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Silica nanoparticles (SiNPs) could induce adverse pulmonary effects, but the mechanism was not clear enough. Metabolomics is a sensitive and high-throughput approach that could investigate the intrinsic causes of adverse health effects caused by SiNPs. The current investigation represented the first in vivo metabolomics study examining the chronic pulmonary toxicity of SiNPs at a low dosage, mimicking real human exposure situation. The recovery process after the cessation of exposure was also taken into consideration. Fisher 344 rats were treated with either saline or SiNPs for 6 months. Half of the animals in each group received an additional six-month period for recovery. The findings indicated that chronic low-level exposure to SiNPs resulted in notable alterations in pulmonary metabolism of amino acids, lipids, carbohydrates, and nucleotides. SiNPs exerted an impact on various metabolites and metabolic pathways which are linked to oxidative stress, inflammation and tumorigenesis. These included but were not limited to L-carnitine, spermidine, taurine, xanthine, and glutathione metabolism. The metabolic alterations caused by SiNPs exhibited a degree of reversibility. However, the interference of SiNPs on two metabolic pathways related to tumorigenesis was observed to persist after a recovery period. The two metabolic pathways are glycerophospholipid metabolism as well as phenylalanine, tyrosine and tryptophan biosynthesis. This study elucidated the metabolic alterations induced by chronic low-level exposure to SiNPs and presented novel evidence of the chronic pulmonary toxicity and carcinogenicity of SiNPs, from a metabolomic perspective.

The characteristics of acoustic emission signals generated in the process of rock deformation and fission contain rich information on internal rock damage. The use of acoustic emissions monitoring technology can analyze and identify the precursor information of rock failure. At present, in the field of acoustic emissions monitoring and the early warning of rock fracture disasters, there is no real-time identification method for a disaster precursor characteristic signal. It is easy to lose information by analyzing the characteristic parameters of traditional acoustic emissions to find signals that serve as precursors to disasters, and analysis has mostly been based on post-analysis, which leads to poor real-time recognition of disaster precursor characteristics and low application levels in the engineering field. Based on this, this paper regards the acoustic emissions signal of rock fracture as a kind of speech signal generated by rock fracture uses this idea of speech recognition for reference alongside spectral analysis (STFT) and Mel frequency analysis to realize the feature extraction of acoustic emissions from rock fracture. In deep learning, based on the VGG16 convolutional neural network and AlexNet convolutional neural network, six intelligent real-time recognition models of rock fracture and key acoustic emission signals were constructed, and the network structure and loss function of traditional VGG16 were optimized. The experimental results show that these six deep-learning models can achieve the real-time intelligent recognition of key signals, and Mel, combined with the improved VGG16, achieved the best performance with 87.68% accuracy and 81.05% recall. Then, by comparing multiple groups of signal recognition models, Mel+VGG-FL proposed in this paper was verified as having a high recognition accuracy and certain recognition efficiency, performing the intelligent real-time recognition of key acoustic emission signals in the process of rock fracture more accurately, which can provide new ideas and methods for related research and the real-time intelligent recognition of rock fracture precursor characteristics.

It has been reported that silica nanoparticles (SiNPs) could cause epithelial-to-mesenchymal transition (EMT), but the specific mechanism is still unclear. Thus, the purpose of this study was to investigate the underlying mechanisms of pulmonary EMT after subacute exposure to SiNPs. The results showed intratracheal instillation of SiNPs increased the pulmonary MDA content, while decreased the activity of SOD and GSH-Px in rats. Western blot analysis demonstrated that SiNPs induced autophagy dysfunction via the upregulation of p62. Meanwhile, the inflammation cytokines (TNF-α, IL-18, IL-1β) were released in rat lung. Immunohistochemistry and western blot assays both showed that SiNPs could regulate the related protein biomarkers of EMT through decreasing E-cadherin and increasing vimentin in a dose-dependent manner. Besides, SiNPs activated the proteins expression involved in p62/NF-κB signaling pathway, whereas the pulmonary EMT induced by SiNPs was significantly dampened after the knock down of p62. In this study, we illustrated that subacute exposure to SiNPs could trigger the autophagy dysfunction and pulmonary inflammation, further lead to EMT via activating the p62/NF-κB signaling pathway. Our findings provide new molecular evidence for SiNPs-induced pulmonary toxicity.

Autophagy is a cellular self-defense mechanism by which cells can kill invading pathogenic microorganisms and increase the presentation of components of pathogens as antigens. Contrarily, pathogens can utilize autophagy to enhance their own replication. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) NSP6 can interact with ATPase proton pump component to inhibit lysosomal acidification, which was implicated in the autophagy process. However, research on how SARS-CoV-2 NSP6 affected autophagy, and its impact on virus replication is still lacking. Coronavirus NSP6 has been reported to promote coronavirus replication by limiting autophagosome expansion. However, this finding has not been confirmed in coronavirus disease 2019 (COVID-19). We investigated the effect of NSP6 protein on autophagosomes in different mutant strains of SARS-CoV-2 and revealed that the size of autophagosomes was reduced by NSP6 of the wild-type and Delta variant of SARS-CoV-2. In addition, we found that SARS-CoV-2 NSP6 localized to the lysosome and had an inhibitory effect on the binding of autophagosomes to the lysosome, which blocked the autophagy flux; this may be related to endoplasmic reticulum (ER)-related pathways. We also found that sigma-1 receptor (SIGMAR1) knock out (KO) reversed NSP6-induced autophagosome abnormality and resisted SARS-CoV-2 infection, which responds to the fact that SIGMAR1 is likely to be used as a potential target for the treatment of SARS-CoV-2 infection. In summary, we have provided a preliminary explanation of the effects on autophagy of the SARS-CoV-2 NSP6 protein from the pre-autophagic and late stages, and also found that SIGMAR1 is likely to be used as a potential target for SARS-CoV-2 therapy to develop relevant drugs. IMPORTANCE We have provided a preliminary explanation of the effects on autophagy of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) non-structure protein 6 from the pre-autophagic and late stages, and also found that sigma-1 receptor is likely to be used as a potential target for SARS-CoV-2 therapy to develop relevant drugs. [ABSTRACT FROM AUTHOR]