Tunable Construction of Chiral Nematic Cellulose Nanocrystals/ZnO Films for Ultra-Sensitive, Recyclable Sensing of Humidity and Ethanol.

The investigation of functional materials derived from sustainable and eco-friendly bioresources has generated significant attention. Herein, nanocomposite films based on chiral nematic cellulose crystals (CNCs) were developed by incorporating xylose and biocompatible ZnO nanoparticles (NPs) via evaporation-induced self-assembly (EISA). The nanocomposite films exhibited iridescent color changes that corresponded to the birefringence phenomenon under polarized light, which was attributed to the formation of cholesteric structures. ZnO nanoparticles were proved to successfully adjust the helical pitches of the chiral arrangements of the CNCs, resulting in tunable optical light with shifted wavelength bands. Furthermore, the nanocomposite films showed fast humidity and ethanol stimuli response properties, exhibiting the potential of stimuli sensors of the CNC-based sustainable materials.

Biomimetic construction of environmental-tolerant composite hydrogels based on galactomannan for tough, flexible and conductive sensors.

Sustainable composite hydrogel materials with harsh environmental adaption and tolerance capability have received considerable interests but still remain as challenges. In this work, biomimetic strategy was adapted for construction of three-dimensional galactomannan (GM) hydrogels with intercalation of flexible polymer chains polyethyleneimine (PEI), biomacromolecules tannin acid (TA) and CeO2 nanoparticles (NPs). The hydrogels cross-linked with double-networks (DN) present not only pH-responsive water absorption property, but also boosted mechanical strength with highest toughness of 326 kJ/m3 and Young's modulus of 220 kPa. Self-healing and anti-freezing capabilities were revealed for the hydrogels by maintaining of fracture elongation (23 %) and fracture strength (250 kPa). TA, CeO2 NPs as well as the amide groups in PEI of the hydrogels introduced excellent bacterial prohibition performance on both Bacillus subtilis (B. subtilis) and Escherichia coli (E. coli). Also, due to the existence of the free ions, the hydrogels exhibited electric conductive properties, with wide-range high sensitivity and long-time conductive stability. In addition, various tensile strain degrees were related to the conductive resistance values, and the great recovery performance was proved by cyclic tensile-conductive tests for 3000 times. Therefore, the proposed GM-based hydrogels displayed great potentials as strain sensors that are adaptable and tolerant to various environmental conditions.

PyCoCa:A quantifying tool of carbon content in airway macrophage for assessment the internal dose of particles.

Given the lack of a comprehensive understanding of the complex metabolism and variable exposure environment, carbon particles in macrophages have become a potentially valuable biomarker to assess the exposure level of atmospheric particles, such as black carbon. However, the tedious and subjective quantification method limits the application of carbon particles as a valid biomarker. Aiming to obtain an accurate carbon particles quantification method, the deep learning and binarization algorithm were implemented to develop a quantitative tool for carbon content in airway macrophage (CCAM), named PyCoCa. Two types of macrophages, normal and foamy appearance, were applied for the development of PyCoCa. In comparison with the traditional methods, PyCoCa significantly improves the identification efficiency for over 100 times. Consistency assessment with the gold standard revealed that PyCoCa exhibits outstanding prediction ability with the Interclass Correlation Coefficient (ICC) values of over 0.80. And a proper fresh dye will enhance the performance of PyCoCa (ICC = 0.89). Subsequent sensitivity analysis confirmed an excellent performance regarding accuracy and robustness of PyCoCa under high/low exposure environments (sensitivity > 0.80). Furthermore, a successful application of our quantitative tool in cohort studies indicates that carbon particles induce macrophage foaming and the foaming decrease the carbon particles internalization in reverse. Our present study provides a robust and efficient tool to accurately quantify the carbon particles loading in macrophage for exposure assessment.