A diketopyrrolopyrrole-based small molecule with an extended conjugated skeleton and J-aggregation behavior for 808 nm laser triggered phototheranostics.

The development of phototheranostic agents, specifically those based on organic small molecules (OSMs) with long wavelength excitation/emission, is an attractive but challenging project. In this contribution, we designed and synthesized a novel conjugate small molecule with a linear structure, named DPP-OPIC. Water-soluble nanoparticle DPP-OPIC NPs were fabricated. They exhibited strong absorption in the region of 600-1000 nm, which was due to the extended conjugate length of the molecular skeleton and J-aggregation behavior. Under 808 nm laser excitation, DPP-OPIC NPs were capable of producing outstanding near-infrared-II (NIR-II, 900-1700 nm) fluorescence. The photoluminescence quantum yield was determined as 0.58%, which enabled high-resolution in vivo tumor imaging. Additionally, a notable photothermal effect with a high photothermal conversion efficiency (41.5%) was achieved by the irradiation of DPP-OPIC NPs. Hence, DPP-OPIC NPs can be used as superior phototheranostic agents, providing valuable contributions to NIR-II fluorescence imaging and photothermal therapy.

Molecular Oligomerization and Donor Engineering Strategies for Achieving Superior NIR-II Fluorescence Imaging and Thermotherapy under 1064 nm Laser Irradiation.

An enormous challenge still exists for designing molecules with the second near-infrared (NIR-II, 1000-1700 nm) window absorption, NIR-II fluorescence emission, and batch-to-batch reproducibility, which is the premise for high-performance NIR-II phototheranostics. Although organic small molecules and polymers have been largely explored for phototheranostics, it is difficult to satisfy the above three elements simultaneously. In this work, molecular oligomerization (the general structure is S-D-A-D'-A-D-S) and donor engineering (changing the donor linker D') strategies are applied to design phototheranostic agents. Such strategies are proved to be efficient in adjusting molecular configuration and energy level, affecting the optical and thermal properties. Three oligomers (O-T, O-DT, and O-Q) are further prepared into water-soluble nanoparticles (NPs). Particularly, the O-T NPs exhibit a higher molar extinction coefficient at 1064 nm (≈4.3-fold of O-DT NPs and ≈4.8-fold of O-Q NPs). Furthermore, the O-T NPs show the highest NIR-II fluorescence brightness and heating capacity (PCE = 73%) among the three NPs under 1064 nm laser irradiation and served as agents for NIR-II imaging guided in vivo photothermal therapy. Overall, by using molecular oligomerization and donor engineering strategies, a powerful example of constructing high-performance NIR-II phototheranostics for clinical translation is given.

Multispectral palmprint recognition using a quaternion matrix.

Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.