Structural and economic dynamics in diversified Italian farms

Objective of this work is to investigate the structural change and economic dynamics of farms pursuing diversification and differentiation strategies in Italy. The analysis was performed on a panel of data built on the basis of information collected by the Italian FADN between 2003-2009. For the purpose of the analysis, we divided the population of commercial Italian farms into a five-fold farm typology based on size and the extent of diversification and differentiation strategies adopted by the farms. In detail, farms are defined as differentiated when they make use of a system of quality certification, while they are defined as diversified when they take up non farming activities (agritourism, social farms etc.). The findings show that conventional farms remain by far the largest category within the population of Italian commercial farms, while only 13% of the total commercial farms are classified as differentiated and/or diversified. Farms adopting product differentiation strategies are found to have an income growth path similar to that of conventional farms. Yet the category of diversified farms is the only one showing an upward trend with regard to income per worker in the observed years, while farms relying entirely on agricultural products appear to perform poorly in terms of labour productivity

Streamlining intersectoral provision of real-world health data: a service platform for improved clinical research and patient care

IntroductionObtaining real-world data from routine clinical care is of growing interest for scientific research and personalized medicine. Despite the abundance of medical data across various facilities — including hospitals, outpatient clinics, and physician practices — the intersectoral exchange of information remains largely hindered due to differences in data structure, content, and adherence to data protection regulations. In response to this challenge, the Medical Informatics Initiative (MII) was launched in Germany, focusing initially on university hospitals to foster the exchange and utilization of real-world data through the development of standardized methods and tools, including the creation of a common core dataset. Our aim, as part of the Medical Informatics Research Hub in Saxony (MiHUBx), is to extend the MII concepts to non-university healthcare providers in a more seamless manner to enable the exchange of real-world data among intersectoral medical sites.MethodsWe investigated what services are needed to facilitate the provision of harmonized real-world data for cross-site research. On this basis, we designed a Service Platform Prototype that hosts services for data harmonization, adhering to the globally recognized Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) international standard communication format and the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). Leveraging these standards, we implemented additional services facilitating data utilization, exchange and analysis. Throughout the development phase, we collaborated with an interdisciplinary team of experts from the fields of system administration, software engineering and technology acceptance to ensure that the solution is sustainable and reusable in the long term.ResultsWe have developed the pre-built packages “ResearchData-to-FHIR,” “FHIR-to-OMOP,” and “Addons,” which provide the services for data harmonization and provision of project-related real-world data in both the FHIR MII Core dataset format (CDS) and the OMOP CDM format as well as utilization and a Service Platform Prototype to streamline data management and use.ConclusionOur development shows a possible approach to extend the MII concepts to non-university healthcare providers to enable cross-site research on real-world data. Our Service Platform Prototype can thus pave the way for intersectoral data sharing, federated analysis, and provision of SMART-on-FHIR applications to support clinical decision making

Impairment of Immunoproteasome Function by β5i/LMP7 Subunit Deficiency Results in Severe Enterovirus Myocarditis

Proteasomes recognize and degrade poly-ubiquitinylated proteins. In infectious disease, cells activated by interferons (IFNs) express three unique catalytic subunits β1i/LMP2, β2i/MECL-1 and β5i/LMP7 forming an alternative proteasome isoform, the immunoproteasome (IP). The in vivo function of IPs in pathogen-induced inflammation is still a matter of controversy. IPs were mainly associated with MHC class I antigen processing. However, recent findings pointed to a more general function of IPs in response to cytokine stress. Here, we report on the role of IPs in acute coxsackievirus B3 (CVB3) myocarditis reflecting one of the most common viral disease entities among young people. Despite identical viral load in both control and IP-deficient mice, IP-deficiency was associated with severe acute heart muscle injury reflected by large foci of inflammatory lesions and severe myocardial tissue damage. Exacerbation of acute heart muscle injury in this host was ascribed to disequilibrium in protein homeostasis in viral heart disease as indicated by the detection of increased proteotoxic stress in cytokine-challenged cardiomyocytes and inflammatory cells from IP-deficient mice. In fact, due to IP-dependent removal of poly-ubiquitinylated protein aggregates in the injured myocardium IPs protected CVB3-challenged mice from oxidant-protein damage. Impaired NFκB activation in IP-deficient cardiomyocytes and inflammatory cells and proteotoxic stress in combination with severe inflammation in CVB3-challenged hearts from IP-deficient mice potentiated apoptotic cell death in this host, thus exacerbating acute tissue damage. Adoptive T cell transfer studies in IP-deficient mice are in agreement with data pointing towards an effective CD8 T cell immune. This study therefore demonstrates that IP formation primarily protects the target organ of CVB3 infection from excessive inflammatory tissue damage in a virus-induced proinflammatory cytokine milieu

An attempt to measure the economic sustainability of farm diversification

The recent CAP has increasingly supported the process of farm diversification throughout a set of measures aimed at enhancing alternative forms of incomes. The paper focuses on evaluating to what extent the diversification strategy enhanced the economic sustainability of different typologies of farms, ranking from micro farms to traditional conventional ones and to the diversified and quality-differentiated farm. The paper analyses the evolution a set of indicators used to assess and compare the performance of these farm typologies over the 2003-09 period. Results show that a certain level of multifunctionality and diversification is actually featured in most farms. The majority of farms in the panel is focused on the strategy of differentiation through quality products, which is key for Italian agriculture performance and competitiveness. Moreover, the indicators of economic sustainability seem to confirm the complementary role of rural development policies to the first pillar of the CAP

Structural and economic dynamics in diversified Italian farms

Objective of this work is to investigate the structural change and economic dynamics of farms pursuing diversification and differentiation strategies in Italy. The analysis was performed on a panel of data built on the basis of information collected by the Italian FADN between 2003-2009. For the purpose of the analysis, we divid- ed the population of commercial Italian farms into a five-fold farm typology based on size and the extent of diversification and differentiation strategies adopted by the farms. In detail, farms are defined as differentiated when they make use of a system of quality certification, while they are defined as diversified when they take up non- farming activities (agritourism, social farms etc.). The findings show that conventional farms remain by far the largest category within the population of Italian commer- cial farms, while only 13% of the total commercial farms are classified as differenti- ated and/or diversified. Farms adopting product differentiation strategies are found to have an income growth path similar to that of conventional farms. Yet the category of diversified farms is the only one showing an upward trend with regard to income per worker in the observed years, while farms relying entirely on agricultural products appear to perform poorly in terms of labour productivity

Structural and economic dynamics in diversified Italian farms

Objective of this work is to investigate the structural change and economic dynamics of farms pursuing diversification and differentiation strategies in Italy. The analysis was performed on a panel of data built on the basis of information collected by the Italian FADN between 2003-2009. For the purpose of the analysis, we divided the population of commercial Italian farms into a five-fold farm typology based on size and the extent of diversification and differentiation strategies adopted by the farms. In detail, farms are defined as differentiated when they make use of a system of quality certification, while they are defined as diversified when they take up non farming activities (agritourism, social farms etc.). The findings show that conventional farms remain by far the largest category within the population of Italian commercial farms, while only 13% of the total commercial farms are classified as differentiated and/or diversified. Farms adopting product differentiation strategies are found to have an income growth path similar to that of conventional farms. Yet the category of diversified farms is the only one showing an upward trend with regard to income per worker in the observed years, while farms relying entirely on agricultural products appear to perform poorly in terms of labour productivity

Conceptual design of a generic data harmonization process for OMOP common data model

Abstract Background To gain insight into the real-life care of patients in the healthcare system, data from hospital information systems and insurance systems are required. Consequently, linking clinical data with claims data is necessary. To ensure their syntactic and semantic interoperability, the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) from the Observational Health Data Sciences and Informatics (OHDSI) community was chosen. However, there is no detailed guide that would allow researchers to follow a generic process for data harmonization, i.e. the transformation of local source data into the standardized OMOP CDM format. Thus, the aim of this paper is to conceptualize a generic data harmonization process for OMOP CDM. Methods For this purpose, we conducted a literature review focusing on publications that address the harmonization of clinical or claims data in OMOP CDM. Subsequently, the process steps used and their chronological order as well as applied OHDSI tools were extracted for each included publication. The results were then compared to derive a generic sequence of the process steps. Results From 23 publications included, a generic data harmonization process for OMOP CDM was conceptualized, consisting of nine process steps: dataset specification, data profiling, vocabulary identification, coverage analysis of vocabularies, semantic mapping, structural mapping, extract-transform-load-process, qualitative and quantitative data quality analysis. Furthermore, we identified seven OHDSI tools which supported five of the process steps. Conclusions The generic data harmonization process can be used as a step-by-step guide to assist other researchers in harmonizing source data in OMOP CDM

Use of Metadata-Driven Approaches for Data Harmonization in the Medical Domain: Scoping Review

BackgroundMultisite clinical studies are increasingly using real-world data to gain real-world evidence. However, due to the heterogeneity of source data, it is difficult to analyze such data in a unified way across clinics. Therefore, the implementation of Extract-Transform-Load (ETL) or Extract-Load-Transform (ELT) processes for harmonizing local health data is necessary, in order to guarantee the data quality for research. However, the development of such processes is time-consuming and unsustainable. A promising way to ease this is the generalization of ETL/ELT processes. ObjectiveIn this work, we investigate existing possibilities for the development of generic ETL/ELT processes. Particularly, we focus on approaches with low development complexity by using descriptive metadata and structural metadata. MethodsWe conducted a literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We used 4 publication databases (ie, PubMed, IEEE Explore, Web of Science, and Biomed Center) to search for relevant publications from 2012 to 2022. The PRISMA flow was then visualized using an R-based tool (Evidence Synthesis Hackathon). All relevant contents of the publications were extracted into a spreadsheet for further analysis and visualization. ResultsRegarding the PRISMA guidelines, we included 33 publications in this literature review. All included publications were categorized into 7 different focus groups (ie, medicine, data warehouse, big data, industry, geoinformatics, archaeology, and military). Based on the extracted data, ontology-based and rule-based approaches were the 2 most used approaches in different thematic categories. Different approaches and tools were chosen to achieve different purposes within the use cases. ConclusionsOur literature review shows that using metadata-driven (MDD) approaches to develop an ETL/ELT process can serve different purposes in different thematic categories. The results show that it is promising to implement an ETL/ELT process by applying MDD approach to automate the data transformation from Fast Healthcare Interoperability Resources to Observational Medical Outcomes Partnership Common Data Model. However, the determining of an appropriate MDD approach and tool to implement such an ETL/ELT process remains a challenge. This is due to the lack of comprehensive insight into the characterizations of the MDD approaches presented in this study. Therefore, our next step is to evaluate the MDD approaches presented in this study and to determine the most appropriate MDD approaches and the way to integrate them into the ETL/ELT process. This could verify the ability of using MDD approaches to generalize the ETL process for harmonizing medical data