Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Overview Of Cell Separation And Isolation01:20

Overview Of Cell Separation And Isolation

Cell separation was first achieved in 1964 by S. H. Seal, who separated large tumor cells from the smaller blood cells using filtration. Two years later, Pohl and Hawk performed experiments on how cells respond differently to a nonuniform electric field based on the cell type. Such observations were the inception of cell separation methods, which allow isolating a single cell type from a heterogeneous sample.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A clinical evaluation of amlexanox oral adhesive pellicles in the treatment of recurrent aphthous stomatitis and comparison with amlexanox oral tablets: a randomized, placebo controlled, blinded, multicenter clinical trial.

Trials·2009
Same author

Long-term assessment of bladder and bowel dysfunction after radical hysterectomy.

Gynecologic oncology·2009
Same author

Oxidative stress contributes to silica nanoparticle-induced cytotoxicity in human embryonic kidney cells.

Toxicology in vitro : an international journal published in association with BIBRA·2009
Same author

A rapid and simple method for identifying Mycobacterium tuberculosis W-Beijing strains based on detection of a unique mutation in Rv0927c by PCR-SSCP.

Microbes and infection·2009
Same author

CO oxidation over AuPd(100) from ultrahigh vacuum to near-atmospheric pressures: the critical role of contiguous Pd atoms.

Journal of the American Chemical Society·2009
Same author

Daunorubicin-loaded magnetic nanoparticles of Fe(3)O(4) greatly enhance the responses of multidrug-resistant K562 leukemic cells in a nude mouse xenograft model to chemotherapy.

Zhongguo shi yan xue ye xue za zhi·2009
Same journal

The Potential for Bioactive Peptide Production in a Fermented Dairy Beverage Based on Chickpea Water Extract Using Proteolytic Lactic Acid Bacteria.

Foods (Basel, Switzerland)·2026
Same journal

Influence of Protein Concentration on Heat-Induced Fouling of Oat Drink.

Foods (Basel, Switzerland)·2026
Same journal

Microalgae as Future Foods: Unlocking Their Potential and Overcoming Barriers to Market Adoption and Commercialization.

Foods (Basel, Switzerland)·2026
Same journal

Effect of High-Intensity Ultrasound and Calcium Chelation on Functional Properties of Casein Micelles.

Foods (Basel, Switzerland)·2026
Same journal

GC-MS and GC-IMS Based Metabolomics Combined with Cellular Assays to Characterize Volatile Compounds and Pharmacological Activity of <i>Lysimachia foenum-graecum</i> Hance from Different Origins.

Foods (Basel, Switzerland)·2026
Same journal

Research on the Potential Mechanism of Guanine Nucleotides Enhancing the Tolerance of <i>Lactiplantibacillus plantarum</i> Y12.

Foods (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jun 27, 2026

BEST: Barcode Enabled Sequencing of Tetrads
12:59

BEST: Barcode Enabled Sequencing of Tetrads

Published on: May 1, 2014

Stable and High-Throughput Single-Cell Sorting of Food Bacteria Using Spatiotemporal Video-Enhanced Raman Tweezers.

Yi Sun1,2, Zhipeng Li1,2, Hua Xia1,2

  • 1State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.

Foods (Basel, Switzerland)
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

A new Spatiotemporal Video-Enhanced Raman Tweezers (SVERT) system rapidly detects foodborne pathogens in liquids. This innovation overcomes motion blur and low signal issues, significantly improving accuracy for food safety screening.

Keywords:
Raman tweezers spectroscopydetection and analysis methodsfood safetyfoodborne pathogensmicrofluidics

More Related Videos

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter
07:37

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Published on: February 13, 2014

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
09:09

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Published on: November 23, 2015

Related Experiment Videos

Last Updated: Jun 27, 2026

BEST: Barcode Enabled Sequencing of Tetrads
12:59

BEST: Barcode Enabled Sequencing of Tetrads

Published on: May 1, 2014

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter
07:37

Sorting of Streptomyces Cell Pellets Using a Complex Object Parametric Analyzer and Sorter

Published on: February 13, 2014

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
09:09

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Published on: November 23, 2015

Area of Science:

  • Microfluidics
  • Spectroscopy
  • Machine Learning

Background:

  • Rapid detection of foodborne pathogens is vital for food safety.
  • Raman tweezers spectroscopy (RTS) offers label-free single-cell analysis but struggles with high flow rates causing motion blur and low signal-to-noise ratios (SNR).
  • Existing methods are limited in high-throughput inline food inspection.

Purpose of the Study:

  • To develop an advanced system for rapid, high-throughput, and accurate detection of microorganisms in liquid food matrices.
  • To overcome the limitations of traditional RTS in dynamic, high-flow environments.
  • To enhance automated food safety screening using a novel microfluidic and deep learning approach.

Main Methods:

  • Integration of a deceleration-optimized microfluidic chip with a deep learning-based visual feedback loop, forming the Spatiotemporal Video-Enhanced Raman Tweezers (SVERT) system.
  • Development of a Local-Global Unified Denoising Network (LGU-Net) for high-fidelity bacterial structure recovery from low-SNR video streams.
  • Experimental validation using bacterial species relevant to food safety and testing in a commercial beverage sample.

Main Results:

  • The SVERT system achieved a deterministic processing latency of ~0.49 ms.
  • Optical trapping success rate dramatically improved from 21.27% ± 2% to 91.47% ± 1.8%.
  • Achieved 96.74% classification accuracy for four bacterial species and successfully isolated trace E. coli in a commercial beverage.

Conclusions:

  • The SVERT system effectively mitigates motion blur and low SNR issues in high-throughput microbial detection.
  • This technology significantly enhances spectral acquisition efficiency and bacterial classification accuracy.
  • The system demonstrates practical robustness for real-world food safety screening, with potential for broader applications.