Accreditation and Quality Assurance最新文献

In this study, two different concentrations of matrix certified reference materials (CRMs) were produced for the accurate measurement of aflatoxin M1(AFM1) in milk powder (GBW(E) 100552, GBW(E) 100553). The raw material was obtained by feeding cows with positive drugs. The homogeneity, stability and characterization of these matrix CRMs were examined by liquid chromatography tandem mass spectrometry with isotope-labeled internal standard method. The certified value for the low concentration of AFM1 in milk powder was 2.45 µg/kg with an expanded uncertainty of 0.43 µg/kg (coverage factor k = 2, at 95% confidence). The certified value for the high concentration of AFM1 in milk powder was 3.45 µg/kg with an expanded uncertainty of 0.49 µg/kg (coverage factor k = 2, at 95% confidence). In addition, the samples were evaluated in detail for homogeneity, long-term stability at − 80 °C for 6 months and short-term stability at 4 °C for 7 days. The results showed that the samples were stable and homogeneous under the above conditions.

Graphical abstract

It is now widely accepted that the measurement process usually begins when the primary sample is taken. The uncertainty of measurement (MU) must therefore include contributions that arise from the primary sampling, and also from any physical preparation of the sample which often occurs before the sample reaches the laboratory. Guidance on how to estimate MU that includes that arising from sampling (UfS) has been widely applied to a wide range of application sectors (e.g. food, feed, water, sediment, soil, gases). Recent revision of ISO/IEC 17025:2017 (https://www.iso.org/standard/66912.html) has also recognised the inclusion of sampling within the measurement process. This recognition has implications for the validation of measurement procedures that include sampling (VaMPIS). The scope of method (or procedure) validation has therefore to be expanded and reassessed, in order to include all of these components. The uncertainty of the measurement value (MU) is a key parameter that encompasses the effects of all the other operating characteristics of the analytical procedure that is traditionally considered during its validation. It has the further advantage that it can also incorporate the uncertainty due to sampling and physical sample preparation, thus providing a single value of uncertainty that derives from the entire measurement procedure. The fitness for purpose (FnFP) of the whole measurement procedure, which is required for validation, can be judged by comparing the estimated MU (including UfS), against a Target MU, however that is set. A case study for the determination of nitrate in glasshouse lettuce shows how this VaMPIS approach can be applied to a whole measurement procedure. The experimental MU is estimated using the Duplicate Method and compared against a Target MU set using the Optimised Uncertainty (OU) method. The measurement procedure published in EU guidance is shown not to be fit for purpose (FFP). However, this approach identifies how that sampling procedure can be modified to achieve FnFP for the whole procedure, by increasing the number of sample increments per batch from 10 to 40.

In this paper, the main changes in ISO 15189:2022 in comparison with the 2012 version are discussed. They affect, directly or indirectly, the actions of medical laboratories towards ensuring validity and accuracy of examination results. A main change refers to the structure that is now aligned with ISO/IEC 17025 and recent editions of other standards in the ISO 17000 series. Further to this, requirements for medical laboratories to plan and implement actions addressing risks and opportunities are introduced in the new standard. This is part of the overall philosophy of the Standard and is reflected in almost all its clauses, mainly those dealing with the pre-examination, the examination and the post-examination processes. Great emphasis is given to sampling and the pre-examination process. Contrary to ISO/IEC 17025, uncertainty arising from sampling is not referred to; this seems to be related to inherent difficulties for such an evaluation. Requirements for equipment calibration and metrological traceability of measurement results are more detailed; similarly, the specific clause on ensuring the validity of examination results, specifying requirements for the internal quality control (IQC), the external quality assessment (EQA) and the comparability of examination results is also more detailed. A new important clause refers to continuity and emergency. The new standard includes requirements for point-of-care testing (POCT) activities, previously included in ISO 22870. Some flexibility on how to meet management requirements is given. Reference is made to a number of additional supporting standards.

External quality assessment data of clinical microbiology obtained over ten years by the Colombian company PROASECAL in laboratories of seven countries in Central and South America are analyzed. The objective is to describe the quality of clinical microbiology results of the participants in the study period (2010–2021). This analysis includes the results of genus and species identification and proper reporting of both Gram staining and susceptibility testing. Data from 195 laboratories, which processed 31 bacteria, were analyzed. In this study, 32 % of laboratories were classified as good because they successfully determined the genus and species, 36 % fair, 12 % poor, and 20 % critical, to which recommendations for improvement were sent as part of the reports. In the analysis conducted for concordance between Genus, Morphology, and Gram, the success rates obtained are between 83 % and 94 %. Regarding antibiograms, the performance observed in Gram-positive bacteria ranges from 57 to 98 %, while in Gram-negative bacteria, it is between 82 and 98 %. The descriptive tools to explain external quality assessment results in clinical microbiology are limited to the percentage of successes in each item to be reported. For the analysis of the population data set, in this article, we propose to use contingency tables (including estimates of sensitivity, specificity, and predictive values) and equality of proportions tests as techniques that facilitate the interpretation of the data. On the other hand, the statistical analysis described here can be used as an analysis methodology for similar studies.

The S-score is a new performance score applicable to proficiency testing (PT) for binary data. It allows the proficiency test provider to choose how the assigned value (AV) is defined, e.g., positive versus negative, either by the PT provider or by laboratory consensus based on participating laboratories. It is a flexible tool that can be used to select as a maximum four types of proficiency test items (PTIs) depending on the required correct results and expected correct results predefined by the PT provider. Regarding the required correct results, for an easy tasks, e.g., easy analyte detection, correct results matching with the assigned value are required for all PTI1s. For difficult tasks, e.g. close to the limit of detection (LOD) with replicated samples and for mixed tasks with unreplicated, an acceptable range of correct results is required using the binomial probability density from at least six PTI2s. Regarding correct results expected but not required for difficult tasks, results matching with the assigned value are requested by the PT provider for all PTI3s and by a participating laboratory consensus (LC) for all PTI4s. The S-score was designed as a numerical indicator taking into account all the combinations of the different types of PTIs. The decimal part summarizes the laboratory results indicating the rate of incorrect results in relation to the different PTIs assigned values. The integer part provides a similar interpretation to the one of the z-score for quantitative PT, with ‘satisfactory’ (1 ≤ S-score < 2), ‘questionable’ (2 ≤ S-score < 3), and ‘unsatisfactory’ (S-score ≥ 3) performance, respectively.

In this study, lipid oxidation kinetics were examined with in vitro methods to investigate whether the antioxidant substances in the final product formulations of four antioxidant-added skin care creams have an antioxidant effect on the skin layers. For the determination of primary and secondary products, iron (III)-thiocyanate (Fe(III)-SCN) and thiobarbituric acid reactive substance methods (TBARS) were used in Cu(II)-induced linoleic acid (LA) emulsions, respectively. It was found that THCl and THC2 coded cream samples slowed down the lipid oxidation rate, while THC3 and THC4 coded samples accelerated the oxidation. The inhibition effects of the same cream samples were confirmed using the 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) scavenging method. In addition, UV-B-induced oxidation of the LA emulsion containing soy lecithin + Tween 20 emulsifier (HLB:10), prepared as a skin simulation medium for cream samples, was investigated at 35 °C and pH 5.5. The same results were supported by conjugated diene absorbance measurements. Kinetic data were explained by GC–MS analysis. Accordingly, it was observed that the degradation of fatty acids with 17 and 19 carbons into secondary products with low carbon numbers during the development of oxidation occurred at a lower rate in THCl and THC2 coded samples compared to THC3 and THC4 coded samples. The results of this study will raise consumer awareness about these high-cost cosmetic products and enable manufacturers to offer these products to the market with accurate information to users. Conducting in vivo studies supporting this study will provide resources for production suitable for human health.

Graphical abstract

Alternative Tools (AT) such as on-site test kits, on-site portable devices and continuous measuring devices, are useful to improve water quality assessment under EU directives, and water treatment processes, thus contributing to improving water management, as well as get insights on the dynamic of pollutants within water bodies. Although these tools have clear advantages (e.g. fast response allowing for real-time monitoring, ease-of-use, lower cost), they are perceived as less reliable than conventional analytical methods. Their alternative nature, innovative status, and non-standard operation mode require specific validation strategies that differ significantly from those of conventional analytical methods. Nevertheless, the validation of ATs, especially on-site test kits, portable devices and continuous measuring devices for water quality monitoring is crucial to support their acceptance, promote their use and make their application sustainable. In this paper, a validation procedure in 4 steps is proposed: (1) Comprehensive description of the AT; (2) Assessment of intrinsic metrological performance and operational factors within a single laboratory; (3) Assessment of inter-laboratory performances through an inter-laboratory comparison and, (4) Demonstration of the equivalence of results between the AT and a reference method. This paper discusses each step of the validation procedure, and examples to illustrate critical issues are provided.

Analysis of blood alcohol concentration (BAC) is a routine analysis performed in many forensic laboratories. As BAC results are usually contested in court, measurement uncertainty (MU) becomes a critical topic. This contribution reports the results of an investigation of the major sources of uncertainty affecting BAC determinations and compares two different approaches to the quantification of the corresponding measurement uncertainty in routine BAC determinations. First, a bottom-up approach with method validation data was used to evaluate and estimate the MU of the analytical method. The interplay between the different sources of uncertainty was characterized using a cause-and-effect diagram, their contributions were evaluated, and they were combined using standard methods for uncertainty propagation to derive the overall uncertainty of the analytical method. Second, a top-down approach is presented where MU is estimated from long-term results obtained in proficiency testing. Comparison and validation of the results of the two approaches suggests that the top-down approach yielded a reasonable evaluation of MU while also being much simpler and more cost-effective than the bottom-up approach.

In recent years, the scientific community has made great efforts to establish procedures for the estimation of uncertainty in various measurement processes in laboratories. In this regard, the Guide to the Expression of Uncertainty in Measurement has been one of the most widely used documents for the estimation of uncertainty values in measurement processes. In spite of its success, the linear propagation method of uncertainties proposed in this guide presents serious deficiencies when trying to estimate uncertainty in measurement or calibration processes where an intensive mathematical treatment is used, particularly when these introduce important sources of variability. An example of this is the quantification of Sn, Sb and Cu in Babbitt metal by energy-dispersive X-ray fluorescence. In this material, Sn and Sb present a strong spectral interference between their different lines, which forces the use of mathematical methods of deconvolution and correction of inter-element effects that introduce sources of variability usually neglected. This work proposes an alternative to the uncertainty quantification based on the Monte Carlo method where the sources of variability resulting from the spectral treatment and matrix effects are included. Methodologies for the establishment of the main practical aspects of the Monte Carlo method and its adaptation to calibration methodologies are also proposed. The influence of disregarding the variability introduced by the spectrum treatment algorithms on the uncertainty estimation is shown.

Residue behavior and consumer risk assessment of combination of betacyfluthrin and imidacloprid at recommended dose (X) and double the recommended dose (2X) on cucumber crop were studied during kharif season, 2019. The combination product was applied thrice as foliar sprays at 7 days interval with first application at fruit initiation stage. Residues of betacyfluthrin and imidacloprid were detected using gas chromatography-electron capture detector and high pressure liquid chromatography, respectively, after the extraction and clean-up of samples with modified QuEChERS technique. The average initial deposits at X and 2X dose of betacyfluthrin were 0.69 and 1.41 mg kg⁻¹, which dissipated to half of its concentration in 1.51 and 1.73 days with a suggested safe waiting period of 5.73 and 8.34 days whereas, for imidacloprid, initial deposits were 0.84 and 1.56 mg kg⁻¹, which dissipated to half of its concentration in 1.29 and 1.51 days with a suggested safe waiting period of 5.24 and 7.49 days, respectively. Residues in soil samples collected at harvest were found to be below determination level for both components. Dietary risk assessment calculated as hazard quotient came out to be less than 1, thus establishing the safety of combination product of betacyfluthrin and imidacloprid for consumers when used following good agricultural practices.