Search Results (149)

Background/Objectives: Accurate full-arch impressions are crucial for predictable prosthodontic outcomes. While intraoral scanners (IOSs) are increasingly adopted, evidence comparing their accuracy with conventional analog impressions across full mandibular arches—particularly under both laboratory and clinical conditions using an objective intraoral reference—is limited. Our study aims to evaluate the in vitro and in vivo accuracy of digital impressions compared to conventional methods in full-arch scans using an intraoral reference tool. Methods: In this study, a custom stainless steel transfer aid carrying four 5 mm steel spheres in a trapezoidal configuration, provided with known reference distances, was used. Ten mandibular Frasaco models (in vitro) and ten healthy young adults (18–30 yrs) with intact lower arches (in vivo) received the bonded spheres. Six inter-sphere distances were defined: intermolar (BL-BR), interpremolar (FL-FR), diagonals (BL-FR, FL-BR), and lateral spans (BL-FL, BR-FR). Each arch underwent a digital scan (Medit i700) and a conventional monophase PVS impression, which was poured in Type IV stone and digitized (GOM Scan 1). The inter-sphere linear distances were measured in GOM Inspect, and trueness (deviation from reference) and precision (SD) were calculated. Data normality and homogeneity were verified; parametric t-tests and one-sample tests (α = 0.05) assessed differences between workflows and against reference values. Results: In vitro, analog impressions closely matched reference distances, with only the long-span BL-BR showing minor deviation (0.053 mm, p < 0.001). Digital scans showed significantly greater deviations across all spans (max 0.117 mm), particularly over long distances. In vivo, both workflows demonstrated comparable accuracy: only BL-BR (analog) and BR-FR (digital) differed significantly from the reference, and all AMEs remained within clinical thresholds (≤0.10 mm), except for BL-BR and BL-FL spans. ICC values ranged from moderate to high. Direct paired comparisons revealed statistically equivalent performance across most spans. Conclusions: Analog impressions outperformed digital scans in vitro, particularly across longer spans, confirming their superior dimensional fidelity under controlled conditions. However, in vivo, both workflows delivered statistically comparable and clinically acceptable accuracy. These findings suggest that while analog impressions remain the gold standard for precision-demanding contexts, modern intraoral scanners—when used correctly—can offer reliable full-arch mandibular impressions. The four-sphere reference system proved valuable for objective, anatomy-independent measurement. Full article

The use of gait analysis to differentiate among paediatric populations with neurological and developmental conditions such as idiopathic toe walking (ITW), cerebral palsy (CP), and hereditary spastic paraplegia (HSP) remains challenging due to the insufficient precision of current diagnostic approaches, leading in some cases to misdiagnosis. Existing methods often isolate the analysis of gait variables, overlooking the whole complexity of biomechanical patterns and variations in motor control strategies. While previous studies have explored the use of statistical physics principles for the analysis of impaired gait patterns, gaps remain in integrating both kinematic and kinetic information or benchmarking these approaches against Deep Learning models. This study evaluates the robustness of statistical physics metrics in differentiating between normal and abnormal gait patterns and quantifies how the data source affects model performance. The analysis was conducted using gait data sets from two research institutions in Madrid and Dublin, with a total of 81 children with ITW, 300 with CP, 20 with HSP, and 127 typically developing children as controls. From each kinematic and kinetic time series, Shannon’s entropy, permutation entropy, weighted permutation entropy, and time irreversibility metrics were derived and used with Random Forest models. The classification accuracy of these features was compared to a ResNet Deep Learning model. Further analyses explored the effects of inter-laboratory comparisons and the spatiotemporal resolution of time series on classification performance and evaluated the impact of age and walking speed with linear mixed models. The results revealed that statistical physics metrics were able to differentiate among impaired gait patterns, achieving classification scores comparable to ResNet. The effects of walking speed and age on gait predictability and temporal organisation were observed as disease-specific patterns. However, performance differences across laboratories limit the generalisation of the trained models. These findings highlight the value of statistical physics metrics in the classification of children with different toe walking conditions and point towards the need of multimetric integration to improve diagnostic accuracy and gain a more comprehensive understanding of gait disorders. Full article

A collaborative inter-laboratory study was conducted to characterise the performance of the novel 250 W External Discharge Plasma Thruster (XPT) with a channel-less Hall effect-type thruster designed to address lifetime limitations and lower-power efficiency challenges in conventional Hall effect thrusters. This study aimed to validate performance measurements across different facilities and thrust stands, investigating potential facility effects on thrust characterisation. Performance testing was conducted both at the University of Surrey using a torsional thrust balance and at the University of Southampton with a double inverted pendulum thrust stand, providing independent verification of the thrust and efficiency metrics. The comparison highlighted the importance of cross-facility testing with differing background pressures, calibration methods, and thrust balance types. These differences provide valuable insights, ensuring more robust and reliable low-power thruster characterisation. The XPT thruster demonstrated consistent performance across both the University of Surrey and University of Southampton facilities, with thrust levels ranging from 1.60 mN to 11.8 mN, specific impulses from 327 s to 1067 s, and anode efficiencies up to 11%. Higher anode voltages and mass fluxes at Southampton enabled extended operational envelopes, revealing performance plateaus at elevated powers, particularly for flow rates above 8 sccm. Cross-facility testing highlighted facility-dependent influences, with Southampton achieving a higher thrust and specific impulse at lower flow rates (5–6 sccm) due to increased anode currents, while discrepancies between test sites of up to 25% were observed at higher flow rates (8–10 sccm) and powers above 200 W. Characterisation identified an optimal operating range at 200 W of anode power with a mass flux below 8 sccm. This work underscores the importance of inter-laboratory validation in electric propulsion testing and provides insights into the best practices for assessing next-generation Hall effect-type thrusters. Full article

Toxic cyanobacterial blooms are prevalent in surface waters. Depending on several conditions, these blooms produce cyanotoxins. Human exposure to these toxins can occur through multiple routes, including contaminated crops through irrigation with contaminated water. Analytical methods have been developed for cyanotoxin quantification to investigate these exposures. Yet, proper comparisons between different labs via proficiency tests or interlaboratory comparison tests, as well as method quality assurance, are impossible. Developing reference materials for cyanotoxins in plants would help resolve these problems. Therefore, a novel liquid hydroculture setup was optimized to grow and contaminate strawberries. During fruit ripening, these plants were exposed to growth medium contaminated with pure microcystin-LR or freeze-dried cyanobacterial biomass containing different microcystin congeners. Afterwards, fruits, greens, and roots were harvested. Validated UHPLC-MS/MS methods were used to quantify the microcystin congeners in the growth medium and the plants. Furthermore, both contamination conditions resulted in the accumulation of toxin(s) in the roots and the greens. Yet in the contamination models, no toxin(s) accumulated in the fruits. Therefore, this contamination approach, combined with strawberries as a berry plant model, is only suitable for reference material production for limited matrices. Our cultivation model to produce reference material could be evaluated for other berry producers. Full article

Background: Flow cytometric detection of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL) is complex, time-consuming, and subject to inter-operator variability. Deep neural networks (DNNs) offer potential for standardization and efficiency improvement, but require rigorous validation and monitoring for safe clinical implementation. Methods: We evaluated a DNN-assisted human-in-the-loop approach for CLL MRD detection. Initial validation included method comparison against manual analysis (n = 240), precision studies, and analytical sensitivity verification. Post-implementation monitoring comprised four components: daily electronic quality control, input data drift detection, error analysis, and attribute acceptance sampling. Laboratory efficiency was assessed through a timing study of 161 cases analyzed by five technologists. Results: Method comparison demonstrated 97.5% concordance with manual analysis for qualitative classification (sensitivity 100%, specificity 95%) and excellent correlation for quantitative assessment (r = 0.99, Deming slope = 0.99). Precision studies confirmed high repeatability and within-laboratory precision across multiple operators. Analytical sensitivity was verified at 0.002% MRD. Post-implementation monitoring identified 2.97% of cases (26/874) with input data drift, primarily high-burden CLL and non-CLL neoplasms. Error analysis showed the DNN alone achieved 97% sensitivity compared to human-in-the-loop-reviewed results, with 13 missed cases (1.5%) showing atypical immunophenotypes. Attribute acceptance sampling confirmed 98.8% of reported negative cases were true negatives. The DNN-assisted workflow reduced average analysis time by 60.3% compared to manual analysis (4.2 ± 2.3 vs. 10.5 ± 5.8 min). Conclusions: The implementation of a DNN-assisted approach for CLL MRD detection in a clinical laboratory provides diagnostic performance equivalent to expert manual analysis while substantially reducing analysis time. Comprehensive performance monitoring ensures ongoing safety and effectiveness in routine clinical practice. This approach provides a model for responsible AI integration in clinical laboratories, balancing automation benefits with expert oversight. Full article

Pantoea stewartii subsp. stewartii (Pss) is a Gram-negative bacterium causing Stewart wilt, a severe disease in maize. Native to North America, it has spread globally through the maize seed trade. Resistant maize varieties and insecticides are crucial to mitigate the disease’s economic impact. Pss is a quarantine pest, requiring phytosanitary certification for the seed trade in European countries. Accurate diagnostic tests, including real-time PCR, are fundamental to detect Pss and distinguish it from other bacteria, like Pantoea stewartii subsp. indologenes (Psi), a non-quarantine bacteria associated with maize seeds. Population genetics is a valuable tool for studying adaptation, speciation, population structure, diversity, and evolution in plant bacterial pathogens. In this study, the key activities of interlaboratory comparisons are reported to assess diagnostic sensitivity (DSE), diagnostic specificity (DSP) and accuracy (ACC) for different real-time PCR able to detect Pss in seeds. The results of complete sequencing of Italian bacterial isolates are presented. This study enhances our understanding of molecular methods for diagnosing and identifying pathogens in maize seeds, improving knowledge of Pss genomes to prevent their spread and trace possible entry routes from endemic to non-endemic areas. Full article

A certified reference material (CRM) for aflatoxins (AFTB1, AFTB2, AFTG1, AFTG2) and zearalenone (ZEN) in corn/peanut blended vegetable oil (GBW(E)100863) was developed to address the critical need for matrix-specific reference materials in mycotoxin analysis. The CRM was prepared by blending naturally contaminated corn and peanut oils, followed by homogenization, sterilization, and sub-packing. Homogeneity and stability studies were conducted using high-performance liquid chromatography isotope-dilution tandem mass spectrometry with a dilute-and-shoot pretreatment process. The CRM demonstrated excellent homogeneity and stability, with no significant degradation observed under either short-term (65 °C for 14 days) or long-term (25 °C for 12 months) storage conditions. An inter-laboratory comparison involving six authoritative laboratories confirmed the CRM’s accuracy and reliability, with recovery rates ranging from 90.3% to 97.3% and low relative standard deviations (RSDs) of 3.79% to 7.99%. The CRM provided a robust metrological tool for mycotoxin analysis in complex oil matrices. This study not only enriches the national reference materials library but also supports food safety initiatives by facilitating accurate and reliable mycotoxin detection in vegetable oils, thereby enhancing regulatory compliance and public health protection. Full article

Cystic fibrosis (CF) is a life-threatening disorder caused by mutations in the CFTR gene, leading to defective chloride ion transport and thickened mucus in the respiratory and gastrointestinal systems. CFTR modulators, including ivacaftor, lumacaftor, tezacaftor, and elexacaftor, have improved patient outcomes, but interindividual pharmacokinetic variability and potential drug–drug interactions require therapeutic drug monitoring (TDM) for optimal efficacy and safety. In this context, a liquid chromatography–tandem mass spectrometry (LC-MS/MS) method has been developed and validated for the simultaneous quantification of CFTR modulators and their major active metabolites in human plasma to support pharmacokinetic studies and routine TDM. The multiplex LC-MS/MS assay was established using plasma protein precipitation, followed by chromatographic separation on an Xselect HSS T3 (Waters^®) column and positive electrospray ionization mode detection. The method was validated based on FDA and EMA guidelines for specificity, linearity, accuracy (89.8–107.8%), repeatability (1.1–8.1%), intermediate fidelity (1.3–10.9%), matrix effects, and stability, demonstrating a robust performance with excellent precision and accuracy. International interlaboratory comparisons confirmed the reliability of the assay. The developed method can be applied for the clinical monitoring of caftors’ plasma concentrations and preliminary data suggest that it can also be applied to alternative matrices, such as breast milk. This method will serve to characterize caftors’ pharmacokinetic variability and monitor drug–drug interactions to further refine personalized dosing strategies and enhance precision medicine treatments for patients with CF. Full article

Portable emission measurement systems (PEMS) are used onboard vehicles to determine the on-road real driving emissions of the vehicles for research or regulatory purposes. The assessment of a PEMS is carried out in a laboratory comparing it with laboratory grade systems (i.e., validation test). This procedure is described in the European Commission Regulation (EU) 2017/1151 and there are limits that must be respected (permissible tolerances). A few inter-laboratory studies evaluated PEMS in the laboratories of different institutes. However, there are no on-road inter-laboratory studies of PEMS because there is no reference instrument available and the source (i.e., emissions of the vehicle) fluctuates significantly due to the variation of the trip characteristics, driver behavior, and environmental conditions, making meaningful evaluation challenging. Here, we present a concept of how such inter-laboratory studies could take place. The concept is that a ‘reference PEMS’ is evaluated first in the laboratory of one of the participating institutes. Then, the ‘reference PEMS’, with a reference vehicle (optionally) is sent to the other institutes to compare their ‘test PEMS’ with the ‘reference PEMS’ on-road. The difference (absolute or relative) of the two PEMS, corrected for any ‘bias’ of the ‘reference PEMS’, is used for the assessment of the ‘test PEMS’ (i.e., comparison with the permissible tolerances) or any statistical analysis (e.g., z-scores). Ideally, the selected reference PEMS should have negligible ‘bias’ (e.g., due to calibration uncertainties, drift), and for this reason, a thorough investigation at the beginning of the exercise is highly recommended. A statistical analysis can be made to confirm if there is bias. Using the differences (absolute or relative) of PEMS, the source (vehicle emissions) variability is cancelled out. The differences can then be compared with the permissible tolerances of the regulation, but up to 40% higher deviations should still be acceptable. We demonstrate the concept with experiments in our institute. Full article

Wastewater-based environmental surveillance enables the monitoring of SARS-CoV-2 dynamics within populations, offering critical epidemiological insights. Numerous workflows for tracking SARS-CoV-2 have been developed globally, underscoring the need for interlaboratory comparisons to ensure data consistency and comparability. An inter-calibration test was conducted among laboratories within the network monitoring SARS-CoV-2 in wastewater samples across the Lombardy region (Italy). The test aimed to evaluate data reliability and identify potential sources of variability using robust statistical approaches. Three wastewater samples were analyzed in parallel by four laboratories using identical pre-analytical (PEG-8000-based centrifugation) and analytical processes (qPCR targeting N1/N3 and Orf-1ab). A two-way ANOVA framework within Generalized Linear Models was applied, and multiple pairwise comparisons among laboratories were performed using the Bonferroni post hoc test. The statistical analysis revealed that the primary source of variability in the results was associated with the analytical phase. This variability was likely influenced by differences in the standard curves used by the laboratories to quantify SARS-CoV-2 concentrations, as well as the size of the wastewater treatment plants. The findings of this study highlight the importance of interlaboratory testing in verifying the consistency of analytical determinations and in identifying the key sources of variation. Full article

We describe a modification of a previously described measurement–analysis protocol to determine the intrinsic properties of triaxial accelerometers by using a measurement protocol based on angular stepwise rotation in the Earth’s gravitational field. This study was conducted with MEMS triaxial accelerometers that were co-integrated in four consumer-grade wireless microsensors. The measurements were carried out on low-cost rotation tables in different laboratories in different countries to simulate the reproducibility environment encountered in inter-comparisons of calibration capabilities. We used a previously described calibration–uncertainty metric to independently characterize the overall uncertainty of the calibration and analysis process. The intrinsic property analysis suggested, and the uncertainty metric confirmed, an unacceptably large error in one combination of microsystem and low-cost rotation table. A simple modification of the analysis protocol provided a substantial improvement in the reproducibility of the protocol with all combinations of microsystem and rotation table. Later, measurements with a high-performance triaxial accelerometer using a significantly more expensive rotation table carried out at one location further validated the usefulness of this modification. The results reported here also demonstrate the existence of unidentified defects in one microsystem and one low-cost rotation table that interact with each other in ways not currently understood to produce anomalously large errors with the old protocol but not with the new protocol. Full article

Due to the lack of a pathogen-killing process, foodborne outbreaks from contaminated fresh produce have been increasing worldwide. Hence, it is increasingly recognized that the washing step with sanitizers is important to control microbial contamination. Ozonated water is suggested as a substitute for chlorine-based sanitizers, addressing concerns about the effectiveness and environmental impact of chlorine-based sanitizers. However, using ozone as a sanitizer in the fresh produce washing process is still challenging because of its unstable and inconsistent antimicrobial effectiveness under various testing conditions. A meta-analysis was focused on the comparison of antimicrobial effectiveness between different ozonation methods commonly adopted in laboratory settings, including stationary pre-ozonated water, agitated pre-ozonated water, and sparging. The meta-analysis showed that the sparging method results in the highest microbial log reduction compared to other methods. We further developed meta-regression models based on three ozonation methods to identify key processing variables influencing the antimicrobial effectiveness of ozonated water. Attempts were made to link key processing variables to ozone stability and the mass transport phenomena involved in the washing process. This research will contribute to designing and developing a washing process to increase fresh produce safety by identifying key factors in each ozonation method and facilitate interlaboratory comparison studies. Full article

Background: Nonsurgical treatment of uncomplicated appendicitis is a reasonable option in many cases despite the sparsity of robust, easy access, externally validated, and multimodally informed clinical decision support systems (CDSSs). Developed by OpenAI, the Generative Pre-trained Transformer 3.5 model (GPT-3) may provide enhanced decision support for surgeons in less certain appendicitis cases or those posing a higher risk for (relative) operative contra-indications. Our objective was to determine whether GPT-3.5, when provided high-throughput clinical, laboratory, and radiological text-based information, will come to clinical decisions similar to those of a machine learning model and a board-certified surgeon (reference standard) in decision-making for appendectomy versus conservative treatment. Methods: In this cohort study, we randomly collected patients presenting at the emergency department (ED) of two German hospitals (GFO, Troisdorf, and University Hospital Cologne) with right abdominal pain between October 2022 and October 2023. Statistical analysis was performed using R, version 3.6.2, on RStudio, version 2023.03.0 + 386. Overall agreement between the GPT-3.5 output and the reference standard was assessed by means of inter-observer kappa values as well as accuracy, sensitivity, specificity, and positive and negative predictive values with the “Caret” and “irr” packages. Statistical significance was defined as p < 0.05. Results: There was agreement between the surgeon’s decision and GPT-3.5 in 102 of 113 cases, and all cases where the surgeon decided upon conservative treatment were correctly classified by GPT-3.5. The estimated model training accuracy was 83.3% (95% CI: 74.0, 90.4), while the validation accuracy for the model was 87.0% (95% CI: 66.4, 97.2). This is in comparison to the GPT-3.5 accuracy of 90.3% (95% CI: 83.2, 95.0), which did not perform significantly better in comparison to the machine learning model (p = 0.21). Conclusions: This study, the first study of the “intended use” of GPT-3.5 for surgical treatment to our knowledge, comparing surgical decision-making versus an algorithm found a high degree of agreement between board-certified surgeons and GPT-3.5 for surgical decision-making in patients presenting to the emergency department with lower abdominal pain. Full article

Coordinate measuring machines are widely used in the industrial field due to their ease of automation. However, estimating the measurement uncertainty is a delicate task, especially when controlling for deviation, given the large number of factors that influence the measurement. A precise estimate of the uncertainty is crucial to avoid incorrect conformity assessments. The purpose of this study is to control geometrical-form tolerance specifications, taking into consideration their associated uncertainty. A surface fitting model based on the least squares criterion is proposed, allowing one to obtain the variance–covariance matrix by iterative calculation according to the Levenberg–Marquard optimization method. The form deviation is then evaluated following the Geometrical Product Specifications (GPS) Standard, and its associated uncertainty is estimated using the guide to the expression of uncertainty in measurement (GUM) propagation of the uncertainty law. Finally, the conformity assessment is performed based on the measured deviation and its associated uncertainty. Different results for the measurement of straightness, flatness, circularity, roundness, and cylindricity are presented and detailed. This model is thereafter validated by a Monte Carlo simulation, and interlaboratory comparisons of the obtained results were performed, which showed satisfactory outcome. This contribution is of great use to manufacturing companies and metrology laboratories, allowing them to meet the normative guidelines, which stipulates that each measurement result must be accompanied by its associated uncertainty. Full article

Anti-AAV neutralizing Abs (NAbs) titer is usually measured by cell-based microneutralization (MN) assay and is crucial for patient screening in AAV-based gene therapy clinical trials. However, achieving uniform operation and comparable results among different laboratories remains challenging. Here, we established a standardized MN assay for anti-AAV9 NAbs in human sera or plasma and transferred the method to the other two research teams. Then, we validated its parameters and tested a set of eight human samples in blind across all laboratories. The end-point titer, defined by a transduction inhibition of 50% (IC₅₀), was calculated using curve-fit modelling. A mouse neutralizing monoclonal antibody in human negative serum was used for system quality control (QC), requiring inter-assay titer variation of <4-fold difference or geometric coefficient of variation (%GCV) of <50%. The assay demonstrated a sensitivity of 54 ng/mL and no cross-reactivity to 20 μg/mL anti-AAV8 MoAb. The intra-assay and inter-assay variation for the low positive QC were 7–35% and 22–41%, respectively. The titers of the blind samples showed excellent reproducibility within and among laboratories, with a %GCV of 18–59% and 23–46%, respectively. This study provides a commonly transferrable MN assay for evaluating anti-AAV9 NAbs in humans, supporting its application in clinical trials. Full article