Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 322

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

A Unique “Integration” Strategy for the Rational Design of Optically Tunable Near-Infrared Fluorophores

Chen, Hua, Dong, Baoli, Tang, Yonghe, Lin, Weiying·2017·Accounts of Chemical Research

Abstract

Fluorescence imaging is a rapidly growing technique for noninvasive imaging of biological molecules and processes with high spatial and temporal resolution. For effective biological imaging, it is essential and important to develop robust fluorescent dyes, in particular, near-infrared (NIR) fluorescent dyes with favorable optical properties. Compared with the visible light emitting dyes, NIR dyes have relatively longer emission wavelengths (650-900 nm) with lower energy and are advantageous as imaging agents owing to the minimum photodamage of NIR light to biological samples, deep penetration into tissues, and low interference from autofluorescence of biomolecules. Although great efforts have been devoted to engineer NIR fluorophores, it is still very challenging to regulate their photophysical properties as they often lack optically tunable mechanisms, and this shortcoming considerably restricts the realization of their full potential. Consequently, the rational design of small-molecule optically tunable NIR fluorophores is of high priority and great value. In general, two key characteristics are indispensable for designing excellent optically tunable NIR fluorescent dyes. First, NIR fluorescent dyes should display the maximal absorption and emission located in the NIR region and also have the prominent properties including excellent fluorescence quantum yields, large Stokes shifts, good chemical stability and photostability, low cytotoxicity, and desirable compatibility with biological systems. Second, in principle, functional NIR dyes should also possess optically tunable groups, which can be easily modified to afford responsive sites for the targets of interest. With these considerations in mind, in this Account, we described a unique "integration" strategy for judicious design of the optically tunable NIR fluorophores, which are an intuitive combination of the traditional NIR dyes and the optically tunable mechanisms in the visible light emissive dyes. Thus, the versatile strategy may allow not only retention of the NIR emission properties of NIR dyes but also inheritance of the optically tunable mechanisms from the visible light emissive dyes. By the unique integration strategy, a built-in optically tunable group is strategically installed into the traditional NIR fluorescent dyes to directly tune their optical properties. Herein, we present a concise review of the rational design strategy and biological applications of small-molecule optically tunable NIR fluorescent dyes via the unique integration strategy, and we focused mainly on our work and some representative examples from other groups based on our NIR platforms. This Account includes the detailed integration strategy of each class of the NIR fluorescent dyes, the development of their derivatives, and their imaging applications in living systems.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acs.accounts.7b00087

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 27 references

Cited by

See all 322

Metadata

Authors
Chen, H., Dong, B., Tang, Y., & Lin, W.
Venue
Accounts of Chemical Research
Published
2017-05-11
Volume
50
Issue
6
Pages
1410-1422
ISSN
  • 0001-4842 (ISSN-L)
  • 1520-4898
OpenAlex
W2612254178
Cited by
322
References
27
FWCI
19.31
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A Unique “Integration” Strategy for the Rational Design of Optically Tunable Near-Infrared Fluorophores. https://app.cochat.ai/papers/10.1021/acs.accounts.7b00087
The paper
Chen, H., Dong, B., Tang, Y., & Lin, W. (2017). A Unique “Integration” Strategy for the Rational Design of Optically Tunable Near-Infrared Fluorophores. Accounts of Chemical Research. https://doi.org/10.1021/acs.accounts.7b00087

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.