Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome

Urinary levels of C24 ceramide, along with those of C24 ceramide plus LPI (18:3), could be potential biomarkers for HL. Machine learning-coupled urinary lipidomics may play an important role in the next-generation AI- driven diagnostic systems for IC/BPS.

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Publication Details

Journal
World Journal of Urology
Published
2025-04-18
DOI
https://doi.org/10.1007/s00345-025-05628-y
Citations
1
Primary Topic
Urinary Bladder and Prostate Research
Type
article
Field-Weighted Citation Impact
1.84

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Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome

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1 citations
World Journal of Urology
Urinary Bladder and Prostate Research
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article

Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome

Tomonori Minagawa, Masahiko Sumitani, Jun Kamei, Takuya Iwaki, Akira Nomiya, Yusuke Sato, Satoru Taguchi, Masaki Nakamura, Daisuke Yamada, Hiroshi Fukuhara, Yuta Yamada, Haruki Kume, Yukio Homma, Makoto Kurano, Yoshiyuki Akiyama, Aya Niimi
article en
1 citations

Abstract

Urinary levels of C24 ceramide, along with those of C24 ceramide plus LPI (18:3), could be potential biomarkers for HL. Machine learning-coupled urinary lipidomics may play an important role in the next-generation AI- driven diagnostic systems for IC/BPS.

World Journal of UrologyVol. 43(1)
Shinshu University (JP), Kyorin University (JP), NTT Medical Center (JP), University of Tokyo Hospital (JP), Japan Organization of Occupational Health and Safety (JP), Tokyo Metropolitan Tama Medical Center (JP), The University of Tokyo (JP)
Japan Agency for Medical Research and Development, Shinshu University, Japan Society for the Promotion of Science
Openalex Percentile: Top 18%
Urinary Bladder and Prostate Research
1.84
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