Evidence map›Paper›PMID 40763470›Full record

ArticleBiosensors & bioelectronics2025

High-temporal-resolution on-site multiplex biomarker monitoring in small animals using microfluidic digital ELISA.

Yujing Song, Andrew D Stephens, Huiyin Deng, Adrienne D Füredi, Shiuan-Haur Su, Yuxuan Ye, Yuxiang Chen, Michael Newstead, Qingtian Yin, Jason Lehto and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biosensors & bioelectronics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  4. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Yujing SongDepartment of Mechanical and Aerospace Engineering, New York University, Brooklyn, NY, 11201, USA; Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA. Electronic address: ys6780@nyu.edu.
Andrew D StephensDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA; Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI, 48109, USA.
Huiyin DengDepartment of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI, 48109, USA; Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, PR China.
Adrienne D FürediDepartment of Biomedical Engineering, New York University, Brooklyn, NY, 11201, USA.
Shiuan-Haur SuDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Yuxuan YeDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Yuxiang ChenDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Michael NewsteadDepartment of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI, 48109, USA.
Qingtian YinDepartment of Mechanical and Aerospace Engineering, New York University, Brooklyn, NY, 11201, USA.
Jason LehtoDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Zeshan FahimDepartment of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI, 48109, USA.
Benjamin H SingerDepartment of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI, 48109, USA; Weil Institute for Critical Care Research & Innovation, Ann Arbor, MI, 48109, USA. Electronic address: singerb@med.umich.edu.
Katsuo KurabayashiDepartment of Mechanical and Aerospace Engineering, New York University, Brooklyn, NY, 11201, USA; Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA; Weil Institute for Critical Care Research & Innovation, Ann Arbor, MI, 48109, USA; Department of Chemical and Biomolecular Engineering, New York University, Brooklyn, NY, 11201, USA. Electronic address: katsuo.k@nyu.edu.

Funding

PULMONARY CELLULAR AND MOLECULAR BIOLOGY TRAININGT32HL007749 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Robert Pickett Dickson · 1993 to 2026
$19.9M
Enhancement of Brain Dysfunction in Sepsis Survivors by Alzheimer’s Disease NeuropathologyR01AG074968 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Benjamin Herschel Singer · 2022 to 2026
$3.3M
The µSiM-hNVU - a human BBB platform for the study of brain injury mechanisms during systemic infectionR33HL154249 · NHLBI · UNIVERSITY OF ROCHESTER · PI ENGELHARDT, BRITTA, GABORSKI, THOMAS R · 2022 to 2024
$2.2M
NHLBI NIH HHS R33 HL154249NHLBI NIH HHS T32 HL007749NIA NIH HHS R01 AG074968
6 · The paper itself

Abstract

Time-course monitoring of blood biomarkers with rapid turnaround has the potential to revolutionize the diagnosis, stratification of phenotypes, and therapeutic/prognostic approaches for various acute inflammatory diseases in both clinical and preclinical studies. Current approaches, however, are hampered by slow turnaround times and large sample volume requirements, limiting the exploration of disease mechanisms and therapeutic strategies. Here, we developed a microfluidic digital ELISA platform prototype, combining single-molecule counting with whole blood assay capability for the first time from small animal models. This platform is semi-automated and enables repeated, rapid biomarker monitoring with just 3.5 μL of whole blood collected from the tail. Our platform demonstrated high sensitivity and multiplexity, allowing real-time cytokine profiling within a 2-h turnaround. Using a murine sepsis model, we achieved precise temporal monitoring of cytokine levels, demonstrating prognostic capability by correlating early-stage cytokine levels with a liver-injury biomarker. This microfluidic platform enables high temporal resolution and rapid monitoring of biomarker dynamics in a single mouse using freshly collected whole blood, significantly reducing the number of animals needed for preclinical studies. This technology has strong potential to transform ICU therapeutic strategies and preclinical research, enabling personalized treatment based on real-time biomarker profiles.

Indexed as

Biosensing TechniquesCytokinesLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesSepsisAnimalsBiomarkersDisease Models, AnimalEnzyme-Linked Immunosorbent AssayEquipment DesignHumansMiceBiomarkersCytokinesDigital ELISAMicrofluidicsSepsisTime-courseWhole blood

Identifiers

PMID40763470
PMCPMC12415874

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.