What question did this study set out to answer?

Develop an ultrasensitive, portable nanobiosensor combined with machine learning for rapid point-of-care quantification of multi-cytokines and early identification of sepsis immunoparalysis.

August 15, 2026Journal of NanobiotechnologyOpen Access

A portable nanobiosensor with machine learning: enabling multi-cytokines point-of-care testing and early identification of sepsis immunoparalysis

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Authors

RYRongjun Yu JWJiangling Wu ACA Chen

Discussion

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Overview

Diagnostic development study demonstrates rapid multi-cytokine detection and sepsis immunoparalysis classification using a portable nanobiosensor, highlighting point-of-care clinical utility.

Key Points

Develop an ultrasensitive, portable nanobiosensor combined with machine learning for rapid point-of-care quantification of multi-cytokines and early identification of sepsis immunoparalysis.
Engineered a portable nanobiosensor based on a Nanozyme-Linked Immunosorbent Assay (NLISA) for parallel, independent detection of multiple cytokines in 30 µL plasma samples.
Trained machine learning models on multi-cytokine concentration profiles under varied conditions to classify sepsis stages.
Achieved a multi-cytokine limit of detection as low as 3.8 fg mL⁻¹ using 30 µL plasma volumes.
Accurately distinguished patients with sepsis immunoparalysis, sepsis without immunoparalysis, and healthy controls across multiple customizable cytokine panels.

Cite This Study

Yu et al. (2026) studied this question.

synapsesocial.com/papers/6a8019a975c2e31742c85c19 https://doi.org/10.1186/s12951-026-04939-5

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August 15, 2026Journal of NanobiotechnologyOpen Access

A portable nanobiosensor with machine learning: enabling multi-cytokines point-of-care testing and early identification of sepsis immunoparalysis

View Full Paper

Ask AI

Bookmark

Authors

RYRongjun Yu JWJiangling Wu ACA Chen

Discussion

Member takes

Overview

Diagnostic development study demonstrates rapid multi-cytokine detection and sepsis immunoparalysis classification using a portable nanobiosensor, highlighting point-of-care clinical utility.

Key Points

Develop an ultrasensitive, portable nanobiosensor combined with machine learning for rapid point-of-care quantification of multi-cytokines and early identification of sepsis immunoparalysis.
Engineered a portable nanobiosensor based on a Nanozyme-Linked Immunosorbent Assay (NLISA) for parallel, independent detection of multiple cytokines in 30 µL plasma samples.
Trained machine learning models on multi-cytokine concentration profiles under varied conditions to classify sepsis stages.
Achieved a multi-cytokine limit of detection as low as 3.8 fg mL⁻¹ using 30 µL plasma volumes.
Accurately distinguished patients with sepsis immunoparalysis, sepsis without immunoparalysis, and healthy controls across multiple customizable cytokine panels.

Cite This Study

Yu et al. (2026) studied this question.

synapsesocial.com/papers/6a8019a975c2e31742c85c19 https://doi.org/10.1186/s12951-026-04939-5

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