Toward the European Health Data Space: The IMPaCT-Data secure infrastructure for EHR-based precision medicine research.

BACKGROUND: Art. 50 of the proposal for a Regulation on the European Health Data Space (EHDS) states that "health data access bodies shall provide access to electronic health data only through a secure processing environment, with technical and organizational measures and security and interoperability requirements". OBJECTIVE: To identify specific security measures that nodes participating in health data spaces shall implement based on the results of the IMPaCT-Data project, whose goal is to facilitate the exchange of electronic health records (EHR) between public entities based in Spain and the secondary use of this information for precision medicine research in compliance with the General Data Protection Regulation (GDPR). DATA AND METHODS: This article presents an analysis of 24 out of a list of 72 security measures identified in the Spanish National Security Scheme (ENS) and adopted by members of the federated data infrastructure developed during the IMPaCT-Data project. RESULTS: The IMPaCT-Data case helps clarify roles and responsibilities of entities willing to participate in the EHDS by reconciling technical system notions with the legal terminology. Most relevant security measures for Data Space Gatekeepers, Enablers and Prosumers are identified and explained. CONCLUSION: The EHDS can only be viable as long as the fiduciary duty of care of public health authorities is preserved; this implies that the secondary use of personal data shall contribute to the public interest and/or to protect the vital interests of the data subjects. This condition can only be met if all nodes participating in a health data space adopt the appropriate organizational and technical security measures necessary to fulfill their role.

Desiderata for discoverability and FAIR adoption of health data hubs.

BACKGROUND: The future European Health Research and Innovation Cloud (HRIC), as fundamental part of the European Health Data Space (EHDS), will promote the secondary use of data and the capabilities to push the boundaries of health research within an ethical and legally compliant framework that reinforces the trust of patients and citizens. OBJECTIVE: This study aimed to analyse health data management mechanisms in Europe to determine their alignment with FAIR principles and data discovery generating best. practices for new data hubs joining the HRIC ecosystem. In this line, the compliance of health data hubs with FAIR principles and data discovery were assessed, and a set of best practices for health data hubs was concluded. METHODS: A survey was conducted in January 2022, involving 99 representative health data hubs from multiple countries, and 42 responses were obtained in June 2022. Stratification methods were employed to cover different levels of granularity. The survey data was analysed to assess compliance with FAIR and data discovery principles. The study started with a general analysis of survey responses, followed by the creation of specific profiles based on three categories: organization type, function, and level of data aggregation. RESULTS: The study produced specific best practices for data hubs regarding the adoption of FAIR principles and data discoverability. It also provided an overview of the survey study and specific profiles derived from category analysis, considering different types of data hubs. CONCLUSIONS: The study concluded that a significant number of health data hubs in Europe did not fully comply with FAIR and data discovery principles. However, the study identified specific best practices that can guide new data hubs in adhering to these principles. The study highlighted the importance of aligning health data management mechanisms with FAIR principles to enhance interoperability and reusability in the future HRIC.

A Data Transformation Methodology to Create Findable, Accessible, Interoperable, and Reusable Health Data: Software Design, Development, and Evaluation Study.

BACKGROUND: Sharing health data is challenging because of several technical, ethical, and regulatory issues. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have been conceptualized to enable data interoperability. Many studies provide implementation guidelines, assessment metrics, and software to achieve FAIR-compliant data, especially for health data sets. Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) is a health data content modeling and exchange standard. OBJECTIVE: Our goal was to devise a new methodology to extract, transform, and load existing health data sets into HL7 FHIR repositories in line with FAIR principles, develop a Data Curation Tool to implement the methodology, and evaluate it on health data sets from 2 different but complementary institutions. We aimed to increase the level of compliance with FAIR principles of existing health data sets through standardization and facilitate health data sharing by eliminating the associated technical barriers. METHODS: Our approach automatically processes the capabilities of a given FHIR end point and directs the user while configuring mappings according to the rules enforced by FHIR profile definitions. Code system mappings can be configured for terminology translations through automatic use of FHIR resources. The validity of the created FHIR resources can be automatically checked, and the software does not allow invalid resources to be persisted. At each stage of our data transformation methodology, we used particular FHIR-based techniques so that the resulting data set could be evaluated as FAIR. We performed a data-centric evaluation of our methodology on health data sets from 2 different institutions. RESULTS: Through an intuitive graphical user interface, users are prompted to configure the mappings into FHIR resource types with respect to the restrictions of selected profiles. Once the mappings are developed, our approach can syntactically and semantically transform existing health data sets into HL7 FHIR without loss of data utility according to our privacy-concerned criteria. In addition to the mapped resource types, behind the scenes, we create additional FHIR resources to satisfy several FAIR criteria. According to the data maturity indicators and evaluation methods of the FAIR Data Maturity Model, we achieved the maximum level (level 5) for being Findable, Accessible, and Interoperable and level 3 for being Reusable. CONCLUSIONS: We developed and extensively evaluated our data transformation approach to unlock the value of existing health data residing in disparate data silos to make them available for sharing according to the FAIR principles. We showed that our method can successfully transform existing health data sets into HL7 FHIR without loss of data utility, and the result is FAIR in terms of the FAIR Data Maturity Model. We support institutional migration to HL7 FHIR, which not only leads to FAIR data sharing but also eases the integration with different research networks.

Health data hubs: an analysis of existing data governance features for research.

BACKGROUND: Digital transformation in healthcare and the growth of health data generation and collection are important challenges for the secondary use of healthcare records in the health research field. Likewise, due to the ethical and legal constraints for using sensitive data, understanding how health data are managed by dedicated infrastructures called data hubs is essential to facilitating data sharing and reuse. METHODS: To capture the different data governance behind health data hubs across Europe, a survey focused on analysing the feasibility of linking individual-level data between data collections and the generation of health data governance patterns was carried out. The target audience of this study was national, European, and global data hubs. In total, the designed survey was sent to a representative list of 99 health data hubs in January 2022. RESULTS: In total, 41 survey responses received until June 2022 were analysed. Stratification methods were performed to cover the different levels of granularity identified in some data hubs' characteristics. Firstly, a general pattern of data governance for data hubs was defined. Afterward, specific profiles were defined, generating specific data governance patterns through the stratifications in terms of the kind of organization (centralized versus decentralized) and role (data controller or data processor) of the health data hub respondents. CONCLUSIONS: The analysis of the responses from health data hub respondents across Europe provided a list of the most frequent aspects, which concluded with a set of specific best practices on data management and governance, taking into account the constraints of sensitive data. In summary, a data hub should work in a centralized way, providing a Data Processing Agreement and a formal procedure to identify data providers, as well as data quality control, data integrity and anonymization methods.

Palmo-plantar hyperkeratosis associated with HTLV-1 infection: a case report.

BACKGROUND: Palmoplantar hyperkeratosis is a cutaneous manifestation that had not been clearly associated with infection by the human T-cell lymphotropic virus, which is a retrovirus that in most cases does not develop clinical pathologies and its symptoms may be undetected. The skin is one of the most affected organs, however until now only seborrheic dermatitis, xerosis/ichthyosis and infective dermatitis associated with HTLV-1 have been described as cutaneous clinical manifestations of this disease. CASE PRESENTATION: We present the case of a 36-year-old male patient with serologically documented HTLV-1 infection, who presented symptoms of diarrhea, malabsorption due to Strongyloides stercoralis, and in whom a physical examination revealed an association with generalized xerosis and palmoplantar keratoderma confirmed by skin biopsy. Other infectious etiologies and malignancy were ruled out. This clinical manifestation was managed with dermal hydration, and skin care which improved the thickened skin and make it less noticeable. CONCLUSIONS: According to our experience, this is the first reported case of palmoplantar keratoderma associated with a human lymphotropic virus infection. This is a skin manifestation that has not been confirmed in conjunction with HTLV-I before. This implies that palmoplantar keratoderma is a new clinical manifestation of this infection, that should be considered in the initial approach of patients in endemic areas with these dermatological characteristics.

Lipid Atlas of Keratinocytes and Betulin Effects on its Lipidome Profiled by Comprehensive UHPLC-MS/MS with Data Independent Acquisition Using Targeted Data Processing.

Betulin is a pentacyclic triterpene with demonstrated healing properties in mid-dermal wounds. A few earlier studies have provided insights into the wound healing effects on the molecular level. However, there are still questions left on the molecular targets of betulin. Therefore, a pharmacolipidomics analysis of betulin is undertaken in human immortalized keratinocytes to monitor alterations in the lipid profiles induced by treatment with betulin. For this purpose, lipid extracts of keratinocytes treated with betulin and untreated controls are comprehensively analyzed by an untargeted UHPLC-ESI-QTOF-MS/MS lipidomics profiling workflow using data-independent acquisition. Targeted data processing allows the identification of 611 lipid species from 21 different lipid classes. Statistical analysis of the identified lipids shows significant changes in 440 lipid species that can be described as downregulation of cholesteryl esters and triacylglycerides and upregulation of glycerophospholipids, sphingolipids, and diacylglycerides. Additionally, some other signals corresponding to triterpenes are found in the betulin group and suggested that betulin is incorporated (in the membrane) and metabolized in keratinocytes.

Lipidomic profiling of non-mineralized dental plaque and biofilm by untargeted UHPLC-QTOF-MS/MS and SWATH acquisition.

Dental plaque is a structurally organized biofilm which consists of diverse microbial colonies and extracellular matrix. Its composition may change when pathogenic microorganisms become dominating. Therefore, dental biofilm or plaque has been frequently investigated in the context of oral health and disease. Furthermore, its potential as an alternative matrix for analytical purposes has also been recognized in other disciplines like archeology, food sciences, and forensics. Thus, a careful in-depth characterization of dental plaque is worthwhile. Most of the conducted studies focused on the screening of microbial populations in dental plaque. Their lipid membranes, on the other hand, may significantly impact substance (metabolite) exchange within microbial colonies as well as xenobiotics uptake and incorporation into teeth. Under this umbrella, a comprehensive lipidomic profiling for determination of lipid compositions of in vivo dental plaque samples and of in vitro cultivated biofilm as surrogate matrix to be used for analytical purposes has been performed in this work. An untargeted lipidomics workflow utilizing a ultra-high-performance liquid chromatography (UHPLC)-quadrupole-time-of-flight (QTOF) platform together with comprehensive SWATH (sequential window acquisition of all theoretical fragment ion mass spectra) acquisition and compatible software (MS-DIAL) that comprises a vast lipid library has been adopted to establish an extensive lipidomic fingerprint of dental plaque. The main lipid components in dental plaque were identified as triacylglycerols, followed by cholesterol, cholesteryl esters as well as diacylglycerols, and various phospholipid classes. In vivo plaque is a rare matrix which is usually available in very low amounts. When higher quantities for specific research assays are required, efficient ways to produce an appropriate surrogate matrix are mandatory. A potential surrogate matrix substituting dental plaque was prepared by cultivation of in vitro biofilm from saliva and similarities and differences in the lipidomics profile to in vivo plaque were mapped by statistical evaluation post-analysis. It was discovered that most lipid classes were highly elevated in the in vitro biofilm samples, in particular diacylglycerols, phosphatidylglycerols, and phosphatidylethanolamines (PEs). Furthermore, an overall shift from even-chain lipid species to odd-chain lipids was observed in the cultivated biofilms. On the other hand, even-chain phosphatidylcholines (PCs), lysoPCs, cholesteryl esters, and cholesterol-sulfate were shown to be specifically increased in plaque samples. Graphical abstract.

The Need to Develop Standard Measures of Patient Adherence for Big Data: Viewpoint.

Despite half a century of dedicated studies, medication adherence remains far from perfect, with many patients not taking their medications as prescribed. The magnitude of this problem is rising, jeopardizing the effectiveness of evidence-based therapies. An important reason for this is the unprecedented demographic change at the beginning of the 21st century. Aging leads to multimorbidity and complex therapeutic regimens that create a fertile ground for nonadherence. As this scenario is a global problem, it needs a worldwide answer. Could this answer be provided, given the new opportunities created by the digitization of health care? Daily, health-related information is being collected in electronic health records, pharmacy dispensing databases, health insurance systems, and national health system records. These big data repositories offer a unique chance to study adherence both retrospectively and prospectively at the population level, as well as its related factors. In order to make full use of this opportunity, there is a need to develop standardized measures of adherence, which can be applied globally to big data and will inform scientific research, clinical practice, and public health. These standardized measures may also enable a better understanding of the relationship between adherence and clinical outcomes, and allow for fair benchmarking of the effectiveness and cost-effectiveness of adherence-targeting interventions. Unfortunately, despite this obvious need, such standards are still lacking. Therefore, the aim of this paper is to call for a consensus on global standards for measuring adherence with big data. More specifically, sound standards of formatting and analyzing big data are needed in order to assess, uniformly present, and compare patterns of medication adherence across studies. Wide use of these standards may improve adherence and make health care systems more effective and sustainable.

ITEMAS ontology for healthcare technology innovation.

BACKGROUND: The Platform for Innovation in Medical and Health Technologies (ITEMAS) is a network of 66 healthcare centres focused on fostering innovation in medical and health technologies as an essential tool for increasing the sustainability of the Spanish healthcare system. The present research is focused on defining a formal representation that details the most relevant concepts associated with the creation and adoption of innovative medical technology in the Spanish healthcare system. METHODS: The methodology applied is based on the methontology process, including peer-review identification and selection of concepts from the ITEMAS innovation indicators and innovation management system standards. This stage was followed by an iterative validation process. Concepts were then conceptualised, formalised and implemented in an ontology. RESULTS: The ontology defined describes how relationships between employees, organisations, projects and ideas can be applied to generate results that are transferrable to the market, general public and scientific forums. Overall, we identified 136 concepts, 138 object properties and 30 properties in a five-level hierarchy. The ontology was tested and validated as an appropriate framework for calculating the ITEMAS innovation indicators. CONCLUSIONS: The consensus concepts were expressed in the form of an ontology to be used as a single communication format between the members of the ITEMAS network. Healthcare centres can compare their innovation results and obtain a better understanding of their innovation context based on the reasoning techniques of artificial intelligence. As a result, they can benefit from advanced analytical capabilities to define the most appropriate innovation policies for each centre based on the common experience of the large number of healthcare centres involved. The results can be used to create a map of agents and knowledge to show capabilities, projects and services provided by each of the participating centres. The ontology could also be applied as an instrument to match needs with existing projects and capabilities from the community of organisations working in healthcare technology innovation.

Chiral separation of disease biomarkers with 2-hydroxycarboxylic acid structure.

Chiral 2-hydroxycarboxylic acids are compounds that have been linked to particular diseases and are putative biomarkers with some diagnostic potential. The importance of identifying whether a particular enantiomer is related to certain diseases has been encouraged recently. However, in many cases it has not yet been elucidated whether there are stereochemical implications with respect to these biomarkers and whether their enantioselective analysis provides new insights and diagnostic potential. In this study 13 disease-related chiral 2-hydrocarboxylic acids were studied for their chiral separation by high-performance liquid chromatography on three cinchona alkaloid-derived chiral stationary phases. From a subgroup of eight 2-hydroxymonocarboxylic acids, baseline resolution could be achieved and inversion of elution order by exchanging tert-butylcarbamoyl quinidine chiral stationary phase (Chiralpak QD-AX) for the corresponding quinine analogue (Chiralpak QN-AX) is shown for seven of them. Furthermore, conditions for chiral separation of the 2-hydroxydicarboxylic acids, citramalic acid, 2-isopropylmalic acid, and 2-hydroxyadipic acid are reported and compared to the previous reported conditions for 2-hydroxyglutaric acid and malic acid.

Measuring the impact of informal elderly caregiving: a systematic review of tools.

PURPOSE: To classify and identify the main characteristics of the tools used in practice to assess the impact of elderly caregiving on the informal carers' life. METHODS: A systematic review of literature was performed searching in Embase, MEDLINE, PsycINFO, CINAHL, IBECS, LILACS, SiiS, SSCI and Cochrane Library from 2009 to 2013 in English, Spanish, Portuguese and French, and in reference lists of included papers. RESULTS: The review included 79 studies, among them several in languages other than English. Their inclusion increased the variety of identified tools to measure this impact (n = 93) and allowed a wider analysis of their geographical use. While confirming their overlapping nature, instruments were classified according to the degree of integration of dimensions they evaluated and their specificity to the caregiving process: caregiver burden (n = 20), quality of life and well-being (n = 11), management and coping (n = 21), emotional and mental health (n = 29), psychosocial impact (n = 10), physical health and healthy habits (n = 2), and other measures. A high use in practice of tools not validated yet and not caregiver-specific was identified. CONCLUSIONS: The great variety and characteristics of instruments identified in this review confirm the complexity and multidimensionality of the effects of elderly caregiving on the informal carer's life and explain the difficulties to assess these effects in practice. According to the classification provided, caregiver burden and emotional and mental health are the most evaluated dimensions. However, further work is required to develop integrated and caregiving focused procedures that can appraise this complexity across different countries and cultures.

[Neuronavigation in the surgical planning of callosotomy]. / Utilidad de la neuronavegación en la planificación quirúrgica de la callosotomía.

OBJECTIVE: To describe the usefulness of 3D computer-assisted preoperative neuronavigation for stereoscopic location of the venous sinuses, arterial branches, and corpus callosum, to extrapolate anatomical landmarks on the surgical field and make decisions before the intervention. METHODS: A prospective analysis was performed on patients with refractory epilepsy who underwent neuronavigation-assisted callosotomy (BRAIN LAB Dual). RESULTS: A total of 10 neuronavigation-assisted callosotomies were performed in the year 2014. The ages of the patients (4 males and 6 females) were between 4 and 13 years (mean 7; SD 3.02). The most common indication for callosotomy in our sample was Lennox Gastoux (5 patients). A right parasagittal craniotomy was performed in 8 patients. An anterior two-thirds callosotomy was performed in 8 patients and anterior three-quarters in 2 patients. The mean accuracy of the neuronavigation procedure was less than 2mm. In no cases were there significant intraoperative surgical complications. CONCLUSION: Callosotomy using frameless guided neuronavigation is an accurate and safe technique in patients with epilepsy refractory to surgical resection.

[Primary care and mental health care collaboration in patients with depression: Evaluation of a pilot experience]. / Colaboración atención primaria-salud mental en la asistencia a pacientes con depresión: evaluación de una experiencia piloto.

OBJECTIVE: To implement and assess a collaborative experience between Primary Care (PC) and Mental Health (MH) in order to improve the care of patients with depression. DESIGN: Pilot collaborative project from a participatory action research approach during 2013. LOCATION: Basque Country. Osakidetza (Basque Health Service). Bizkaia and Gipuzkoa. PARTICIPANTS: The study included 207 professionals from general practice, nursing, psychiatry, psychiatric nursing, psychology and social work of 9 health centres and 6 mental health centres of Osakidetza. INTERVENTIONS: Shared design and development of four axes of intervention: 1) Communication and knowledge between PC and MH professionals, 2) Improvement of diagnostic coding and referral of patients, 3) Training programmes with meetings and common Clinical Practice Guidelines, and 4) Evaluation. MAIN MEASUREMENTS: Intervention and control questionnaires to professionals of the centres on the knowledge and satisfaction in the PC-MH relationship, joint training activities, and assessment of the experience. Osakidetza registers of prevalences, referrals and treatments. Follow-up meetings. RESULTS: Improvement in the 4 axes of intervention in the participant centres compared with the controls. Identification of factors to be considered in the development and sustainability of PC-MH collaborative care. CONCLUSIONS: The pilot experience confirms that collaborative projects promoted by PC and MH can improve depression care and the satisfaction of professionals. They are complex projects that need simultaneous interventions adjusted to the particularities of the health services. Multidisciplinary and continuous participation and management and information system support are necessary for their implementation.

Discovery of Tricyclic Clerodane Diterpenes as Sarco/Endoplasmic Reticulum Ca(2+)-ATPase Inhibitors and Structure-Activity Relationships.

Tricyclic clerodane diterpenes (TCDs) are natural compounds that often show potent cytotoxicity for cancer cells, but their mode of action remains elusive. A computationally based similarity search (CDRUG), combined with principal component analysis (ChemGPS-NP) and docking calculations (GOLD 5.2), suggested TCDs to be inhibitors of the sarco/endoplasmic reticulum Ca(2+)-ATPase (SERCA) pump, which is also the target of the sesquiterpene lactone thapsigargin. Biochemical studies were performed with 11 TCDs on purified rabbit skeletal muscle sarcoplasmic reticulum membranes, which are highly enriched with the SERCA1a isoform. Casearborin D (2) exhibited the highest affinity, with a KD value of 2 µM and giving rise to complete inhibition of SERCA1a activity. Structure-activity relationships revealed that functionalization of two acyl side chains (R1 and R4) and the hydrophobicity imparted by the aliphatic chain at C-9, as well as a C-3,C-4 double bond, play crucial roles for inhibitory activity. Docking studies also suggested that hydrophobic interactions in the binding site, especially with Phe256 and Phe834, may be important for a strong inhibitory activity of the TCDs. In conclusion, a novel class of SERCA inhibitory compounds is presented.

Antitumor efficacy, pharmacokinetic and biodistribution studies of the anticancer peptide CIGB-552 in mouse models.

Accumulation of the COMMD1 protein as a druggable pharmacology event to target cancer cells has not been evaluated so far in cancer animal models. We have previously demonstrated that a second-generation peptide, with cell-penetrating capacity, termed CIGB-552, was able to induce apoptosis mediated by stabilization of COMMD1. Here, we explore the antitumor effect by subcutaneous administration of CIGB-552 in a therapeutic schedule. Outstandingly, a significant delay of tumor growth was observed at 0.2 and 0.7 mg/kg (p < 0.01) or 1.4 mg/kg (p < 0.001) after CIGB-552 administration in both syngeneic murine tumors and patient-derived xenograft models. Furthermore, we evidenced that (131)I-CIGB-552 peptide was actually accumulated in the tumors after administration by subcutaneous route. A typical serine-proteases degradation pattern for CIGB-552 in BALB/c mice serum was identified. Further, biological characterization of the main metabolites of the peptide CIGB-552 suggests that the cell-penetrating capacity plays an important role in the cytotoxic activity. This report is the first in describing the antitumor effect induced by systemic administration of a peptide that targets COMMD1 for stabilization. Moreover, our data reinforce the perspectives of CIGB-552 for cancer targeted therapy.

Cytotoxic clerodane diterpenes from Zuelania guidonia.

The leaves of Zuelania guidonia yielded eight new clerodane diterpenes, namely, zuelaguidins A-H (1-8), and the known clerodane diterpene esculentin A (9). Some of these structures contained a 3,6-dihydro-1,2-dioxin moiety. The new compounds were isolated and identified using 1D- and 2D-NMR experiments. All compounds were evaluated for cytotoxicity against the CCRF-CEM (human acute lymphocytic leukemia), CEM-ADR5000 (human acute lymphocytic leukemia resistant to doxorubicin), and MIA-PaCa-2 (human pancreatic carcinoma) cell lines as well as for their selectivity against peripheral blood mononuclear cells from healthy human subjects. Zuelaguidins B, C, and E were the most potent compounds against the CCRF-CEM cell line, with IC50 values ranging from 1.6 to 2.5 µM.

Using a nonparametric item response theory model to identify patterns of cognitive decline: The Mokken scale analysis.

Cognitive decline, particularly in dementia, presents complex challenges in early detection and diagnosis. While Item Response Theory (IRT) has been instrumental in identifying patterns of cognitive impairment through psychometric tests, its parametric models often require large sample sizes and strict assumptions. This creates a need for more adaptable, less demanding analytical methods. This study aimed to evaluate the effectiveness of Mokken scale analysis (MSA), a nonparametric IRT model, in identifying hierarchical patterns of cognitive impairment from psychometric tests. Using data from 1164 adults over 60 years old, we applied MSA to the orientation subscale of ACE-III. Our analysis involved calculating scalability, monotone homogeneity, invariant item ordering (IIO) and response functions. The MSA effectively retrieved the hierarchical order of cognitive impairment patterns. Most items showed strong scalability and consistent patterns of cognitive performance. However, challenges with IIO were observed, particularly with items having adjacent difficulty parameters. The findings highlight MSA's potential as a practical alternative to parametric IRT models in cognitive impairment research. Its ability to provide valuable insights into patterns of cognitive deterioration, coupled with less stringent requirements, makes it a useful tool for clinicians and researchers.

Executive functions and their relationship with age: Insights from a novel neuropsychological Assessment Battery in Children-a pilot study.

Executive functions (EFs) are a set of cognitive processes that enable individuals to manage and coordinate their thoughts and actions toward achieving specific goals. EFs include planning, organizing, initiating, and monitoring actions, and have been found to improve with age due to the maturation of the brain, especially during childhood. Therefore, our correlational study sought to determine the relationship between the performance in executive functions and age in 79 children (36 girls, 45.6%) throughout development, between the ages of 6 and 12 (mean = 9.25; SD = 2.05), using a battery designed in Chile: BEFE (Batería de Evaluación de las Funciones Ejecutivas: Executive Function Assessment Battery) based on traditional neuropsychological tests to evaluate Working Memory, Inhibitory Control, Cognitive Flexibility, and Planning skills. Our results showed various correlations between the variables age and performance in various behavioral parameters, demonstrating an increase in the number of correct responses (positive correlation) and/or a decrease in errors (negative correlation) with age (6-12) in the subtests that correspond to dimensions of Cognitive Flexibility (Semantic and Phonological Fluency, Card Sorting Game, and Tracing Tasks), Inhibitory Control (ENA-F and Sentence Completion), Working Memory (Audio-verbal WM Forward and Ordering, and Visuospatial WM Forward and Backward), and Planning (La Portada de Antofagasta and FISA Maps). These results are consistent with previous empirical evidence and support the notion of a developmental relationship between EF performance and age. Additionally, this study contributes to understanding EF development in culturally specific contexts, highlighting the importance of contextually relevant assessment tools in evaluating cognitive development.

Privacy-preserving federated machine learning on FAIR health data: A real-world application.

Objective: This paper introduces a privacy-preserving federated machine learning (ML) architecture built upon Findable, Accessible, Interoperable, and Reusable (FAIR) health data. It aims to devise an architecture for executing classification algorithms in a federated manner, enabling collaborative model-building among health data owners without sharing their datasets. Materials and methods: Utilizing an agent-based architecture, a privacy-preserving federated ML algorithm was developed to create a global predictive model from various local models. This involved formally defining the algorithm in two steps: data preparation and federated model training on FAIR health data and constructing the architecture with multiple components facilitating algorithm execution. The solution was validated by five healthcare organizations using their specific health datasets. Results: Five organizations transformed their datasets into Health Level 7 Fast Healthcare Interoperability Resources via a common FAIRification workflow and software set, thereby generating FAIR datasets. Each organization deployed a Federated ML Agent within its secure network, connected to a cloud-based Federated ML Manager. System testing was conducted on a use case aiming to predict 30-day readmission risk for chronic obstructive pulmonary disease patients and the federated model achieved an accuracy rate of 87%. Discussion: The paper demonstrated a practical application of privacy-preserving federated ML among five distinct healthcare entities, highlighting the value of FAIR health data in machine learning when utilized in a federated manner that ensures privacy protection without sharing data. Conclusion: This solution effectively leverages FAIR datasets from multiple healthcare organizations for federated ML while safeguarding sensitive health datasets, meeting legislative privacy and security requirements.

Key Research Areas for Building and Deploying a Common Data Model for an Intensive Medicine Data Space in Europe and Beyond.

Key Research Areas (KRAs) were identified to establish a semantic interoperability framework for intensive medicine data in Europe. These include assessing common data model value, ensuring smooth data interoperability, supporting data standardization for efficient dataset use, and defining anonymization requirements to balance data protection and innovation.