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Dermatomyositis (DM) is an infrequent disease subgroup of idiopathic inflammatory myopathies characterized by distinct skin lesions. However, high heterogeneity makes clinical diagnosis and treatment of DM very challenging.

The intermolecular radical addition to the carbonyl group is difficult due to the facile fragmentation of the resulting alkoxyl radical. To date, the intermolecular radical addition to ketones, a valuable approach to construct quaternary carbon centers, remains a formidable synthetic challenge. Here, we report the first visible-light-induced intermolecular alkyl boronic acid addition to α-ketoacids enabled by the Lewis acid activation. The in situboron complex formation is confirmed by various spectroscopic measurements and mechanistic probing experiments, which facilitates various alkyl boronic acid addition to the carbonyl group and prevents the cleavage of the newly formed C–C bond. Diversely substituted lactates can be synthesized from readily available alkyl boronic acids and ketoacids at room temperature merely under visible light irradiation, without any additional reagent. This boron activation approach can be extended to alkyl dihydropyridines as radical precursors with external boron reagents for primary, secondary, and tertiary alkyl radical additions. The pharmaceutically useful anticholinergic precursors are easily scaled up in multigrams under metal-free conditions in flow reactors.

The construction cost index can reflect the construction market price changes on the project cost. Due to unsuitable way of management and the consideration of data security, there is the possibility of researchable sample data missing, or the possibility of not enough data. This way many classical prediction models cannot function well in practice. The study compared numerous models. According to the characteristics of poor sample data and numerous factors for construction engineering, the grey model and BP neural network were selected to establish the prediction model. This study built material and machinery shift as independent variables, the construction cost as the dependent variable to establish the grey neural network model. In empirical analysis, data processing, training and simulation were used by MATLAB, the results concluded: compared with other conventional models, the combined forecasting model for poor data is more effective.

Herein, we studied the adsorption behaviors of organic micropollutants, such as anticonvulsant carbamazepine (CBZ) and antibiotic tetracycline hydrochloride (TC), on zirconium metal–organic framework UiO-66 in water. The maximum adsorption capacities of CBZ and TC on the UiO-66 were 37.2 and 23.1 mg·g–1at 25 °C, respectively. The adsorption isotherms and kinetics of CBZ and TC were well described by using the Langmuir model and pseudo-second-order model, respectively, and the adsorptions on UiO-66 are endothermic reactions. The adsorption capacities of CBZ and TC on UiO-66 were decreased with the increase of solution pH. The presence of humic acid could improve the adsorption of CBZ and TC on UiO-66, but K+ion inhibited their adsorption obviously. In addition, Ca2+and Al3+ions also suppressed the adsorption of TC on UiO-66. The competitive adsorption suggested that the adsorption sites for CBZ on UiO-66 were different from those for TC. The surface interactions between UiO-66 and the two micropollutants were demonstrated by powder X-ray diffraction, Fourier transform infrared (FT-IR) spectra, scanning electron microscopy, nitrogen adsorption/desorption isotherms, and X-ray photoelectron (XPS) spectra. The characterizations showed that the adsorption of CBZ on UiO-66 is mainly a physisorption, and the hydrophobic effect played a crucial role during the adsorption of CBZ; meanwhile weak π–π electron donor–acceptor interaction and electrostatic attraction also existed. However, the adsorption of TC on UiO-66 is mainly a chemisorption; in addition to the strong electrostatic attraction and π–π electron donor–acceptor interaction forces, the nitrogenous groups of TC played an important role, which can replace the carboxylic groups coordinated with Zr–O clusters. The obtained results will aid us to comprehend the surface interaction between organic micropollutants and UiO-66 and expand the application of UiO-66 as sorbent for removal of pollutants from water.

Metal-organic frameworks (MOFs)-derived nanoporous carbons have attracted widespread concern as adsorbents to remove endocrine-disrupting chemicals (EDCs) in water. However, to explore MOFs-derived nanoporous carbons with high absorption performance is still one of the great challenges, and an in-depth analysis of the adsorption mechanism is insufficient. Herein, two nanoporous carbons were prepared through the pyrolysis of different Zn-MOFs, and their absorptivity was assessed using carbamazepine (CBZ) as the target pollutant. Owing to the higher specific area and the hierarchical pore structure, MOF-5-derived nanoporous carbon (MC) delivered a much higher adsorption capacity (663.7mg/g) and faster uptake rate (634.5mg/(g·min)) than ZIF-8-derived nanoporous carbon (ZC) and commercial powdered activated carbon (AC). Furthermore, the studies of the structure-absorptivity relationship revealed that the graphitic defect demonstrates an enhanced efficacy in the absorption performance of nanoporous carbons whereas the effect of the doped N is negligible. The hydrophobic interaction is the dominant contribution to the CBZ adsorption on MC rather than the π-π interaction, electrostatic attraction, and hydrogen bond. Profited from the unique adsorption mechanism, MC shows an excellent anti-interference capability and good reuse stability. This work provides new insight into the design of high-efficiency adsorbents derived from MOFs toward the removal of EDCs from water.

Intelligent hydrogel, also known as smart hydrogels, are materials with great potential for development in drug delivery system. Intelligent hydrogel also has the ability to perceive as a signal structure change and stimulation. The review introduces the temperature-, pH-, electric signal-, biochemical molecule-, light- and pressure- sensitive hydrogels. Finally, we described the application of intelligent hydrogel in drug delivery system and the recent patents involved for hydrogel in drug delivery.