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

You might also read

Related Articles

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

Sort by
Same author

Radiomics using contrast-enhanced T1-weighted imaging and clinical features for predicting response to EGFR-TKIs in EGFR-mutated non-small cell lung cancer patients with brain metastases.

BMC medical imaging·2026
Same author

Chlorine-induced severe ARDS in an adolescent rescued with VV-ECMO: a case report with 6-month functional follow-up.

Frontiers in pediatrics·2026
Same author

Magnetic resonance imaging characteristics of brain metastases from lung cancer.

Quantitative imaging in medicine and surgery·2026
Same author

Disturbed flow induced targeting of nanomedicine to endothelial cells for effective atherosclerosis therapy.

Cardiovascular research·2026
Same author

Guidewire incarceration in the femoral vein in a 6-month-old Boy.

Journal of cardiothoracic surgery·2026
Same author

The immune response of the mRNA vaccine CS-2034 as a heterologous booster before and after breakthrough infection: A follow-up study.

Vaccine·2026
Same journal

Peripheral B-cell receptor repertoire predicts immune-related adverse events following immune checkpoint inhibitor therapy in advanced renal cell carcinoma.

Scientific reports·2026
Same journal

Effects of black soldier fly (Hermetia illucens L.) larvae zoocompost on the mineral element content of blue honeysuckle berries.

Scientific reports·2026
Same journal

Investigation on absorption refrigeration performance of R1243zf with imidazolium ionic liquid as the working pairs.

Scientific reports·2026
Same journal

DeepTriage-CN: integrating clinical text with vital signs for emergency department admission prediction in an aging population.

Scientific reports·2026
Same journal

Gold nanoparticles as dual-action antiviral agents: disruption of SARS-CoV-2 viral envelopes and RNA integrity.

Scientific reports·2026
Same journal

Comparison of capillary microsampling and venous blood for multi-pathogen serosurveillance.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Mar 22, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
09:01

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Published on: March 14, 2019

7.8K

Semiconductor Electronic Label-Free Assay for Predictive Toxicology.

Yufei Mao1, Kyeong-Sik Shin1, Xiang Wang2

  • 1Department of Electrical Engineering, University of California, Los Angeles, CA 90095, USA.

Scientific Reports
|April 28, 2016
PubMed
Summary
This summary is machine-generated.

A new semiconductor electronic label-free assay (SELFA) offers sensitive, rapid toxicity screening for nanomaterials. This biosensing platform advances predictive toxicology by reducing reliance on animal testing.

More Related Videos

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks
04:53

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks

Published on: May 26, 2023

1.8K
Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

3.4K

Related Experiment Videos

Last Updated: Mar 22, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
09:01

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Published on: March 14, 2019

7.8K
Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks
04:53

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks

Published on: May 26, 2023

1.8K
Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

3.4K

Area of Science:

  • Biomedical Engineering
  • Toxicology
  • Nanotechnology

Background:

  • Animal testing presents logistical challenges for new material toxicity screening.
  • In vitro cellular-level screening, particularly secretomic assays, is crucial for prioritizing materials.
  • Existing assays like ELISA have limitations in sensitivity, throughput, and speed.

Purpose of the Study:

  • To develop a novel, highly sensitive, and rapid assay for predictive toxicology.
  • To introduce the semiconductor electronic label-free assay (SELFA) platform for secretomic analysis.
  • To evaluate SELFA's performance against standard assays and its utility in nanomaterial safety assessment.

Main Methods:

  • Development of a holistic assay platform and procedure named semiconductor electronic label-free assay (SELFA).
  • Incorporation of an amplifying nanowire field-effect transistor biosensor within the SELFA platform.
  • Deployment of SELFA secretomics for predicting inflammatory potential of engineered nanomaterials.

Main Results:

  • SELFA demonstrated superior sensitivity and comparable selectivity to standard enzyme-linked immunosorbent assay (ELISA).
  • SELFA offered a significantly shorter turnaround time compared to ELISA.
  • In vitro and in vivo validation confirmed SELFA's predictive accuracy for nanomaterial inflammatory potential.

Conclusions:

  • SELFA provides a high-sensitivity, label-free method for predictive toxicology.
  • The platform offers a viable alternative to traditional methods, potentially reducing animal experimentation.
  • This work establishes a foundation for advanced biosensing applications in material safety evaluation.