The Digital Product Passport (DPP) as a product-specific data set is a powerful tool that provides information on the origin or composition of products and increases transparency and traceability. This recycling case study accompanies the production of 2192 frisbees, which originated from collected beverage bottle caps. In total, 486.7 kg of feedstock was collected and transformed into 363.2 kg of final product with verified traceability through all process steps via a DPP, provided by the R-Cycle initiative and based on the GS1 standard. This demanded a generally agreed dataset, the availability of technical infrastructure, and additional effort in the processing steps to collect and process the data. R-Cycle offers a one-layer DPP where the data structure is lean and information is visible to everyone. This is beneficial to a variety of stakeholders in terms of transparency. However, it does not allow the sharing of sensitive information. On the one hand, the DPP has a high potential to be an enabler for customer engagement, origin verification, or as a starting point for more efficient and advanced recycling of plastics. On the other hand, the DPP involves a certain effort in data generation and handling, which must be justified by the benefits. For small, simple packaging items, the DPP may not be the perfect solution for all problems. However, with a broader societal mindset and legislative push, the DPP can become a widely used and trusted declaration tool. This can support the plastics industry in its journey towards a circular economy.

Blockchain\'s potential to revolutionize supply chain and logistics with transparency and equitable stakeholder engagement is significant. However, challenges like scalability, privacy, and interoperability persist. This study explores the scarcity of real-world blockchain implementations in supply chain and logistics since we have not witnessed many real-world deployments of blockchain-based solutions in the field. Puzzled by this, we integrate technology, user experience, and operational efficiency to illuminate the complex landscape of blockchain integration. We present blockchain-based solutions in three use cases, comparing them with alternative designs and analyzing them in terms of technical, economic, and operational aspects. Insights from a tailored questionnaire of 50 questions addressed to practitioners and experts offer crucial perspectives on blockchain adoption. One of the key findings from our work shows that half of the companies interviewed agree that they will miss the potential for competitive advantage if they do not invest in blockchain technology, and 61% of the companies surveyed claimed that their customers ask for more transparency in supply chain-related transactions. However, only one-third of the companies were aware of the main features of blockchain technology, which shows a lack of knowledge among the companies that may lead to a weaker blockchain adaption in supply chain use cases. Our readers should note that our study is specifically contextualized in a Netherlands-funded national project. We hope that researchers as well as stakeholders in supply chain and logistics can benefit from the insights of our work.

OBJECTIVE: To evaluate the correlation among the three molecular typing method of pulsed field gel electrophoresis(PFGE), repetitive extragenic palindromic(REP)-PCR and en-terobacterial repetitive intergenic consensus(ERIC)-PCR, and to explore the genetic relationship among strains, and to further understand the distribution and epidemic trend of Vibrio parahaemolyticus in Liaoning Province by combining Serotype analysis.
METHODS: Serum typing, PFGE, REP-PCR, and ERIC-PCR molecular typing and cluster analysis were performed on 150 VP isolates from Liaoning Province in 2018.
RESULTS: 118 isolates could be divided into 14 Serotype, and 32 isolates could not be classified. The main serotypes were O3, O1 and O2. The resolution(DI) of PFGE is 0.969, the resolution(DI) of REP-PCR is 0.948, and the resolution(DI) of ERIC-PCR is 0.927. The Serotype O3 group strains are highly similar to the molecular types of O1 group strains.
CONCLUSIONS: In 2018, the epidemic Serotype of clinical VP isolates in Liaoning Province is still O3: K6, and the epidemic serotype of food VP isolates is still O2. The result of PFGE, REP-PCR, and ERIC-PCR typing method are consistent, and the resolution and reproducibility of PFGE typing method are superior to the other two method. The Serotype O3 group is closely related to O1 group.

BACKGROUND: Secondary investigations into digital health records, including electronic patient data from German medical data integration centers (DICs), pave the way for enhanced future patient care. However, only limited information is captured regarding the integrity, traceability, and quality of the (sensitive) data elements. This lack of detail diminishes trust in the validity of the collected data. From a technical standpoint, adhering to the widely accepted FAIR (Findability, Accessibility, Interoperability, and Reusability) principles for data stewardship necessitates enriching data with provenance-related metadata. Provenance offers insights into the readiness for the reuse of a data element and serves as a supplier of data governance.
OBJECTIVE: The primary goal of this study is to augment the reusability of clinical routine data within a medical DIC for secondary utilization in clinical research. Our aim is to establish provenance traces that underpin the status of data integrity, reliability, and consequently, trust in electronic health records, thereby enhancing the accountability of the medical DIC. We present the implementation of a proof-of-concept provenance library integrating international standards as an initial step.
METHODS: We adhered to a customized road map for a provenance framework, and examined the data integration steps across the ETL (extract, transform, and load) phases. Following a maturity model, we derived requirements for a provenance library. Using this research approach, we formulated a provenance model with associated metadata and implemented a proof-of-concept provenance class. Furthermore, we seamlessly incorporated the internationally recognized Word Wide Web Consortium (W3C) provenance standard, aligned the resultant provenance records with the interoperable health care standard Fast Healthcare Interoperability Resources, and presented them in various representation formats. Ultimately, we conducted a thorough assessment of provenance trace measurements.
RESULTS: This study marks the inaugural implementation of integrated provenance traces at the data element level within a German medical DIC. We devised and executed a practical method that synergizes the robustness of quality- and health standard-guided (meta)data management practices. Our measurements indicate commendable pipeline execution times, attaining notable levels of accuracy and reliability in processing clinical routine data, thereby ensuring accountability in the medical DIC. These findings should inspire the development of additional tools aimed at providing evidence-based and reliable electronic health record services for secondary use.
CONCLUSIONS: The research method outlined for the proof-of-concept provenance class has been crafted to promote effective and reliable core data management practices. It aims to enhance biomedical data by imbuing it with meaningful provenance, thereby bolstering the benefits for both research and society. Additionally, it facilitates the streamlined reuse of biomedical data. As a result, the system mitigates risks, as data analysis without knowledge of the origin and quality of all data elements is rendered futile. While the approach was initially developed for the medical DIC use case, these principles can be universally applied throughout the scientific domain.

Investigation on the distribution and biological characteristics of Shiga-toxin producing Escherichia coli (STEC) during beef processing is essential for in-plant critical control points and food safety risk assessment. Serogroups and subtypes of stx genes of STEC strains isolated from beef processing lines were first investigated. Identification to cross-contamination among different sampling sites was further conducted by combining multilocus sequence typing (MLST) with the previous distribution and characterization data. The PCR-positive rate for STEC in 435 samples from two slaughter plants in China was 14.3% and the isolation rate for the 62 PCR positive and the entire set of 435 samples were 26% and 3.68% respectively. The existence of serotype O157:H7 (33%) and serogroups O121 (42%) and O26 (21%) as well as the high detection rate of high pathogenic gene stx2a (68%) in these serogroups indicated potential risk to the safety of beef. Traceability analysis showed that hide plays a critical role in cross-contamination between feces, lairage pens and post-washing carcasses from a molecular perspective. Intervening measures revolves around de-hiding should be involved in the in-plant safety control policy according to the tracing analysis.

In the context of the Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex data flows to transfer routine health care data into research data repositories for secondary use. Data management practices are of importance throughout these processes, and special attention should be given to provenance aspects. Insufficient knowledge can lead to validity risks and reduce the confidence and quality of the processed data. The need to implement maintainable data management practices is undisputed, but there is a great lack of clarity on the status.
Our study examines the current data management practices throughout the data life cycle within the Medical Informatics in Research and Care in University Medicine (MIRACUM) consortium. We present a framework for the maturity status of data management practices and present recommendations to enable a trustful dissemination and reuse of routine health care data.
In this mixed methods study, we conducted semistructured interviews with stakeholders from 10 DICs between July and September 2021. We used a self-designed questionnaire that we tailored to the MIRACUM DICs, to collect qualitative and quantitative data. Our study method is compliant with the Good Reporting of a Mixed Methods Study (GRAMMS) checklist.
Our study provides insights into the data management practices at the MIRACUM DICs. We identify several traceability issues that can be partially explained with a lack of contextual information within nonharmonized workflow steps, unclear responsibilities, missing or incomplete data elements, and incomplete information about the computational environment information. Based on the identified shortcomings, we suggest a data management maturity framework to reach more clarity and to help define enhanced data management strategies.
The data management maturity framework supports the production and dissemination of accurate and provenance-enriched data for secondary use. Our work serves as a catalyst for the derivation of an overarching data management strategy, abiding data integrity and provenance characteristics as key factors. We envision that this work will lead to the generation of fairer and maintained health research data of high quality.

Seafood elemental profiling (SEP) is the quantification of a range of elements in seafood products and may serve in addressing questions of seafood provenance and quality. Traditional methods for analyzing soft tissue present several limitations for the industry-level use of SEP. Portable handheld X-ray fluorescence (pXRF) analysis is a promising alternative to conventional methods; however, its application for biological analysis has not been fully established. Intact giant tiger prawn (Penaeus monodon) abdomens were analyzed with a Vanta M series XRF portable analyzer following a novel soft tissue protocol. Exploratory statistics (principal component analysis, nonmetric multidimensional scaling, and canonical discriminant analysis), as well as random forest models, have been implemented with pXRF profiles, yielding 81% accuracy when assigning the geographical origin of P. monodon. The results of this study highlight that SEP via pXRF is a viable industry-level analysis, and its application will depend on improved instrument calibration to account for fluctuating wetness factors that are influenced by cooking, storage, and other pre- and post-harvest treatments.

The microbial communities present within fermented foods are diverse and dynamic, producing a variety of metabolites responsible for the fermentation processes, imparting characteristic organoleptic qualities and health-promoting traits, and maintaining microbiological safety of fermented foods. In this context, it is crucial to study these microbial communities to characterise fermented foods and the production processes involved. High Throughput Sequencing (HTS)-based methods such as metagenomics enable microbial community studies through amplicon and shotgun sequencing approaches. As the field constantly develops, sequencing technologies are becoming more accessible, affordable and accurate with a further shift from short read to long read sequencing being observed. Metagenomics is enjoying wide-spread application in fermented food studies and in recent years is also being employed in concert with synthetic biology techniques to help tackle problems with the large amounts of waste generated in the food sector. This review presents an introduction to current sequencing technologies and the benefits of their application in fermented foods.

The main purpose of supply chain systems based on blockchain technology is to take advantage of technology innovations to ensure that a tracked asset\'s audit trail is immutable. However, the challenge lies in tracking the asset among different blockchain-based supply chain systems. The model proposed in this paper has been designed to overcome the identified challenges. Specifically, the proposed model enables: (1) the asset to be tracked among different blockchain-based supply-chain systems; (2) the tracked asset\'s supply chain to be cryptographically verified; (3) a tracked asset to be defined in a standardized format; and (4) a tracked asset to be described with several different standardized formats. Thus, the model provides a great advantage in terms of interoperability between different blockchain-driven supply chains over other models in the literature, which will need to replicate the information in each blockchain platform they operate with, while giving flexibility to the platforms that make use of it and maintain the scalability of those logistic platforms. This work aims to examine the application of the proposed model from an operational point of view, in a scenario within the pharmaceutical sector.

In Italy, the production of manila clams (Ruditapes philippinarum, Adams and Reeve, 1850) is mainly localized in northern Adriatic lagoons in the Po River delta, where shellfish farming provides important socio-economic revenue. However, in our globalized world, the seafood market is threated by fraudulent activities, in which agri-food products whose provenance is not certified are sold, posing a risk to consumer health. Multi-isotope ratio analysis is commonly used to trace the provenance of goods produced in different countries with different climatic and environmental conditions. Here, we investigated the reliability of this approach in terms of tracing the exact provenance of manila clams harvested in three Adriatic northern lagoons that are close to each other. We also verified the origin of samples bought at a local supermarket with a certificate of provenance. We carried out elemental analyses of carbon (C), nitrogen (N), and sulfur (S) and the respective isotopic ratios (13C/12C; 15N/14N; 34S/32S) on manila clam tissues, plus isotopic analyses of carbon (13C/12C), oxygen (18O/16O), and strontium (87Sr/86Sr) on manila clam shells. Each isotopic parameter can be used to identify the marine and continental contributions of water and/or nutrient supplies occurring in the lagoons. Therefore, the combination of isotopic parameters in a linear discriminant analysis (LDA) allowed for the identification of the lagoons in which the manila clams were produced.