BackgroundNanometer silicon dioxide (nano-SiO2) has a wide variety of applications in material sciences, engineering and medicine; however, the potential cell biological and proteomic effects of nano-SiO2 exposure and the toxic mechanisms remain far from clear.ResultsHere, we evaluated the effects of amorphous nano-SiO2 (15-nm, 30-nm SiO2). on cellular viability, cell cycle, apoptosis and protein expression in HaCaT cells by using biochemical and morphological analysis, two-dimensional differential gel electrophoresis (2D-DIGE) as well as mass spectrometry (MS). We found that the cellular viability of HaCaT cells was significantly decreased in a dose-dependent manner after the treatment of nano-SiO2 and micro-sized SiO2 particles. The IC50 value (50% concentration of inhibition) was associated with the size of SiO2 particles. Exposure to nano-SiO2 and micro-sized SiO2 particles also induced apoptosis in HaCaT cells in a dose-dependent manner. Furthermore, the smaller SiO2 particle size was, the higher apoptotic rate the cells underwent. The proteomic analysis revealed that 16 differentially expressed proteins were induced by SiO2 exposure, and that the expression levels of the differentially expressed proteins were associated with the particle size. The 16 proteins were identified by MALDI-TOF-TOF-MS analysis and could be classified into 5 categories according to their functions. They include oxidative stress-associated proteins; cytoskeleton-associated proteins; molecular chaperones; energy metabolism-associated proteins; apoptosis and tumor-associated proteins.ConclusionsThese results showed that nano-SiO2 exposure exerted toxic effects and altered protein expression in HaCaT cells. The data indicated the alterations of the proteins, such as the proteins associated with oxidative stress and apoptosis, could be involved in the toxic mechanisms of nano-SiO2 exposure.

Recently, in-sensor computing with individual sensors or multiple connected sensors directly processing information has been proposed to improve energy, area, and time efficiency of artificial intelligence systems. Current investigations mainly focus on a single sensory processing such as auditory, visual, tactile, olfactory, and so on. However, a human perception system can sense and process different types of information with a complex environment and small perceptive field simultaneously. For example, the recognition accuracy of human eyes is highly affected by the environment such as extremely low or high relative humidity (RH). Here, a multi-modal MXene-ZnO memristor that combines visual data sensing, RH sensing, and pre-processing functions to emulate the unique environmental adaptive behavior of the human eye is designed and constructed. The multi-field controlled resistive switching of the MXene-ZnO memristor is originated from the photon-/protons-regulated formation of oxygen vacancies filaments. Finally, in-sensor computing with a MXene-ZnO memristor functioning as both filter to preprocess the information and synapse to implement a weight updating process with different humidity adaptability has been demonstrated. Multimodal in-sensor computing provides the potential to reduce the underlying circuitry complexity of the traditional neuromorphic visual system and contributes to the development of intelligence in device-level implementations.

Industrially, NH3 is mainly produced via the Haber-Bosch process which is not only energy-consuming but emits a large amount of CO2. Electrochemical reduction is regarded as an environmentally-benign alternative for sustainable NH3 synthesis, and its efficiency heavily depends on the identification of Earth-abundant catalysts with high activity for the N2 reduction reaction (NRR). In this work, we report that a spinel Fe3O4 nanorod on a Ti mesh (Fe3O4/Ti) acts as an efficient and durable NRR electrocatalyst under ambient conditions. When tested in 0.1 M Na2SO4, such Fe3O4/Ti achieves a high faradaic efficiency of 2.6% and a NH3 yield 5.6 × 10-11 mol s-1 cm-2 and at -0.4 V vs. a reversible hydrogen electrode.