110 results about "Olfactory receptor" patented technology

The invention discloses a dynamic optimization system and method for a compound essential oil ratio, and aims to solve the problems that the traditional technology depends on artificial experience, the optimization efficiency is low and the quality tracing is insufficient. According to the method, raw material molecular fingerprint data are collected in real time through a high-precision spectrum sensor array and a micro-fluidic chip, a production environment field domain is constructed in combination with a computational fluid mechanics model, a formula optimization problem is encoded into an Ising model by using a quantum annealing algorithm, and global search is realized through a quantum tunneling effect. The system integrates digital twin bodies, covers molecular dynamics simulation, phase equilibrium prediction and olfactory receptor activation probability simulation, and accurately maps a physical system state; a multi-modal data fusion network and a reinforcement learning framework are adopted to dynamically adjust formula parameters, and an NSGA-III algorithm is combined to optimize efficacy collaboration degree, cost and stability indexes. And the execution control module realizes nanoscale flow regulation through the piezoelectric micro-injection valve array, and realizes non-tampering evidence storage of formula parameters and quality data based on a block chain technology. Dynamic closed-loop optimization of the compound essential oil ratio is achieved, the production efficiency, the product consistency and the supply chain transparency are remarkably improved, and the method is suitable for the field of intelligent manufacturing of high-end essential oil.

The invention discloses a nanopore sensor based on insect olfactory receptor protein as well as a construction method and application thereof, and belongs to the field of biosensors. According to the invention, the insect olfactory receptor protein is used as a sensitive element to be integrated into a nanopore measurement system, so that the nanopore sensor is obtained. By measuring a nanopore current signal, the prepared sensor is applied to detection of target odorant molecules. According to the method, the recognition capability of the insect olfactory receptor protein on odorant molecules and the single molecule level detection capability of the nanopores are utilized, expensive large experimental instruments and complex experimental operation steps are not needed, and sensitive, rapid and direct detection on odorant substances can be realized.

The invention provides a molecular smell recognition method, device and equipment, a medium and a product, and the method comprises the steps: obtaining a plurality of gas molecules in a target region; performing substance identification on the plurality of gas molecules, and determining the substance structure of each gas molecule; determining the SMILES formula of each gas molecule according to the substance structure of each gas molecule; carrying out standardization treatment on the SMILES formula of each gas molecule to obtain a target SMILES formula of each gas molecule; generating a target virtual code according to the plurality of target SMILES formulas and preset olfactory receptor information; inputting the target virtual code and a plurality of target SMILES into a trained OR-POM model, and determining a smell label of each gas molecule; and determining the odor in the target area and an odor space map in the target space according to the odor label of each gas molecule. According to the SMILES type of the gas molecules and olfactory receptor information, stereoisomerous information analysis of the odor molecules can be carried out, and the odor of the gas molecules can be coded and identified.

The invention relates to the technical field of nuclear radiation detection management, and discloses a nuclear radiation detection management system based on artificial intelligence, comprising: a dynamic sensing module which detects nuclear radiation through quantum sensing to obtain radiation data, captures NV color center fluorescence intensity, analyzes to obtain gamma ray dose rate, constructs a nanoscale olfactory receptor simulation structure, and sends the radiation data to a control module; radioactive gas is detected and cooperatively monitored; the reasoning calculation module is used for analyzing space-time correlation based on radiation data, optimizing algorithm to accelerate result output, adjusting calculation complexity by calculating dynamic weight distillation, and correcting data transmission in real time; the decision management module is used for constructing a four-dimensional causal graph based on the radiation data, performing intervention simulation, evaluating a decision long-term effect, screening an optimal decision, and performing adversarial training based on historical repair case data; and the fusion cooperation module is used for establishing a cross-mechanism federated learning framework, carrying out hash operation on the radiation data, and establishing an NFT (Network Fourier Transform) on a block chain through an intelligent contract for query, verification and transaction.

The invention discloses a method for predicting an interaction relationship between aroma substances based on a decision tree algorithm. The method comprises the following steps: constructing an aroma substance interaction relationship database; training the C5.0 decision tree prediction model based on the Booting algorithm by taking data of the aroma substance interaction relationship database as a training test data set to obtain an optimal prediction model; and utilizing the optimal prediction model to obtain the interaction relationship of the aroma substance combination to be predicted. According to the method disclosed by the invention, the decision tree model is adopted to carry out association modeling on binding energy data and sensory experiment results, and a Boosting algorithm is introduced to optimize model parameters, so that deep fusion of olfactory receptor binding energy and sensory evaluation data is realized; and through multi-dimensional data integration, the aroma substance interaction prediction precision is remarkably improved, and the method has wide applicability and good application prospects.

The invention belongs to the technical field of food processing. The invention discloses a method for targeted determination of an optimal composite combination for masking reheating peculiar smell of prefabricated aquatic products by using terpene compounds. The method is characterized by comprising the following steps: (1) selecting peculiar smell compounds; (2) carrying out molecular docking on the odor compound and an olfactory receptor to obtain a key olfactory receptor; (3) combining the terpene compound and the odor compound, and performing binary molecular docking with the key olfactory receptor to obtain a typical terpene compound capable of masking reheating odor; (4) obtaining an odorless substrate; (5) taking the prepared odorless substrate as a medium to obtain a key terpene compound with a masking effect; (6) determining the theoretical minimum inhibition concentration of peculiar smell; and (7) obtaining an optimal compound combination capable of effectively inhibiting reheating peculiar smell and keeping the original flavor of the aquatic products. The optimal composite composition obtained by the method can effectively mask characteristic peculiar smell generated in the reheating process of the prefabricated aquatic product, and can well maintain the original flavor of the aquatic product.

The invention discloses a method for multi-dimensionally researching synergistic effect among aromas based on human sense-olfaction receptors, which comprises the following steps: firstly, measuring threshold values and interaction effects of aroma substances by using sensory experiments so as to characterize olfaction perception interaction among aroma compounds; constructing an olfactory receptor in-vitro heterologous expression cell model and an olfactory receptor expression element; carrying out olfaction receptor expression and determination; and finally, determining the activation effect of the binary aroma system on the olfactory receptor, and comparing the activation effects of the single substance and the binary system on the receptor so as to research the interaction effect of the aroma compounds at the receptor level. The method is a brand-new method for researching interaction among fragrances from multiple angles based on human sense organs and olfactory receptors, combines the advantages of high integration of human sense organs and high sensitivity of olfactory receptors, makes up for the defect that the interaction of flavor substances can be researched only through human sense organ experiments in the prior art, is intuitive and reliable in shown result, and is suitable for large-scale popularization and application. The applicability is wide.

Embodiments of the present application provide a method, device, medium, equipment and product for classifying wine samples, relating to the technical field of artificial intelligence. The method comprises: contacting odor molecules of a wine sample with at least one recombinant cell expressing an olfactory receptor and a reporter protein, the reporter protein generating a detectable signal after the receptor binds to the odor molecules; obtaining time series data of the signal, calculating the maximum value and baseline value thereof, and determining a response characteristic value of each olfactory receptor according to the same; and inputting the characteristic value into a trained machine learning model to obtain a wine sample classification result. The present method accurately extracts a stable characteristic value of the response of an olfactory receptor to a wine sample, thereby eliminating interference caused by initial value fluctuations and improving the accuracy of model classification.

The invention provides methods for associating volatile compounds or mixtures of volatile compounds with combinatorial response patterns of Olfactory Receptors (OlfRs), a biosensor array comprising a plurality of biosensors, the use of said biosensor and of the method of the invention to screen for diseases, a molecule identified by a method of the invention as well as the use se of said molecule to modify the behavior of an insect.

The present invention addresses the problem of providing a cancer inspection technology in which an olfactory receptor is used. The problem is solved by a cancer test agent containing an insect olfactory receptor protein B' which demonstrates reactivity to multiple types of cancer with the same reactivity direction.

The invention discloses a method for analyzing aroma components of cooking wine based on molecular docking and an odor activity value and application. According to the method, cooking wine aroma is taken as a research object, volatile substances are detected by gas chromatography-mass spectrometry (GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), and by combining with odor activity value (OAV) analysis, the combining capacity of aroma molecules and olfactory receptors is simulated through molecular docking, characteristic aroma compounds are screened, and the aroma of the cooking wine is detected. And finally, constructing a recombinant aroma model according to the characteristic aroma compounds, carrying out sensory evaluation, and evaluating the aroma similarity of the recombinant aroma model and the natural cooking wine sample to determine the characteristic aroma components of the cooking wine. The method can be used for analyzing aroma substances of cooking wine and performing standardized flavor management.

To provide a method for screening an olfactory receptor protein or its combination useful in cancer examination.SOLUTION: A method for screening an olfactory receptor protein or a combination thereof, comprising testing the reactivity of a test olfactory receptor protein to cancer, and selecting at least one selected from the group consisting of (1) a combination of the olfactory receptor protein A and the olfactory receptor protein C, (2) a combination of the olfactory receptor protein A ' and the olfactory receptor protein B, and (3) the olfactory receptor protein B '.SELECTED DRAWING: None

To provide a technique for suppressing off-flavor.SOLUTION: An olfactory receptor OR51E1, OR51E2, OR2C1, OR2B11, OR2L8, OR8B3, OR8D1, OR10A3 or OR10G4 is used to screen a substance suppressing off-flavor. The screened substance is used to suppress the off-flavor in a target such as food products.SELECTED DRAWING: None

The present application belongs to the technical field of fruit fly prevention and control, and discloses a disorienting agent, a preparation method and application thereof. The disorienting agent contains rosemary extract and orange peel essential oil. The rosemary extract and orange peel essential oil contain terpenes and other compounds (such as 1,8-cineole in rosemary), which can compete with natural signal molecules to bind to odor binding proteins or olfactory receptors, which can cause fruit flies to fail to activate the correct nerve signal or directly block the signal transduction pathway. The orange peel essential oil in the disorienting agent has a strong smell, which can strongly cover or mask the weak smell signal emitted by the fruit, forming an "olfactory masking" effect, so that the fruit fly cannot find the fruit. Moreover, compared with sex pheromones as disorienting agents, which can only act on male fruit flies, the disorienting agent of the present application can interfere with the olfactory receptors of adult fruit flies to make them unable to find the target, so that they cannot accurately locate the oviposition site and harm the fruit. The disorienting agent is effective for both female and male fruit flies.

The invention discloses application of 6-methylcoumarin in preparation of a medicine for treating prostatic cancer, and relates to the technical field of medicines. The technical problem to be solved is to provide application of 6-methylcoumarin in preparation of drugs, health care products and functional food for treating prostatic cancer. The key point of the technical scheme is as follows: 6-methylcoumarin is used as an efficient ligand of an olfactory receptor OR51E2 to regulate prostate cancer cells so as to treat prostate cancer. In the prostate cancer cells LNCaP highly expressed by OR51E2, the 6-methylcoumarin can significantly inhibit cell proliferation, the inhibition effect of the 6-methylcoumarin is positively correlated with the action concentration of the 6-methylcoumarin, a new molecular target and a technical path are provided for prostate cancer treatment, the adopted 6-methylcoumarin has good chemical stability and application safety, and the 6-methylcoumarin has good application prospects. The potential of further drug development and transformation application is realized.

This invention provides a simple method for evaluating whether or not a peptide binds to isovaleric acid. [Solution] A method for evaluating the binding affinity to isovaleric acid, comprising a preparation step of preparing a fluorescently labeled compound in which a fluorescent group is bonded to the α-carbon atom of isovaleric acid, and a contact step of contacting the fluorescently labeled compound with a peptide fragment of an olfactory receptor.

The application discloses a multi-parameter integrated bionic smell sensing chip and a preparation method and application thereof, and has the characteristics of high flux, small size, high integration and low energy consumption by integrating tens of human olfactory receptor proteins and field effect transistors on the same chip by combining MEMS technology and bionic sensing technology. When gas molecules are combined with the olfactory receptor proteins on the chip, the protein conformation changes, the gate current of the field effect transistor is changed, the current signal is normalized, the response spectrum of different gas molecules is constructed to form a smell database, the cross-sensitivity of the olfactory receptor proteins is utilized, and a pattern recognition algorithm is combined to realize high-dimensional detection and accurate identification of a large number of different smells. The smell sensing chip has wide application prospects in the fields of air quality monitoring, food safety and hazardous product detection.

Disclosed herein are compounds and ligands, and compositions formed therewith, that modulate insulin secretion and suppress appetite by activating ectopic olfactory receptors. Also disclosed herein are methods for using the compositions to treat endocrine diseases, such as type-2 diabetes, and disorders, such as abnormal insulin secretion.

The present invention discloses a method for predicting olfactory receptor function based on transfer learning and molecular docking, comprising: obtaining a source domain dataset and a target domain dataset; using a feature extraction module to build a function prediction model by merging feature vectors and inputting them into a fully connected neural network; pre-training the function prediction model using the source domain dataset, and fine-tuning the function prediction model using the target domain dataset to obtain a first-step transfer learning model; determining whether the target species for which the olfactory receptor function is to be predicted is consistent with the species corresponding to the target domain dataset; if so, using the first-step transfer learning model to predict the olfactory receptor function; if not, performing one or more fine-tuning steps on the first-step transfer learning model until a second-step transfer learning model for predicting the olfactory receptor function is obtained. The method of the present invention effectively combines experimental data, molecular simulation, and deep learning technology to achieve rapid and accurate prediction of large-scale olfactory receptor function.

The purpose of the present invention is to suppress the effect of ultraviolet light on melanocytes. Upon performance of gene expression analysis with a focus on the olfactory receptor OR2L13 expressed by melanocytes, it was discovered that addition of (−)-carvone, a ligand of OR2L13, increased the expression of genes related to suppression of active oxygen, suppression of the production of inflammatory cytokines or chemokines, suppression of senescence, and / or degradation of abnormal proteins. As a result of said discovery, the present invention provides an inhibitor of the effects of ultraviolet light on melanocytes that includes (−)-carvone.

The invention relates to the technical field of food flavor analysis and intelligent perception. The aroma prediction method and system based on olfactory receptors and dynamic simulation are provided, and the method comprises the following steps: based on a public olfactory receptor database, carrying out integration processing on ligand specificity data of various human olfactory receptors and combination experiment data of a target aroma substance to generate a combination characteristic database; performing simulation processing on the environmental parameters of the target scene through the bionic reactor to obtain dynamic release data; carrying out machine learning model training processing based on the combination characteristic database and the dynamic release data, and generating an aroma contribution degree prediction model; performing aroma reconstruction experiment and sensory evaluation processing based on key aroma substance sorting output by the aroma contribution degree prediction model, and verifying prediction accuracy; the technical effects that the goodness of fit between aroma prediction and real olfactory experience is improved, the correlation deviation between the dynamic release process and the sensory intensity is reduced, the analysis efficiency is improved, and the industrial high-throughput requirement is met are achieved.

Provided is an approach which can express an olfactory receptor and function. The present invention provides a method for expressing an olfactory receptor polypeptide, comprising expressing, in a cell, an olfactory receptor polypeptide consisting of an amino acid sequence obtained by, in an amino acid sequence of an olfactory receptor of interest, altering at least one amino acid residue different from that in a consensus amino acid sequence to the amino acid residue at a position corresponding thereto in the consensus amino acid sequence, wherein the consensus amino acid sequence is an amino acid sequence obtained by alignment of the amino acid sequence of the olfactory receptor of interest and amino acid sequences of particular olfactory receptors.

Provided in the present invention are a method for preparing a compound and the use thereof as an olfactory receptor OLFR110 agonist. The compound of the present invention is capable of activating OLFR110 in vitro, and binding to OLFR110. The results of animal experiments show that the compound can significantly reduce the body weight of mice and improve blood glucose homeostasis. The compound of the present invention or a pharmaceutically acceptable salt or solvate thereof can be used as a potential pharmaceutical lead compound for treating obesity and diabetes.

A butyric acid detection based platform for verifying placement of a patient airway device or a gastric tube comprising at least one of i) a colorimetric based butyric acid detection platform, ii) a bioelectronic sensors based butyric acid detection platform using olfactory receptors, and iii) an IR based butyric acid detection platform. Each platform comprises a housing coupled to the patient airway device or gastric tube whereby flow from the coupled patient airway device or a gastric tube can flow through an internal passage of the housing; and wherein sensors within the housing come into contact with the flow from the coupled patient airway device or a gastric tube, the sensors including at least one of a chemical sensor array including at least one of i) colorimetric based butyric acid sensor, ii) a bioelectronic butyric acid detection sensor using olfactory receptors, and iii) an IR based butyric acid sensor.

This invention discloses a nanopore sensor based on insect olfactory receptor proteins, its construction method, and its applications, belonging to the field of biosensors. This invention obtains the nanopore sensor by integrating insect olfactory receptor proteins as sensitive elements into a nanopore measurement system. By measuring the nanopore current signal, the prepared sensor is applied to the detection of target odor molecules. This invention utilizes the recognition ability of insect olfactory receptor proteins for odor molecules and the single-molecule level detection capability of nanopores, achieving sensitive, rapid, and direct detection of odor substances without the need for expensive, large-scale experimental equipment and complex experimental procedures.

To provide a method for searching for soybean off-flavor suppressants, and to provide soybean off-flavor suppressants.SOLUTION: Provided is a method for searching for soybean off-flavor suppressants, comprising the following steps (1) to (3): (1) contacting the olfactory receptor OR5K1 with a test substance and a soybean off-flavor-causing substance; (2) measuring the olfactory receptor response to the test substance and the soybean off-flavor-causing substance after the contact; and (3) selecting, based on the results of the measurement, a test substance that suppresses the olfactory receptor response compared to a control as a candidate soybean off-flavor suppressant.SELECTED DRAWING: None

This invention discloses a method for screening odor inhibitors based on olfactory receptors and intermolecular interactions in the field of deodorization technology. The method includes: using an olfactory receptor database, multi-level screening or machine learning to predict olfactory receptors that a target odor pollutant can bind to or activate; multi-level screening or machine learning to predict potential inhibitors of the olfactory receptors; calculating the binding energy between the olfactory receptors and the target odor pollutant, and the screened or predicted inhibitors; preferentially selecting potential inhibitors with binding energies lower than those of the target odor pollutant; and using an electronic nose to test the odor-reducing effect of the potential inhibitors on the target odor pollutant. This invention proposes a screening method for odor inhibitors from the perspective of olfactory mechanisms. By utilizing the competitive and inhibitory effects of substances on olfactory receptors, it weakens the olfactory response of the target odor pollutant, thereby achieving the effect of odor suppression. Compared with manual olfactory screening methods, this method can effectively improve the development efficiency of deodorants and reduce workload, cost, and health risks.

The application relates to a smell molecule and olfactory receptor reaction prediction method and device based on a multi-modal deep learning network. The method first uses the interaction data between smell molecules and olfactory receptors, extracts the physical and chemical descriptors of the smell molecules as the characteristics of the smell molecules, uses a deep learning network model to determine whether unknown smell molecules can stimulate olfactory receptors. Secondly, sequence data of the smell molecules are used to determine the possibility of the reaction between the smell molecules and each olfactory receptor through a network calculation model. Then, smell molecule structure image data are further introduced to calculate the reaction probability between the smell molecules and each olfactory receptor. Finally, in order to improve the accuracy and reliability of the recognition result, the obtained calculation results, i.e. two probability distributions, are analyzed to determine the final reaction olfactory receptor of the smell molecule. The application significantly improves the accuracy of the recognition of the smell molecules and the olfactory receptors, reduces the dependence on experimental methods, and provides a new tool for chemical and biological research.

The present invention relates to the fragrance industry. More specifically, the present invention relates to assays and methods for screening and identifying compositions and / or ingredients that enhance a subject's perception of a target odorant compound based on the use of specific olfactory receptors activated by the target odorant compound.

The invention discloses a tomato leaf miner behavior regulating agent and a screening method and application thereof, and relates to the technical field of agricultural pest control, and the active ingredients of the behavior regulating agent are any one or more of limonene, E-beta-caryophyllene and terpinene. The screening method comprises the following steps: screening volatile matters with high affinity with a tomato leaf miner olfaction receptor from a tomato volatile matter library through a molecular docking technology, and carrying out biological activity verification in combination with an electroantennal potential experiment and a Y-type olfactometer behavior experiment, so as to accurately obtain the component with remarkable attraction activity. The behavior regulating agent can be used for preparing an attractant and is applied to green prevention and control of tomato leaf miners. According to the invention, efficient screening from a molecular mechanism to a behavior effect is realized, and a new product and technical support are provided for targeted prevention and control.