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Upregulation of RPLP1 in PBMCs as a screening biomarker for melanoma
Early detection of melanoma is essential for improving patient outcomes. This research aimed to identify upregulated gene expression in peripheral blood mononuclear cells (PBMCs) induced by secretory factors derived from melanoma cells. These gene alterations may serve as potential non-invasive biomarkers for melanoma detection. Melanoma gene expression profiles from NCBI database were analyzed using the bioinformatics tool (CU-DREAM). A total of 85 participants were enrolled in the study. Expression levels of seven candidate genes were evaluated in a coculture model using PBMCs from healthy participants (n = 5) and melanoma cell lines at 24, 48, and 72 hours by quantitative real-time polymerase chain reaction (qRT-PCR). Based on these findings, the upregulated gene was further examined in PBMC samples for clinical expression analysis, including melanoma patients (n = 15), patients with various cancer types (n = 35), and healthy controls (n = 30). Receiver operating characteristic (ROC) curve analysis was carried out to determine the diagnostic performance of the candidate gene. Among the seven candidate genes, RPLP1 mRNA expression showed statistically significant upregulation in PBMCs cocultured with both melanoma cell lines, A375 ( p = 0.0328) and SK-MEL-28 ( p = 0.0311), at 24 hours compared with PBMC controls. The RPLP1 expression in PBMC blood samples also showed upregulation in melanoma patients compared to healthy controls ( p = 0.0006). RPLP1 upregulation demonstrated good discriminative performance in this cohort with 93.30% sensitivity, 70.00% specificity, and an area under the curve (AUC) of 0.813 ( p < 0.0001). RPLP1 upregulation in PBMCs may reflect a cancer-associated signal with relative enrichment in melanoma. Although elevated expression was also observed in breast cancer PBMCs, RPLP1 may still have potential as a minimally invasive and cost-effective screening biomarker for melanoma, given its high sensitivity in this study cohort. Further validation in larger, independent cohorts is required before clinical application.
Computational carrier dynamics across heterojunction interface between hole injection and transport layers in quantum-dot light-emitting diodes
Abstract Physics-based charge transport modelling is widely used to analyse multilayer optoelectronic devices. However, conventional drift–diffusion discretisation schemes can exhibit numerical instability at heterojunction interfaces with abrupt discontinuities in energy levels and doping density. In quantum-dot light-emitting diodes (QD-LEDs), the heterojunction between the hole injection layer (HIL) and the hole transport layer (HTL) represents such a critical interface. In this study, a field-dependent current density scheme is proposed to stabilise the discretisation of drift–diffusion currents across heterojunction interfaces. By incorporating the local electric-field direction when evaluating carrier densities at discretised boundaries, the scheme suppresses numerical artefacts associated with mean-value interpolation of the carrier density. The stability and convergence of our model are examined using a one-dimensional finite-difference framework and subsequently implemented in a charge transport model for QD-LEDs. Using this model, the effects of energy-level alignment and acceptor doping density at the HIL/HTL interface on charge transport and electro-optical characteristics are analysed. The simulations reproduce typical voltage-dependent experimental trends in current density, luminance, and external quantum efficiency, providing insight into the role of the HIL/HTL heterojunction in carrier injection. Owing to its numerical formulation, the proposed approach is applicable to a broad range of multilayer semiconductor devices involving heterojunction interfaces.
Hp1bp3 loss links chromatin reorganization to metabolic vulnerability in glioma
High-grade gliomas (HGGs) are aggressive brain tumors with poor prognosis, driven in part by metabolic and epigenetic adaptations. Methionine metabolism supports HGG growth by supplying S-adenosylmethionine for methylation reactions, yet how nutrient availability influences chromatin organization in HGG remains incompletely understood. Using an immunocompetent mouse model of HGG, we found that dietary methionine restriction reduced tumor proliferation, extended survival, and induced partial nuclear inversion. We identified Hp1bp3 as a key regulator of tumor growth that functions by interacting with nuclear tethering proteins to mediate chromatin reorganization. Loss of Hp1bp3 results in the upregulation of histone demethylases leading to selective depletion of H3K9me3-marked heterochromatin and accelerated glioma growth. Combining methionine restriction with Hp1bp3 loss increased the frequency of partial nuclear inversion and further suppressed tumor progression. These findings identify Hp1bp3 as a chromatin regulator linking methionine metabolism to heterochromatin stability and suggest that dietary methionine modulation can influence the structural organization of chromatin to slow tumor growth in HGG.
Diagnostic performance of discriminant formulas and machine learning models for detecting β-thalassemia trait in Bangladesh
Background β-thalassemia poses a considerable public health burden in Bangladesh, where a high carrier frequency underlies widespread disease risk. It is necessary to distinguish β-thalassemia trait (βTT) and iron deficiency anemia (IDA) to ensure genetic counseling and enable effective prevention strategies. Despite the availability of various discriminant formulas and machine learning algorithms (MLAs), their comparative diagnostic performance within the Bangladeshi population has not been comprehensively investigated. This study aimed to assess different discriminant formulas and ML models as well as to propose novel combinations of formulas for population-specific screening of βTT. Methods In this cross-sectional study, we compared 47 discriminant formulas and 12 machine learning models to distinguish β-thalassemia trait from iron-deficiency anemia in 467 individuals (143 βTT, 324 anemia) drawn from a 2,514-participant cohort. DF-6 and DF-27 were two new formulas constructed by integrating high-performing formulas. Multi-criteria decision-making (MCDM) techniques, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and SECA (Simultaneous Evaluation of Criteria and Alternatives), provided the final ranking for performance. Cluster analysis was performed to identify groups with similar diagnostic performance. Results Population-specific optimal cut-off values were determined for the discriminant formulas. The newly proposed formulas, DF-6 and DF-27, ranked among the top ten performers alongside RBC, Janel (11T), Ravanbakhsh-F1, Srivastav, Alparslan, Hisham, Index 26, and Kerman I. DF-6 (AUC: 0.9707) achieved the best overall performance across the diagnostic metrics. DF-6 achieved the best overall performance (AUC: 0.98, 95% CI: 0.97–0.99, p < 0.0001). Assessment of ML models revealed that XGBoost (XGB) (AUC: 0.98, 95% CI: 0.97–0.99, p < 0.0001) and Support Vector Machine (SVM) (AUC: 0.97, 95% CI: 0.95–0.99, p < 0.0001) provided the highest diagnostic accuracy. The reliability of ensemble ML models was confirmed by MCDM and cluster analyses. Conclusions The combination of novel discriminant formula DF-6 and integration of XGB and SVM ML models can substantially strengthen nationwide screening programs to reduce the burden of thalassemia in Bangladesh.
M²B-Net: a lightweight multi-scale multi-attention boundary-aware network for liver tumor segmentation from CT images
Opportunities to strengthen US phosphorus supply resilience through circular pathways
With diminishing availability of high-quality phosphate rock and increasing supply uncertainties, improving phosphorus (P) recovery, recycling, and waste reduction has become critical for sustaining agricultural production. We developed an integrated P cycling and soil dynamics model to quantify 7 circular strategies for reducing mineral P demand in the United States, using data for 91 major crops and 20 livestock types across 3,142 counties from 1866 to 2050. We show that soil residual P reuse has the largest potential to reduce mineral P demand in the United States. By 2023, total soil P stocks had accumulated to 99 Tg, equivalent to approximately 68% of mineral P inputs over 1866–2023. For 2024–2050, projections under various socioeconomic scenarios indicate that soil residual P reuse alone could potentially supply approximately 2.4 to 5.1 times projected US mineral P demand, with substantial residual P stocks accumulated in both cropland and pastureland soils. Recycling from sewage sludge and livestock and crop by-products could collectively offset an additional approximately 0.5 to 1.0 times mineral P demand, while food waste reduction could reduce requirements by approximately 0.3 times. Spatial analyses further highlight a mismatch between circular P availability and cropland P demand, with high mineral P avoidance potential concentrated in the South and West, but relatively low ratios of circular P supply to projected mineral P demand across most counties in the Midwest. These findings provide spatially explicit and decision-relevant insights into how circular P strategies can enhance the stability and resilience of US food systems under future resource constraints.
Participatory Rapid Appraisal and Focus Groups to co-design technology-supported integrated care
Background Co-design methods, which create innovation tailored to the end-user needs and setting, are increasingly used to improve research uptake and impact. Peer review and methodologists have emphasised the need for early, meaningful, and continuous involvement of stakeholders, and the transparent and detailed reporting of co-design methods. The implementation of both complex interventions (such as an integrated care pathway), and technology, into healthcare is difficult and has high failure rates. Designing, implementing, and adapting interventions to ensure they work in the local context requires in-depth understanding of multiple end-users’ needs, processes, and contexts. Achieving this requires early, meaningful, and continuous engagement between multiple end-users. This study aimed to contribute to co-design research by reporting the: 1) process used to develop and test Participatory Rapid Appraisal and Focus Groups methods to co-design integrated care. 2) details of how the method was applied in the GERONTE project. 3) core steps involved in this co-design method (to facilitate use and/ or adaptation of the method). Aim The study aimed to develop, test, and evaluate a co-design method that: I. enabled early, continuous, and meaningful engagement of multiple end-users in different locations and across different design iterations. II. enabled timely feedback and checking between the end-users and design team. III. optimised end-users participation by being flexible in the time, duration, and method of data collection and feedback. Materials and methods The Participatory Rapid Appraisal and Focus Group to co-design integrated care method was developed in four stages. The first stage involved defining the project’s co-design needs and reviewing the co-design literature to identify how to meet these. GERONTE aimed to co-design, evaluate, and prepare for EU-wide deployment, an integrated technology-supported care pathway for older adults with cancer and other morbidities. Focus Groups and Participatory Rapid Appraisal, in combination, were chosen as an empirically-based and practical approach. Focus Groups (FG) provided a participatory-based way to collect data in order to identify and agree multiple stakeholders’ needs and collective priorities. Participatory Rapid Appraisal (PRA) provided a timely way; to gain participant feedback on the data collected; and, to ensure accuracy in the data sent to the pathway and technology design teams. The second stage involved applying the method in the GERONTE Project (using meetings between the project team, technologists, and older adults to develop a co-design protocol for the project). The third stage involved the use, refinement, evaluation, and reporting of the co-design method. The fourth stage, evaluation of the method, is ongoing. Results and discussion This study resulted in the development of a structured approach to using Participatory Rapid Appraisal and Focus Groups in combination to co-design technology-supported integrated care. This method is proposed as an evidenced-based, practical, user-friendly way to co-design (or adapt an existing design) an integrated technology-supported care pathway. This co-design method involves three cycles of design. Each cycle involves multidisciplinary FG to collect semi-structured data followed by rapid analysis and feedback of the FG data to the participants to design or refine the intervention.
Effective charge saturation in ferritin cages
Nf2 orchestrates β-arrestin2-biased PTH1R signaling to couple bone mass with skeletal integrity
Precise spatiotemporal regulation of parathyroid hormone (PTH) and PTH-related peptide signaling through the parathyroid hormone receptor 1 (PTH1R) is fundamental to skeletal development and metabolic bone remodeling, yet the intracellular mechanisms that fine-tune this signaling remain a central unanswered question. Here, we identify neurofibromin 2 (Nf2) as an essential regulator of PTH1R trafficking and signaling. Conditional knockout of Nf2 in chondrocytes results in short-limbed dwarfism, disrupted growth plate organization, and suppressed chondrocyte proliferation and hypertrophy, and a paradoxical bone phenotype marked by trabecular hyperproliferation and cortical thinning. Mechanistically, Nf2 binds to the PTH1R C-terminal domain (464–591 aa) to promote selective receptor internalization via β-arrestin2 without altering G protein–coupled receptor kinase-mediated PTH1R phosphorylation. Loss of Nf2 decouples PTH1R from β-arrestin2‐mediated endocytosis, leading to sustained and amplified signaling through the cAMP‐CREB‐pSOX9 (S181) and VEGF axis. Consequently, Nf2 -deficient mice exhibited bone changes similar to those induced by the PTH1R agonist abaloparatide. These findings establish Nf2 as a chondrocyte‐intrinsic gatekeeper of PTH1R signaling and uncover a cellular mechanism for bone homeostasis by targeting Nf2‐mediated β-arrestin2 recruitment.
Screening disease feature genes and analyzing correlations with immune cell infiltration in knee osteoarthritis chondrocytes based on multiple machine learning algorithms
Objective This study aimed to comprehensively analyze differentially expressed genes (DEGs) in chondrocytes from patients with knee osteoarthritis (OA) by integrating multiple machine learning algorithms and bioinformatics techniques, to unravel the underlying molecular mechanisms associated with OA chondrocytes, and to provide novel insights for the innovation of clinical therapeutic strategies. Methods We downloaded the GSE117999, GSE114007, GSE169077, GSE246425, and GSE178557 datasets from the public Gene Expression Omnibus (GEO) database as the training set, while GSE57218 served as an independent validation set. To ensure data consistency and comparability, the training set was normalized, and the ComBat algorithm was applied to eliminate batch effects, yielding a merged gene expression dataset. Subsequent differential expression analysis was performed to identify genes with significant changes under disease conditions, followed by enrichment analysis. To more accurately identify genes closely linked to disease characteristics, we independently analyzed the merged dataset using three machine learning algorithms: Lasso regression, random forest, and support vector machine (SVM). The intersection of results from these three methods was used to construct a robust list of disease-related feature genes. These prominent feature genes were validated in the training set and further externally confirmed using the GSE57218 dataset. Additionally, the CIBERSORT algorithm was employed to quantify immune cell infiltration in the normalized gene expression data, selecting infiltration results with high reliability (P < 0.05). Focusing on the target genes, we clarified the strength and significance of their associations with immune cell infiltration levels, comprehensively revealing differences in immune cell infiltration profiles between groups and the potential associations with target genes. Results DDIT3 and PFKFB3 were significantly downregulated in OA patients. DDIT3 was specifically associated with lipid metabolism, apoptosis, and inflammatory genes (e.g., TNFRSF12A ), whereas PFKFB3 was linked to phospholipid synthesis and cell cycle genes (e.g., CHKA ). Both genes were associated with core OA-related pathways, including PI3K-Akt and AGE-RAGE. Immune infiltration analysis revealed that DDIT3 was positively correlated with pro-inflammatory mast cells and M1 macrophages, while PFKFB3 was negatively correlated with activated dendritic cells. Collectively, these two genes were associated with immune cell infiltration patterns. The competing endogenous RNA (ceRNA) network analysis indicated that DDIT3 was associated with axes such as LINC00689-miR-769-5p , and PFKFB3 was associated with complex networks like GAS6-AS1-miR-146a-5p. Conclusion DDIT3 and PFKFB3 are key candidate genes associated with the pathological progression of OA. Their downregulation is correlated with inflammatory and metabolic disturbances in chondrocytes, supporting their potential use as diagnostic biomarkers and therapeutic targets for OA.
Effects of the Paleo diet on resting metabolic rate in handball players
Abstract The Paleolithic diet (PD) has positive effects on health status and body composition. The Paleo diet has been also used to assess the effects on handball players performance but the association of adherence to PD and resting metabolic rate (RMR) has not been investigated especially in this group. This study aimed to impact of the moderate-carbohydrate diet on RMR among professional handball players. Twenty-five handball players were assigned into two groups: 14 in the experimental group (the Paleo diet; PD) and 11 in the control group (rational diet; CD) for 8-weeks of normoenergetic nutritional intervention. Resting metabolic rate was measured by indirect calorimetry using a Cortex MetaLyzer 3R ergospirometer (Germany), using the breath-by-breath method. Oxygen uptake (VO 2 ), carbon dioxide production (VCO 2 ), respiratory quotient (RQ), RMR, and substrate utilization (carbohydrate, fat, protein) and energy expenditure from each substrate were measured during the measurement. There were no differences in RMR parameters, as well as VO 2 (L/min), VCO 2 (L/min), RQ, substrate utilization (g/day): CHO, PRO, FAT, and EE (kcal/hour) from each substrate between PD and CD groups. Eight weeks of a normoenergetic Paleo diet did not affect resting metabolic rate.
Adaptive self-organization of global swidden forests
Does swidden agriculture, a prototypical coupled human and natural system, exhibit a process of adaptive self-organization in which cultural practices balance environmental constraints through adaptive feedback? Here, we investigate whether quantitative signatures of adaptive self-organization can be detected in a dataset consisting of 18,000+ contiguous swidden patches in 18 remote sensing images of swidden mosaics from tropical and subtropical regions globally. We find that the distributions of patch sizes in 16 of 18 swidden areas exhibit power law patterns with scaling exponents ≈1, and correlation distances of ≈548 m. To account for these patterns, we develop a plausible ethnographically informed agent-based model of labor exchange, land use, and swidden site selection in which both sustainable and unsustainable resource uses can emerge out of interactions among individuals or households. By analyzing the model, we identify spatial synchronization of swidden sites as the driver of power law formation, while social norms of swidden labor can guide the system to an intermediate level of landscape disturbance. Both mechanisms are required to maintain harvests and ecosystem productivity at high levels. Our model advances theoretical understanding of the socioecological dynamics of swidden agriculture, and supports the hypothesis that adaptive self-organization may be a general characteristic of coupled human and natural systems.
Association between increased duodenal eosinophil count and functional dyspepsia
Background Functional dyspepsia (FD) is a common gastrointestinal disorder with multifactorial pathogenesis. Recent evidence suggests that duodenal eosinophilia may contribute to low-grade immune activation in FD. This study evaluated the association between increased duodenal eosinophil count and functional dyspepsia. Materials and methods This case-control study was conducted in the Department of Gastroenterology, Sir Salimullah Medical College, Mitford Hospital, Dhaka, Bangladesh, from January to December 2022. Forty-six adult patients with functional dyspepsia diagnosed by Rome-III criteria were included as cases, while forty age- and sex-matched individuals without functional dyspepsia undergoing upper gastrointestinal endoscopy for other indications with normal endoscopic findings served as controls. Multiple biopsies were obtained from the second part of the duodenum. Formalin-fixed paraffin-embedded tissue sections were stained with hematoxylin and eosin. Eosinophils were counted manually by light microscopy in five randomly selected high- power fields (x 400 magnification), and the mean eosinophil count per high-power field (HPF) was calculated. Results The mean duodenal eosinophil count was significantly higher in patients with functional dyspepsia compared with controls (23.98 ± 7.98 versus 15.63 ± 5.94 eosinophils/HPF, p <0.001). Duodenal eosinophilia (≥21 Eosinophils/HPF) was present in 69.6% of patients with functional dyspepsia compared with 17.5% of controls. Increased duodenal eosinophil count was significantly associated with functional dyspepsia (odds ratio 9.74, 95% confidence interval 3.50-27.08). Conclusions Patients with functional dyspepsia demonstrated significantly greater duodenal eosinophil infiltration than controls, supporting the role of low-grade immune activation in its pathogenesis. Further multicenter studies with larger samples are required to clarify the clinical implications of duodenal eosinophilia in functional dyspepsia.
Improving quantum-battery charging via unidirectional quantum jumps to metastable state
The tyrosine phosphatase STEP is a developmental suppressor of synaptogenesis
Striatal-Enriched Protein Tyrosine Phosphatase (STEP) constrains synaptic potentiation by dephosphorylating postsynaptic substrates, but its presynaptic role has remained unclear. Here, we identify a previously unrecognized function of STEP in regulating axonal differentiation and synapse assembly. Genetic and pharmacological manipulation of STEP in vivo and in vitro show that STEP limits presynaptic maturation by restricting synaptic vesicle protein clustering along developing hippocampal axons. Using a reconstituted circuit-on-a-chip we show that loss of presynaptic STEP is sufficient to significantly increase the number of axodendritic synapses. Functional imaging further revealed that the increased synaptic puncta observed in STEP KO neurons actively undergo depolarization-evoked vesicle exocytosis, representing bona fide functional synapses. Multielectrode array recordings reveal that STEP deletion increases neuronal excitability, and network synchrony, hallmarks of enhanced presynaptic efficacy. Mechanistically, these effects reflect sustained phosphorylation of STEP promoting presynaptic assembly and release competence. Importantly, inhibiting STEP also rescues presynaptic differentiation defects in Fmr1 KO neurons, implicating aberrant STEP signaling in Fragile X–associated synaptic pathology. Thus, STEP serves as a phosphatase gatekeeper that restrains presynaptic differentiation and neurotransmission, and its inhibition may offer a therapeutic strategy to correct synaptic deficits in Fragile X Syndrome.
Study protocol on antimicrobial resistance burden, transmission dynamics, and therapeutic bacteriophages in livestock and exposed farming populations in Nagpur, India: An integrated One Health approach
The rise in antimicrobial resistance (AMR) is a severe public health threat worldwide. India bears a disproportionately heavy burden of this problem due to ample antimicrobial usage in both humans and animals and scarce integrated surveillance. Since humans, animals, and environmental reservoirs which can harbour resistant microorganisms interact very closely on farms livestock, these are considered critical hotspots for the emergence and dissemination of antimicrobial-resistant bacteria and resistance genes. This work presents a 36-month prospective longitudinal observational study protocol aimed at quantifying the burden and characterizing the transmission dynamics of a selected set of key bacteria, that are clinically significant and hence, pathogenic— Escherichia coli , Staphylococcus aureus , Klebsiella pneumoniae , Streptococcus pneumoniae , Acinetobacter baumannii , and Pseudomonas aeruginosa —alongside their AMRprofiles in livestock, farm-exposed human populations, and environmental reservoirs in Nagpur, India, within the framework of One Health. Seasonal sampling of milk, animal faeces, human stool, soil, wastewater, drinking water, and animal feed will be carried out on dairy farms located in urban, peri-urban, and rural areas. Pathogens will be isolated using standard microbiological techniques and characterized based on antimicrobial susceptibility by employing VITEK®2 and disc diffusion methods. At the same time, bacteriophages against multidrug-resistant isolates will be isolated, purified, and characterized through plaque assays, host-range analysis, electron microscopy, and whole-genome sequencing for their therapeutic potential evaluation. Additionally, metagenomic next-generation sequencing will be utilized on a select number of samples to comprehensively characterize the resistomes and diversity of phages. The research will provide detailed longitudinal data on the frequency and spread of AMR among human, animal, and environmental compartments, create a biobank of AMR isolates and lytic bacteriophages, and offer genomic clues to delineate phage-based treatments and well-informed mitigation strategies of AMR within the framework of One Health in India. The results will be made public through peer-reviewed articles, presentations at scientific meetings, and deposition of sequence data in open-access databases.
Correlation of vitamin D levels with TNF-α and IL-6 expression in insulin-resistant type 2 diabetes mellitus patients
Cryo-EM reveals a right-handed double-helix dimer architecture of PCDH15
Tip links connect the stereocilia of mechanosensory hair cells in the inner ear and transmit force onto mechanotransduction (MET) channels. Tip links consist of protocadherin 15 (PCDH15) and cadherin 23, which assemble into an extracellular filament approximately 150 nm in length. Rare freeze-etched electron microscopy (EM) images have suggested that tip links could be right-handed double helices in vivo, but direct structural evidence has been lacking. Using cryo-EM we determined the structure of a large part of the extracellular PCDH15 domain. Two PCDH15 molecules form a parallel cis dimer stabilized by several dimerization interfaces, including two strand crossovers and two parallel contacts, yielding a right-handed double helix. Functional studies show that mutations in PCDH15 dimerization-domains impair MET. Our results establish the molecular foundation for how PCDH15 forms a right-handed double helix to enable mechanical sensing.
Mapping the terminology of the early rescue chain to the Foundation of ICD-11: Registered report protocol
Background The World Health Organization (WHO) emphasizes digital technologies as a key accelerator for strengthening health emergency preparedness and response. One such application is the early rescue chain (ERC), which coordinates automated alerting, responding, and clinical systems. However, current ERC implementations primarily rely on spoken language and lack standardized terminology. The ERC Terminology (ERC_T) defines the minimum set of concepts required for automated and standardized ERC information exchange. The International Classification of Diseases, 11th Revision (ICD-11) extensively covers adverse events in its sections: “External causes of morbidity or mortality” and “Dimensions of external causes”. However, there is no comprehensive mapping of ERC_T to the ICD-11 Foundation (ICD-11_F), the terminological resource from which the successor to ICD-10, ICD-11 Mortality and Morbidity Statistics (MMS), is derived. Therefore, we aim to: (I) assess semantic relationships between ERC_T and ICD-11_F; (II) evaluate the overall mapping quality; and (III) identify missing concepts and semantic gaps between ERC_T and ICD-11_F. Methods We will select ICD-11_F as the target of the mapping because of its greater specificity and its structure as a terminology rather than a classification that is constrained to a single-parent monohierarchy with residual categories. We will systematically map concepts from ERC_T to ICD-11_F using predefined mapping criteria and procedures. The mapping process addresses two complementary aspects of semantic alignment. First, we will classify the semantic relationship between an ERC_T concept and an ICD-11_F entity using HL7 FHIR ConceptMap relationships. Second, we will evaluate the quality of each mapping using ISO 21564:2025 (MapQual) measures, which provide a structured assessment of how well the ICD-11_F entity represents the ERC_T concept. Two coders will independently conduct the mapping following predefined mapping procedures. We will assess intercoder agreement using percentage and Krippendorff’s alpha (α), and will resolve disagreements through structured consensus or, if unresolved, by a senior expert.