function. We identified a phosphorylation site at residue Ser237 of TRIP8b that enhances binding to HCN channels and influences channel gating by altering the affinity of TRIP8b for the HCN cytoplasmic domain. Using a phosphospecific antibody, we demonstrate that TRIP8b phosphorylated at Ser237 is enriched in CA1 distal dendrites and that phosphorylation is reduced in the kainic acid model of TLE. Overall, our findings indicate that the TRIP8b-HCN interaction can be modulated by changes in phosphorylation and suggest that loss of TRIP8b phosphorylation may affect HCN channel properties during epileptogenesis. These results highlight the potential of drugs targeting posttranslational modifications to restore TRIP8b phosphorylation to reduce excitability in TLE

Evaluation of Cage Designs and Feeding Regimes for Honey Bee (Hymenoptera: Apidae) Laboratory Experiments

The aim of this study was to improve cage systems for maintaining adult honey bee (Apis mellifera L.) workers under in vitro laboratory conditions. To achieve this goal, we experimentally evaluated the impact of different cages, developed by scientists of the international research network COLOSS (Prevention of honey bee COlony LOSSes), on the physiology and survival of honey bees. We identified three cages that promoted good survival of honey bees. The bees from cages that exhibited greater survival had relatively lower titers of deformed wing virus, suggesting that deformed wing virus is a significant marker reflecting stress level and health status of the host. We also determined that a leak- and drip-proof feeder was an integral part of a cage system and a feeder modified from a 20-ml plastic syringe displayed the best result in providing steady food supply to bees. Finally, we also demonstrated that the addition of protein to the bees' diet could significantly increase the level of vitellogenin gene expression and improve bees' survival. This international collaborative study represents a critical step toward improvement of cage designs and feeding regimes for honey bee laboratory experiment

Selective Expression of Flt3 within the Mouse Hematopoietic Stem Cell Compartment

The fms-like tyrosine kinase 3 (Flt3) is a cell surface receptor that is expressed by various hematopoietic progenitor cells (HPC) and Flt3-activating mutations are commonly present in acute myeloid and lymphoid leukemias. These findings underscore the importance of Flt3 to steady-state and malignant hematopoiesis. In this study, the expression of Flt3 protein and Flt3 mRNA by single cells within the hematopoietic stem cell (HSC) and HPC bone marrow compartments of C57/BL6 mice was investigated using flow cytometry and the quantitative reverse transcription polymerase chain reaction. Flt3 was heterogeneously expressed by almost all of the populations studied, including long-term reconstituting HSC and short-term reconstituting HSC. The erythropoietin receptor (EpoR) and macrophage colony-stimulating factor receptor (M-CSFR) were also found to be heterogeneously expressed within the multipotent cell compartments. Co-expression of the mRNAs encoding Flt3 and EpoR rarely occurred within these compartments. Expression of both Flt3 and M-CSFR protein at the surface of single cells was more commonly observed. These results emphasize the heterogeneous nature of HSC and HPC and the new sub-populations identified are important to understanding the origin and heterogeneity of the acute myeloid leukemias

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them