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Novel B-DNA dermatophyte assay for demonstration of canonical DNA in dermatophytes: Histopathologic characterization by artificial intelligence.
Gagna, Claude E; Yodice, Anthony N; D'Amico, Juliana; Elkoulily, Lina; Gill, Shaheryar M; DeOcampo, Francis G; Rabbani, Maryam; Kaur, Jai; Shah, Aangi; Ahmad, Zainab; Lambert, Muriel W; Clark Lambert, W.
Affiliation
  • Gagna CE; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA; Department of Pathology and Laboratory Medicine, Rutgers-New Jersey Medical School, Newark, New Jersey, USA; Department of Dermatology, Rutgers-New Jersey Medi
  • Yodice AN; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • D'Amico J; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • Elkoulily L; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • Gill SM; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • DeOcampo FG; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • Rabbani M; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • Kaur J; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • Shah A; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • Ahmad Z; Department of Biological and Chemical Sciences, College of Arts and Sciences, New York Institute of Technology, Old Westbury, New York, USA.
  • Lambert MW; Department of Pathology and Laboratory Medicine, Rutgers-New Jersey Medical School, Newark, New Jersey, USA; Department of Dermatology, Rutgers-New Jersey Medical School, Newark, New Jersey, USA.
  • Clark Lambert W; Department of Pathology and Laboratory Medicine, Rutgers-New Jersey Medical School, Newark, New Jersey, USA; Department of Dermatology, Rutgers-New Jersey Medical School, Newark, New Jersey, USA; Department of Medicine, Rutgers-New Jersey Medical School, Newark, New Jersey, USA.
Clin Dermatol ; 42(3): 233-258, 2024.
Article in En | MEDLINE | ID: mdl-38185195
ABSTRACT
We describe a novel assay and artificial intelligence-driven histopathologic approach identifying dermatophytes in human skin tissue sections (ie, B-DNA dermatophyte assay) and demonstrate, for the first time, the presence of dermatophytes in tissue using immunohistochemistry to detect canonical right-handed double-stranded (ds) B-DNA. Immunohistochemistry was performed using anti-ds-B-DNA monoclonal antibodies with formalin-fixed paraffin-embedded tissues to determine the presence of dermatophytes. The B-DNA assay resulted in a more accurate identification of dermatophytes, nuclear morphology, dimensions, and gene expression of dermatophytes (ie, optical density values) than periodic acid-Schiff (PAS), Grocott methenamine silver (GMS), or hematoxylin and eosin (H&E) stains. The novel assay guided by artificial intelligence allowed for efficient identification of different types of dermatophytes (eg, hyphae, microconidia, macroconidia, and arthroconidia). Using the B-DNA dermatophyte assay as a clinical tool for diagnosing dermatophytes is an alternative to PAS, GMS, and H&E as a fast and inexpensive way to accurately detect dermatophytosis and reduce the number of false negatives. Our assay resulted in superior identification, sensitivity, life cycle stages, and morphology compared to H&E, PAS, and GMS stains. This method detects a specific structural marker (ie, ds-B-DNA), which can assist with diagnosis of dermatophytes. It represents a significant advantage over methods currently in use.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: DNA, Fungal / Artificial Intelligence / Arthrodermataceae Limits: Humans Language: En Journal: Clin Dermatol / Clin. dermatol / Clinics in dermatology Year: 2024 Document type: Article Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: DNA, Fungal / Artificial Intelligence / Arthrodermataceae Limits: Humans Language: En Journal: Clin Dermatol / Clin. dermatol / Clinics in dermatology Year: 2024 Document type: Article Country of publication: Estados Unidos