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Mass spectrometry combined with machine learning identifies novel protein signatures as demonstrated with multisystem inflammatory syndrome in children

Crossref DOI link: https://doi.org/10.1038/s41598-025-20684-5

Published Online: 2025-10-22

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Guzmán Rivera, Jeisac

Zheng, Haiyan

Richlin, Benjamin

Suarez, Christian

Gaur, Sunanda

Ricciardi, Elizabeth

Hasan, Uzma N.

Cuddy, William

Singh, Aalok R.

Bukulmez, Hulya

Kaelber, David C.

Kimura, Yukiko

Brady, Patrick W.

Wahezi, Dawn

Rothschild, Evin

Lakhani, Saquib A.

Herbst, Katherine W.

Hogan, Alexander H.

Salazar, Juan C.

Moroso-Fela, Sandra

Roy, Jason

Kleinman, Lawrence C.

Horton,, Daniel B.

Moore, Dirk F.

Gennaro, Maria Laura
Funding

Funding for this research was provided by:

Eunice Kennedy Shriver National Institute of Child Health and Human Development (R61HD105619)
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Text and Data Mining valid from 2025-10-22

Version of Record valid from 2025-10-22
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Article History

Received: 20 June 2025

Accepted: 16 September 2025

First Online: 22 October 2025

Declarations

:

: The authors declare no competing interests.

: All study activities were approved by the Rutgers Institutional Review Board (Pro2020002961) and all methods were performed in accordance with the relevant guidelines. All participants, including parents and/or legal guardians, provided informed consent prior to engaging in study activities.

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