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264 results for “Odorants”

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zenodo36/100

Fig. 1 in Comparison of natural and artificial odor lures for nilgai (Boselaphus tragocamelus) and white-tailed deer (Odocoileus virginianus) in South Texas: Developing treatment for cattle fever tick eradication

Fig. 1. The location of the study site (Santa Rosa Ranch) near Riviera, TX.

opencc-by-4.0Aug 2017View details →
zenodo36/100

Fig. 3 in Comparison of natural and artificial odor lures for nilgai (Boselaphus tragocamelus) and white-tailed deer (Odocoileus virginianus) in South Texas: Developing treatment for cattle fever tick eradication

Fig. 3. Lure bucket recessed into soil at each treatment location at the Santa Rosa Ranch.

opencc-by-4.0Aug 2017View details →
zenodo36/100

Fig. 4 in Comparison of natural and artificial odor lures for nilgai (Boselaphus tragocamelus) and white-tailed deer (Odocoileus virginianus) in South Texas: Developing treatment for cattle fever tick eradication

Fig. 4. Distribution of animal visits to lure sites at the Santa Rosa Ranch, near Riviera, TX.

opencc-by-4.0Aug 2017View details →
zenodo36/100

Dataset on the characterization of the flavor of two red wine varieties using sensory descriptive analysis, volatile organic compounds quantitative analysis by GC-MS and odorant composition by GC-MS-O

<p>The dataset contains data that were collected on 2 sets of 8 French red wines from two grape varieties, Pinot Noir (PN) and Cabernet Franc (CF). It provides, for the 16 wines, (i) sensory descriptive data obtained with a trained panel, (ii) volatile organic compounds (VOC) quantification data obtained by Gas Chromatography&ndash;Mass Spectrometry (GC-MS) and (iii) odorant composition obtained by Gas Chromatography&ndash;Mass Spectrometry&ndash;Olfactometry (GC-MS-O).</p> <p>&nbsp;</p> <p>The dataset is a&nbsp;Microsoft Excel Worksheet containing 8 sheets.</p> <p>- Sheet 1: Information</p> <p>Gives information about the sheets contained in this .xlsx file</p> <p>- Sheet 2: Experimental_factors</p> <p>Each row represents a wine</p> <p>Each column corresponds to an experimental factors of the wines (Grape variety, Vintage and Protected Designation of Origin)</p> <p>- Sheet 3: List_sensory_descriptors</p> <p>Lists the 33 sensory descriptors used for the sensory descriptive analysis of the wines</p> <p>- Sheet 4: Sensory_descriptive_analysis</p> <p>Each row represents a wine</p> <p>Each column corresponds to a condition (2640 columns)</p> <p>Senso_(ortho or retro)_(Panelist1 to Panelist 16)_(1 to 33 Sensory descriptors)_(1 to 3 repetitions for ortho and 1 to 2 repetitions for retro)</p> <p>For the ortho (orthonasal) measurements, there is 16 panelists, 33 sensory descriptors and 3 repetitions = 1584 columns</p> <p>For the retro (retronasal) measurements, there is 16 panelists, 33 sensory descriptors and 2 repetitions = 1056 columns</p> <p>Each cell contains a sensory measurement for the corresponding condition in the corresponding wine</p> <p>- Sheet 5: List_VOC</p> <p>Lists the 45 VOC quantified in the wines with their corresponding CAS number</p> <p>VOC: Volatil Organic Compounds</p> <p>- Sheet 6: VOC_quantification</p> <p>Each row represents a wine</p> <p>Each column corresponds to a VOC (45 columns)</p> <p>Each cell contains the quantification of the corresponding VOC in the corresponding wine</p> <p>- Sheet 7: List_GC-MS-O</p> <p>Lists the 49 odor-active compounds identified with their corresponding CAS number and the 34 compounds identified by their apex indice</p> <p>-&nbsp;Sheet 8: GC-MS-O</p> <p>Each row represents a wine</p> <p>Each column corresponds to an odor-active compound identified by its CAS number or by its Apex indice if the compound was not identify (81 odor-active compounds) + the number of judges who smelled the compound and its description (by 8 judges) = 9 columns per odor-active compound for a total of 729 columns</p>

opencc-by-4.0Apr 2018View details →
zenodo36/100

Local synaptic inputs support opposing, network-specific odor representations in a widely projecting modulatory neuron

<p>This is the data set for Zhang et al. 2019 &quot;Local synaptic inputs support opposing, network-specific odor representations in a widely projecting modulatory neuron&quot; published at eLife.</p>

opencc-by-4.0Jul 2019View details →
zenodo36/100

Smell the stress: Subjective ratings of body odors reliably indicate stress levels

<p><strong><span>Background:</span></strong><span> Chemosensory signals like body odor carry information about the emotional state of individuals like fear or stress. Analysis of sweat odor could therefore deliver an easy option of assessing stress. Our aim was to examine if subjective odor ratings can reliably and validly capture characteristics of sweat odor. For this we presented odor samples of stressed individuals to na&iuml;ve participants who rated these concerning their intensity, valence, and stress. Furthermore, we compared odor rating results to well-studied physiological markers of stress that we obtained from the odor donors during the stress task.</span></p> <p><strong><span>Method:</span></strong><span> Odor donors were 30 men and 30 women who performed a standardized protocol to induce social stress while wearing axillary pads under each armpit. Additionally, we measured <span>&nbsp;</span><span>&nbsp;</span>cortisol in saliva, adrenaline in blood and recorded participants&rsquo; heart rate. For odor ratings, we recruited an independent sample of 40 individuals. Participants rated the odor samples using visual analog scales.</span></p> <p><strong><span>Results:</span></strong><span> Intraclass correlations revealed a fair level of clinical significance for intensity and valence of sweat odors. Additionally, retest reliability was moderate for these two odor qualities. Ratings of stress also showed a moderate retest reliability, but the intraclass correlation was on a poor level. In further analyses we found significant relationships between all three qualities. Correlations between subjective ratings of body odors and physiological stress markers of odor donors were not significant. </span></p> <p><strong><span>Discussion: </span></strong><span>Our data show that<strong> </strong>subjective ratings of body odor qualities, in particular intensity and valence are reliable. Further research on validity is needed.</span></p>

opencc-by-4.0Oct 2024View details →
zenodo36/100

Active sensing in bees through antennal movements is independent of odor molecule (source videos)

<p>Videos of restrained bombus terrestris stimulated by odors to record their antennal movements. The video were used in the following preprint: https://www.biorxiv.org/content/10.1101/2021.09.13.460114v1</p> <p>&nbsp;</p>

opencc-by-4.0Oct 2021View details →
zenodo36/100

Data for: Neural correlates of individual odor preference in Drosophila

<p>Data associated with: Neural correlates of individual odor preference in Drosophila</p> <p>Abstract: Behavior varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical origins of this individuality. We show individual <em>Drosophila </em>odor preferences (odor-vs-air and odor-vs-odor) are predicted by idiosyncratic calcium dynamics in olfactory receptor neurons (ORNs) and projection neurons (PNs), respectively. Variation in ORN presynaptic density also predicts odor-vs-odor preference. The ORN-PN synapse appears to be a locus of individuality where microscale variation gives rise to idiosyncratic behavior. Finally, simulating microscale stochasticity in ORN-PN synapses of a 3,062-neuron model of the antennal lobe recapitulates patterns of variation in PN calcium responses matching experiments. Our results demonstrate how physiological and microscale structural circuit variations can give rise to individual behavior, even when genetics and environment are held constant.</p>

opencc-by-4.0Dec 2021View details →
dryad36/100

Spatial learning overshadows learning odors and sounds in both predatory and frugivorous bats

<p>To forage efficiently, animals should selectively attend to and remember the cues of food that best predict future meals. One hypothesis is that animals with different foraging strategies should vary in their reliance on spatial versus feature cues. Specifically, animals that store food in dispersed caches or that feed on spatially stable food, like fruit or flowers, should be relatively biased to learning a meal's location, whereas predators that hunt mobile prey should instead be relatively biased towards learning feature cues such as odor or sound. Several authors have predicted that nectar-feeding and fruit-feeding bats would rely relatively more on spatial cues, whereas closely related predatory bats would rely more on feature cues, yet no experiment has compared these two foraging strategies under the same conditions. To test this hypothesis, we compared learning in the frugivorous bat, <em>Artibeus jamaicensis</em>, and the predatory bat, <em>Lophostoma silvicolum</em>, which hunts katydids using acoustic cues. We trained bats to find food paired with a unique and novel odor, sound, and location. To assess which cues each bat had learned, we then dissociated these cues to create conflicting information. Rather than finding that the frugivore and predator clearly differ in their relative reliance on spatial versus feature cues, we found that both species used spatial cues over sounds or odors in subsequent foraging decisions. We interpret these results alongside past findings on how foraging animals use spatial cues versus feature cues and explore why spatial cues may be fundamentally more rich, salient, or memorable.</p>

opencc-zeroDec 2022View details →
dryad36/100

Odor plume tracking behavior of walking and flying insects

<p><span></span></p> <p>Many animals locate food, mates, and territories by following plumes of attractive odors. There are clear differences in the structure of this plume tracking behavior depending on whether an animal is flying, swimming, walking, or crawling. These differences could arise from different control rules used by the central nervous system during these different modes of locomotion or one set of rules interacting with the different environments encountered by animals suspended in flow or moving across the ground. Flow speeds and turbulence that characterize the environments where walking and flying insects track plumes may alter the structure of odor plumes in an environment-specific way that results in the same control rules generating behaviors that appear quite different. We tested these ideas by challenging walking male cockroaches, <em>Periplaneta</em> <em>americana</em>, and flying male moths, <em>Manduca</em> <em>sexta</em>, to track plumes of their species' sex-pheromones in low wind speeds characteristic of cockroach experimental environments, higher wind speeds characteristic of moth experimental environments, and conditions ranging from low to high turbulence. Introducing a turbulence-generating structure into the flow significantly improved the flying plume tracker's ability to locate the odor source, and changed the structure of the behavior of both flying and walking plume trackers. Specifically, the walking and flying plume trackers located the odor source more often in experimental conditions characteristic of environments in which they live suggesting differing reliance on spatial and temporal measurements of the odor plume.</p>

opencc-zeroJan 2023View details →
dryad36/100

The raw data of large odorous frogs mate selection

<p><span>In anurans, the complexity of courtship calls may effect female mate choice. The current study suggests that nonlinear phenomena (NLP) components can contribute to increasing complexity in courtship calls and attracting female attention. The results</span><span> of a recent study showed that calls of large odorous frog (<em>Odorrana graminea</em>) contained NLP components. However, whether the nonlinear components of courtship calls in </span><em><span>O</span><span>.</span><span> graminea</span></em><span> improve male attractiveness </span><span>remains</span><span> unknown. </span></p> <p><span>We hypothesized that female <em>O. graminea</em> would prefer males producing calls with a higher proportion of NLP components (P-NLP-C). To test this hypothesis, we recorded the advertisement calls of 28 males and confirmed that the P-NLP-C was significantly positively related to body size. We also measured the body size of natural amplectant males and non-amplectant males in the field, and found that amplectant males had larger body sizes than non-amplectant males, and the results of two-choice amplexus experiments similarly revealed a female preference for males with larger body sizes. Additionally, phonotaxis experiments also revealed that females preferred male calls with a high P-NLP-C. </span></p> <p><span>The results suggest that a higher P-NLP-C in calls can enhance male attractiveness, and</span> <span>the P-NLP-C may provide key information about male body conditions for female <em>O. graminea</em>. Our study provides a new insight for better understanding the role of NLP in anuran mate selection.</span></p>

opencc-zeroFeb 2023View details →
zenodo36/100

Data and codes of "Odor descriptive ratings can predict some odor-color associations in different color features of hue or lightness"

<p>This project included data and codes used in our original article titled &quot;Odor descriptive ratings can predict some odor-color associations in different color features of hue or lightness&quot;, written by Kaori Tamura and Tsuyoshi Okamoto.</p> <p>Please see https://gitlab.com/tamurak415/olfqr</p>

opencc-by-4.0Mar 2023View details →
zenodo36/100

Data for: Neural correlates of individual odor preference in Drosophila

<p>Data associated with: Neural correlates of individual odor preference in <em>Drosophila</em></p> <p>Behavior varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical origins of this individuality. We show individual <em>Drosophila</em> odor preferences (odor-vs-air and odor-vs-odor) are predicted by idiosyncratic calcium dynamics in olfactory receptor neurons (ORNs) and projection neurons (PNs), respectively. Variation in ORN presynaptic density also predicts odor-vs-odor preference. The ORN-PN synapse appears to be a locus of individuality where microscale variation gives rise to idiosyncratic behavior. Finally, simulating microscale stochasticity in ORN-PN synapses of a 3,062-neuron model of the antennal lobe recapitulates patterns of variation in PN calcium responses matching experiments. Our results demonstrate how physiological and microscale structural circuit variations can give rise to individual behavior, even when genetics and environment are held constant.</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

Insect Odorant Binding Protein Dataset of Binding Affinities against Volatile Organic Compounds

<p>This is an archival version of the initial iOBPdb dataset of insect odorant binding protein binding affinities against volatile organic compounds. It&nbsp;contains&nbsp;181 functional studies containing 382&nbsp;unique OBPs from 91 insect species for 622 individual VOC targets.</p>

opencc-by-4.0Sep 2022View details →
dryad36/100

Data from: African elephant dietary responses to odors of monoterpene mixtures and individual monoterpenes

<p>The detoxification limitation hypothesis posits that, unless plant defense compounds interact synergistically or additively to increase their harmful effects, generalist herbivores will prefer consuming combinations of these compounds over singular compounds. Monoterpenes are odoriferous defense compounds that may be toxic to mammalian herbivores when ingested in sufficient quantities. Previous research has shown that the addition of individual monoterpenes to food sources reduces consumption by generalist mammalian herbivores. By using African elephants as a case study, we aimed to determine whether odors from monoterpene combinations (i.e., two or more monoterpenes) also deter generalist mammalian herbivory, and whether generalist herbivores prefer the odors of monoterpene combinations over individual monoterpenes. First, we tested whether the odor of monoterpene combinations that resemble the monoterpene profiles of a high-acceptability, intermediate-acceptability, and low-acceptability plant deter herbivory. We found that elephants preferred plants without the added odors of the monoterpene combinations. Second, we explored how elephants responded to individual monoterpenes found within the combinations compared to the combinations at the same set concentration, and found that the elephants did not always prefer the combinations over the individual monoterpenes. Moreover, the more diverse the combination, the less frequently it was preferred when compared to the individual monoterpene odors. Our results imply that generalist herbivores do not necessarily prefer combinations of plant chemical defenses at comparatively lower concentrations and that, consequently, the composition and diversity of monoterpene profiles in plants likely determine the efficacy of these compounds as an olfactory defense against mammalian herbivory.</p>

opencc-zeroJul 2023View details →
zenodo36/100

The transcriptional logic of ant odorant receptors

<p>We utilize snRNA-Seq to investigate the expression of odorant receptor genes in olfactory sensory neurons of the developing pupae of the clonal raider ant, <em>Ooceraea biroi</em>.</p>

opencc-by-4.0Aug 2023View details →
ClinicalTrials.gov36/100

Evaluation of Potential Screening Tools for Metabolic Body Odor and Halitosis

ClinicalTrials.gov study NCT02692495. IPD Sharing: YES. Countries: 1. Publications: 8.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov36/100

Bacteriotherapy to Improve Underarm Odor

ClinicalTrials.gov study NCT03967470. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
dryad36/100

Data from: Odor source distance is predictable from time-histories of odor statistics for large scale outdoor plumes

Open the record for dataset details and reuse information.

publicMar 2024View details →
dryad36/100

Data presented in: Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters

Open the record for dataset details and reuse information.

publicJul 2021View details →

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