In a 2016 study published in Scientifica (Cairo), Egyptian researchers examined the effects of titanium dioxide nanoparticles on the organs of mice by orally administering the food additive daily, for five days. The results showed that the exposure produced “mild to moderate changes in the cytoarchitecture of brain tissue in a time dependent manner.” Furthermore, “Comet assay revealed the apoptotic DNA fragmentation, while PCR-SSCP pattern and direct sequencing showed point mutation of Presenilin 1 gene at exon 5, gene linked to inherited forms of Alzheimer’s disease.” The researchers wrote: “From these findings, “the present study concluded that TiO2NPs is genotoxic and mutagenic to brain tissue which in turn might lead to Alzheimer’s disease incidence.”

The safety of the food additive E 171 was re-evaluated by the EFSA ANS Panel in 2016 in the frame of Regulation (EU) No 257/2010, as part of the re-evaluation programme for food additives authorised in the EU before 20 January 2009.  

Description:

Chloride process. This process requires a high titanium feedstock. Rutile is reacted with hydrochloric acid to produce titanium tetrachloride, which can be hydrolyzed with steam or oxidized with air to render the dioxide. A rutile form of titanium dioxide is obtained.

Earlier this year, a bill was introduced in the California legislature to ban the manufacture, sale and distribution of foods in the state containing titanium dioxide, along with four other harmful food chemicals. 

The realization of neuromorphic resistive memory in TiO₂ thin films (Strukov et al., 2008) marked an important milestone in the search for bio-inspired technologies (Chua and Kang, 1976). Many research proposals urged a focus on memristivity as the common feature of two electrical models: (i) electromigration of point defects in titanium oxide systems (Baiatu et al., 1990; Jameson et al., 2007) and (ii) voltage-gated ionic channels in the membranes of biological neurons (Hodgkin and Huxley, 1952). In this regard, memristors functionally mimic the synaptic plasticity of biological neurons, and thus can be implemented in artificial and hybrid neural networks. This includes a new paradigm of future computing systems (Zidan, 2018) and biocompatible electronics such as biointerfaces and biohybrid systems (Chiolerio et al., 2017).

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