Multiple Odor Research Articles

The Impact of Odor Category Similarity on Multimedia Experience.

Although we have multiple senses, multimedia mainly targets vision and olfaction. To expand the senses impacted by multimedia, olfactory stimulation has been used to enhance the sense of reality. Odors are primarily matched with objects in scenes. However, it is impractical to select all odors that match all objects in a scene and offer them to viewers. As an alternative, offering a single odor in a category as representative of other odors belonging to that category has been suggested. However, it is unclear whether viewers' responses to videos with multiple odors (e.g., rose, lavender, and lily) from a category (e.g., flowers) are comparable. Therefore, we studied whether odors belonging to a given category could be similar in behavioral congruency and in the five frequency bands (delta, theta, alpha, beta, and gamma) of electroencephalogram (EEG) data collected while viewers watched videos. We conducted questionnaires and EEG experiments to understand the effects of similar odors belonging to categories. Our results showed that similar odors in a specific odor category were more congruent with videos than those in different odor categories. In our EEG data, the delta and theta bands were mainly clustered when odors were offered to viewers in similar categories. The theta band is known to be primarily related to the neural signals of odor information. Our studies showed that choosing odors based on odor categories in multimedia can be feasible.

Olfactory stimulation with multiple odorants prevents stress-induced cognitive and psychological alterations.

Acute and chronic stress markedly affects behavior by triggering sympathetic nervous system activation and several hypothalamus-pituitary-adrenal-dependent responses. Brain regions of the limbic system are responsible for the regulation of stress response, and different reports have demonstrated that their activity can be influenced by olfactory stimuli. Here we report that, in mice exposed to acute restraint stress, olfactory stimulation employing a combination of three odorants, i.e. vanillin, limonene and green odor (trans-2-hexenal and cis-3-hexenol) decreased anxiety behavior, assessed in the elevated plus maze, and halted recognition and spatial memory deficits, as appraised in two different object recognition tasks. Of note, when applied singularly, the same odorants were unable to block the detrimental effects of stress. We also found that the multiple odorants stimulation prevented the development of depressive symptoms assessed by the sucrose splash test and forced swim test in an experimental model of depression, i.e. mice exposed to a chronic unpredictable stress paradigm, and reduced interleukin 1β levels in the prefrontal cortex of depressed mice. Collectively, our data indicate that olfactory stimulation counteracts the detrimental effects of acute and chronic stress on mood regulation and cognitive functions, thus representing a potential tool for the treatment of stress-induced disorders.

Inkjet-Printed Localized Surface Plasmon Resonance Subpixel Gas Sensor Array for Enhanced Identification and Visualization of Gas Spatial Distributions from Multiple Odor Sources

The visualization of the spatial distributions of gases from various sources is essential to understanding the composition, localization, and behavior of these gases. In this study, an inkjet-printed localized surface plasmon resonance (LSPR) subpixel gas sensor array was developed to visualize the spatial distributions of gases and to differentiate between acetic acid, geraniol, pentadecane, and cis-jasmone. The sensor array, which integrates gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and fluorescent pigments, was positioned 3 cm above the gas source. Hyperspectral imaging was used to capture the LSPR spectra across the sensor array, and these spectra were then used to construct gas information matrices. Principal component analysis (PCA) enabled effective classification of the gases and localization of their sources based on observed spectral differences. Heat maps that visualized the gas concentrations were generated using the mean squared error (MSE) between the sensor responses and reference spectra. The array identified and visualized the four gas sources successfully, thus demonstrating its potential for gas localization and detection applications. The study highlights a straightforward, cost-effective approach to gas sensing and visualization, and in future work, we intend to refine the sensor fabrication process and enhance the detection of complex gas mixtures.

The impact of training method on odor learning and generalization in dogs (Canis lupus familiaris).

Detection dogs are required to learn and alert to multiple different odors during training and to generalize this learning to similar odors when working. They should be both sensitive to variation in the target odors and specific enough to avoid false alerts, but how readily they achieve this is likely to depend on the training method employed. The majority of agencies train by presenting single target odors in isolation, and adding additional odors consecutively, although recent research with rats suggests intermixing the target odors concurrently throughout training may be a more effective approach. This study therefore tested the relative efficacy of intermixed training in dogs. Using an odor-detection lineup, pet dogs were trained to detect two target odors, A and B. Those allocated to the "sequential" group were trained to criterion on odor A and then trained on odor B (or vice versa), the "compound" group were trained on a mixture of AB, and the "intermixed" group trained on A and B concurrently. Each dog was then tested on all combinations of the test stimuli (A, B, and AB), as well as combinations containing a novel interferent (AC, BC, and ABC). Results revealed that dogs trained by the intermixed method made significantly more correct (true positive) indications, and significantly fewer miss (false negative) indications than the other two methods, suggesting that intermixed training is more effective than currently used alternative training methods. Thus, for improved performance and generalization, we recommend detection dog training should use an intermixed method of training. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Multi-channel portable odor delivery device for self-administered and rapid smell testing

To improve our understanding of the perception of odors, researchers are often required to undertake experimental procedures with users exposed to multiple odors in a variety of settings, including to diagnose smell loss in clinics and care homes. Existing smell tests are typically administered using multiple sniffing pens, manually presented to patients by a highly specialized nurse using a time-consuming and complex testing paradigm. Automated odor delivery devices, such as olfactometer systems, exist but are expensive, bulky and typically lab based, making them difficult to use for on the ground odor delivery. Here we have developed a portable, affordable, odor delivery device that can deliver 24 odors through individual channels with high temporal precision and without cross-contamination. The device allows for the rapid, flexible sequencing of odors via digital control using a mobile application and has been experimentally validated in the lab, as well as tested on patients. The design provides several advantages for investigating olfactory perception and offers the possibility that users can one day self-administer smell tests in a range of settings, including at home, allowing smell healthcare services to evolve and become part of a routine practice and self-care culture.

Deciphering aroma complexity between melting flesh and stony hard peach (Prunus persica L.) fruit through integrative analysis of volatile contributions

Stony hard peach is favored in production for resistance to storage and transportation, but presents a challenge of lacking fragrance compared to traditional fragrant peach i.e., melting flesh peach. Addressing this concern necessitates material composition analysis from the perspective of volatile composition and aroma characteristics. However, the complex relationship between volatile compounds and aroma profiles in melting flesh and stony hard peach cultivars remains poorly understood. To address this gap, we examined contribution of volatiles to their aroma. The application of multiple analysis methods, including distribution, odor importance, and partial least squares discriminant analysis facilitated a comprehensive understanding of the contribution of 30 volatiles to aroma; and hierarchical clustering analysis revealed relationships among the compounds within the two types of peaches. The primary differential volatiles between them were cis-3-hexenol, pentyl acetate, prenyl acetate, trans-2-hexenal, cis-3-hexenyl acetate, dihydro-β-ionone, benzaldehyde, and a range of lactones (γ-decalactone, γ-hexalactone, γ-octalactone, δ-decalactone and γ-undecalactone). Overall, the melting flesh peach exhibited more pronounced aroma than the stony hard type. This study underscores the significance of understanding the intricate interplay between volatile compounds and aroma characteristics across cultivars with different textures, offering valuable insights into cultivar selection, flavor enhancement, and consumer preference assessment within the peach industry.

The Olfactory Working Memory Capacity Paradigm.

Working memory capacity (WMC), a crucial component of working memory (WM), has consistently drawn the attention of researchers. Exploring the underlying neurobiological mechanisms behind it is currently a prominent focus in the field of neuroscience. Previously, we developed a novel behavioral paradigm for rodents called the olfactory working memory capacity (OWMC) paradigm, which serves as an effective tool for quantifying the WMC of rodents. The OWMC task comprises five phases: context adaptation, digging training, rule-learning for nonmatching to a single sample odor (NMSS), rule-learning for nonmatching to multiple sample odors (NMMS), and capacity testing. In the first phase, mice are handled to reduce stress and acclimate to the training cage. The second phase involves training mice to dig in a bowl of unscented sawdust to locate a piece of cheese. In the third phase, mice are trained to locate the cheese pellet in a bowl with a noveal odor. The fourth phase requires mice to distinguish the novel odor among multiple scented bowls to locate the cheese pellet. Finally, in the fifth phase, mice undergo several WMC tests until they achieve a stable level of performance. In this protocol paper, we will provide detailed instructions on how to implement the behavioral paradigm. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Context adaptation Basic Protocol 2: Digging training Basic Protocol 3: Rule-learning for NMSS Basic Protocol 4: Rule-learning for NMMS Basic Protocol 5: Capacity testing.

Odor Biosensors Based on Cell Expressing Olfactory Receptor: Recent Advances

AbstractInspired by the powerful biological olfaction, scientists extracted numerous materials such as olfactory sensory neuron, olfactory receptor (OR) protein, and odorant binding protein from animal olfactory systems, then combined them with transducers to form multiple odor biosensors. These biosensors, despite well inheriting the sensing ability of creatures, have several drawbacks, such as complex preparation process, unstable sensing material characteristics, and high cost. Unlike the biological materials listed above, cell expressing heterologous OR maintains a stable sensing performance after passaging for multiple generations, also its experimental operation is simple, and cost is low. Therefore, odor biosensors based on cell expressing OR have been well developed in recent years. In this review, we first listed several odor biosensors based on cell expressing OR, mainly focusing on fluorescent and electrophysiological measurement methods. Furthermore, we illustrated the techniques to improve the biosensor performance, e. g., wider detection range, longer lifetime, more OR types, and higher quantification efficiency. In addition, we explained the possible prospects such as big sensor array and predicting odor response.

Discrete and continuous odor quantification in gas-phase odor biosensor

Cells expressing heterologous olfactory receptors (ORs) were commonly used as the sensing elements in odor biosensors owing to their high sensitivity and selectivity. However, The odor quantification performance of these biosensors especially in speed and accuracy aspects is not so favorable yet. To overcome this problem, we proposed discrete and continuous odor quantification. In this study, two ORs, Or13a and Or56a, and their agonists, 1-octen-3-ol and geosmin were used. The cell images were handled online to accelerate the processing speed. The odor intensity that we intended to quantify was the target odor, the odor intensity that we provided was the generated odor. The target and generated odors were repeatedly applied thus mitigating the sensor drift and aging influence. The target odor quantification outcome could be one of several discrete candidates (discrete quantification) or a continuous value computed based on the standard response curve (continuous quantification). We first obtained the typical results of the discrete and continuous quantification methods using single OR. After this, we executed the experiments in multiple target odor intensities and made a comparison between two methods. Discrete quantification was simpler while continuous quantification was faster and more accurate. In addition, both methods were tested under binary odor mixture conditions and their quantification results were satisfactory. The methods proposed here will benefit the on-site precise quantification of odor biosensors.

Odorant-sensing cell micropatterns for odor discrimination

A technology that can effectively distinguish between various odorants with high sensitivity and selectivity has numerous applications ranging from water quality testing to disease diagnosis. Here, we report a cell-based odorant-sensing display that utilizes Sf21 cells expressing odorant receptors, co-receptors, and a calcium-sensitive fluorescent protein as the sensing elements for detecting multiple odorants. Integrated micropatterns of the sensor cells in a few hundred micrometer-size patterns were fabricated on photoactivatable cell-anchoring surfaces consisting of photo-responsive polymeric materials. In the microfluidic system equipped with the sensing display, the injection of two model odorants, such as Bombykal and 1-octen-3-ol, at micro-molar concentrations resulted in selective and rapid fluorescence emission from the corresponding sensor cell patterns. Furthermore, when both odorants were injected together, the fluorescence from each corresponding sensor cell could be observed simultaneously. This study provides the proof of principle that the current cell patterning system enables the discrimination of odors, including multiple odorants, through a finely patterned sensing display on the device.

Sex differences in the context dependency of episodic memory.

Context contributes to multiple aspects of human episodic memory including segmentation and retrieval. The present studies tested if, in adult male and female mice, context influences the encoding of odors encountered in a single unsupervised sampling session of the type used for the routine acquisition of episodic memories. The three paradigms used differed in complexity (single vs. multiple odor cues) and period from sampling to testing. Results show that males consistently encode odors in a context-dependent manner: the mice discriminated novel from previously sampled cues when tested in the chamber of initial cue sampling but not in a distinct yet familiar chamber. This was independent of the interval between cue encounters or the latency from initial sampling to testing. In contrast, female mice acquired both single cues and the elements of multi-cue episodes, but recall of that information was dependent upon the surrounding context only when the cues were presented serially. These results extend the list of episodic memory features expressed by rodents and also introduce a striking and unexpected sex difference in context effects.

Olfactory receptors in Bactrocera species for sustainable fruit fly management: A review and future perspectives

AbstractMolecular studies on odorant receptors (ORs), odorant‐binding proteins (OBPs) and the functioning of the receptor and pheromone signal transduction in fruit fly Bactrocera species have expanded exponentially during the past few decades. OBPs contribute to the sensing of the olfactory system (OS) via the transduction of odorants through the sensillum lymph. However, ORs, a family of G‐protein‐coupled receptors in Bactrocera and various other species, exhibit heightened responsiveness to multiple chemical odours such as hormones, sensory stimuli and neurotransmitters. The apparent mechanism involves a combinatorial code encompassing both peripheral and antennal lobe processing, facilitating the reception of sexual pheromones and environmental cues. The OS is specifically designed to recognize and process information from volatile chemical signals, and these chemical signals play an important function in various flies. Insects rely on these chemicals to navigate and comprehend their surroundings. A mature insect OS is composed of two pairs of sensillae‐covered palps, antennae and two primary pairs of olfactory appendages on the anterior head. It has been shown that chemosensory gene families contribute in odour perception. These include various neuroreceptor families, such as OBPs, chemosensory proteins and sensory neuron membrane proteins. Additionally, there are three divergent chemoreceptors, namely ORs, ionotropic receptors and gustatory receptors. Methods based on systematic biology, molecular biology and bioinformatics tools have rapidly emerged to investigate the insect communication systems and provide new insights for the management of many agricultural pest. Several aromatic compounds, including semiochemicals and pheromones, have been employed to defend crops and animals from destructive fruit flies and other invasive and frugivorous species. To promote the expansion of the cropping system, the utilization of phytochemical lures can be convenient for sustainable agriculture production and enhance food security. Hence, this review examined the state of the art in chemical communication of insects with a focus on fruit fly pest species to identify OS and their semiochemical receptors, protein receptors and chemosensory receptors (CSRs), as well as their practical applications for biological control and integrated pest management are highlighted.

Biosensor systems: determination of optimal time parameters of olfactory stimulation

Biosensor systems are improving swiftly and become increasingly important in areas such as defense and security, medical field, especially, cancer screening and detection, environmental quality monitoring, and so forth. The present work describes the development of a biosensor system, based on the use of macrosmatic animal olfactory bulb (OB) visualized by optical imaging of odor-evoked glomerular activity patterns. The difficulties that automatic detection of odor-evoked patterns presents under multiple stimulation are associated with adaptation processes, which are manifested as a reversible change in the sensitivity of the neural structures of the olfactory system. The optimal stimulus duration and interstimulus intervals for stabilizing the glomerular response and getting images of glomerular activity patterns under the multiple odor stimulation with constant accuracy have been experimentally found. The results obtained show the availability of other resource in addition to the existing tools used for the development of biosensor systems.

Association Between Olfactory Test Data with Multiple Levels of Odor Intensity and Suspected Cognitive Impairment: A Cross-Sectional Study.

Olfactory function decline has recently been reported to be associated with a risk of cognitive impairment. Few population-based studies have included younger adults when examining the association between olfactory test data with multiple odor intensities and suspected cognitive impairment. We investigated the association between high-resolution olfactory test data with fewer odors and suspected cognitive impairments. We also examined the differences between older and younger adults in this association. The Japanese version of the Montreal Cognitive Assessment (MoCA-J) was administered to 1,450 participants, with three odor-intensity-level olfactometry using six different odors. Logistic regressions to discriminate suspected cognitive impairment were conducted to examine the association, adjusted for age, sex, education duration, and smoking history. Data were collected from the Program by Tohoku University Tohoku Medical Megabank Organization, with an additional olfactory test conducted between 2019 and 2021. We generally observed that the lower the limit of distinguishable odor intensity was, the higher the MoCA-J score was. The combination of spearmint and stuffy socks contributed most to the distinction between suspected and unsuspected cognitive impairment. Furthermore, the association was significant in women aged 60-74 years (adjusted odds ratio 0.881, 95% confidence interval [0.790, 0.983], p = 0.024). The results indicate an association between the limit of distinguishable odor intensity and cognitive function. The olfactory test with multiple odor intensity levels using fewer odors may be applicable for the early detection of mild cognitive impairment, especially in older women aged 60-74 years.

An Open-Source Olfactory Display to Add the Sense of Smell to the Metaverse

Abstract As the Metaverse gains popularity due to its use in various industries, so does the desire to take advantage of all its potential. While visual and audio technologies already provide access to the Metaverse, there is increasing interest in haptic and olfactory technologies, which are less developed and have been studied for a shorter time. Currently, there are limited options for users to experience the olfactory aspect of the Metaverse. This paper introduces an open-source kit that makes it simple to add the sense of smell to the Metaverse. The solution is modular, allowing for the simultaneous use of multiple odors and compatibility with both desktop and wearable applications. The details of the solution, including its technical specifications, are outlined to enable potential users to utilize, test, and enhance the project and make it available to the scientific community.

A Comparison of Multiple Odor Source Localization Algorithms

There are two primary algorithms for autonomous multiple odor source localization (MOSL) in an environment with turbulent fluid flow: Independent Posteriors (IP) and Dempster–Shafer (DS) theory algorithms. Both of these algorithms use a form of occupancy grid mapping to map the probability that a given location is a source. They have potential applications to assist in locating emitting sources using mobile point sensors. However, the performance and limitations of these two algorithms is currently unknown, and a better understanding of their effectiveness under various conditions is required prior to application. To address this knowledge gap, we tested the response of both algorithms to different environmental and odor search parameters. The localization performance of the algorithms was measured using the earth mover’s distance. Results indicate that the IP algorithm outperformed the DS theory algorithm by minimizing source attribution in locations where there were no sources, while correctly identifying source locations. The DS theory algorithm also identified actual sources correctly but incorrectly attributed emissions to many locations where there were no sources. These results suggest that the IP algorithm offers a more appropriate approach for solving the MOSL problem in environments with turbulent fluid flow.

FoxO directly regulates the expression of odorant receptor genes to govern olfactory plasticity upon starvation in Bactrocera dorsalis

Under nutrient-poor conditions, animals must save energy by adjusting their behavior and physiology in order to survive. Although the impact of feeding state on olfactory sensory neuron activity has been well studied, the regulatory mechanisms underlying the transcriptional changes in odorant receptors (Ors) induced by feeding signals are seldom mentioned. Here, we showed that starvation could attenuate antennal responses of Bactrocera dorsalis toward multiple odorants, which could be reverted by sugar re-feeding, but not by a protein-rich diet. Using methyl eugenol (ME) as a paradigm, our study provided molecular evidence that Forkhead Box protein O (FoxO) can be expressed in antennal tissues to govern starvation-induced olfactory modifications by binding to the upstream regulatory regions of ME-responsive Ors and regulating their expressions. Since the consensus FoxO binding motif was also identified in other 17 Ors whose expression levels were also significantly altered upon FoxO knockdown and starvation, our data suggest that FoxO-dependent binding is likely a universal regulatory mechanism for Or genes during starvation and re-feeding cycles. Taken together, the FoxO-Ors axis elucidated in this study provides an improved understanding of how the insulin signaling pathway senses the feeding state and certain macronutrient composition to shape olfactory plasticity, allowing flies to dynamically alter chemosensory sensitivities toward different odors. Our study also highlights sugar as a satiety signal, which could increase ME-mediated trap efficiency in the field.

Treatability evaluation of fourteen aldehyde odorants in drinking water by powdered activated carbon: Influence of odorant's properties on adsorption characteristics

Powdered activated carbon (PAC) was frequently used for removing musty and septic odor-causing compounds in water matrix. However, it is not known if PAC is effective on removing various aldehyde odorants. In this study, the treatability of fourteen aldehyde odorants by PAC adsorption was evaluated comprehensively. The results indicated that most aldehyde odorants' removal rates could reach 90 % after 0.5 h exposure, while adsorption kinetic was better fitted for pseudo second-order model, and adsorption capacity was better fitted with Freundlich model. However, adsorption predictions from these models, which neglected olfactory threshold concentration (OTC), were unsuitable for evaluating that odor caused by aldehyde odorant could be controlled effectively or not. Therefore, treatability value, which considered residual concentration and OTC, was calculated, the result of 0.3– 0.67 suggested they could be removed below OTC effectively by PAC adsorption. Furthermore, the effect of aldehyde odorant's property on adsorption and treatability was studied through Pearson and Spearman correlation analysis. The results indicated that there were not significant correlations between adsorption capacity and aldehyde odorants' properties. Comparatively speaking, treatability had significant and positive correlations with aldehyde odorants' properties including molar refractivity (MR), octanal and water (LogKW), parachar, polarizability and volume (r: 0.860– 0.942, p: 0.000), suggesting that odorant with larger volume, more hydrophobic, higher MR and polarizability would be adsorbed by PAC easily. This is the first study for evaluating adsorption of multiple aldehyde odorants onto PAC completely, which would supply more understanding for controlling aldehyde odorants in drinking water treatment plant (DWTP).

Decoding Seven Basic Odors by Investigating Pharmacophores and Molecular Features of Odorants

Background: The odors we perceive are primarily the result of a mixture of odorants. There can be one or multiple odors associated with an odorant. Several studies have attempted to link odorant physicochemical properties to specific olfactory perception; however, no universal rule that can determine how and to what extent molecular properties affect odor perception exists. Objective: This study aims to identify important and common features of odorants with seven basic odors (floral, fruity, minty, nutty, pungent, sweet, woody) to comprehend the complex topic of odors better. Methods: We adopted an in-silico approach to study key and common odorants features with seven fundamental odors (floral, fruity, minty, nutty, pungent, sweet, and woody). A dataset of 1136 odorants having one of the odors was built and studied. Results: A set of nineteen structural features has been proposed to identify seven fundamental odors rapidly. The findings also indicated associations between odors, and specific molecular features associated with each group of odorants and shared spatial distribution of odor features. Conclusion: This study revealed olfactory associations, unique chemical properties linked with each set of odorants, and a common spatial distribution of odor features for considered odors.

Decoding Structure–Odor Relationship Based on Hypergraph Neural Network and Deep Attentional Factorization Machine

Understanding the relationship between the chemical structure and physicochemical properties of odor molecules and olfactory perception, i.e., the structure–odor relationship, remains a decades-old, challenging task. However, the differences among the molecular structure graphs of different molecules are subtle and complex, and the molecular feature descriptors are numerous, with complex interactions that cause multiple odor perceptions. In this paper, we propose to decompose the features of the molecular structure graph into feature vectors corresponding to each odor perception descriptor to effectively explore higher-order semantic interactions between odor molecules and odor perception descriptors. We propose an olfactory perception prediction model noted as HGAFMN, which utilizes a hypergraph neural network with the olfactory lateral inhibition-inspired attention mechanism to learn the molecular structure feature from the odor molecular structure graph. Furthermore, existing methods cannot effectively extract interactive features in the large number of molecular feature descriptors, which have complex relations. To solve this problem, we add an attentional factorization mechanism to the deep neural network module and obtain a molecular descriptive feature through the deep feature combination based on the attention mechanism. Our proposed HGAFMN has achieved good results in extensive experiments and will help product design and quality assessment in the food, beverage, and fragrance industries.