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Related Concept Videos

Olfaction01:25

Olfaction

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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...
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Olfactory Receptors: Location and Structure01:03

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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...
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Physiology of Smell and Olfactory Pathway01:20

Physiology of Smell and Olfactory Pathway

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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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Structures of Aldehydes and Ketones01:04

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Vanillin—a flavoring agent in vanilla, cinnamaldehyde—a molecule responsible for the distinct smell of cinnamon, and acetone—a strong-smelling ingredient in nail polish removers, all belong to a class of carbonyl compounds called aldehydes and ketones (Figure 1). Although both aldehydes and ketones contain the characteristic carbonyl (C=O) bond, their chemical structures vary with respect to the groups directly attached to the carbonyl carbon.
In aldehydes (Figures 1a and 1b),...
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Polymer Classification: Architecture01:14

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Polymers are classified as linear or branched on the basis of their chain architecture. The polymer chains in linear polymers have a long chain-like structure with minimal to no branching at all. Even if a polymer features large substituent groups on the monomer, which appear as branches to the skeleton, it is not considered a branched polymer. A branched polymer contains secondary polymer chains that arise from the main polymer chain. The branching occurs when the polymer growth shifts from...
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Aromatic Hydrocarbon Anions: Structural Overview01:18

Aromatic Hydrocarbon Anions: Structural Overview

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Neutral hydrocarbons like cyclopentadiene with an odd number of carbon atoms and one intervening CH2 group in the ring are not aromatic. Cyclopentadiene with 4 π electrons does not satisfy the 4n + 2 π electron rule. Additionally, the intervening CH2 group is sp3 hybridized and lacks a vacant p orbital, thereby interrupting the overlap of p orbitals in a continuous manner and preventing the delocalization of π electrons throughout the ring.
Due to the absence of continuous...
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Related Experiment Video

Updated: Jul 31, 2025

Real-time In Vitro Monitoring of Odorant Receptor Activation by an Odorant in the Vapor Phase
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OWSum: algorithmic odor prediction and insight into structure-odor relationships.

Doris Schicker1,2, Satnam Singh3,4, Jessica Freiherr3,4

  • 1Sensory Analytics and Technologies, Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauser Straße 35, 85354, Freising, Germany. doris.schicker@ivv.fraunhofer.de.

Journal of Cheminformatics
|May 7, 2023
PubMed
Summary

We developed Olfactory Weighted Sum (OWSum), a new algorithm predicting molecular odor using structural patterns. This method offers insights into chemical interactions and improves odor prediction accuracy.

Keywords:
Odor predictionOlfactionStructure-odor relationships

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Area of Science:

  • Computational chemistry
  • Cheminformatics
  • Machine learning

Background:

  • Predicting molecular odor is crucial for various industries.
  • Current methods often lack interpretability and struggle with odor descriptor ambiguity.

Purpose of the Study:

  • To develop a novel algorithm for predicting molecular odor based on structural features.
  • To provide an interpretable model that offers insights into structure-odor relationships.
  • To address the ambiguity in natural language odor descriptors.

Main Methods:

  • Implemented a linear classification algorithm named Olfactory Weighted Sum (OWSum).
  • Utilized molecular structural patterns as features.
  • Employed conditional probabilities and tf-idf values for classification.
  • Introduced descriptor overlap metric to quantify semantic similarity between odor descriptors.

Main Results:

  • OWSum accurately predicts molecular odor based on structural patterns.
  • The algorithm provides quantitative assignments of structural patterns to odors, enhancing interpretability.
  • Descriptor overlap metric effectively quantifies semantic relationships between odor descriptors, enabling higher-level descriptor derivation.

Conclusions:

  • OWSum represents a significant advancement in understanding and predicting molecular odor.
  • The approach offers chemists intuitive insights into structure-odor interactions.
  • The methodology enhances the ability to handle and interpret complex odor-related data.