Aggregation enhanced fluorescence and Raman signals for highly sensitive cancer detection

Guo, Rui; Qi, Yu; Li, Junrong

doi:10.1016/j.ymeth.2023.06.001

Methods

2023

DOI: 10.1016/j.ymeth.2023.06.001

|View full text |Cite

Aggregation enhanced fluorescence and Raman signals for highly sensitive cancer detection

Rui Guo

Yu Qi

Junrong Li

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Complexity made easy: Aggregation‐induced emission small molecules for cancer diagnosis and phototherapies

Chen,

Yuan

et al. 2024

Aggregate

View full text Add to dashboard Cite

Phototheranostics has garnered sustained attention due to its significant potential for revolutionizing conventional cancer treatment strategies. While being one of the most commonly employed strategies for constructing phototheranostic systems by engineering the integration of photosensitizers (PSs) into nanosystems, nano‐PSs face challenges including complexity in the preparation process, low delivery efficiency, and potential toxicity issues. Contrastingly, the burgeoning popularity of small molecule PSs characterized by aggregation‐induced emission (AIE) has become evident in the arena of cancer phototheranostics. This preference is underscored by their well‐defined structures, adjustable photophysical properties, and low toxicity. Therefore, acquiring profound insights into the pioneering strides achievable through a solitary small molecule PS with AIE in tumor phototheranostics is of paramount scientific significance. In this review, we will discuss the recent progress of small molecule PSs with AIE properties in cancer diagnosis and phototherapies with representative examples, guided by the ethos of “Complexity made easy”. We also look forward to the future development direction of AIE small molecules, with a central objective of advancing cancer research through a focal emphasis on simplicity, expeditiousness, and safety.

show abstract

Complexity made easy: Aggregation‐induced emission small molecules for cancer diagnosis and phototherapies

Chen,

Yuan

et al. 2024

Aggregate

View full text Add to dashboard Cite

show abstract

Applying virtual sample generation and ensemble modeling for improving the spectral diagnosis of cancer

Chen,

Tan,

Lin

et al. 2024

Spectrochimica Acta Part A: Molecular and Biomolecular Spectros

View full text Add to dashboard Cite

Special issue Methods: Nano-/bio-interface and biomedical applications

Li,

Wuethrich

2024

Methods

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Aggregation enhanced fluorescence and Raman signals for highly sensitive cancer detection

Cited by 3 publications

References 57 publications

Complexity made easy: Aggregation‐induced emission small molecules for cancer diagnosis and phototherapies

Complexity made easy: Aggregation‐induced emission small molecules for cancer diagnosis and phototherapies

Applying virtual sample generation and ensemble modeling for improving the spectral diagnosis of cancer

Special issue Methods: Nano-/bio-interface and biomedical applications

Contact Info

Product

Resources

About