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Could the Olfactory System Be a Target for Homeopathic Remedies as Nanomedicines?

ABSTRACT: Homeopathic remedies (HRs) contain odorant molecules such as flavonoids or terpenes and can lose their efficiency in presence of some competitive odors. Such similarities, along with extreme sensitivity of the olfactory system, widespread presence of olfactory receptors over all organic tissues (where they have metabolic roles besides perception of odors), and potential direct access to the brain through olfactory nerves (ONs) and trigeminal nerves, may suggest the olfactory system as target for HRs. Recent works highlighted that HRs exist in a dual form, that is, a still molecular form at low dilution and a nanoparticulate form at high dilution, and that remnants of source remedy persist in extremely high dilutions. From the literature, both odorants and nanoparticles (NPs) can enter the body through inhalation, digestive absorption, or through the skin, especially, NPs or viruses can directly reach the brain through axons of nerves. Assuming that HRs are recognized by olfactory receptors, their information could be transmitted to numerous tissues through receptor-ligand interaction, or to the brain by either activating the axon potential of ONs and trigeminal nerves or, in their nanoparticulate form, by translocating through axons of these nerves. Moreover, the nanoparticulate form may activate the immune system at multiple levels, induce systemic various biological responses through the pituitary axis and inflammation factors, or modulate gene expression at the cellular level. As immunity, inflammation, pituitary axis, and olfactory system are closely linked together, their permanent interaction triggered by olfactory receptors may thus ensure homeostasis.

SUBMITTER: Courtens F

PROVIDER: S-EPMC6247980 | biostudies-other | 2018 Nov

REPOSITORIES: biostudies-other

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Could the Olfactory System Be a Target for Homeopathic Remedies as Nanomedicines?

Courtens Florence F Demangeat Jean-Louis JL Benabdallah Mourad M

Journal of alternative and complementary medicine (New York, N.Y.) 20180611 11

Homeopathic remedies (HRs) contain odorant molecules such as flavonoids or terpenes and can lose their efficiency in presence of some competitive odors. Such similarities, along with extreme sensitivity of the olfactory system, widespread presence of olfactory receptors over all organic tissues (where they have metabolic roles besides perception of odors), and potential direct access to the brain through olfactory nerves (ONs) and trigeminal nerves, may suggest the olfactory system as target for ...[more]

PMID: 29889551

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Project description:The lack of a deeper understanding of how olfactory sensory neurons (OSNs) encode odors has hindered the progress in understanding the olfactory signal processing in higher brain centers. Here we employ methods of system identification to investigate the encoding of time-varying odor stimuli and their representation for further processing in the spike domain by Drosophila OSNs. In order to apply system identification techniques, we built a novel low-turbulence odor delivery system that allowed us to deliver airborne stimuli in a precise and reproducible fashion. The system provides a 1% tolerance in stimulus reproducibility and an exact control of odor concentration and concentration gradient on a millisecond time scale. Using this novel setup, we recorded and analyzed the in-vivo response of OSNs to a wide range of time-varying odor waveforms. We report for the first time that across trials the response of OR59b OSNs is very precise and reproducible. Further, we empirically show that the response of an OSN depends not only on the concentration, but also on the rate of change of the odor concentration. Moreover, we demonstrate that a two-dimensional (2D) Encoding Manifold in a concentration-concentration gradient space provides a quantitative description of the neuron's response. We then use the white noise system identification methodology to construct one-dimensional (1D) and two-dimensional (2D) Linear-Nonlinear-Poisson (LNP) cascade models of the sensory neuron for a fixed mean odor concentration and fixed contrast. We show that in terms of predicting the intensity rate of the spike train, the 2D LNP model performs on par with the 1D LNP model, with a root mean-square error (RMSE) increase of about 5 to 10%. Surprisingly, we find that for a fixed contrast of the white noise odor waveforms, the nonlinear block of each of the two models changes with the mean input concentration. The shape of the nonlinearities of both the 1D and the 2D LNP model appears to be, for a fixed mean of the odor waveform, independent of the stimulus contrast. This suggests that white noise system identification of Or59b OSNs only depends on the first moment of the odor concentration. Finally, by comparing the 2D Encoding Manifold and the 2D LNP model, we demonstrate that the OSN identification results depend on the particular type of the employed test odor waveforms. This suggests an adaptive neural encoding model for Or59b OSNs that changes its nonlinearity in response to the odor concentration waveforms.

Dataset Information

Could the Olfactory System Be a Target for Homeopathic Remedies as Nanomedicines?

Publications

Could the Olfactory System Be a Target for Homeopathic Remedies as Nanomedicines?

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