Peptide-based materials are one of the most important biomaterials, with diverse structures and functionalities. Over the past few decades, a self-assembly strategy is introduced to construct peptide-based nanomaterials, which can form well-controlled superstructures with high stability and multivalent effect. More recently, peptide-based functional biomaterials are widely utilized in clinical applications. However, there is no comprehensive review article that summarizes this growing area, from fundamental research to clinic translation. In this review, the recent progress of peptide-based materials, from molecular building block peptides and self-assembly driving forces, to biomedical and clinical applications is systematically summarized. Ex situ and in situ constructed nanomaterials based on functional peptides are presented. The advantages of intelligent in situ construction of peptide-based nanomaterials in vivo are emphasized, including construction strategy, nanostructure modulation, and biomedical effects. This review highlights the importance of self-assembled peptide nanostructures for nanomedicine and can facilitate further knowledge and understanding of these nanosystems toward clinical translation.

Self-Assembled Peptide-Based Nanomaterials for Biomedical Imaging and Therapy.

An assembly-induced retention effect for enhanced tumor photoacoustic (PA) imaging and therapeutics is described. A responsive small-molecule precursor is prepared that simultaneously self-assembles into nanofibers in tumor sites that exhibit an assembly-induced retention effect, which results in an improved PA imaging signal and enhanced therapeutic efficacy. This successful proof-of-concept study paves the way to develop novel supramolecular biomaterials for cancer diagnostics and therapeutics.

In Situ Formation of Nanofibers from Purpurin18‐Peptide Conjugates and the Assembly Induced Retention Effect in Tumor Sites

Polymeric nanoparticles promote macrophage reversal from M2 to M1 phenotypes in the tumor microenvironment.

A peptide-conjugated poly(β-amino ester) that self-assembles into micelle-like nanoparticles is prepared by a convenient and modular supramolecular approach. The polymer-beclin-1 (P-Bec1) nanoparticles display enhanced cytotoxicity to breast cancer cells through induction of autophagy. This approach overcomes two major limitations of the haploinsufficient tumor suppressor Bec1 compared to small-molecule drugs: poor delivery to tumors owing to enzymatic degradation, and unstable, non-specific bio-distribution and targeting in the tumor tissues.

Self‐Assembled Autophagy‐Inducing Polymeric Nanoparticles for Breast Cancer Interference In‐Vivo

Geometrical shape of nanoparticles plays an important role in cellular internalization. However, the applicability in tumor selective therapeutics is still scarcely reported. In this article, we designed a tumor extracellular acidity-responsive chimeric peptide with geometrical shape switch for enhanced tumor internalization and photodynamic therapy. This chimeric peptide could self-assemble into spherical nanoparticles at physiological condition. While at tumor extracellular acidic microenvironment, chimeric peptide underwent detachment of acidity-sensitive 2,3-dimethylmaleic anhydride groups. The subsequent recovery of ionic complementarity between chimeric peptides resulted in formation of rod-like nanoparticles. Both in vitro and in vivo studies demonstrated that this acidity-triggered geometrical shape switch endowed chimeric peptide with accelerated internalization in tumor cells, prolonged accumulation in tumor tissue, enhanced photodynamic therapy, and minimal side effects. Our results suggested t...

Tumor-Triggered Geometrical Shape Switch of Chimeric Peptide for Enhanced in Vivo Tumor Internalization and Photodynamic Therapy.

https://www.rsc.org/suppdata/py/c3/c3py01117h/c3py01117h.pdf

One-pot synthesis of pH-sensitive poly(RGD-co-β-amino ester)s for targeted intracellular drug delivery

Two-phase flow is a kind of complex fluid flow state, and the flow pattern characteristics are very difficult to obtain accurately. First, the principle of two-phase flow pattern image reconstruction based on electrical resistance tomography technology and the complex flow pattern recognition method are developed. Next, the back propagation (BP), wavelet, and radial basis function (RBF) neural networks are applied to the two-phase flow pattern image identification process. The results show that the RBF neural network algorithm has higher fidelity and faster convergence speed than the BP and wavelet network algorithms, and the fidelity is more than 80%. Then, deep learning of the pattern recognition algorithm fusing the RBF network and convolution neural network is proposed to improve the precision of the flow pattern identification. Additionally, the recognition accuracy of the fusion recognition algorithm is more than 97%. Finally, a two-phase flow test system is constructed, the test is finished, and the correctness of the theoretical simulation model is verified. The research process and results provide important theoretical guidance for the accurate acquisition of two-phase flow patterns.

Theoretical and experimental research on two-phase flow image reconstruction and flow pattern recognition.

Objective We aimed to explore the relationship of sleep efficiency (SE) with the prevalence of hypertension in Chinese obstructive sleep apnea (OSA) patients based on polysomnography (PSG) records. Methods We studied 2360 patients with OSA and 764 primary snorers who underwent PSG in our hospital. SE was divided into three grades, including ≥85%, 80%~84.9%, and <80%. Hypertension was defined based either on direct blood pressure measurements, under anti-hypertensive treatments or on physician diagnosis. Multivariate logistic regression models were conducted to investigate the association between SE and hypertension. Results After adjusting for potential confounding factors, OSA patients with <80% SE and those with 80% to 84.9% SE were significantly associated with the prevalence of hypertension (OR = 1.248, 95% CI 1.018~1.531, P=0.033; OR = 1.380, 95% CI 1.040~1.832, P=0.026). Compared to primary snorers, OSA combined with <85% SE increased the odds of hypertension. In stratified analysis by SE, risk of hypertension only in those with <80% SE was significantly different between OSA and primary snorers. Furthermore, this relationship between reduced SE and hypertension was evident especially in female, younger ages, obese, moderate and severe OSA patients. No significant relationship between reduced SE and hypertension was found in primary snores group. Conclusion We found that poor SE was correlated with the prevalence of hypertension in Chinese OSA patients, but not in those with primary snoring. Moreover, this relationship was evident especially in female, younger ages, obese, moderate and severe OSA patients.

Yu Chen

Papers

One-pot synthesis of pH-sensitive poly(RGD-co-β-amino ester)s for targeted intracellular drug delivery

Theoretical and experimental research on two-phase flow image reconstruction and flow pattern recognition.

Association Between Sleep Efficiency and Hypertension in Chinese Obstructive Sleep Apnea Patients