417 results about "Drug dosages" patented technology

The invention relates to the technical field of medical evaluation, and provides an evaluation system and method for potential complications of the department of cardiology, and the method comprises the following steps: S1, collecting information data of a patient, and carrying out the data verification and data preprocessing; s2, based on the obtained information, classifying types of complications which may occur on the patient; and S3, based on a complication type classification result, risk factors are extracted, and a risk factor network is constructed. By classifying the complication types, constructing the risk factor network and comprehensively considering multiple factors to calculate the risk index, compared with a traditional assessment mode, the risk of potential complication of a patient can be assessed more comprehensively and accurately, misdiagnosis and missed diagnosis caused by incomplete assessment are reduced, and the risk assessment efficiency is improved based on the risk score, the risk index and the risk type. The drug dosage or the measure intensity is adjusted through the patient specificity index, the prevention measures are dynamically adjusted in combination with the treatment time, and the pertinence and effectiveness of the prevention scheme are improved.

The invention discloses a diagnostic drug dose key information extraction system based on a multi-agent architecture, which comprises a diagnostic drug dose key information extraction system and a diagnostic drug dose key information extraction system, the diagnostic drug dose key information extraction system comprises a data acquisition and preprocessing module, a natural language processing and information extraction module, a medical knowledge graph construction module, a diagnosis and drug dose recommendation module, a user interaction and feedback module and a safety management and privacy protection module. According to the system, key information about diagnosis and drug dosage can be automatically extracted, analyzed and processed from complex medical data, the system provides accurate and personalized diagnosis and drug dosage suggestions for patients through cooperative work of a plurality of intelligent modules, and meanwhile, the safety and privacy of the data are ensured.

The invention relates to a nitric oxide data analysis method and system for bronchial asthma assessment. According to the method, exhaled air nitric oxide and pulmonary alveolar nitric oxide of a patient, omics data and clinical information are acquired in a standardized manner, and multi-dimensional features are constructed after data cleaning and fusion; comprise an inflammation level index, an inflammation region entropy, an inflammation synergy index, a glucocorticoid response factor, an infection-smoking synergy influence factor and a heredity-symptom distribution index. And outputting initial risk assessment based on an explainable elevator EBM model, and finally generating an asthma risk probability through a weighted integration formula to realize three-level layering: low / medium / high risk. The system dynamically associates treatment decisions, for example, the drug dosage and the monitoring frequency are improved when the risk is upgraded, and the medication scheme is optimized when the risk is degraded. According to the scheme, the limitation of traditional single marker static analysis is broken through, multiple mechanisms of dissection, immunity and pharmacology are fused, the evaluation precision and clinical applicability are remarkably improved, the acute attack rate is reduced, and accurate typing treatment is guided.

The invention discloses an intelligent anesthesia monitoring and regulation system, and relates to the technical field of medical monitoring and automatic control. The system comprises a data acquisition and preprocessing module, a dynamic physiological model construction module, an anesthesia state evaluation and prediction module, a real-time uncertainty quantification module and a layered hybrid closed-loop regulation and control module. The layered mixed closed-loop regulation and control module is used for predicting the change track of the anesthesia depth under different administration strategies in a few minutes in the future through a dynamic physiological model, and calculating an optimal administration rate sequence which can maintain the anesthesia depth in a target range and can minimize the drug dosage and blood pressure fluctuation through online optimization, so as to obtain the optimal administration rate sequence. The confidence score is referenced when controlling the administration rate. The system can realize highly personalized anesthesia monitoring and regulation and control, and has the advantages of quantifiability, high reliability, stable operation, accurate regulation and control and the like.

The invention relates to the field of medical information management, in particular to a children malignant tumor treatment process and follow-up visit electronic management system and a children malignant tumor treatment process and follow-up visit electronic management method. The method comprises the steps that the body surface area of a patient is calculated, and the chemotherapy drug dosage in each cycle is calculated based on the body surface area of the patient; performing cycle-by-cycle accumulation on the chemotherapeutic drug dose in each cycle to obtain an actual accumulated dose; calculating and standardizing the specific numerical value of each curative effect index based on the actual accumulated dose, and calculating a comprehensive therapeutic effect score by combining the importance weight of each curative effect index; and calculating the disease-free survival rate based on the actual accumulated dose and the comprehensive treatment effect score. The problems that at present, most medicine dosage calculation methods neglect the special physiological features of children, a treatment monitoring system lacks dynamic adjustment support in the treatment process, a follow-up management system is insufficient in quantitative analysis capacity for long-term prognosis, and personalized long-term health management suggestions cannot be provided for patients are solved.

The invention relates to the technical field of medical severe illness monitoring and management systems, in particular to an intensive illness medical patient monitoring and management system based on multi-modal data fusion, and the system comprises a physiological feature extraction module which collects a first feature set and processes the first feature set into a second feature set containing an electroencephalogram entropy value and cerebral perfusion pressure; the pathological state decoupling module is used for inversely calculating an observation vector, calculating a pharmacological stress vector in combination with a pharmacological baseline and a drug dosage, obtaining a pathological vector after stripping, and generating a pathological index; the evolution trend prediction module is used for predicting risk factors according to the pathological vector time sequence data; the closed-loop intervention decision-making module is used for combining the pathological indexes and the risk factors, calculating the medicine dosage adjustment amount according to a second mapping relation, and updating the infusion rate to achieve closed-loop regulation and control, and according to multi-modal data fusion and module cooperation, pharmacological stress is stripped, and the pathological indexes are generated so as to accurately judge the illness state; the risk can be actively predicted, and the drug dosage is automatically adjusted in combination with pathological indexes, so that the management efficiency and safety of critical patients are improved.

The invention provides a drug dosage adjusting system and method based on blood concentration prediction, and belongs to the field of medical artificial intelligence, and the method comprises the steps: obtaining a standard structured data code based on a preset historical clinical database; performing standard structured data coding based on the predicted feature factor set to obtain a predicted feature factor set and a time point combination; constructing a classification prediction model and a regression prediction model based on the prediction feature factor set; a to-be-predicted blood sample is collected in a prediction characteristic factor set time point combination mode, and a blood concentration prediction result is obtained based on the to-be-predicted blood sample of the prediction characteristic factor set, the prediction characteristic factor set classification prediction model and the regression prediction model; and adjusting the dosage according to the blood concentration prediction result. According to the invention, individual differences are analyzed individually, personalized medication dosage adjustment suggestions are generated, and the medication dosage adjustment reliability is improved.

The invention discloses an agricultural protection unmanned aerial vehicle and a dynamic path optimization method, and belongs to the technical field of unmanned aerial vehicles. The agricultural protection unmanned aerial vehicle comprises an unmanned aerial vehicle body, a mounting part is arranged on the unmanned aerial vehicle body, a pesticide barrel which is vertically arranged and used for containing pesticide liquid is arranged in the mounting part, and a plurality of nozzles which are annularly arranged and used for pesticide spraying operation are arranged at the bottom of the pesticide barrel; the unmanned aerial vehicle body is further provided with an acquisition module used for acquiring a whole area image of a plant operation area and an image processing module used for identifying the acquired image according to plants and marking plant growth density in a partitioned mode. Compared with the prior art, the self-adaptive pesticide spraying device has the advantages that self-adaptive pesticide distribution and spraying are realized according to different growth densities, the conditions of excessive spraying and insufficient spraying of the plants in areas with lower growth densities are avoided, and the spraying efficiency of the plants is improved. The crop planting quality is improved, and the high use value is achieved.

The invention relates to the technical field of medical decision and artificial intelligence, and discloses an artificial intelligence-driven new adjuvant therapy scheme optimization method and system for antral sinus cancer, and the method comprises the steps: S1, obtaining clinical data of a antral sinus cancer patient, and carrying out the preprocessing; s2, screening core features by adopting an iterative ReliefF algorithm, and constructing composite features; s3, constructing a prediction model based on a Bayesian optimization K-nearest neighbor algorithm, taking the composite features as input of the prediction model to predict treatment response, and outputting individual tumor recession grade probability distribution of the patient; s4, taking the tumor recession grade probability distribution as a core component of a state space, inputting the tumor recession grade probability distribution into a double-layer reinforcement learning framework based on a penalty mechanism to optimize a treatment decision, and outputting a personalized treatment strategy parameter set; and S5, performing real-time scanning and verification on the drug dosage parameters in the strategy parameter set, and outputting a final approved personalized treatment scheme. The precision and intelligent level of gastric antrum cancer treatment is improved.

The invention discloses a pharmaceutical composition for preventing and / or treating pain and application thereof.The pharmaceutical composition contains a Sigma-1 receptor antagonist and a histamine H3 receptor antagonist / inverse agonist and has a synergistic analgesic effect on various pains, the curative effect of the pharmaceutical composition is remarkably superior to that of a single drug, the use dosage of the single drug can be reduced, and therefore the side effect of single drug dosage dependence is reduced; good application prospects are realized.

The invention relates to the technical field of medical care informatics and precision medical treatment, and discloses a hemodialysis patient precision medication system based on multiple omics and big data, and the system comprises a multi-source data collection module which collects the multi-source heterogeneous data of a patient and carries out the standardization and integration processing; the drug metabolism analysis module is used for analyzing drug metabolism paths and individual differences through multi-omics data, constructing a drug metabolism polymorphic model and outputting gene metabolism capability grades and biomarker risk tags; the initial medication decision-making module is used for constructing an initial medication decision-making model based on a federal optimization framework of a momentum enhancement and robust aggregation mechanism, and outputting a personalized initial medication scheme for erythropoietin and a vein iron agent; and the drug dosage adjustment module is used for dynamically optimizing the time node and dosage adjustment opportunity of drug administration through an asynchronous federal reinforcement learning framework in combination with a prospective parameter correction strategy. According to the invention, the intelligent medication system with strong robustness and fine decision is constructed.

The invention discloses a wound healing state evaluation method and system based on artificial intelligence, and belongs to the field of wound healing evaluation. The method comprises the following steps: integrating medical record data and wound physiological parameters, and extracting relevance between a medication history and an infection type to form a multi-dimensional pathological factor; hemoglobin oxygenation, blood flow and metabolic heat are subjected to cross-period correlation analysis to construct dynamic physiological time-space information, pathological factors and the physiological time-space information are fused into a heterogeneous graph, nodes comprise drug intensity quantized values, infection risk levels and microcirculation fluctuation values, and edge weights are determined by the time sequence matching degree of drug doses and blood flow changes; based on the node weight and the edge association relationship, the treatment time and the physiological parameter acquisition period are aligned to generate a spatio-temporal evolution matrix, the spatial distribution of the infection risk level and the metabolic heat value characteristics are combined, the dynamic association of the drug action intensity and the microcirculation fluctuation is analyzed, and wound healing evaluation information is generated. The accuracy of wound healing state evaluation can be improved.

The invention belongs to the technical field of biological medicine and data processing, and particularly relates to a multi-modal-based liver transplantation drug dosage prediction method, which comprises the following steps: collecting clinical data of liver transplantation recipients and processing to obtain a sample set, and dividing the sample set into a training set and a test set; constructing a multi-modal linear regression model; samples in the training set pass through a feature extraction module to obtain an original feature sequence; inputting the original feature sequence into a feature dimension reduction module to obtain a dimension reduction feature sequence; inputting the dimension reduction feature sequence into an attention mechanism module to obtain an enhanced feature sequence; the enhanced feature sequence passes through a multi-modal fusion module to obtain a fused feature sequence; inputting the fused feature sequence into a prediction module to obtain a prediction result, and training optimization model parameters; obtaining to-be-processed clinical data, inputting the to-be-processed clinical data into the trained multi-modal linear regression model, and obtaining a medicament dosage prediction result; according to the method, the individualized dosage of tacrolimus can be accurately predicted.

The invention discloses a thyroid disease full-period management system and method, and the system comprises a medical service module which is used for medical registration appointment; the data management module is used for collecting and storing human body life health indications of the patient in the hospital treatment period and in the remote re-treatment period; the follow-up diagnosis monitoring module is used for storing dose change data and setting regular review reminding; the health risk early warning module is used for performing correlation analysis on the disease health risk of the patient according to the human body life health indication and the dosage use data, and giving out doctor seeing guidance according to an analysis result; and the daily health management module is used for giving daily diet suggestions and exercise suggestions to the patient according to the analysis result of the health risk early warning module. The thyroid disease full-period management system shows obvious advantages in the aspects of optimizing the re-consultation process, improving the medical treatment efficiency, enhancing remote management, improving the medical compliance, providing personalized health guidance and the like, and provides more comprehensive, convenient and efficient health management services for patients.

The invention relates to the technical field of adjuvant therapy monitoring, in particular to an anorectal disease adjuvant therapy monitoring system and method based on a radix scrophulariae extract. The method comprises two stages of system initialization and adjuvant therapy monitoring, in the initialization stage, initialization setting is completed, and a dynamic monitoring code is generated to guarantee data transmission security; in the auxiliary treatment stage, baseline data are collected, abnormal values are removed, then personalized baselines are generated, the drug dosage and the release rate are adjusted according to the baseline data, meanwhile, pressure, temperature, blood flow and electrophysiological data are monitored in real time, key indexes are calculated, monitoring labels are generated, the physiological indexes are standardized, the treatment effect is comprehensively evaluated, and classification is conducted. The dynamic trend is analyzed by adopting a polynomial fitting method, an evaluation result is generated, the drug release rate and dosage are dynamically optimized in combination with real-time monitoring data and patient feedback, and fine treatment is further performed by adopting a feedback adjustment mechanism. According to the invention, efficient auxiliary treatment and intelligent monitoring of anorectal diseases are realized.

The invention relates to the technical field of precision medical treatment, in particular to an interpretation system and method for tumor precision medication and a storage medium, and the system comprises a data collection module which is used for collecting gene data, clinical data and drug response data of tumor patients from a plurality of data sources; the data standardization processing module is used for carrying out formatting and standardization processing on the data, so that the data formats are consistent, and effective processing and analysis can be carried out in subsequent modules; the gene data analysis module is used for performing variation analysis according to the gene data of the patient, identifying a gene mutation site and generating a drug sensitivity analysis result; and the drug screening module is used for screening drugs matched with the gene variation sites of the patient from a drug database according to the gene data analysis result, and providing drug dosage recommendation. By adopting the technical scheme of combining a quantum optimization technology and gene data analysis, the technical effect of remarkably improving the drug screening and dose recommendation precision is achieved.

The invention discloses a computer-aided drug dosage optimization method. The method comprises the following steps: constructing and optimizing a QSP model of a drug and a patient; defining a state space and an action space, and initializing a bidirectional model; performing bidirectional deduction on the trained bidirectional model to obtain a virtual track; forming integrated data based on the real data, the output of the QSP model and the virtual track; constructing a learning relationship between the hierarchies; a learner and a guider are trained based on the integrated data and a PPO algorithm. According to the application, PBPK / PD modeling of the medicine in bodies of different crowds is carried out through a quantitative systematic pharmacology (QSP) model, and the physiological status of the patient after taking the medicine is calculated and predicted through a formula. According to the method, the PPO algorithm is used for strategy optimization, the amplitude of strategy updating is limited, the problem that strategy updating is too large in a traditional strategy gradient method is avoided, and the efficiency of the algorithm is improved while the strategy updating stability is guaranteed.

The invention provides a stem cell exosome for overexpressing A beta degrading enzyme as well as a preparation method and application of the stem cell exosome. Specifically, the invention provides an application of the stem cell exosome overexpressing A beta degrading enzyme in preparation of drugs, and the drugs are used for at least one of the following: prevention, improvement or treatment of cognitive impairment related diseases; neuronal cell damage is improved; wherein the stem cells for overexpressing the A beta degrading enzyme are prepared through lentivirus transfection. According to the stem cell exosome overexpressing the A beta degrading enzyme, the content of the A beta degrading enzyme is obviously higher than that of the exosome prepared by a traditional method. Therefore, when the compound is prepared into a medicine for treating or preventing cognitive impairment related diseases, the medicine can be efficiently conveyed to the brain, and the concentration of the medicine in the brain is remarkably improved, so that the curative effect is enhanced, the dosage of the medicine can be reduced, the side effect is reduced, and the prognosis of brain diseases is effectively improved.

The invention discloses a drug targeted delivery device and method, and belongs to the technical field of intelligent medical treatment. The device comprises the following modules: an intelligent targeted recognition module for accurately recognizing a gastric cancer specific molecular marker and improving the selectivity and specificity of targeted recognition in combination with a dynamic surface modification strategy; the microenvironment real-time monitoring module is used for monitoring key physiological parameters of the gastric cancer microenvironment in real time; the intelligent path planning module is used for dynamically calculating and optimizing a drug delivery path and realizing accurate drug positioning; the personalized drug administration regulation and control module is used for accurately predicting the drug dosage demand of an individual and dynamically and finely adjusting the drug administration amount in real time; the drug resistance risk management module is used for early warning a drug resistance risk in advance and automatically generating a personalized alternative drug administration strategy through multi-dimensional drug resistance analysis and real-time early warning; and the intelligent drug release module adopts a temperature-sensitive / pH-sensitive polymer shell layer and a nano valve to control drug release, so that precise gradient release of drug concentration is realized.

The invention discloses a clinical decision-oriented medical data analysis system, and relates to the technical field of medical data analysis, the clinical decision-oriented medical data analysis system comprises a patient end, a medical diagnosis end and a medical decision-making system, the medical decision-making system comprises a data acquisition unit, a data analysis unit, a decision-making output unit and a decision-making optimization unit; according to the method, the medical data is acquired, the disease course prediction model is established according to the historical diagnosis and treatment data of the patient, the disease course prediction result is obtained in combination with the medical data, and the medical seeing ability evaluation coefficient of the patient is obtained through comprehensive calculation based on the personal economic data of the patient and the social income data of the patient. The method comprises the following steps: judging the doctor-seeing ability of a patient according to a preset doctor-seeing ability evaluation interval, outputting a target decision scheme which can be loaded by the patient according to the doctor-seeing ability level of the patient, and when the scheme adaptation degree reaches a preset scheme evaluation threshold value, marking the target decision scheme as an optimizable scheme. And controlling and outputting a target optimization scheme by simplifying the examination process and the drug dosage in the treatment process.

The invention discloses an individualized drug dose optimization method based on causal traceability, which improves the accuracy and clinical adaptability of dose regulation and control through a multi-modal space-time alignment and feature decoupling technology, causal reasoning modeling and causal effect quantification and individualized dose optimization, can effectively reduce adverse reactions in the treatment process, and improves the treatment efficiency. The life cycle of a patient is prolonged, the life quality is improved, meanwhile, the long-term medication cost is reduced, and wide clinical application prospects and popularization values are achieved.

The invention discloses an intelligent monitoring, prevention and control system for tobacco brown spot, and relates to the technical field of agricultural disease monitoring and intelligent prevention and control. A lower canopy monitoring array, elevation thermal infrared and red edge near infrared imaging and spore sampling (fluorescent quantitative PCR / loop-mediated isothermal amplification) are used as inputs; fog drop deposition D, leaf surface water film W and spore concentration S are predicted through multi-modal alignment and a physical field generator; carrying out long sequence risk assessment by inputting a correlation state space model and superposing a liquid state self-correlation kernel, and carrying out long sequence risk assessment by using concentric wheel patterns and narrow yellow halo (rlt; 0.15) + near-infrared / short-wave infrared black mould layer triple discrimination and checking, and a prescription is formed by combining double-pulse triggering that leaf surface wetting is larger than or equal to 8 h or a spore index reaches a threshold. The prescription comprises night microclimate intervention, variable spraying and leaf thinning control; resistance rotation compliance is realized through prescription uplink pre-check and electronic control unit unlocking; based on row belt / Thiessen polygon scheduling, 36 h coverage is larger than or equal to 95%, the dosage and residues are reduced, and the hit rate and timeliness are improved.

The invention discloses a machine learning-based doctor drug dosage supernormal grading early warning method and system, and the system comprises a data layer which is mainly a data center, collects risk analysis data of drug consumable usage, departments, suppliers and the like from a hospital, carries out the data cleaning, and carries out the management of the data, including personnel management and query statistics; the business layer is mainly used for realizing key personnel monitoring and data intelligent research and judgment through an algorithm model, including clue mining, associated factor analysis and data visualization analysis; and the application layer comprises an intelligent early warning and forecasting function module, realizes red, yellow and green three-level risk early warning through big data analysis of the business layer according to threshold setting, and performs visual display. According to the method, a visual grading early warning mechanism condition is adopted, the drug dosage of a doctor is detected by using an anomaly detection algorithm model, the detection result is more accurate, the warning effect is more obvious, and meanwhile, the detection result provides a reference basis for the abnormal dosage condition for subsequent related departments.

The invention discloses an excrement character recognition and drug delivery closed-loop control method and system, and the system comprises an excrement collection and preprocessing module which is used for carrying out the automatic collection, preliminary physical and chemical character detection and sample preprocessing of the excrement of a patient; the multi-modal data analysis module is used for carrying out deep fusion analysis on the original multi-modal data output by the excrement collection and preprocessing module and carrying out diarrhea type diagnosis and severity evaluation; the drug delivery closed-loop control module is used for accurately and dynamically infusing drugs according to the diagnosis result of the multi-modal data analysis module; and the man-machine interaction and early warning module is used for monitoring and intervening the state of the system by medical staff and receiving important alarms. According to the invention, objective and continuous evaluation of excrement properties is realized, the drug dosage and scheme can be dynamically adjusted according to the properties, and the accuracy, individualization level and safety of diarrhea treatment of critical patients are significantly improved.

The invention discloses a subcutaneous administration intelligent health management system based on dynamic data, and relates to a medical instrument. According to the system, the data monitoring system, the drug delivery strategy calculation system and the subcutaneous drug delivery system are adopted for monitoring and processing health data and quickly responding to drug intervention, so that the problem that only health data can be monitored and health suggestions can be provided at the present stage, and abnormal health conditions cannot be handled in time is solved; according to the full-automatic management method of'detection, diagnosis and administration ', the compliance of a patient is improved; personalized and intelligent real-time administration calculation is achieved, the effect is guaranteed, meanwhile, the dosage of the medicine is reduced to the maximum extent, and side effects are reduced; the non-invasive transdermal drug delivery performed by using the microneedle system can reduce the problem of low bioavailability of the drug due to the effects of first pass metabolism and the like, and is more friendly to patients with dysphagia.

The utility model discloses a medicine taking bottle capable of controlling the medicine amount, and belongs to the field of medical instruments. Comprising a bottle body part used for containing medicine; the bottle cap part is mounted on the bottle body part in a threaded manner; the medicine taking opening is used for taking out medicines; the medicine taking assembly is arranged in the bottle cap piece; the medicine taking assembly comprises a medicine storage tray arranged in the bottle cap piece; a plurality of medicine storage cavities are formed in the medicine storage tray; the plurality of fan-shaped baffles are arranged on the medicine storage tray; the bottom plate is rotationally arranged on the bottle cap part; the through hole is formed in the bottom plate; and the medicine taking tray is rotationally arranged on the bottle cap. The medicine taking bottle capable of controlling the medicine amount has the beneficial effects that the medicine taking amount is controlled by arranging the medicine storage disc and the fan-shaped baffle and adjusting the number of the medicine storage cavities shielded by the fan-shaped baffle, the medicine inner cavities are separated from the outside through the arranged baffle and the medicine taking disc, and it is avoided that external pollution enters the medicine bottle during medicine taking.

The invention belongs to the technical field of medicines, and provides application of a natural-source compound monomer medicine composition in preparation of medicines for preventing and / or treating pancreatitis. The pharmaceutical composition comprises baicalin, paeoniflorin, geniposide, wogonin, baicalein, albiflorin, tetrahydropalmatine, rhein, wogonin, aloe-emodin, saikoside A, emodin, benzoyl paeoniflorin, chlorogenic acid, costunolide, or a pharmaceutically acceptable salt thereof. Compared with the prior art, the pharmaceutical composition disclosed by the invention has the advantages that the components of the composition are definite and are all natural sources, the safety is good, the pharmaceutical effect has a remarkable synergistic effect, the administration dosage is reduced by about 200 times under the condition that the treatment effect is better than that of a compound traditional Chinese medicine, the administration mode of the compound medicine for treating pancreatitis is innovated, and the pharmaceutical composition is suitable for clinical application. A new scheme is provided for the treatment of the disease.

A system including a user device and a storage device communicating wirelessly with each other. The user device includes a processor, a memory, and a wireless transceiver. The storage device includes multiple openings, each opening being configured to store an unused injection device for a period of time and wherein each opening has an associated sensor, and a storage device wireless transceiver. The user device can be configured to scan a first injection device to determine at least one of a drug dosage contained within the first injection device and a device expiration date of the first injection device, and to create first device data relating to the drug dosage and the device expiration date and to associate the first device data with a first opening of the plurality of openings of the storage device.

The invention relates to construction of an oral drug-loading nano-structure lipid carrier with double-targeting design and application of the oral drug-loading nano-structure lipid carrier in treatment of ulcerative colitis, the oral drug-loading nano-structure lipid carrier comprises solid liposome, liquid liposome and active substances, and the active substances are entrapped in a lipid layer formed by the solid liposome and the liquid liposome. The dual-targeting nano-structure liposome can effectively improve the solubility of the drug, target colon and inflammatory tissues, improve the curative effect and reduce the dosage of the drug.

The invention relates to the technical field of medicines, and particularly provides an active oxygen responsive paclitaxel prodrug which has a structure as shown in a formula I or a formula II. Aiming at the problem of hydrophobic aggregation of paclitaxel, the paclitaxel drug is modified, the water solubility of the modified paclitaxel drug is greatly enhanced, the self-assembly performance is obtained, the modified paclitaxel drug can be self-assembled in an aqueous solution to obtain the nano particles, and the nano particles have ultrahigh drug loading capacity and drug loading efficiency. The paclitaxel nano-preparation prepared by the method can be used for preparing the paclitaxel nano-preparation, can specifically respond to high-concentration active oxygen in a tumor microenvironment, not only can improve the insufficiency of drug loading capacity of a traditional paclitaxel nano-preparation, but also can respond to release paclitaxel at a tumor position, is beneficial to reduction of drug dosage and reduction of toxic and side effects, and has important significance on improvement of patient prognosis and prolonging of patient lifetime.