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Olfactory Receptors: Location and Structure

Olfactory Receptors: Location and Structure

The process of olfaction, also known as the sense of smell, is a sophisticated chemical response system. The specialized sensory neurons that facilitate this process, known as olfactory receptor neurons, are situated in an upper segment of the nasal cavity, known as the olfactory epithelium. Olfactory sensory neurons are bipolar, with their dendrites extending from the epithelium's apex into the mucus that lines the nasal cavity. Airborne molecules, when inhaled, traverse the olfactory...

Olfaction

Olfaction

The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
The olfactory receptors are embedded in the cilia of the...

Physiology of Smell and Olfactory Pathway

Physiology of Smell and Olfactory Pathway

Humans detect odors with the help of specialized cells located in the upper part of the nasal cavity, called olfactory receptor neurons (ORNs). ORNs possess hair-like structures called cilia, which are receptive to sensations from the inhaled air. When an odorant molecule binds to a specific receptor on the cell of the cilia, it leads to a series of events that ultimately cause the ORN to send electrical signals to the olfactory bulb in the brain through the olfactory nerves.
The olfactory...

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Related Experiment Video

Updated: Oct 21, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Predicting olfactory loss in chronic rhinosinusitis using machine learning.

Vijay R Ramakrishnan¹, Jaron Arbet², Jess C Mace³

¹Department of Otolaryngology-Head and Neck Surgery, University of Colorado, Aurora, CO, USA.

Chemical Senses

|September 2, 2021

Summary

This summary is machine-generated.

Machine learning methods effectively classify olfactory dysfunction in chronic rhinosinusitis (CRS-OD), outperforming traditional logistic regression. Key predictors for smell loss in CRS patients were identified, including socioeconomic factors.

Keywords:

AI/ML artificial intelligence chronic disease olfaction outcome assessment (health care)predictive analytics sinusitis smell

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Published on: May 20, 2016

Area of Science:

Otolaryngology
Data Science
Medical Informatics

Background:

Olfactory dysfunction (OD) is a common complication of chronic rhinosinusitis (CRS).
Predicting and understanding the risk factors for CRS-OD remains a clinical challenge.

Purpose of the Study:

To compare machine learning (ML) predictive analytics with logistic regression for classifying CRS-OD.
To identify predictors of olfactory dysfunction in a large cohort of refractory CRS patients.

Main Methods:

A prospective, multi-institutional observational study of adult CRS patients.
Classification of normosmia versus CRS-OD using smell identification tests.
Comparison of four ML methods against traditional logistic regression.

Main Results:

34% of CRS patients exhibited olfactory loss.
ML methods demonstrated favorable predictive ability compared to logistic regression.
Identified predictors included objective disease measures, demographics, and socioeconomic factors.

Conclusions:

ML methods are effective for classifying CRS-OD and incorporating numerous risk factors.
Identified actionable features can enhance understanding and future study of sinonasal disease-induced hyposmia.
ML holds promise for studying olfactory loss, the most common cause of persistent smell loss.