Reactive Oxygen Species-Manipulated Drug Release from a Smart Envelope-Type Mesoporous Titanium Nanovehicle for Tumor Sonodynamic-Chemotherapy

Despite advances in drug delivery systems (DDSs), the stimuli-responsive controlled release DDSs with high spatial/temporal resolution are still the best choice. Herein, a novel type of envelope-type mesoporous titanium dioxide nanoparticle (MTN) was developed for one-demand drug delivery platform. Docetaxel (DTX) was loaded in the pores of MTN with a high drug loading efficiency (∼26%). Then β-cyclodextrin (β-CD, a bulky gatekeeper) was attached to the outer surface of MTN via a reactive oxygen species (ROS) sensitive linker to block the pores (MTN@DTX-CD). MTN@DTX-CD could entrap the DTX in the pores and allow the rapid release until a focused ultrasound (US) emerged. A large number of ROS were generated by MTN under US radiation, leading to the cleavage of the ROS-sensitive linker; thus, DTX could be released rapidly since the gatekeepers (β-CD) were detached. Besides, the generation of ROS could also be used for tumor-specific sonodynamic therapy (SDT). Studies have shown the feasibility of MTN@DTX-CD for US-triggered DTX release and sonodynamic-chemotherapy. In the in vitro and in vivo studies, by integrating SDT and chemotherapy into one system, MTN@DTX-CD showed excellent antitumor efficacy. More importantly, this novel DDS significantly decreased the side effects of DTX by avoiding the spleen and hematologic toxicity to tumor-bearing mice

Highly Selective Fluorescent Turn-On Probe for Protein Thiols in Biotin Receptor-Positive Cancer Cells

Sulfhydryl-containing proteins play critical roles in various physiological and biological processes, and the activities of those proteins have been reported to be susceptible to thiol oxidation. Therefore, the development of protein thiol target fluorescent probe is highly desirable. In the present work, a biotinylated coumarin fluorescence “off–on” probe SQ for selectively detecting protein thiols in biotin receptor-positive cancer cells was designed with a 2,4-dinitrobenzenesulfony as the thiol receptor. The probe exhibited dramatic fluorescence responses toward sulfhydryl-containing proteins (ovalbumin (OVA), bovine serum albumin (BSA)): up to 170-fold fluorescence enhancement with 70 nm blue-shift was observed with the addition of OVA. However, low molecular weight thiols (Cys, glutathione (GSH), Hcy) caused negligible fluorescence changes of SQ. In addition, biotin receptor-positive Hela cells displayed strong red and green fluorescence after incubation of SQ for 1 h; neither red nor green fluorescence signal could be visualized in biotin-negative normal lung Wi38 cells. These results imply that the probe has potential application in fluorescent imaging protein thiols on the surface of Hela cells

Micromixing in a Novel Microannular Rotating Bed

Microchannel reactors have garnered significant attention in various chemical processes due to their ability to achieve rapid mixing. However, there remains ample opportunity for the development of microchannel reactors with simple structures and high throughput. In this work, we propose a novel microannular rotating bed (MARB) that integrates the high-gravity field and microscale effect to enhance the micromixing efficiency. The Villermaux–Dushman reaction system is employed to investigate the influence of the operating parameters on the mixing performance. The micromixing time of the MARB ranges from 10–4 to 10–3 s for low-viscosity Newtonian fluids and from 10–4 to 10–2 s for shear-thinning non-Newtonian fluids. In a lab-scale setup, the MARB demonstrates a throughput of 6 L/min, markedly surpassing the capabilities of the existing microchannel reactors. Furthermore, the evaluation of energy dissipation rate underscores the MARB’s remarkable energetic efficiency in intensifying mixing processes. The MARB, with its simple design, high throughput capacity, and efficiency, presents a promising alternative for the intensification of mixing across diverse chemical applications

Additional file 1: Figure S1. of Highly Enhanced H2 Sensing Performance of Few-Layer MoS2/SiO2/Si Heterojunctions by Surface Decoration of Pd Nanoparticles

AFM images of the Pd-decorated MoS2 films with the Pd thickness of (a) d Pd  = 1 nm, (b) d Pd  = 3 nm, (c) d Pd  = 5 nm, (d) d Pd  = 10 nm, (e) d Pd  = 15 nm and (f) d Pd  = 30 nm. Figure S2. UV spectrum of the few-layer MoS2 film. Figure S3. Sensing curves of (a) the few-layer MoS2/SiO2/Si heterojunction and (b) 5-nm Pd/SiO2/Si heterojunction. (DOCX 1723 kb

Efficient Production of Coaxial Core–Shell MnO@Carbon Nanopipes for Sustainable Electrochemical Energy Storage Applications

Adverse structural changes and poor intrinsic electrical conductivity as well as the lack of an environmentally benign synthesis for MnO species are major factors to limit their further progress on electrochemical energy storage applications. To overcome the above constraints, the development of reliable and scalable techniques to confine MnO within a conductive matrix is highly desired. We herein propose an efficient and reliable way to fabricate coaxial core–shell hybrids of MnO@carbon nanopipes merely via simple ultrasonication and calcination treatments. The evolved MnO nanowires disconnected/confined in pipe-like carbon nanoreactors show great promise in sustainable supercapacitors (SCs) and Li-ion battery (LIB) applications. When used in SCs, such core–shell MnO@carbon configurations exhibit outstanding positive and negative capacitive behaviors in distinct aqueous electrolyte systems. This hybrid can also function as a prominent LIB electrode, demonstrating a high reversible capacity, excellent rate capability, long lifespan, and stable battery operation. The present work may shed light on effective and scalable production of Mn-based hybrids for practical applications, not merely for energy storage but also in other broad fields such as catalysts and biosensors

Sulfonic Acid Functionalized Ionic Liquids for Defect Passivation via Molecular Interactions for High-Quality Perovskite Films and Stable Solar Cells

The high photoelectric conversion efficiency and low cost of perovskite solar cells (PSCs) have further inspired people’s determination to push this technology toward industrialization. The high-quality perovskite films and high-efficiency and stable PSCs are the crucial factors. Ionic liquids have been proven to be an effective strategy for regulating high-quality perovskite films and high-performance PSCs. However, the regulation mechanism between ionic liquids and perovskites still needs further clarification. In this study, a novel sulfonic acid-functionalized ionic liquid, 1-butyl-3-methylimidazolium trifluoromethanesulfonate (BSO3HMImOTf), was used as an effective additive to regulate high-quality perovskite films and high-performance devices. Microscopic mechanism studies revealed strong interactions between BSO3HMImOTf and Pb2+ ions as well as halogens in the perovskite. The perovskite film is effectively passivated with the controlled crystal growth, suppressed ion migration, facilitating to the greatly improved photovoltaic performance, and superior long-term stability. This article reveals the regulatory mechanism of sulfonic acid type ionic liquids through testing characterization and mechanism analysis, providing a new approach for the preparation of high-quality perovskite devices

Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity

Neurotoxicity can be resulted from many diverse clinical drugs, which has been a cause of concern to human populations across the world. The detection of drug-induced neurotoxicity (DINeurot) potential with biological experimental methods always required a lot of budget and time. In addition, few studies have addressed the structural characteristics of neurotoxic chemicals. In this study, we focused on the computational modeling for drug-induced neurotoxicity with machine learning methods and the insights into the structural characteristics of neurotoxic chemicals. Based on the clinical drug data with neurotoxicity effects, we developed 35 different classifiers by combining five different machine learning methods and seven fingerprint packages. The best-performing model achieved good results on both 5-fold cross-validation (balanced accuracy of 76.51%, AUC value of 0.83, and MCC value of 0.52) and external validation (balanced accuracy of 83.63%, AUC value of 0.87, and MCC value of 0.67). The model can be freely accessed on the web server DINeuroTpredictor (http://dineurot.sapredictor.cn/). We also analyzed the distribution of several key molecular properties between neurotoxic and non-neurotoxic structures. The results indicated that several physicochemical properties were significantly different between the neurotoxic and non-neurotoxic compounds, including molecular polar surface area (MPSA), AlogP, the number of hydrogen bond acceptors (nHAcc) and donors (nHDon), the number of rotatable bonds (nRotB), and the number of aromatic rings (nAR). In addition, 18 structural alerts responsible for chemical neurotoxicity were identified. The structural alerts have been integrated with our web server SApredictor (http://www.sapredictor.cn). The results of this study could provide useful information for the understanding of the structural characteristics and computational prediction for chemical neurotoxicity

Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity

Neurotoxicity can be resulted from many diverse clinical drugs, which has been a cause of concern to human populations across the world. The detection of drug-induced neurotoxicity (DINeurot) potential with biological experimental methods always required a lot of budget and time. In addition, few studies have addressed the structural characteristics of neurotoxic chemicals. In this study, we focused on the computational modeling for drug-induced neurotoxicity with machine learning methods and the insights into the structural characteristics of neurotoxic chemicals. Based on the clinical drug data with neurotoxicity effects, we developed 35 different classifiers by combining five different machine learning methods and seven fingerprint packages. The best-performing model achieved good results on both 5-fold cross-validation (balanced accuracy of 76.51%, AUC value of 0.83, and MCC value of 0.52) and external validation (balanced accuracy of 83.63%, AUC value of 0.87, and MCC value of 0.67). The model can be freely accessed on the web server DINeuroTpredictor (http://dineurot.sapredictor.cn/). We also analyzed the distribution of several key molecular properties between neurotoxic and non-neurotoxic structures. The results indicated that several physicochemical properties were significantly different between the neurotoxic and non-neurotoxic compounds, including molecular polar surface area (MPSA), AlogP, the number of hydrogen bond acceptors (nHAcc) and donors (nHDon), the number of rotatable bonds (nRotB), and the number of aromatic rings (nAR). In addition, 18 structural alerts responsible for chemical neurotoxicity were identified. The structural alerts have been integrated with our web server SApredictor (http://www.sapredictor.cn). The results of this study could provide useful information for the understanding of the structural characteristics and computational prediction for chemical neurotoxicity

Achieving Efficient CO₂ Electrolysis to CO by Local Coordination Manipulation of Nickel Single-Atom Catalysts

Selective electroreduction of CO2 to C1 feed gas provides an attractive avenue to store intermittent renewable energy. However, most of the CO2-to-CO catalysts are designed from the perspective of structural reconstruction, and it is challenging to precisely design a meaningful confining microenvironment for active sites on the support. Herein, we report a local sulfur doping method to precisely tune the electronic structure of an isolated asymmetric nickel–nitrogen–sulfur motif (Ni1-NSC). Our Ni1-NSC catalyst presents >99% faradaic efficiency for CO2-to-CO under a high current density of −320 mA cm–2. In situ attenuated total reflection surface-enhanced infrared absorption spectroscopy and differential electrochemical mass spectrometry indicated that the asymmetric sites show a significantly weaker binding strength of *CO and a lower kinetic overpotential for CO2-to-CO. Further theoretical analysis revealed that the enhanced CO2 reduction reaction performance of Ni1-NSC was mainly due to the effectively decreased intermediate activation energy