The contribution of sampling uncertainty to total measurement uncertainty in the enumeration of microorganisms in foods.

Random samples of each of several food products were obtained from defined lots during processing or from retail outlets. The foods included raw milk (sampled on farm and from a bulk-milk tanker), sprouted seeds, raw minced meat, frozen de-shelled raw prawns, neck-flaps from raw chicken carcasses and ready-to-eat sandwiches. Duplicate sub-samples, generally of 100 g, were examined for aerobic colony counts; some were examined also for counts of presumptive Enterobacteriaceae and campylobacters. After log(10)-transformation, all sets of colony count data were evaluated for conformity with the normal distribution (ND) and analysed by standard ANOVA and a robust ANOVA to determine the relative contributions of the variance between and within samples to the overall variance. Sampling variance accounted for >50% of the reproducibility variance for the majority of foods examined; in many cases it exceeded 85%. We also used an iterative procedure of re-sampling without replacement to determine the effects of sample size (i.e. the number of samples) on the precision of the estimate of variance for one of the larger data sets. The variance of the repeatability and reproducibility variances depended on the number of replicate samples tested (n) in a manner that was characteristic of the underlying distribution. The results are discussed in relation to the use of measurement uncertainty in assessing compliance of results with microbiological criteria for foods.

The effect of the number of sample units tested on the precision of microbial colony counts.

Studies on the precision of chemical methods of analysis, and the associated 'sampling uncertainty', suggest that analysis of eight replicate sample units (the sample size) is required to ensure adequate analytical precision. The primary purpose of this work was to assess whether these findings are equally applicable in microbiological examination of foods. We examined the effect of sample size on the analytical precision of microbiological data by iteratively 're-sampling without replacement' (SNR). Using both theoretical data sets and colony counts from foods we demonstrate that SNR provides an effective and efficient guide to (a) choosing the number of samples to be examined in order to optimise precision and (b) deciding whether logarithmic transformation of the raw data is appropriate. We also discuss theoretical aspects of the procedure and their impact on the results obtained.

Minimising the between-sample variance in colony counts on foods.

The objective of this study was to assess whether it is possible to minimise the variance in colony counts on replicate target samples of foods by aseptic compositing of the samples or by increasing the quantity of sample examined. The results show that compositing reduces the overall variance, and hence the standard deviation, to very low levels, although in some cases the overall variance remains relatively high, reflecting the heterogeneous distribution of microorganisms in the foods. Increasing the weight of target sample examined (e.g. from 10 g to 100g) had a pronounced effect on the mean log(10) colony count and significantly reduced the variance of the mean. The results are discussed in relation to the quantity of sample that is recommended for examination in international and other standards.

PD-1 suppresses the maintenance of cell couples between cytotoxic T cells and target tumor cells within the tumor.

The killing of tumor cells by CD8+ T cells is suppressed by the tumor microenvironment, and increased expression of inhibitory receptors, including programmed cell death protein-1 (PD-1), is associated with tumor-mediated suppression of T cells. To find cellular defects triggered by tumor exposure and associated PD-1 signaling, we established an ex vivo imaging approach to investigate the response of antigen-specific, activated effector CD8+ tumor-infiltrating lymphocytes (TILs) after interaction with target tumor cells. Although TIL-tumor cell couples readily formed, couple stability deteriorated within minutes. This was associated with impaired F-actin clearing from the center of the cellular interface, reduced Ca2+ signaling, increased TIL locomotion, and impaired tumor cell killing. The interaction of CD8+ T lymphocytes with tumor cell spheroids in vitro induced a similar phenotype, supporting a critical role of direct T cell-tumor cell contact. Diminished engagement of PD-1 within the tumor, but not acute ex vivo blockade, partially restored cell couple maintenance and killing. PD-1 thus contributes to the suppression of TIL function by inducing a state of impaired subcellular organization.

Transient protein accumulation at the center of the T cell antigen-presenting cell interface drives efficient IL-2 secretion.

Supramolecular signaling assemblies are of interest for their unique signaling properties. A µm scale signaling assembly, the central supramolecular signaling cluster (cSMAC), forms at the center of the interface of T cells activated by antigen-presenting cells. We have determined that it is composed of multiple complexes of a supramolecular volume of up to 0.5 µm3 and associated with extensive membrane undulations. To determine cSMAC function, we have systematically manipulated the localization of three adaptor proteins, LAT, SLP-76, and Grb2. cSMAC localization varied between the adaptors and was diminished upon blockade of the costimulatory receptor CD28 and deficiency of the signal amplifying kinase Itk. Reconstitution of cSMAC localization restored IL-2 secretion which is a key T cell effector function as dependent on reconstitution dynamics. Our data suggest that the cSMAC enhances early signaling by facilitating signaling interactions and attenuates signaling thereafter through sequestration of a more limited set of signaling intermediates.

Cells receive dozens of signals at different times and in different places. Integrating incoming information and deciding how to respond is no easy task. Signaling molecules on the cell surface pass messages inwards using chemical messengers that interact in complicated networks within the cell. One way to unravel the complexity of these networks is to look at specific groups of signaling molecules in test tubes to see how they interact. But the interior of a living cell is a very different environment. Molecules inside cells are tightly packed and, under certain conditions, they interact with each other by the thousands. They form structures known as 'supramolecular complexes', which changes their behavior. One such supramolecular complex is the 'central supramolecular activation cluster', or cSMAC for short. It forms under the surface of immune cells called T cells when they are getting ready to fight an infection. Under the microscope, the cSMAC looks like the bullseye of a dartboard, forming a crowd of signaling molecules at the center of the interface between the T cell and another cell. Its exact role is not clear, but evidence suggests it helps to start and stop the signals that switch T cells on. The cSMAC contains two key protein adaptors called LAT and SLP-76 that help to hold the structure together. So, to find out what the cSMAC does, Clark et al. genetically modified these adaptors to gain control over when the cSMAC forms. Clark et al. examined mouse T cells using super-resolution microscopy and electron microscopy, watching as other immune cells delivered the signal to switch on. As the T cells started to activate, the composition of the cSMAC changed. In the first two minutes after the cells started activating, the cSMAC included a large number of different components. This made T cell activation more efficient, possibly because the supramolecular complex was helping the network of signals to interact. Later, the cSMAC started to lose many of these components. Separating components may have helped to stop the activation signals. Understanding how T cells activate could lead to the possibility of turning them on or off in immune-related diseases. But these findings are not just relevant to immune cells. Other cells also use supramolecular complexes to control their signaling. Investigating how these complexes change over time could help us to understand how other cell types make decisions.

Assessment of measurement uncertainty for quantitative methods of analysis: comparative assessment of the precision (uncertainty) of bacterial colony counts.

An interlaboratory trial was made, by three analysts in each of the 19 laboratories, of three International Standards Organisation (ISO) colony count methods for aerobic organisms (ACC), Enterobacteriaceae (ECC) and Escherichia coli (EcCC). All tests were done in duplicate and were further replicated by plating both on culture media supplied by the organisers and on each laboratory's own choice of culture media. In order to avoid any influence of food matrix on the results, the inoculum for each test was a freeze-dried ampoule of a standardised mixed culture. After collation of test results, individual data sets were examined for obvious non-consistency, and colony counts for each individual test were determined both as simple and 'weighted' mean values. The derived colony counts were then log(10)-transformed and examined statistically. Estimates of repeatability and reproducibility for each set of results were derived and used to calculate the parameters for the uncertainty of measurement. Estimated values of the uncertainty of reproducibility and repeatability for the ACC ranged, respectively, from 9.3 to 12.1% and 2.0 to 3.9% of the mean log(10) colony count, depending on the specific culture media, the method of deriving the mean count and the statistical procedure employed. Similarly, estimates of the uncertainty of reproducibility and repeatability for the ECC ranged, respectively, from 14.0 to 17.4% and 4.1 to 6.7%. The estimates of uncertainty of reproducibility and repeatability for the EcCC data ranged, respectively, from 21.1 to 30.9% and 6.7 to 15.4%. Whilst the uncertainty estimates for the ACC data conform to long-held views on the repeatability and reproducibility of microbial count data, the estimates for the ECC and EcCC are considerably greater. It was notable that no benefits were seen in the use of the weighted mean as compared to simple mean colony count. The importance of uncertainty estimates of colony count data in the assessment of the microbiological quality of foods is discussed.

Application of "robust" methods to the analysis of collaborative trial data using bacterial colony counts.

We describe techniques for the application of two methods, robust to the presence of "outliers", to the hierarchical analysis of variance of bacterial count data from collaborative trials. The techniques are tested against both artificially-generated data with known distributional parameters and actual trial results containing outliers. The relative merits of the robust methods are discussed in comparison with conventional ANOVA techniques.

Human CD8 responses to a complete epitope set from preproinsulin: implications for approaches to epitope discovery.

PURPOSE: In this study, we explored the breadth of CD8 T cell reactivity to preproinsulin (PPI) in type 1 diabetes. MATERIALS AND METHODS: We tested a complete peptide set in pools covering all 406 potential 8-11mer epitopes of PPI and 61 algorithm-predicted human leukocyte antigen (HLA)-A2-specific epitopes (15 pools) from islet-specific glucose-6-phophatase catalytic subunit-related protein (IGRP), using a CD8-specific granzyme B enzyme-linked immunosorbent spot assay. RESULTS: Responses were seen to 64 of the 102 PPI pools in two or more newly diagnosed patients (63%) compared to 11 pools in the control subjects (11%, p < 0.0001, Fisher's exact test). We identified five pools containing 20 peptides, which distinguished patients from control subjects, most of which had predicted low-affinity binding to HLA class I molecules. In contrast, fewer (5 of 15 = 33%) IGRP peptide pools, selected by higher binding affinity for HLA-A2 (present in seven of eight patients and five of seven control subjects), stimulated responses in two or more patients, and none stimulated responses in more than two control subjects (p = 0.042, Fisher's exact test). CONCLUSION: Thus, we conclude that CD8 T cell reactivity to PPI in patients with type 1 diabetes can be much broader than shown previously and more diverse than seen in control subjects. Furthermore, responses were often stimulated by peptides with low predicted HLA-binding affinities.

A critical review of measurement uncertainty in the enumeration of food micro-organisms.

Derivation of uncertainty provides a way to standardize the expression of variability associated with any analytical procedure. The published information on uncertainty associated with data obtained using microbiological procedures is reviewed to highlight the causes and magnitude of such variability in food microbiology. We also suggest statistical procedures that can be used to assess variability (and hence, uncertainty), within and between laboratories, including procedures that can be used routinely by microbiologists examining foods, and the use of 'robust' methods which allow the retention of 'outlying' data. Although concerned primarily with variability associated with colony count procedures, we discuss also the causes of variability in presence/absence and indirect methods, such as limiting dilution, most probable number and modern instrumental methods of microbiological examination. Recommendations are also made concerning the most important precautions to be taken in order to minimize uncertainty in microbiology. These include strict internal controls at all stages of microbiological testing, as well as validation of methods, trend analysis, use of reference materials and participation in proficiency testing schemes. It is emphasized that the distribution of microbes in foods is inherently heterogeneous, and that this review only addresses uncertainty of measurement with respect to the sample taken, not the lot or consignment of food from which the sample was taken.

Measurement uncertainty of the EU methods for microbiological examination of red meat.

Three parallel trials were made of EU methods proposed for the microbiological examination of red meat using two analysts in each of seven laboratories within the UK. The methods involved determination of aerobic colony count (ACC) and Enterobacteriaceae colony count (ECC) using simulated methods and a freeze-dried standardised culture preparation. Trial A was based on a simulated swab test, Trial B a simulated meat excision test and Trial C was a reference test on reconstituted inoculum. Statistical analysis (ANOVA) was carried out before and after rejection of outlying data. Expanded uncertainty values (relative standard deviation x2) for repeatability and reproducibility, based on the log10 cfu/ml, on the ACC ranged from +/-2.1% to +/-2.7% and from +/-5.5% to +/-10.5%, respectively, depending upon the test procedure. Similarly for the ECC, expanded uncertainty estimates for repeatability and reproducibility ranged from +/-4.6% to +/-16.9% and from +/-21.6% to +/-23.5%, respectively. The results are discussed in relation to the potential application of the methods.