Labeling System Research Articles

Potential reformulation of food products two years after implementation of Nutri-Score in Belgium

Abstract Background Nutri-score is a front of pack labeling system that provides consumers with simplified information of the nutritional quality of food products. It is based on a five color (green to red) or letter (A to E) scheme that grades the quality of the product using an algorithm that takes into account the energy, sugar, saturated fats, salt, fiber, protein content, and percent of fruits and vegetables. In Belgium, Nutri-score was implemented on a voluntary basis in April 2019. This study aims to explore reformulation of products with Nutri-score by comparing their nutrient content and Nutri-score distribution in 2019 and 2021. Methods Product data from one of the major retailers was used in the analysis. Similar products in 2019 and 2021 with matched barcodes were used. Descriptive statistics were computed and statistical analyses such as the signed rank test and the McNemars test were performed to respectively evaluate the changes in the nutrient content and Nutri-score. The tests were conducted at 5% level of significance. Results From the matched sample of 668 products, about 55% had a Nutri-score of A and B in both 2019 and 2021. The proportion of food products with Nutri-Score of A/B and of D/E was not significantly different after two years of Nutri-Score implementation. Results showed a significant decrease in the median energy content of dairy, sauces, and meat products and in the median sugar content of dairy and fruit and vegetable products. There was a significant increase in the median fiber content of the dairy, meat products, and non-alcoholic beverages. For all food groups, the salt content of the products in 2019 and 2021 was not significantly different. Conclusions This two-year interval analysis described the changes in the classification and reformulation of the products with Nutri-score. Favorable changes in the nutrient quality of the product profiles reveals improvement in their reformulation. Key messages • In this analysis, changes has been observed in the nutrient content of food products between 2019 and 2021. • Producers or manufacturers should continue working on commitments to enhance the nutritional quality of the products delivered to consumers.

The impact of the health star rating front-of-packaging label on preferences for food products

PurposeThe Health Star Rating (HSR) is a front-of-pack labeling system that helps consumers understand the nutritional values of foods. In this study, we examined the effects of the presence (vs. absence) of an HSR label on consumer choice behavior and perception of healthiness.Design/methodology/approachIn an experimental study, we tested if the presence (vs. absence) of an HSR label provides a competitive advantage over a rival product that lacks the label, influencing purchase intentions. Participants were asked to choose among two competing products, with and without the labels, in a full factorial design.FindingsResults showed that products with an HSR label had a competitive advantage over the rival products that did not have the label. Moreover, this effect emerged more strongly for some products than others. Thus, while front-of-pack (FOP) labels can enhance sales, their impact may vary based on the specific product or brand.Originality/valueThis paper offers novel insights into the implications of HSR labels for consumer behavior and marketing strategies, particularly in the context of their potential use as a marketing tool by companies to boost sales in the food industry.

VASARI-AUTO: PERFORMANT, EQUITABLE, EffiCIENT, ECONOMIC, AND SURVIVAL PREDICTIVE FEATURISATION OF GLIOMA MRI

Abstract AIMS The VASARI (Visually AcceSAble Rembrandt Images) MRI feature set is a quantitative system designed to standardize glioma imaging descriptions. Though effective, deriving VASARI is time-consuming and therefore seldom used in clinical practice. This is however a problem that performant machine-learning software could plausibly automate. METHOD In 100 patients, two consultant neuroradiologists independently quantified VASARI features. In parallel, we developed VASARI-auto, an automated VASARI-labelling software applied to both open-source hand-segmented lesion masks and our openly available tumour segmentation model. We quantified: 1) agreement across neuroradiologists and VASARI-auto; 2) calibration of patient equity; 3) an economic workforce analysis; and 4) fidelity in predicting patient overall survival. Neuroradiologists were blinded to VASARI-auto software development and evaluations, and software developers were blinded to neuroradiologist labelling. RESULTS Segmentation and VASARI-auto were equally performant regardless of age or sex (mean segmentation Dice coefficient 0.947). A modest inter-rater variability between neuroradiologists (mean Cohen’s Kappa 0.49) was comparable between neuroradiologists and VASARI-auto (mean Cohen’s Kappa 0.41), with higher agreement across VASARI-auto methods (mean Cohen’s Kappa 0.94). The time taken for neuroradiologists to derive VASARI features was substantially higher than VASARI-auto (mean time per case 317 vs. 3 seconds, p<0.0001). A hospital workforce analysis of our centre forecast that three years of VASARI glioma featurisation would demand 771 consultant neuroradiologist workforce hours (£40,789) or 8.6 hours of computing time (£3.76 of power) with VASARI-auto. The best-performing survival model utilised VASARI-auto features (R2 0.25), opposed to those derived by consultant neuroradiologists (R2 0.21). CONCLUSION VASARI-auto is a highly efficient automated labelling system for VASARI featurisation with equitable performance regardless of patient age or sex, a favourable economic profile if used as a decision support tool, and with non-inferior fidelity in downstream patient survival prediction. Future work should integrate such tools to enhance patient care.

Ecotoxicity and Mutagenicity Assessment of Novel Antifungal Agents VT-1161 and T-2307.

Antifungal substances are essential for managing fungal infections in humans, animals, and plants, and their usage has significantly increased due to the global rise in fungal infections. However, the extensive application of antifungal agents in pharmaceuticals, personal care products, and agriculture has led to their widespread environmental dissemination through various pathways, such as excretion, improper disposal, and agricultural runoff. Despite advances in wastewater treatment, many antifungal compounds persist in the environment, affecting non-target organisms and contributing to resistance development. This study investigates the environmental impact of two novel antifungal agents, VT-1161 and T-2307, recently introduced as alternatives for treating resistant Candida spp. We assessed their ecotoxicity and mutagenicity using multiple bioassays: immobilization of Daphnia magna, growth inhibition of Raphidocelis subcapitata, luminescence inhibition of Aliivibrio fischeri, and mutagenicity on Salmonella typhimurium strain TA100. Results indicate that both VT-1161 and T-2307 exhibit lower toxicity compared to existing antifungal compounds, with effective concentrations (EC50) causing 50% response ranging from 14.34 to 27.92 mg L-1. Furthermore, both agents were classified as less hazardous based on the Globally Harmonized System of Classification and Labeling of Chemicals. Despite these favorable results, further research is needed to understand their environmental behavior, interactions, and potential resistance development among non-target species. Our findings highlight the importance of comprehensive environmental risk assessments to ensure the sustainable use of new antifungal agents.

Vibroacoustic simulation for truck tire tread noise prediction

In the last years, the introduction to the market of electric vehicles and a new labeling system introduced by the European Commission raised a strong interest in the noise produced by the tire-road interaction. The reduction of noise emissions became a strong challenge for the tire manufacturers that are constantly in need of developing new simulation tools capable of predicting the noise emitted by a tire. In this paper, the application of a simulation methodology capable of predicting the noise performance of a tire is shown and validated by means of experimental data. The experimental activities consisted of the acquisitions of noise produced by three truck tires made up of a particular tread pattern in which a single geometric feature is analyzed in each configuration, in a near field indoor condition. The simulation process aims to faithfully reproduce the procedure of the experimental test and involves the use of non-linear explicit finite element analysis followed by a vibroacoustic simulation to account for the radiated noise by structural vibrations and fluid-pumping.

ISO test track influence on the EU tyre label noise value

In 2009, the European Union (EU) introduced a directive governing the labelling of tyres, which underwent revision in 2020. This labelling system encompasses three key parameters related to tyre performance: wet grip (safety), rolling resistance (energy consumption), and external rolling noise (environmental impact). These label values serve as crucial information for customers seeking to purchase replacement tyres for their vehicles.However, the accuracy and reliability of noise measurements have been a concern. Testing conducted across various ISO-standardized tracks has revealed significant inconsistencies in noise levels, with variations of 4–5 dB between tracks. Such discrepancies directly impact the labelling process, introducing uncertainty.This paper presents results of tyre noise measurements conducted on a limited number of ISO test tracks and proposes a methodology to mitigate track-to-track variability. The study exclusively focuses on passenger car tyres. By addressing these inconsistencies, this research aims to enhance the accuracy and reliability of tyre noise labelling, thereby facilitating informed consumer decision-making and promoting environmental sustainability.

Voluntary versus mandatory food labels, Australia.

To compare uptake of the voluntary Health Star Rating front-of-pack nutrition labelling system with uptake of a mostly mandatory country-of-origin label in Australia over a similar period. We used data on numbers and proportions of products carrying health stars and country-of-origin labelling recorded annually between 2015 and 2023 through surveys of four large Australian food retailers. We determined the proportion of products with health stars and country-of-origin labels for each year by dividing the number of products carrying each label by the total number eligible to carry that label. The uptake of the voluntary Health Star Rating increased steadily between 2014 and 2018, reaching a maximum of 42% (8587/20 286) of products in 2021 before decreasing to 39% (8572/22 147) in 2023. Mandatory country-of-origin labelling uptake rose rapidly and was found on 93% (17 567/18 923) of products in 2023. In categories where country-of-origin labelling was voluntary, uptake by 2023 was 48% (3313/6925). In our 2023 sample of 22 147 products, 11 055 (50%) carried country-of-origin labelling only, 7466 (35%) carried both health star and country-of-origin labelling, 1106 (5%) carried health star labels only and 2520 (11%) carried neither label. The experience with country-of-origin labelling shows that widespread and rapid food labelling change can be achieved when required by law. The Australian government should mandate the Health Star Rating without delay. Australia's experience supports other jurisdictions in implementing mandatory front-of-pack nutrition labelling as well as updates to global guidance to recognize mandatory labelling as best-practice in delivering benefits to consumers.

Automatic bridge inspection database construction through hybrid information extraction and large language models

Regular bridge inspections generate extensive reports that, while critical for maintenance, often remain underutilized due to their unstructured format. Traditional information extraction methods depend on intricate labeling systems that commonly require time-consuming and labor-intensive labeling. This paper presents a novel bridge inspection database construction method leveraging LLM-assisted information extraction. First, we introduce the pseudo-labelling method using a closed-source LLM to generate high-quality data. Then we propose the hybrid extraction pipeline to extract relevant information segments and process them by a generation-based IE model, fine-tuned on pseudo-labeled data. Finally, the extracted data is used to construct the bridge inspection database. The proposed method, validated with real-world data, not only demonstrates higher extraction precision than the closed-source LLM used for pseudo-labeling but also outperforms traditional methods in both data preparation time and extraction accuracy. This approach provides a scalable solution for more proactive and data-driven bridge maintenance strategies.

Knowledge, Behavior, and Influencing Factors of Coarse Grain Consumption among Chinese Adults: A Focus Group Study in Xi’an

BackgroundCoarse grains are rich in fiber, minerals, and other beneficial nutrients but are consumed at low levels in modern populations. The factors that influence coarse grain consumption in current living and dietary environments are not fully understood. ObjectiveThis study aimed to explore the knowledge and behavior related to coarse grain consumption and identify the influencing factors among Chinese citizens. MethodSix focus group discussions were conducted with 39 participants aged 18–65 years from diverse social backgrounds in Xi'an, China. All discussions were transcribed verbatim and analyzed using inductive thematic analysis. ResultsThe majority of participants demonstrated insufficient knowledge about coarse grains, including their definitions, health benefits, and recommended intake. A small number of the participants reported regular consumption. The barriers to coarse grain consumption were poor sensory properties, insufficient cooking skills and time, limited availability of ready-to-eat foods, established dietary habits, and high price. Additionally, the new barriers included psychological burden, concerns about food safety, the impact of processing methods on health benefits, and special health conditions. Health benefits and family influence emerged as the two primary factors motivating coarse grain consumption. Most participants expressed a positive attitude toward partially replacing staple foods with coarse grains. Enhancing health education, innovating food processing methods, improving labeling systems, and strengthening safety supervision have been recommended for increasing coarse grain consumption. ConclusionA gap exists between health awareness and healthy behaviors regarding in coarse grain consumption, thus, collaborative efforts among government agencies, educational institutions, nutrition societies, the food industry, policymakers, and health professionals are essential to overcome these challenges.

Dual responsive polymersomes as versatile, intelligent labeling system in biosensing

The ability to manipulate artificial nanosystems is still one of the current challenges in devel-oping multifunctional nanomaterials. Those based on the photochromic effect are particularly interesting because of structural and functional control by the transient activation/inactivation with high spatiotemporal resolution. To mimic the photocontrol of natural nanosystems, we developed the first photochromic polymersomes from the novel poly(ethylene-alt-maleic an-hydride)-random-aminoazobenzene copolymer (PEMA-r-AAB) and its derivatives. Ultraviolet (UV)-triggered azobenzene (AZO) moieties’ medium-dependent isomerization from non-polar trans- to polar cis-AZO controls polymersome’s bilayer selective permeability. As a result, small hydrophilic molecules loaded inside polymersomes can be released according to the release profiles, while those outside the polymersome bilayer can eventually penetrate it. Remarkably, as a new look, cargo photorelease from the nanopolymersomes was studied in real-time by cyclic voltammetry (CV). Finally, as a proof-of-concept, horseradish peroxidase (HRP)-loaded polymersomes were assembled as an intelligent labeling system of an optical biosensor of interleukin-6 (IL-6). This synthesis route can be exploited with other photo-switching AZO derivatives, paving the way toward new AZO compound-based nanocarrier systems.

Scalable Photo-Responsive Physical Unclonable Functions via Particle Kinetics.

The increasing menace of counterfeiting and information theft underscores the urgent need for security platforms compatible with both micro- and nanoelectronics. Existing methods for anticounterfeiting labeling and cryptographic systems rely on unclonable patterns derived from the unpredictable variability of physical phenomena. However, these approaches impose limitations on the scalability of security components. Here we present a scalable platform for photoresponsive physically unclonable functions based on oxide particle kinetics in polymer solutions. The stochastic agglomeration process occurring during the formation of polymer films with dispersed oxide particles yields random patterns, with pixel sizes scalable from micro to nanoscales. We produce mechanically flexible and self-destructible optical unclonable function patterns utilizing oxide aggregates on a polymer film. Moreover, we establish a strategy for generating electrical unclonable patterns on a conducting polymer film. This involves covering the polymer film with an aggregate pattern mask, which serves as an ultraviolet-blocking layer for randomly exposing the film to ultraviolet ozone treatment. These unclonable patterns constitute robust and compact security systems, exhibiting effective resilience against machine-learning attacks (∼50% prediction error for training data sets of 1000). The developed scalable platforms for physically unclonable functions provide a hardware solution for robust cryptographic applications.

Reputation-Driven Asynchronous Federated Learning for Optimizing Communication Efficiency in Big Data Labeling Systems

With the continuous improvement of the performance of artificial intelligence and neural networks, a new type of computing architecture-edge computing, came into being. However, when the scale of hybrid intelligent edge systems expands, there are redundant communications between the node and the parameter server; the cost of these redundant communications cannot be ignored. This paper proposes a reputation-based asynchronous model update scheme and formulates the federated learning scheme as an optimization problem. First, the explainable reputation consensus mechanism for hybrid intelligent labeling systems communication is proposed. Then, during the process of local intelligent data annotation, significant challenges in consistency, personalization, and privacy protection posed by the federated recommendation system prompted the development of a novel federated recommendation framework utilizing a graph neural network. Additionally, the method of information interaction model fusion was adopted to address data heterogeneity and enhance the uniformity of distributed intelligent annotation. Furthermore, to mitigate communication delays and overhead, an asynchronous federated learning mechanism was devised based on the proposed reputation consensus mechanism. This mechanism leverages deep reinforcement learning to optimize the selection of participating nodes, aiming to maximize system utility and streamline data sharing efficiency. Lastly, integrating the learned models into blockchain technology and conducting validation ensures the reliability and security of shared data. Numerical findings underscore that the proposed federated learning scheme achieves higher learning accuracy and enhances communication efficiency.

Prepackaged foods healthiness ranking index: developing front-of-pack labeling to facilitate the assessment and validation of healthiness rankings of prepackaged foods in China

BackgroundThe Medium and Long-Term Plan for the Prevention and Treatment of Chronic Diseases (2017–2025) in China has highlighted the importance of reducing fat, sodium, and sugar in foods. However, front-of-pack labeling, which enables consumers to assess the health levels of prepackaged foods, is lacking in China. In response to the Zhejiang Provincial Health Commission’s request, we sought to develop a method for efficiently evaluating the health level of prepackaged foods.MethodsThrough a comprehensive literature review, we established a systematic framework: the Prepackaged Foods Healthiness Ranking Index (PHRI). We determined specific threshold values and grading criteria and conducted two rounds of Delphi survey to refine the index. Using a measurement dataset, we aimed to determine the optimal limit values for assessing the health level of prepackaged foods in real-world settings.ResultsAfter two rounds of Delphi surveys, the PHRI underwent multiple revisions until consensus among experts was reached. The final decision regarding the upper limit values set 30% Nutrient Reference Values as the limit for solid foods and 15% Nutrient Reference Values for liquid foods. The calculation of PHRI values was successfully implemented with the dataset, in accord with current nutrition awareness and real-world conditions.ConclusionsThe PHRI provides a valuable tool for assessing the healthiness of prepackaged foods. This front-of-pack labeling system provides a convenient method for evaluating the nutritional quality of prepackaged foods. Ultimately, the PHRI has the potential to contribute to advancements in health policy, practice, and education in China.

Neuropsychological performance labels: do patients understand?

Objective: Descriptive labels to communicate performance are integral in neuropsychological reports. Although the American Academy of Clinical Neuropsychology (AACN) reached consensus on standardizing uniform labels of performance, consumer understanding of these labels is unclear. This pilot prospective cohort study evaluated patient, family member, and medical provider understanding of neuropsychological performance labels. Method: Patients (n = 62), family members (n = 31), and referral sources (n = 34) completed a 13-question survey evaluating the uniform label system and an alternative, patient-centered language system (PCL). Questions assessed label knowledge and associated percentiles and relative relationships between labels. Results: Patients had significantly higher accuracy on knowledge questions using PCL labels (54.8%) versus AACN labels (32.2%) as were families (51.6% versus 35.5%). When ranking labels, providers and patients were more accurate when using PCL labels compared to AACN labels, although no significant difference was seen in the family group. Generally, participants were more accurate in identifying highest/lowest scores using AACN labels and more accurate in identifying relatively higher and lower scores using PCL terminology. Conclusions: Results illustrate that current and alternative score labels may not be understandable for audiences who read and base decisions on neuropsychological reports. The findings highlight the need for further consideration of patient-centered language to improve understanding of neuropsychological score labels.

Recommendation mobile antivirus for Android smartphones based on malware detection

<p>The proliferation of smartphone malware attacks due to a lack of vigilance in app selection raises serious concerns. Built-in smartphone security features often must be improved to protect devices from these threats. Although numerous articles recommend top-tier antivirus solutions, there need to be more reliable data sources that raise suspicions about undisclosed promotional motives. This research endeavors to establish a ranking of antivirus efficacy to provide optimal recommendations for Android smartphone users. The research methodology entails a meticulous comparison of malware detection and labeling outcomes between various antivirus programs within Virustotal and the labeling system employed by the Euphony application. The comparative results are categorized into three groups: antivirus solutions proficient in identifying specific malware types, those detecting malware presence without categorization, and antivirus software failing to detect malware effectively. The experimental findings present the five leading antivirus solutions, ranked from the highest to lowest scores, as Ikarus, Fortinet, ESET-NOD32, Avast-Mobile, and SymantecMobileInsight. Based on the comprehensive assessment conducted in this study, these solutions are recommended as the top antivirus choices. These recommendations are poised to significantly aid users in selecting the most suitable antivirus protection for their Android smartphones.</p>

Consumer response analysis to use-by date labeling system: Focused on willingness to accept

Consumer response analysis to use-by date labeling system: Focused on willingness to accept

Abstract P224: RbFox2 is a Rho-related BTB Domain Containing 1 (RhoBTB1)-Cullin 3 (CUL3) Pathway Target that Regulates the Actin Cytoskeleton

Blood pressure (BP) is controlled by an array of cellular pathways. Our prior research revealed that endothelial nitric oxide (NO)-dependent vessel tone and BP are regulated through the RhoBTB1-CUL3 mediated proteasomal degradation of Phosphodiesterase 5 (PDE5). RhoBTB1 is an adaptor protein which delivers protein substrates to the CUL3 E3 ubiquitin ligase for proteasomal degradation. However, the range of protein targets of RhoBTB1 remains unknown. We employed the ascorbate peroxidase (APEX2) proximity labelling system coupled with mass spectroscopy to identify RhoBTB1 targets in A7r5 smooth muscle cells. This analysis identified nearly 75 proteins which putatively bind to the C terminal half of RhoBTB1 (known as B1B2C), the region we previously identified was essential for adaptor function. One of these proteins was RNA binding motif protein 9, known as RBM9 and RbFox2, a key regulator of splicing events. Subsequent co-immunoprecipitation (Co-IP) assays validated the interaction of RbFox2 with RhoBTB1 and its B1B2C domains. Expression of Rbfox2 was increased in response to treatment of A7r5 cells with either MG132, an inhibitor of the proteasome, and MLN4924, an inhibitor of the CUL family. Similarly, RbFox2 expression was increased in CRISPR-Cas9 generated CUL3-deficient HEK293 cells, in aorta isolated from SMC-specific CUL3-deficient mice, and in A7r5 cells expressing an siRNA targeting RhoBTB1. Ang-II treatment of mice, which raised blood pressure by 40 mmHg, also increased RbFox2 expression, presumably through down regulation of RhoBTB1. Targeting RbFox2 by siRNA in A7r5 cells resulted in a decrease in actin fiber formation detected by phalloidin staining. In summary, our findings suggest that RbFox2 regulation may occur through the RhoBTB1-CUL3 proteasomal pathway and may potentially play a mechanistic role in actin cytoskeleton organization and thus arterial stiffness associated with hypertension.

Assessing the Validity of Front-of-Pack Nutrition Labels for Evaluating the Healthiness of Mediterranean Food Choices: A Global Comparison.

In response to growing public health concerns, governments worldwide have implemented various nutrition labelling schemes to promote healthier eating habits. This study aimed to assess the consistency and effectiveness of these labels in an out-of-home context, specifically focusing on restaurant, hospitality, and institutional food service settings. In total, 178 different dishes from Spain were analysed using labels from the Mazocco method, the UK's traffic light system, the Health Star Rating (Australia), Nutri-Score (France), multiple traffic lights (Ecuador), and warning labels (Chile and Uruguay). The results demonstrated a generally low level of agreement among these labels (K < 0.40), indicating notable variability and a lack of consensus, which could hinder consumers' ability to make informed food choices in out-of-home settings. Nutri-Score classified the highest number of dishes as unhealthy (38%). This study underscores the need for an easy-to-understand labelling system tailored to each country's culinary and socio-cultural contexts to improve consumer decision-making in various dining environments. Future research should focus on developing and testing qualitative methods to more accurately gauge the nutritional quality of cooked dishes in diverse out-of-home settings, thereby enhancing public health outcomes. By addressing the specific needs of the home, restaurants, hospitality, and institutional food services, tailored labelling schemes could significantly improve consumers' ability to make healthier food choices.

Abstract P197: Identification and Characterization of Rho-related BTB Domain Containing 1 (RhoBTB1)-Cullin 3 (CUL3) Proteins in Placenta

Preeclampsia is life threatening condition affecting about 10% of all pregnancies. A potential mechanism is via malfunctioning syncytiotrophoblasts in the placenta. RhoBTB1 is an adapter protein for the CUL3 E3 ubiquitin ligase which delivers protein substrates for proteasomal degradation. An analysis of gene expression databases revealed that the highest level of RhoBTB1 expression is in the placenta. RNAscope in situ hybridization data reveals that RhoBTB1 expression is specifically localized to syncytiotrophoblasts. In blood vessels, RhoBTB1 controls the state of nitric oxide mediated vasodilation because it acts as a substrate adaptor for Phosphodiesterase 5. Thus, we wanted to identify potential protein targets of RhoBTB1 in the placenta to assess if RhoBTB1 plays a role in placental function. To simplify the first identification of RhoBTB1 binding proteins, we employed HTR-8 /SVneo (HTR-8) cells as a model of placental trophoblast cells. We biotinylated the HTR-8 proteome utilizing ascorbate peroxidase (APEX2) proximity labelling system followed by mass spectrometry to identify RhoBTB1 targets. We employed a fusion protein consisting of the C-terminal half of RhoBTB1 (B1B2C), the region required for the binding of other protein substrates, and a control lacking the most C-terminal region (B1B2). We next chose proteins with binding to B1B2C &gt; B1B2 of 2-fold or greater that were expressed in the placenta based on the Human Protein Atlas. Rho GTPase Activating Protein 29 (ARHGAP29), which controls the regulation of small GTP binding proteins, and S-phase Kinase associated Protein 2 (SKP2), a regulator of cell cycle progression was studied further. SKP2 is interesting because it exhibits a tissue specific tropism for placental expression with its highest expression in extravillous trophoblasts, cytotrophoblasts, and syncytiotrophoblasts. Expression of ARHGAP29 and SKP2 in HTR-8 cells were markedly upregulated by MLN4924 suggesting they are regulated by the CUL pathway. They were also modestly upregulated after partial inhibition of RhoBTB1 by siRNA suggesting they may be RhoBTB1-CUL3 targets. Studies are ongoing to validate the physical interaction of ARHGAP29 and SKP2 with RhoBTB1 by co-immunoprecipitation. We are also using RNAscope to assess the co-expression of RhoBTB1, ARHGAP29 and SKP2 in the human placenta from normal and preeclamptic pregnancies.

Transfusion sample mislabelling and wrong blood in tube in the UK: Insights from the national comparative audits of blood transfusion in 2012 and 2022.

Samples for transfusion rejected due to mislabelling can lead to harm when a patient has to be re-bled or has a transfusion or procedure delayed. Electronic labelling systems which scan the patient's identification band and generate a label at their side aim to reduce mislabelling and misidentification leading to wrong blood in tube (WBIT) errors. The 2022 National Comparative audit of sample collection aimed to compare national rates of sample mislabelling and WBIT to the 2012 audit and to examine the impact of electronic systems. All UK hospitals were invited to provide data on rejected transfusion samples and WBIT incidents in 1 month (October 2022) and were asked if they had electronic labelling. Twenty-three thousand five hundred and eighty-four rejected samples were reported by 179 sites in 1 month. The rejection rate of 4.4% represents a 47% increase compared to 2012 (2.99%). There were 92 WBIT incidents, an incidence of 1 in 5882 samples-a 45% increase compared to 1 in 8547 in 2012. Twenty-three percent of sites can print a sample label at the patient's side, up by 224%. The six sites using only electronic sample labelling had a 46.9% lower rejection rate than sites using only hand-labelling but still reported WBIT. The increase in sample rejection and WBIT may reflect pressures facing clinical staff, zero tolerance policies and the two-sample rule. A human factors approach to understanding and tackling underlying reasons locally is recommended. Electronic systems are associated with fewer labelling errors, but careful implementation and training is needed to maximise their safety benefits.