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Updated: Jun 18, 2026

Rapid Subtractive Patterning of Live Cell Layers with a Microfluidic Probe
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ML-Powered MultiFluid-mRNAplex31: A Self-Developed Panel for Precise Tracing of Five Body Fluids.

Meiming Cai1, Qiong Lan1, Man Chen2

  • 1Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China.

Genomics, Proteomics & Bioinformatics
|June 16, 2026
PubMed
Summary

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This summary is machine-generated.

Forensic scientists can now precisely identify single-source and mixed body fluids using a new mRNA multiplex system and machine learning. This advanced method improves accuracy in crime scene investigations by reliably distinguishing between blood, saliva, and other crucial biological samples.

Area of Science:

  • Forensic molecular biology
  • Biotechnology
  • Genomics

Background:

  • Messenger RNA (mRNA) expression profiling is a sensitive method for identifying body fluid origins.
  • Current methods face challenges like false positives due to marker cross-reactivity.
  • Accurate body fluid identification is crucial for linking individuals to criminal activity.

Purpose of the Study:

  • To develop an advanced mRNA multiplex amplification system for precise body fluid identification.
  • To create robust machine-learning models for analyzing both single-source and mixed body fluid samples.
  • To enhance forensic capabilities in characterizing crime scenes through reliable biological sample analysis.

Main Methods:

  • Developed MultiFluid-mRNAplex31, an mRNA multiplex system with 26 body fluid-specific mRNAs, 2 sex-specific markers, and 3 housekeeping genes.
Keywords:
Body fluid identificationMachine learning algorithmMixed samplesMultiplex amplificationmRNA

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  • Utilized reverse transcription-polymerase chain reaction (RT-PCR) and capillary electrophoresis (CE) for multiplex amplification detection.
  • Created and evaluated four machine-learning models (random forest, SVM, NN, CatBoost) for body fluid classification.

    • Main Results:

    • The MultiFluid-mRNAplex31 system demonstrated exceptional species specificity, sensitivity, and robustness with aged and mixed samples.
    • Machine-learning models accurately identified five types of body fluids in single-source samples.
    • Support Vector Machine (SVM) and Neural Network (NN) models achieved an average accuracy exceeding 0.96 for mixed samples after 1000 validation iterations.

    Conclusions:

    • The developed system provides a comprehensive analysis for precise body fluid identification in forensic science.
    • This technology offers strong technical capabilities for distinguishing common single-source and mixed body fluids.
    • The integration of mRNA profiling and machine learning significantly advances forensic molecular biology.