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Nature-derived exosomes have been noted as emerging carriers for anticancer drugs. In this study, as a proof-of-concept, the anticancer drug doxorubicin (Dox) was loaded onto i-motif-modified exosomes (Exo-i-motif) to deliver Dox to cancer cells efficiently. The double-stranded biotin-i-motif/flare (ds-i-motif-bio)s efficiently released Dox in an acidic pH-responsive manner within 1 h. Based on gel electrophoresis, it was clearly confirmed that ds-i-motif-bio successfully interacts with biotin-conjugated exosomes and streptavidin (strep) via the biotin–streptavidin interaction. The particle sizes were below 150 nm without aggregation after strep-mediated modification of ds-i-motif-bio on the surfaces of the exosomes. In addition, released Dox had intact bioactivity for anti-proliferation after immobilization onto the exosomes. This study could serve as a new concept of pH-responsive delivery systems of anticancer drug using nature-derived exosomes with i-motifs.

Blue-green microalgal blooms have been caused concerns about environmental problems and human-health dangers. For removal of such cyanobacteria, many mechanical and chemical treatments have been trialled. Among various technologies, the flocculation-based harvesting (precipitation) method can be an alternative if the problem of the low yield of recovered biomass at low concentrations of cyanobacteria is solved. In the present study, it was utilized mixtures of magnesium aminoclay [MgAC] and cerium aminoclay [CeAC] with different particle sizes to harvest cyanobacteria feedstocks with ∼100% efficiency within 1h by ten-fold lower loading of ACs compared with single treatments of [MgAC] or [CeAC]. This success was owed to the compact networks of the different-sized-ACs mixture for efficient bridging between microalgal cells. In order to determine the usage potential of biomass harvested with AC, the mass was heat treated under the reduction condition. This system is expected to be profitably utilizable in adsorbents and catalysts.

We describe the preparation of a nanohybrid consisting of nitrogen doped reduced graphene oxide and CuS nanoparticles (N-rGO/CuS) by in-situ microwave irradiation at weight ratios of 25/75, 50/50, and 75/25. The resulting nanohybrids were characterized by X-ray diffraction, X-ray photoelectron spectroscopy, FTIR, spectroscopy, scanning electron and transmission electron microscopy, electrochemically by cyclic voltammetry and electrochemical impedance analysis. It is shown that the CuS nanoparticles are evenly decorated onto the N-rGO surface. The nanohybrids was placed on glassy carbon electrode (GCE) where they showed electro-reductive activity towards picric acid, typically at working voltages between −0.2 and −0.8 V (vs. SCE). Effects of pH value and scan rate were evaluated, and it is shown that two electrons are involved in electro-reduction. The detection limits of the GCE modified with various N-rGO/CuS hybrids (with 25/75, 50/50, and 75/25 wt%) are 6.2, 3.2, and 0.069 μM respectively. The method demonstrates its applicability in sensing of picric acid with good reproducibility.

Cobalt oxide (Co 3 O 4 ) nanospindles-decorated reduced graphene oxide (RGO) composite is prepared via thermal decomposition of a three-dimensional coordination complex precursor, cobalt benzoate dihydrazinate, at 200 °C. Transmission electron microscopy reveals that Co 3 O 4 nanospindles with an average particle size of I (μA) = 2.0660 C + 6.7869 ( R 2 = 0.9992). The sensor exhibits a high sensitivity of 29.5 μA μM −1 cm −2 , a rapid response time of 5 s, and a low detection of limit of 0.14 μM. The proposed electrode shows good reproducibility and long-term stability. The sensor is used to determine the nitrite level in tap water with acceptable recovery, implying its feasibility for practical application.

The recoveries of Sr2+ and La3+ as rare earth metals (REMs) were studied using Mg-aminoclay–humic acid [MgAC–HA] complexes prepared by self-assembled precipitation due to electrostatic attraction between water-solubilized [MgAC] and water-soluble [HA], and were compared with the recoveries using [MgAC] and [HA]. The influences of pH and Sr2+ and La3+ concentrations in single and binary systems were evaluated. The adsorbents before/after adsorption of Sr2+ and La3+ were characterized by (1) scanning electron microscopy (SEM) micrographs, (2) Fourier transform infrared (FT-IR), X-ray photoelectron spectroscopy (XPS), and extended X-ray absorption fine structure (EXAFS) spectra, and by (3) powder X-ray diffraction (XRD) pattern analysis. After fitting Langmuir and Freundlich isotherms, the Langmuir model was found to present better matches than the Freundlich one: the maximum adsorption capacities of Sr2+ and La3+ were 0.12 mg g−1 and 4.76 mg g−1 in the binary system at room temperature, and the optimal recovery pH was ∼8.0. In practical seawater meanwhile, the recoveries of Sr2+ and La3+ by [MgAC–HA] complexes were the highest in the binary system. However, with further recycling runs, the recoveries of Sr2+ and La3+ were critically diminished due to disassembly in [MgAC–HA] complexes under acidic conditions. Thus, for the purposes of industrial application, we are currently pursuing the enhancement of recyclability for [MgAC–HA] complexes by their encapsulation or direct hydrogel formation.

This study set out to invent an Information and Communication Technologies (ICT)-based smart Acer mono sap collection electric device to make efficient use of the labor force by reducing inefficient activities of old manual work to record sap exudation and state information. Based on the assumption that environmental information would have close connections with Acer mono sap exudation to reinforce the competitive edge of production in forest products, the study analyzed correlations between Acer mono sap exudation and environmental information and predicted Acer mono exudation. A smart collection of electric devices would gather data about Acer mono sap exudation per hour on outdoor temperature, humidity, conductivity, and wind direction and velocity, and was installed in four areas in the Republic of Korea, including Sancheong, Gwangyang, Geoje, and Inje. Collected data were used to analyze correlations between environmental information and Acer mono sap exudation using four different algorithms, including linear regression, Support Vector Machine (SVM), Artificial Neural Network (ANN), and random forest, to predict Acer mono sap exudation. Remarkable outcomes were obtained across all the algorithms except for linear regression, demonstrating close connections between environmental information and Acer mono sap exudation. The random forest model, which showed the most outstanding performance, was used to make a mobile app capable of providing predicted Acer mono sap exudation and collected environmental information.