Assessment of the Severity of Atopic Dermatitis Using Atomic Force Microscopy Analysis of Skin Tape Strips
Non classé | Scientific PublicationsAssessment of the Severity of Atopic Dermatitis Using Atomic Force Microscopy Analysis of Skin Tape Strips
Allergy, 2025; 0:1-3
This letter for the European Journal of Allergy and Clinical Immunology presents new results showing that atomic force microscopy (AFM) can non-invasively assess the severity of atopic dermatitis (AD) by measuring tiny surface changes on skin cells collected with tape strips. Researchers quantified “circular nanosize objects” (CNOs)—small protrusions linked to skin-barrier damage—using a new index called the Effective Corneocyte Topographical Index (ECTI). In 120 participants, ECTI increased consistently with AD severity, even in skin that looked normal, while natural moisturizing factor levels showed the opposite trend. These findings suggest that AFM-based nanoscale measurements could help detect early barrier impairment and objectively monitor AD progression or treatment response.
Other articles
Skin Nanotexture Biometrics: A Novel Deep Learning Approach for Quantifying Atopic Dermatitis Severity Across Fitzpatrick Skin Types
Skin Nanotexture Biometrics: A Novel Deep Learning Approach for Quantifying Atopic Dermatitis Severity Across Fitzpatrick Skin TypesIFSCC 2025 Congress 2025, Full Paper (Abstract N° IFSCC2025-1771)This study presents a new deep learning method for objectively...
From bits to biometrics: sustainable hacking of optical storage technologies for atomic force microscopy and medical applications
From bits to biometrics: sustainable hacking of optical storage technologies for atomic force microscopy and medical applicationsJapanese Journal of Applied Physics 64 040804, 2025This article highlights how everyday tech from CD and Blu-ray players can be "hacked"...
Stratum corneum nanotexture feature detection using deep-learning and spatial analysis: a non-invasive tool for skin barrier assessment
Stratum corneum nanotexture feature detection using deep-learning and spatial analysis: a non-invasive tool for skin barrier assessmentGigaScience, 1-10, September 2024Building on prior work, this study improves atopic dermatitis severity assessment by refining...