617 results about "Respiratory disease" patented technology

The invention relates to the field of biological medicine, and discloses a method and system for analyzing cough sound by using disease characteristics to diagnose respiratory diseases, and the method comprises the steps: deploying a six-microphone annular array to achieve the precise positioning and triggering of a sound source; self-adaptive spectral subtraction and Wiener filtering cascade are adopted to enhance the audio; segmenting a cough segment based on energy envelope; fusing the Mel-cepstrum, the linear prediction residual error, the harmonic energy ratio and the transient zero-crossing rate to construct a pathological feature matrix; extracting local, medium-range and global time sequence features through a three-branch parallel convolutional network; inputting a disease specific classifier to discriminate asthma, pneumonia and laryngitis respectively, and applying a feature decoupling regular term to improve interpretability. The system correspondingly realizes the modularized processing flow. According to the method, the cough sound collection quality and the disease subtype recognition accuracy in a complex environment are improved, meanwhile, the thermodynamic diagram is output to assist clinical decision making, and the diagnosis credibility and practicability are enhanced.

The invention relates to a sodium channel regulator for inhibiting Nav1.8, and provides a compound as shown in a formula I which can be used as the sodium channel regulator for inhibiting Nav1.8, and an isomer of the compound, or a pharmaceutically acceptable salt of the compound, the invention also provides a pharmaceutical composition containing the compound and the isomer thereof, or the pharmaceutically acceptable salt thereof and a carrier or excipient, and a pharmaceutical application of the pharmaceutical composition as a NaV1.8 inhibitor (such as pain, respiratory diseases, neurological disorders, mental diseases and the like).

The present invention relates to a pharmaceutical composition comprising a weak acid drug, with the use of a bicarbonate salt to achieve a high incorporation of the drug into the liposome and a better therapeutic efficacy. Also disclosed is a method for treating a respiratory disease using the pharmaceutical composition disclosed herein.

The invention discloses a respiratory disease oxygen precise conveying system based on a sensor, and relates to the technical field of medical equipment, and the system comprises a sensing module which integrates multiple sensors to collect and process airway and physiological data of a patient; the disease matching module identifies disease types through database comparison; the dynamic adaptation module calculates exclusive oxygen concentration based on a multi-mode fusion initial algorithm; the conveying module executes adjustment; the closed-loop feedback module continuously fine-tunes the oxygen concentration through a closed-loop stepped fine-tuning algorithm to form a closed-loop link, so that accurate dynamic control of oxygen delivery is realized; according to the invention, multi-sensor collaborative acquisition and disease precise matching are combined with a dynamic algorithm and closed-loop feedback, so that individuation and dynamic oxygen delivery are realized, the system avoids misjudgment by relying on a standardized database, and the oxygen concentration, flow and pressure are ensured to be adjusted in real time along with physiological indexes of a patient through multi-parameter collaborative adjustment and stepped fine adjustment; the treatment comfort, the effectiveness and the long-term adaptability are improved.

The invention discloses a respiratory infectious disease multi-pathogen nucleic acid detection kit based on a fluorescent PCR detection technology and application of the respiratory infectious disease multi-pathogen nucleic acid detection kit. The invention provides two detection kits aiming at 20 and 6 respiratory tract detection, the two kits can specifically detect respiratory tract pathogens, the detection sensitivity is high, the whole detection system is short in time consumption and simple and convenient in use process, and detection results of 20 pathogenic microorganisms can be reported within 40 min at the shortest; the whole set of detection kit and the detection method are high in sensitivity and good in specificity; the normal-temperature storage and transportation of the reagent can be realized.

Methods and devices for analyzing non-volatile organics in exhaled breath and other aerosols using various diagnostic tools that enable rapid, low-cost point of care assays for several diseases including respiratory tract diseases such as COVID-19. The disclosed methods and systems selectively capture non-volatile organics in exhaled breath and other aerosols in a packed bed column. The non-volatile organics are eluted and samples are analysis using diagnostic devices including MALDI-TOFMS. The disclosed systems and methods provide for a diagnostic test result in less than about 20 minutes and provides for autonomous operation with minimal human intervention.

The invention discloses an equipment invariance enhanced multi-modal deep learning model and application thereof, and the model comprises an input module, a coding module, a modal fusion module, a classification module, an equipment adversarial branch module, an output module and a final total loss function. Extracting features through a coding module to obtain audio features and text features; after the audio features and the text features are processed by the modal fusion module to obtain final joint representation, the classification module processes the final joint representation to obtain classification results and corresponding probabilities, and the classification results and the corresponding probabilities are output by the output module; the equipment confrontation branch module enables an audio encoder to confront an equipment classification head in a training stage; and finally, introducing the total loss function in a training stage to optimize the model. The model provided by the invention has the capability of realizing high-accuracy identification on various respiratory system diseases on the premise of not depending on acquisition equipment of a specific brand, and shows excellent generalization performance and robustness in multi-equipment and multi-center data.

The present disclosure provides a compound of formula H having excellent PDE4B inhibitory activity, and a pharmaceutical composition thereof and a use thereof. The compound provided by the present disclosure can be used for effectively treating PDE4-related diseases and disorders, including but not limited to inflammatory respiratory diseases, inflammatory bowel diseases, inflammatory joint diseases, inflammatory skin diseases, inflammatory eye diseases, and diseases or cancers of the peripheral or central nervous system.

The invention discloses a cutting and polishing device for mold machining, and relates to the technical field of cutting and polishing devices.The cutting and polishing device comprises a cutting and polishing mechanism, the cutting and polishing mechanism is provided with a collecting mechanism, the collecting mechanism comprises a porous shell, a collecting box and a rectangular hole, and a box plate is additionally arranged at an opening of the collecting box; a perforated plate is additionally arranged in the collecting box, an annular filtering net piece is fixed in the perforated plate, a round pipe is fixed to the surface of the perforated plate, and fan blades are additionally arranged at the other end of the round pipe. The device can directly clean metal chippings, abrasive particles and dust driven in the high-speed rotating process of the cutting disc and the grinding wheel, so that the concentration of the metal chippings, abrasive particles and dust in the environment is reduced to a great extent, the probability of causing respiratory diseases of workers is reduced, the body health of the workers is guaranteed, and the working efficiency is improved. And meanwhile, the cleaning and maintaining cost is reduced, and the use efficiency of the cutting and polishing device is improved.

Novel compounds that act as antagonists to human GPR39 protein are disclosed. Pharmaceutical compositions and methods of use for antagonists to human GPR39 protein are disclosed. In particular, methods of using the antagonists in the treatment of diseases or conditions including cardiovascular conditions, endocrine system and hormone disorders, cancer disorders, metabolic diseases, gastrointestinal and liver diseases, hematological disorders, neurological disorders and respiratory diseases are disclosed herein.

The invention particularly relates to a respiratory disease diagnosis device and method, and the device comprises a respiratory sound signal collection unit which is used for obtaining a current respiratory sound signal; the breathing sound signal preprocessing unit is used for performing segmentation processing and denoising processing on the current breathing sound signal to obtain a preprocessed breathing sound signal; the feature extraction unit is used for extracting multi-modal features of the preprocessed breath sound signals; and the detection unit is used for inputting the multi-modal features into a preset deep learning network model to obtain a respiratory system disease detection result. Therefore, through multi-modal feature extraction, dynamic fusion and an efficient classification strategy, the problems of relatively low feature identification degree, relatively low disease classification accuracy and the like in the process of researching disease diagnosis based on the breath sound signals in related technologies are solved, and the detection performance of chronic respiratory system diseases based on the breath sound signals is remarkably improved.

The invention relates to a compound according to general formula (I), which acts as a bradykinin (BK) B2 receptor antagonist; to a pharmaceutical composition containing one or more of the compound(s) of the invention; to a combination preparation containing at least one compound of the invention and at least one further active pharmaceutical ingredient; and to said compound(s) for use as in a method of treating a skin disorder; eye disease; ear disease; mouth, throat and respiratory disease; gastrointestinal disease; liver, gallbladder and pancreatic disease; urinary tract and kidney disease; disease of male genitale organs and female genitale organs; disease of the hormone system; metabolic disease; cardiovascular disease; blood disease; lymphatic disease; disorder of the central nervous system; brain disorder; musculoskeletal system disease; allergy disorder; pain; infectious disease; inflammatory disorder; injury; immunology disorder; cancer; hereditary disease; or edema.

The utility model discloses a fuel gas heat conduction oil boiler, which relates to the technical field of oil boilers, and comprises a base, the upper side of the base is fixedly connected with a water suction pump, the input end of the water suction pump is fixedly connected with a water suction pipe, the output end of the water suction pump is fixedly connected with a plurality of supporting legs, and the upper side of the base is fixedly connected with a water inlet pipe. A boiler body is fixedly connected to the upper ends of the supporting legs, an air outlet valve is fixedly connected to the upper side of the outer wall of the boiler body, and a safety valve is fixedly connected to the upper side of the outer wall of the boiler body. Through the mutual cooperation of a filtering adsorption plate, a sliding groove, a push block, a sliding block, a limiting rod, a first spring, a first connecting plate and a U-shaped inserting plate, the filtering adsorption plate can be detached and replaced, the filtering effect of the device is improved, the emission of harmful substances in waste gas can be effectively reduced, the health of surrounding residents and workers can be protected, and the practicability is high. And respiratory system diseases or other health problems caused by inhalation of harmful gas are avoided.

The invention discloses an intelligent diagnosis and treatment integrated system for respiratory diseases, and the system comprises a data collection module which introduces a hospital information system to record clinical data, medical images and physiological signals of a to-be-detected object; the edge calculation module is used for carrying out filtering processing on the physiological signal and carrying out noise reduction and lung field segmentation processing on the medical image; the multi-modal fusion diagnosis module is used for generating disease prediction types, severity and treatment suggestions according to the clinical data, the medical images and the physiological signals, and introducing an analysis module to generate a diagnosis report; the application service module is used for providing diagnosis and treatment feedback for the doctor end, the patient end and the management end and supporting the model optimization module to dynamically optimize the multi-modal fusion diagnosis module; according to the invention, multi-modal data is deeply fused through the multi-modal fusion diagnosis module, so that the limitation of single data is overcome; therefore, the method and the device play a role in improving the diagnosis accuracy.

The invention relates to the technical field of sleep respiratory disease analysis, and discloses a method for analyzing obstructive sleep apnea. The method comprises the following steps: acquiring an original physiological signal flow which is output by a multi-channel sleep monitoring device and comprises a respiratory waveform, blood oxygen fluctuation, an electrocardio rhythm and a sound vibration signal; and then, carrying out adaptive window function segmentation and multi-resolution conversion on the original signal flow to generate a standardized multi-modal signal sequence. State decoding is carried out on the sequence through a hidden Markov model, and steady state physiological mode features and transient abnormal mode features are extracted. And fusing the steady state features and clinical archive data of the patient, calculating an apnea risk index, and forming an initial evaluation report. Meanwhile, a dynamic evolution path of transient abnormal mode characteristics is monitored, and a real-time pathology indicator in the signal is detected. And finally, a risk weight coefficient in the initial evaluation report is adjusted according to the real-time pathology indicator, and a more accurate optimization evaluation report is generated.

The invention belongs to the field of traditional Chinese medicines, and particularly relates to an inhalation type pharmaceutical composition for treating inflammatory respiratory diseases and a preparation method thereof. The inhalation type pharmaceutical composition comprises an active component and a nano-liposome, and mannose is modified on the surface of the nano-liposome; the active ingredients comprise bulbus fritillariae cirrhosae total alkaloids and platycodin D; the nano-liposome is prepared from the following raw materials: phospholipid, cholesterol and cholesterol-polyethylene glycol 1000-mannose ester. The liposome can be specifically recognized by a mannose receptor highly expressed on the surface of alveolar macrophage through a surface-modified mannose ligand, so that the receptor-mediated endocytosis is started, and the wrapped bulbus fritillariae cirrhosae total alkaloids and platycodin D are efficiently introduced into cells. The inhaled pharmaceutical composition of the present invention collectively pushes macrophages from a pro-inflammatory M1 phenotype to a repairable M2 phenotype. Therefore, the overall curative effect of the combination of the two components is far better than that of the independent use of any component.

The invention relates to the field of intelligent medical treatment, in particular to a percutaneous lung channel acupoint electrical stimulation optimization system based on artificial intelligence, which comprises a multi-source data acquisition module (M1), a dynamic modeling module (M2) and a self-adaptive electrical stimulation module (M3). M1, collecting lung channel acupoint skin impedance, infrared thermal imaging, respiratory rhythm and cough frequency data in real time, and generating multi-source fusion features through space-time alignment; m2, based on a deep learning model, combining with a preset database to dynamically generate an electrical stimulation parameter combination, and ensuring parameter safety through impedance calibration and constraint optimization; and M3, adjusting the stimulation intensity according to the parameters, and setting an impedance threshold to trigger power-off protection. The traditional Chinese medicine meridian theory and the AI algorithm are fused, accurate acupoint positioning, personalized electrical stimulation and dynamic safety regulation are achieved, and the respiratory system disease treatment effect is improved.

The invention provides application of tea extracellular vesicles in preparation of drugs for relieving or treating allergic respiratory diseases, and belongs to the technical field of extracellular vesicles. The invention provides application of tea extracellular vesicles in preparation of drugs for relieving or treating allergic respiratory diseases. The tea extracellular vesicles are proved to be capable of remarkably improving related symptoms of allergic respiratory diseases including allergic rhinitis, have good anti-inflammatory and immunoregulation effects, and have the application potential of being used as natural active ingredients for preparing drugs or nasal delivery preparations for treating the allergic respiratory diseases. Compared with existing hormone drugs, the tea extracellular vesicles have the advantages of being natural in source, high in safety, low in side effect and the like; moreover, the extracellular vesicles have nanoscale particle sizes, good mucous membrane permeability and bioavailability, can improve the curative effect, and are suitable for long-term intervention.

The invention discloses a PatchTST model-based respiratory signal restoration method, which comprises the following steps of: S1, reading low-resolution sensor input data and high-resolution respiratory physiological waveform target data, and carrying out data cleaning, formatting and time alignment to form a unified data set; and S2, dividing the aligned time sequence data into window samples with fixed lengths, dividing a training set and a verification set, carrying out standardization processing on the data, and then constructing a PyTorch data loader. According to the method, the adaptation problem of the low-resolution input data and the high-resolution target waveform can be effectively solved, the target data quality can be further optimized, the breathing physiological state of a patient can be reflected more truly, and reliable data support is provided for clinical intensive care and respiratory disease diagnosis.

The invention discloses an intelligent respiratory disease detection system based on lung function measurement indexes, and relates to the technical field of intelligent medical detection. The problems that diagnosis standards are not uniform and depend on experience, primary doctors are prone to missed diagnosis or misdiagnosis due to insufficient experience, and the efficiency of the detection process is low are solved. According to the method, a machine learning model is constructed based on lung function indexes, parameters are optimized through five-fold cross validation, automatic classification of asthma, COPD and ILD / DPLD is achieved, the overall diagnosis accuracy rate reaches 81.3%, the limitation that traditional diagnosis depends on doctor experience is broken through, and the basic medical diagnosis capacity is especially improved. Healthy people are rapidly eliminated through the FVC / FEV1 ratio, invalid calculation is reduced, meanwhile, multi-model weighted fusion is adopted for complex cases, diagnosis robustness is improved, it is ensured that diagnosis results conform to medical logic, the recognition degree of doctors is enhanced, a data basis is provided for clinical research and curative effect tracking, and respiratory disease diagnosis is promoted to develop towards the direction of automation and precision.

The invention relates to the technical field of remote monitoring, in particular to a chronic respiratory disease patient remote monitoring system based on the Internet of Things, which comprises a physiological baseline initialization module, an event response delay measurement and calculation module, a cardiopulmonary coupling phase quantization module and a decompensation risk early warning module. According to the method, an individual blood oxygen and cardiopulmonary coupling health baseline is established to provide accurate reference for subsequent analysis, then the blood oxygen recovery time after apnea is measured and calculated, the physiological response delay characteristic of an individual is quantified, and the characteristic is used for setting a dynamic analysis window to continuously calculate the phase difference between a breathing mode and a blood oxygen signal, so that the phase difference between the breathing mode and the blood oxygen signal is calculated. By continuously comparing the current phase difference with the individual health baseline and triggering early warning when the difference value continuously exceeds a specific range, the early sign of the instability of the cardiopulmonary system can be effectively captured, the conversion from passive response type alarm to active predictive early warning is realized, and a precious time window is provided for preventing decompensation.

The present invention relates to a composition comprising a Bifidobacterium longum transitional microorganism and a mixture of human milk oligosaccharides (HMOs) consisting of 2'-fucosyllactose (2'-FL), difucosyllactose (DFL), lacto-N-tetraose (LNT), 6'-sialyllactose (6SL), and 3'-sialyllactose (3SL), and optionally lacto-N-fucopentaose I (LNFP-I), 3- fucosyllactose (3-FL) and / or lacto-N-neotetraose (LNnT), wherein the Bifidobacterium longum transitional microorganism has an Average Nucleotide Identity (ANI) of at least 98% with CNCM I-5942. The invention also relates to the use of the composition for preventing, reducing the risk of and / or treating an infection in a subject. The invention also provides the composition for use in promoting a long-term immune benefit in a subject, preventing and / or reducing the risk of allergen sensitisation, preventing and / or reducing the risk of developing a respiratory condition in a subject, and / or preventing and / or reducing the risk of developing asthma in a subject.

The invention provides a training method of a pig respiratory tract health recognition model, a recognition method and a related device. The training method of the pig respiratory tract health recognition model comprises the following steps: acquiring respiratory characteristics according to RGB channel intensity changes of target pixels in continuous video frames respectively corresponding to a plurality of pigs; extracting dog sitting features from the sitting posture data of the plurality of pigs; extracting audio features from the audio data of the plurality of pigs; the target pixel is a pixel point far away from the frame boundary in the abdomen labeling frame of the single pig; the audio features comprise non-cough audio features of healthy pigs and cough audio features of pigs with respiratory diseases; carrying out feature fusion on the breathing feature, the dog sitting feature and the audio feature to obtain a fused feature; and carrying out iterative training on a neural network by taking the fusion feature as an input feature and taking whether the pig suffers from the respiratory disease as a label to obtain a pig respiratory tract health recognition model. According to the method, the recognition accuracy and generalization ability of the pig respiratory tract health recognition model are improved.

A method of treating a human subject which is effected by intermittent inhalation of gaseous nitric oxide at a concentration of at least 160 ppm is disclosed. The method can be utilized for treating a human subject suffering from, or prone to suffer from, a disease or disorder that is manifested in the respiratory tract, or from a disease or disorder that can be treated via the respiratory tract. The disclosed method can be effected while monitoring one or more of on-site and off-site parameters such as vital signs, methemoglobin levels, pulmonary function parameters, blood chemistry and hematological parameters, blood coagulation parameters, inflammatory marker levels, liver and kidney function parameters and vascular endothelial activation parameters, such that no substantial deviation from a baseline in seen in one or more of the monitored parameters.

The invention provides a compound as shown in a formula I which can be used as a sodium channel regulator, and a stereoisomer, a tautomer or a pharmaceutically acceptable salt thereof. The invention also provides a pharmaceutical composition containing the compound and the stereoisomer, the tautomer or the pharmaceutically acceptable salt thereof and a carrier or excipient, and a pharmaceutical application of the pharmaceutical composition as a NaV1.8 inhibitor (such as pain, respiratory diseases, neurological disorders, mental diseases and the like).

The invention relates to a system and a method for determining a severity of a respiratory disease of a patient. The patient is instructed by a system to recite a phrase. The system receives the phrase recited by the patient as acoustic signal and analyzes the acoustic signal with respect to a severity of a respiratory disease. The result of the analysis is provided, which is indicative for the severity of the respiratory disease of the patient.

The present invention provides a Lactiplantibacillus plantarum strain capable of resisting Streptococcus pneumoniae infection in the respiratory tract, with a deposit number of CCTCC NO: M2022359. The Lactiplantibacillus plantarum VHProbi P06 strain provided by the present invention has a strong adhesion effect on nasal epithelial cells and can colonize in the nasal cavity; and can significantly inhibit the adhesion effect of Streptococcus pneumoniae, the main pathogenic microorganism of sinusitis, on nasal epithelial cells; it also has an inhibitory effect on the growth of most other pathogenic microorganisms of sinusitis, including β-hemolytic streptococcus, Streptococcus pyogenes, Escherichia coli, Staphylococcus aureus, etc. The Lactiplantibacillus plantarum VHProbi P06 strain provided by the present invention has no toxic effect on the body and has good safety. It can be added to drugs for preventing respiratory diseases or improving respiratory symptoms caused by bacterial infections, and has broad application prospects.

The invention belongs to the technical field of pharmaceutical preparations, and particularly relates to a beclomethasone propionate suspension for inhalation and a preparation method thereof. The beclomethasone propionate suspension for inhalation comprises beclomethasone propionate, a suspending stabilizer and a propellant, and the preparation method comprises the steps of raw material crushing, suspending stabilizer pretreatment, dynamic circulating temperature control mixing, high-pressure homogenization and the like. The settling volume ratio of the suspension is obviously superior to that in the prior art. The preparation provided by the invention has excellent physical and chemical stability and loose storage conditions, and provides a safe and efficient inhalation preparation choice for the treatment of respiratory diseases.

The invention provides a breathing mode analysis method and device based on a calm breathing pressure difference waveform and electronic equipment, and relates to the technical field of medical signal processing and artificial intelligence, and the method comprises the following steps: obtaining a calm breathing pressure difference original signal of a target user; preprocessing the calm breathing pressure difference original signal to obtain a target waveform sequence; performing feature extraction based on the target waveform sequence to obtain a plurality of dimension features; combining the at least two dimension features to obtain a multi-modal feature; and inputting the multi-modal features into a trained classification model, and outputting a breathing pattern classification result. According to the method, the whole analysis process is completely based on natural calm breathing, special cooperation or forced breathing actions of the user are not needed, the pain point that traditional lung function examination has a high requirement for the user cooperation degree is solved, and auxiliary decision making of chronic respiratory diseases is achieved.

Methods and devices for capturing and analyzing aerosolized particles in exhaled breath characteristic of a respiratory disease to enable rapid, low-cost point of care assays for several diseases including respiratory tract diseases such as COVID-19 are disclosed. The disclosed methods and systems selectively capture aerosolized particles using a packed bed column. The captured particles are then eluted using solvents and analyzed using analytical devices including MALDI-TOFMS.