china titanium dioxide dissolved in oil

Scientists analyzed research that examined how titanium dioxide nanoparticles interact with the brain for a 2015 review published in Nanoscale Research Letters. The researchers wrote: “Once the TiO2 NPs are translocated into the central nervous system through [certain] pathways, they may accumulate in the brain regions. For their slow elimination rates, those NPs could remain in the brain zones for a long period, and the Ti contents would gradually increase with repeated exposure.” After reviewing dozens of studies, the scientists concluded: “Long-term or chronic exposure to TiO2 nanoparticles could potentially lead to the gradually increased Ti contents in the brain, which may eventually induce impairments on the neurons and glial cells and lead to CNS dysfunction as a consequence.”

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For research published in Archives of Toxicology in 2020, scientists fed one group of mice a solution containing titanium dioxide for one month, and compared it to those that did not receive the additive. They found “the richness and evenness of gut microbiota were remarkably decreased and the gut microbial community compositions were significantly changed” in the titanium dioxide group when compared with the control group. The tests also revealed that the titanium dioxide exposure could cause locomotor dysfunction, or mobility issues “by elevating the excitement of enteric neurons, which might spread to the brain via gut-brain communication by vagal pathway.” The researchers concluded: “These findings provide valuable insights into the novel mechanism of TiO2NP-induced neurotoxicity. Understanding the microbiota-gut-brain axis will provide the foundation for potential therapeutic or prevention approaches against TiO2NP-induced gut and brain-related disorders.”

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  • As they mimic the synapses in biological neurons, memristors became the key component for designing novel types of computing and information systems based on artificial neural networks, the so-called neuromorphic electronics (Zidan, 2018; Wang and Zhuge, 2019; Zhang et al., 2019b). Electronic artificial neurons with synaptic memristors are capable of emulating the associative memory, an important function of the brain (Pershin and Di Ventra, 2010). In addition, the technological simplicity of thin-film memristors based on transition metal oxides such as TiO2 allows their integration into electronic circuits with extremely high packing density. Memristor crossbars are technologically compatible with traditional integrated circuits, whose integration can be implemented within the complementary metal–oxide–semiconductor platform using nanoimprint lithography (Xia et al., 2009). Nowadays, the size of a Pt-TiOx-HfO2-Pt memristor crossbar can be as small as 2 nm (Pi et al., 2019). Thus, the inherent properties of memristors such as non-volatile resistive memory and synaptic plasticity, along with feasibly high integration density, are at the forefront of the new-type hardware performance of cognitive tasks, such as image recognition (Yao et al., 2017). The current state of the art, prospects, and challenges in the new brain-inspired computing concepts with memristive implementation have been comprehensively reviewed in topical papers (Jeong et al., 2016; Xia and Yang, 2019; Zhang et al., 2020). These reviews postulate that the newly emerging computing paradigm is still in its infancy, while the rapid development and current challenges in this field are related to the technological and materials aspects. The major concerns are the lack of understanding of the microscopic picture and the mechanisms of switching, as well as the unproven reliability of memristor materials. The choice of memristive materials as well as the methods of synthesis and fabrication affect the properties of memristive devices, including the amplitude of resistive switching, endurance, stochasticity, and data retention time.

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