On-chip optical wavefront shaping by transverse-spin-induced Pancharatanam-Berry phase.

Pancharatnam-Berry (PB) metasurfaces can be applied to manipulate the phase and polarization of light within subwavelength thickness. The underlying mechanism is attributed to the geometric phase originating from the longitudinal spin of light. Here, we demonstrate, to the best of our knowledge, a new type of PB geometric phase derived from the intrinsic transverse spin of guided light. Using full-wave numerical simulations, we show that the rotation of a metallic nano-bar sitting on a metal substrate can induce a geometric phase covering 2π full range for the surface plasmons carrying an intrinsic transverse spin. Especially, the geometric phase is different for the surface plasmons propagating in opposite directions due to spin-momentum locking. We apply the geometric phase to design metasurfaces to manipulate the wavefront of surface plasmons to achieve steering and focusing. Our work provides a new mechanism for on-chip light manipulations with potential applications in designing ultra-compact optical devices for imaging and sensing.

pH/H2 O2 Cascade-Responsive Nanoparticles of Lipid-Like Prodrugs through Dynamic-Covalent and Coordination Interactions for Chemotherapy.

Traditional lipid nanoparticles (LNPs) suffer from low drug loading capacity (DLC), weak stability, and lack of responsiveness. Conventional approaches to address these issues involve the synthesis of lipid-prodrug by incorporating responsive covalent linkers. However, such approaches often result in suboptimal sensitivity for drug release and undermine therapeutic effectiveness. Herein, the study reports a fundamentally different concept for designing lipid-like prodrugs through boron-nitrogen (B-N) coordination and dynamic covalent interaction. The 5-fluorouracil-based lipid-like prodrugs, featuring a borate ester consisting of a glycerophosphoryl choline head and a boronic acid-modified 5Fu/dodecanamine complex tail, are used to prepare pH/H2 O2 cascade-responsive LNPs (5Fu-LNPs). The 5Fu-LNPs exhibit enhanced DLC and stability in a neutral physiological environment due to the B-N coordination and enhanced hydrophobicity. In tumors, acidic pH triggers the dissociation of B-N coordination to release prodrugs, which further responds to low H2 O2 concentrations to release drugs, showcasing a potent pH/H2 O2 -cascade-responsive property. Importantly, 5Fu-LNPs demonstrate greater antitumor efficiency and lower toxicity compared to the commercial 5Fu. These results highlight 5Fu-LNPs as a safer and more effective alternative to chemotherapy. This work presents a unique LNP fabrication strategy that can overcome the limitations of conventional LNPs and broaden the range of intelligent nanomaterial preparation techniques.

Correction: Pyrrolopyrrole aza-BODIPY near-infrared photosensitizer for dual-mode imaging-guided photothermal cancer therapy.

Correction for 'Pyrrolopyrrole aza-BODIPY near-infrared photosensitizer for dual-mode imaging-guided photothermal cancer therapy' by Chaolong Wu et al., Chem. Commun., 2019, 55, 790-793, https://doi.org/10.1039/C8CC07768A.

Reactive Oxygen Species-Responsive Gel-Based Microneedle Patches for Prolonged and Intelligent Psoriasis Management.

Psoriasis is an inflammatory skin disease. Microneedle (MN) patches can improve psoriasis treatment outcomes by increasing local drug content in the skin. As psoriasis frequently relapses, developing intelligent MN-based drug delivery systems with prolonged therapeutic drug levels and improved treatment efficiency is of great significance. Here, we designed detachable H2O2-responsive gel-based MN patches containing methotrexate (MTX) and epigallocatechin gallate (EGCG) by using EGCG as both cross-linkers for needle-composited materials and anti-inflammatory drugs. The gel-based MNs had dual-mode drug release kinetics, which quickly released MTX diffusively and sustainably released EGCG in an H2O2-responsive way. Compared with dissolving MNs, the gel-based MNs extended skin retention of EGCG, leading to prolonged reactive oxygen species (ROS) scavenging effects. The ROS-responsive MN patches that transdermally delivered antiproliferative and anti-inflammatory drugs improved treatment outcomes in both psoriasis-like and prophylactic psoriasis-like animal models.

Transparent absorber composed of two stacked ultrathin metal films perforated with small holes.

A transparent absorber refers to the device which can absorb light strongly within a narrow frequency range but transmit light efficiently outside that range. Because of the contradiction between absorption and transmission, however, the performances of the transparent absorbers are usually compromised. In this work, we propose a transparent absorber based on a sandwiched metal-insulator-metal (MIM) structure, i.e., two perforated ultrathin metal films separated by a central dielectric layer. This structure has the advantage that the narrow-band absorption can be greatly enhanced because of the cooperation of surface-plasmon polariton (SPP) mode and multiple reflections in the dielectric cavity. Moreover, the ultrathin thickness of the stacked metal films enables high transmission when the wavelength of incident light deviates from the SPP resonance. A semi-analytical Fabry-Perot model has been employed to describe the optical properties, which agrees well with the simulation. The dependence of optical properties on the structural parameters has also been studied systematically. In addition, by covering the transparent absorber with an antireflection layer, highly efficient absorption of red (∼87% @ 629 nm), green (∼89% @ 524 nm), or blue (∼68% @ 472 nm) light and high transmission (∼80%) in the transparent region have been suggested. With its excellent visible-wavelength selective absorption, polarization independence, high angle-tolerance, and structural simplicity, the proposed MIM transparent absorber may have potential applications in the display technology and other smart scenarios.

PredDBP-Stack: Prediction of DNA-Binding Proteins from HMM Profiles using a Stacked Ensemble Method.

DNA-binding proteins (DBPs) play vital roles in all aspects of genetic activities. However, the identification of DBPs by using wet-lab experimental approaches is often time-consuming and laborious. In this study, we develop a novel computational method, called PredDBP-Stack, to predict DBPs solely based on protein sequences. First, amino acid composition (AAC) and transition probability composition (TPC) extracted from the hidden markov model (HMM) profile are adopted to represent a protein. Next, we establish a stacked ensemble model to identify DBPs, which involves two stages of learning. In the first stage, the four base classifiers are trained with the features of HMM-based compositions. In the second stage, the prediction probabilities of these base classifiers are used as inputs to the meta-classifier to perform the final prediction of DBPs. Based on the PDB1075 benchmark dataset, we conduct a jackknife cross validation with the proposed PredDBP-Stack predictor and obtain a balanced sensitivity and specificity of 92.47% and 92.36%, respectively. This outcome outperforms most of the existing classifiers. Furthermore, our method also achieves superior performance and model robustness on the PDB186 independent dataset. This demonstrates that the PredDBP-Stack is an effective classifier for accurately identifying DBPs based on protein sequence information alone.

HMMPred: Accurate Prediction of DNA-Binding Proteins Based on HMM Profiles and XGBoost Feature Selection.

Prediction of DNA-binding proteins (DBPs) has become a popular research topic in protein science due to its crucial role in all aspects of biological activities. Even though considerable efforts have been devoted to developing powerful computational methods to solve this problem, it is still a challenging task in the field of bioinformatics. A hidden Markov model (HMM) profile has been proved to provide important clues for improving the prediction performance of DBPs. In this paper, we propose a method, called HMMPred, which extracts the features of amino acid composition and auto- and cross-covariance transformation from the HMM profiles, to help train a machine learning model for identification of DBPs. Then, a feature selection technique is performed based on the extreme gradient boosting (XGBoost) algorithm. Finally, the selected optimal features are fed into a support vector machine (SVM) classifier to predict DBPs. The experimental results tested on two benchmark datasets show that the proposed method is superior to most of the existing methods and could serve as an alternative tool to identify DBPs.

Recent Advances in Tumor Microenvironment Hydrogen Peroxide-Responsive Materials for Cancer Photodynamic Therapy.

Photodynamic therapy (PDT), as one of the noninvasive clinical cancer phototherapies, suffers from the key drawback associated with hypoxia at the tumor microenvironment (TME), which plays an important role in protecting tumor cells from damage caused by common treatments. High concentration of hydrogen peroxide (H2O2), one of the hallmarks of TME, has been recognized as a double-edged sword, posing both challenges, and opportunities for cancer therapy. The promising perspectives, strategies, and approaches for enhanced tumor therapies, including PDT, have been developed based on the fast advances in H2O2-enabled theranostic nanomedicine. In this review, we outline the latest advances in H2O2-responsive materials, including organic and inorganic materials for enhanced PDT. Finally, the challenges and opportunities for further research on H2O2-responsive anticancer agents are envisioned .

Predicting Apoptosis Protein Subcellular Locations based on the Protein Overlapping Property Matrix and Tri-Gram Encoding.

To reveal the working pattern of programmed cell death, knowledge of the subcellular location of apoptosis proteins is essential. Besides the costly and time-consuming method of experimental determination, research into computational locating schemes, focusing mainly on the innovation of representation techniques on protein sequences and the selection of classification algorithms, has become popular in recent decades. In this study, a novel tri-gram encoding model is proposed, which is based on using the protein overlapping property matrix (POPM) for predicting apoptosis protein subcellular location. Next, a 1000-dimensional feature vector is built to represent a protein. Finally, with the help of support vector machine-recursive feature elimination (SVM-RFE), we select the optimal features and put them into a support vector machine (SVM) classifier for predictions. The results of jackknife tests on two benchmark datasets demonstrate that our proposed method can achieve satisfactory prediction performance level with less computing capacity required and could work as a promising tool to predict the subcellular locations of apoptosis proteins.

Pyrrolopyrrole aza-BODIPY near-infrared photosensitizer for dual-mode imaging-guided photothermal cancer therapy.

A NIR photosensitizer pyrrolopyrrole aza-BODIPY (PPAB) was synthesized in a straightforward manner. Through the use of PPAB NPs as a photothermal agent, photoacoustic imaging (PAI) and NIR fluorescence imaging (NIR-FI) can be achieved in vivo. In addition, the photothermal ablation of tumor cells can be realized both in vitro and in vivo, even at a low concentration (0.5 mg kg-1).

2-Pyridone-functionalized Aza-BODIPY photosensitizer for imaging-guided sustainable phototherapy.

To overcome irradiation-dependence of cancer phototherapy, a near infrared aza-BODIPY-based photothermogenic photosensitizer BDY with 2-Pyridone group has been synthesized for imaging-guided photothermal synergistic sustainable photodynamic therapy. Multifunctional water-soluble BDY nanoparticles (NPs), with high photothermal conversion efficiency of 35.7% and excellent singlet oxygen (1O2) generation ability, are prepared by self-assembling. The reversible transformation between 2-pyridone moiety and its endoperoxide form endows BDY with continuous 1O2 generation ability under illumination and non-illumination conditions. Simultaneously, BDY NPs exhibit excellent tumor targeting properties by enhanced permeability and retention (EPR) effect and photoacoustic imaging (PAI) ability. Furthermore, the photothermal assisted sustainable photodynamic therapy can significantly inhibit tumor growth (93.4% inhibition) with almost no side effects by intermittent laser illumination. The finding highlights that this photothermal synergistic sustainable phototherapy presents great potential for clinical applications.

A fullerene-rhodamine B photosensitizer with pH-activated visible-light absorbance/fluorescence/photodynamic therapy.

The development of smart photosensitizers with tumor microenvironment-activable fluorescence turn-on and singlet oxygen generation plays an important role in tumor bioimaging and photodynamic therapy. Herein, a pH-activable heavy-atom-free photosensitizer (C60-RB) has been successfully synthesized through introducing a fullerene unit onto rhodamine B hydrazide. Under acidic conditions, C60-RB, having a spirolactam structure, can be activated to its ring-opened structure C60-RB-H and thus, visible-light absorbance enhancement, fluorescence turn-on and triplet excited state generation can be accomplished. In the presence of hydrion, the fullerene unit in C60-RB C60-RB-H acting as an intramolecular spin converter can cause good intersystem crossing, and the energy gap between S1 and T1 (ΔEST) is lowered to 0.017 eV. Through encapsulation with amphiphilic DSPE-mPEG2000, water-soluble nanoparticles (NPs) of C60-RB are obtained. In vitro experiments indicate that C60-RB NPs are capable of universal cellular uptake and lysosomal activation (pH 4.5-5.0), and they also exhibit excellent photodynamic therapeutic effect. The fluorescence turn-on and efficient singlet oxygen generation enabled by pH-activated C60-RB NPs testify their great potential applications for cancer diagnosis and treatment.