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Exploring scanning electrochemical probe microscopy in single-entity analysis in biology: Past, present, and future. | LitMetric

Exploring scanning electrochemical probe microscopy in single-entity analysis in biology: Past, present, and future.

Biosens Bioelectron

Hubei University of Science & Technology, Xianning Medical College, Xianning, Hubei, 437100, China. Electronic address:

Published: March 2025

AI Article Synopsis

  • Scanning Electrochemical Probe Microscopy (SEPM) is a promising tool for analyzing localized electrochemical activity at biological interfaces, enabling real-time monitoring of single entities' morphology and physiological activities.
  • The review highlights five specific SEPM techniques that provide high-resolution imaging and quantitative analysis of biological structures, emphasizing their distinct advantages in observing and evaluating biological morphology.
  • The integration of Artificial Intelligence (AI) is discussed as a way to enhance data processing and image analysis, paving the way for automation and deeper analysis in SEPM technology despite still being in an early developmental stage.

Article Abstract

Scanning Electrochemical Probe Microscopy (SEPM) shows significant potential promise for analyzing localized electrochemical activity at biological interfaces of single entities. Utilizing various SEPM probe manipulations allows real-time monitoring of the morphology and physiological activities of single biological entities, offering vital electrochemical insights into biological processes. This review focuses on the application of five SEPM techniques in imaging single biological entities, highlighting their unique advantages in the observation and quantitative evaluation of biological morphology. Specifically, these techniques not only enable high-resolution imaging of single biological structures but also allow for quantitative analysis of their response behavior. Additionally, the integration of Artificial Intelligence (AI) is discussed to improve data processing and image analysis, potentially advancing SEPM technology towards automation. Although still in an early stage, AI integration opens new avenues for deeper single-entity analysis. This review aims to offer an interdisciplinary perspective and encourage advancements in SEPM-based imaging and analytical techniques, contributing to the bioanalytical field.

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Source
http://dx.doi.org/10.1016/j.bios.2024.117060DOI Listing

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