Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Automated Microbial Diagnostics

Automated Microbial Diagnostics

Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...

Three-Dimensional Microscopy in Microbiology

Three-Dimensional Microscopy in Microbiology

Three-dimensional imaging techniques are essential in cell biology, allowing researchers to visualize intricate cellular structures with high resolution. Two prominent methods, Differential Interference Contrast Microscopy (DIC) and Confocal Scanning Laser Microscopy (CSLM), provide distinct advantages for imaging live and thick specimens, respectively.Differential Interference Contrast MicroscopyDIC microscopy enhances contrast in transparent, unstained samples by converting phase...

You might also read

Related Articles

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

Sort by

Same author

Enantioselective Radical Cascade Cyclization to Axially Chiral Medium-Sized Lactones.

Angewandte Chemie (International ed. in English)·2026

Same author

(+)-Miliusol suppresses the Warburg effect and induces regulated cell death in triple-negative breast cancer through targeting EIF3D and remodeling cancer metabolism.

Acta pharmaceutica Sinica. B·2026

Same author

6-Methoxyluteolin from the Invasive Plant <i>Tithonia diversifolia</i> Suppresses Melanization and Impairs Epidermal Integrity in <i>Spodoptera litura</i> Larvae.

Insects·2026

Same author

Enhanced Anti-Counterfeiting Using Dynamic Encryption with Dual Physically Unclonable Functions.

ACS applied materials & interfaces·2026

Same author

ViT-ConvGAN: a hybrid model for spatiotemporal action recognition using video transformer and 3D CNN.

Scientific reports·2026

Same author

A ppb-Level Chloroform Photoacoustic Gas Sensor Based on Omnidirectional Acoustic Sensing with a 3D Microphone Phased Array.

Analytical chemistry·2026

Search research articles

Related Experiment Video

Updated: May 18, 2026

Rapid Detection of Helicobacter pylori Virulence and Typing Using Quantum Dot Labeling Technology

Rapid Detection of Helicobacter pylori Virulence and Typing Using Quantum Dot Labeling Technology

Published on: June 13, 2025

Highly Efficient Broad-Spectrum Antibacterial Carbon Dots through Hierarchical Machine Learning Framework.

Fu-Kui Li¹, Wen-Bo Zhao¹, Yong Wang¹

¹Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, School of Physics and Laboratory of Zhong Yuan Light, Zhengzhou University, Zhengzhou 450001, China.

|May 16, 2026

Summary

This summary is machine-generated.

Machine learning designed carbon dots (CDs) show high efficacy against antibiotic-resistant bacteria. These nanomaterials offer a promising strategy for developing next-generation antibacterial agents.

Keywords:

Antibacteria Broad-spectrum Carbon dots Machine learning Treating

Related Experiment Videos

Last Updated: May 18, 2026

Rapid Detection of Helicobacter pylori Virulence and Typing Using Quantum Dot Labeling Technology

Rapid Detection of Helicobacter pylori Virulence and Typing Using Quantum Dot Labeling Technology

Published on: June 13, 2025

Area of Science:

Nanomaterials Science
Machine Learning Applications
Antimicrobial Research

Background:

Antibiotic resistance poses a significant global health threat, demanding novel antibacterial strategies.
Developing effective broad-spectrum antibacterial nanomaterials requires intelligent design approaches.

Purpose of the Study:

To design and demonstrate high-efficacy, broad-spectrum antibacterial carbon dots (CDs) using a hierarchical machine learning (ML) framework.
To optimize the antibacterial performance of CDs through ML-guided prediction and screening.

Main Methods:

A hierarchical ML framework combining classification and regression models was developed.
Carbon dots (CDs) were screened for antibacterial type and their efficacy was predicted and optimized.
SHapley Additive exPlanations (SHAP) analysis was used to identify key determinants of antibacterial performance.

Main Results:

The ML-designed CDs achieved 99.99% bactericidal efficacy against both Gram-positive and Gram-negative pathogens.
Positively charged (+25 mV) and hydrophilic surfaces of CDs were identified as crucial for broad-spectrum activity.
In situ reactive oxygen species (ROS) generation contributed to efficient bacterial inactivation.
ML-designed CDs demonstrated significant therapeutic efficacy in a murine model of bacterial wound infection.

Conclusions:

Hierarchical ML-assisted strategies are effective for developing highly efficient, broad-spectrum antibacterial nanomaterials.
The designed carbon dots show potential as next-generation antibacterial agents to combat antibiotic resistance.