Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 27, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Quantifying the Functional Gap in Alkaptonuria Through Machine Learning and Clinical Data Integration.

Anna Visibelli1, Rebecca Finetti1, Bianca Roncaglia1

  • 1Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy.

Bioengineering (Basel, Switzerland)
|June 26, 2026
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Architecture and dynamics of a supramolecular oxygen transport system in human homogentisate 1,2-Dioxygenase.

Journal of structural biology·2026
Same author

Unveiling a Novel Molecular Interaction and Pro-Metastatic Signaling Cascades Driven by KRIT1.

International journal of molecular sciences·2026
Same author

Serum Biomarkers in Bladder Cancer: NMR Metabolomics for Identification and Monitoring during Platinum-Based Therapy.

Oncology research·2026
Same author

Valorization of Chestnut By-Products: Extraction, Bioactivity, and Applications of Shells, Spiny Burs, and Leaves.

Life (Basel, Switzerland)·2026
Same author

Agricultural and Agro-Industrial Residues as Sustainable Sources of Next-Generation Biomedical Materials: Advances, Challenges, and Perspectives.

Life (Basel, Switzerland)·2025
Same author

Uncovering Proteomic and Biochemical Alterations in Plasma from Lesch-Nyhan Disease Patients.

Cellular and molecular neurobiology·2025
Same journal

Correction: Komatsu et al. Three-Dimensional Visualization and Detection of the Pulmonary Venous-Left Atrium Connection Using Artificial Intelligence in Fetal Cardiac Ultrasound Screening. <i>Bioengineering</i> 2026, <i>13</i>, 100.

Bioengineering (Basel, Switzerland)·2026
Same journal

Comparison of CO<sub>2</sub> Laser and Microdebrider in the Surgical Treatment of Pediatric Recurrent Respiratory Papillomatosis: A Retrospective Analysis.

Bioengineering (Basel, Switzerland)·2026
Same journal

Toward More Translational Tumor Models: Breast dECM-Based 3D Systems Capture Native Microenvironmental Cues.

Bioengineering (Basel, Switzerland)·2026
Same journal

Postural Stability Changes During the 4 Phases of the Half Squat: Kinematics Profile of the Center of Pressure and Center of Mass in High-Performance Weightlifters-A Pilot Study.

Bioengineering (Basel, Switzerland)·2026
Same journal

Definite Implant Position as Novel Readout for Effectiveness of Ridge Preservation Indicates to Beneficial Effect of Combined Treatment with Platelet-Rich Fibrin (PRF) and Xenogenic Biomaterial in Bone Regeneration.

Bioengineering (Basel, Switzerland)·2026
Same journal

Trueness and Precision of Intraoral Scanners for 3D-Printed Orthodontic Models with Attachments: An In Vitro Comparative Study.

Bioengineering (Basel, Switzerland)·2026
See all related articles
This summary is machine-generated.

Alkaptonuria (AKU) patients are functionally older than their chronological age, with a 15-year average functional age gap. This metric helps assess AKU

Area of Science:

  • Rare inherited metabolic disorders
  • Musculoskeletal health
  • Biostatistics and data analysis

Background:

  • Alkaptonuria (AKU) causes progressive musculoskeletal damage and chronic pain.
  • Functional heterogeneity is a key characteristic of AKU patients.
  • Quantifying functional variability is crucial for AKU management.

Purpose of the Study:

  • Introduce and validate the functional age gap as a metric for AKU.
  • Explore clinical predictors of functional age gap severity.
  • Assess the utility of functional age gap in AKU patient assessment.

Main Methods:

  • Utilized the ApreciseKUre database with 134 AKU patients.
  • Calculated functional age using HAQ-DI and KOOS scores against normative data.
Keywords:
alkaptonuriadata integrationfunctional gapmachine learningprecision medicinerare diseases

More Related Videos

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

Related Experiment Videos

Last Updated: Jun 27, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

  • Employed a bagging ensemble of decision trees and SHapley Additive exPlanations for analysis.

    • Main Results:

    • 94.8% of AKU patients exhibited a positive functional age gap, averaging 15 years older.
    • The predictive model showed moderate, stable classification performance (64%).
    • Key predictors included age, AKUSSI spinal/joint pain, Schober test, and hip/knee activity.

    Conclusions:

    • The functional age gap is a valuable, interpretable metric for describing functional status in AKU.
    • It serves as a hypothesis-generating tool for AKU research.
    • Further validation in larger, longitudinal cohorts is needed for predictive utility.