68 results about "Medication intervention" patented technology

The invention discloses an internal medicine drug curative effect evaluation method based on big data analysis of an electronic health record, and the method comprises the steps: extracting basic health data, diagnosis and treatment time sequence data and drug intervention data from the electronic health record, and carrying out the time-space alignment to generate a dynamic feature set; subgroups are obtained based on disease typing standard hierarchical clustering, and historical data and real world data are fused through transfer learning to construct a subgroup curative effect reference matrix; collecting data after medication in real time, and generating an evaluation vector containing short-term physiological response, middle-term symptom improvement and long-term prognosis risk through deep learning; dynamically matching the evaluation vector with the reference matrix, and introducing an individual weight coefficient to correct deviation; taking the deviation correction value as input, constructing a self-adaptive evaluation model through reinforcement learning, and performing iterative optimization; and generating an individualized report containing the curative effect level, the medication suggestion and the risk early warning, and quantifying the curative effect level through a fuzzy comprehensive evaluation method. According to the method, individual differences are accurately captured, full-cycle dynamic evaluation is realized, and the curative effect evaluation accuracy and the clinical decision-making efficiency are improved.

The invention discloses a compound probiotic for improving cognitive function of old people and a preparation method and application thereof. Firstly, maltodextrin is dried and then sieved, metal impurities are removed after sieving, and maltodextrin freeze-dried powder, lactobacillus paracasei Lpc37 freeze-dried powder, phytobacterium plantarum Lp-115 freeze-dried powder and bifidobacterium animalis subsp. Lactis Bl-04 freeze-dried powder are weighed and sieved respectively; the preparation method comprises the following steps: preparing freeze-dried powder of three strains, then premixing the freeze-dried powder of the three strains with a part of maltodextrin, adding the residual maltodextrin after the strains are premixed, continuously mixing until the materials are uniformly distributed to obtain the compound probiotics, exerting a synergistic effect through a specific strain combination (Lp115 + Lpc37 + Bl-04), providing a new way for non-drug intervention, being beneficial to regulating intestinal flora metabolism (such as generating short-chain fatty acid SCFA), and improving the immunity of the human body. The synthesis and release of neurotrophic factors are promoted, the nerve cell function is improved, and the cognitive function improvement is indirectly assisted.

The invention belongs to the technical field of curative effect evaluation of teenager depression drugs, and particularly relates to a curative effect evaluation method of a drug for treating teenager depression. According to the method, through dynamic fusion analysis of multi-dimensional physiological and behavior data, the dynamic effect of drug intervention can be reflected more comprehensively and accurately, meanwhile, the data dimension is effectively reduced through dimension reduction processing and key feature vector extraction, capture of key information is ensured, and the accuracy of drug intervention is improved by constructing a drug use window and conducting quantitative scoring on the drug curative effect in the window. According to the method, evaluation of the drug curative effect and introduction of an interpolation compensation technology are realized, the problem of data missing is further solved, a continuous dynamic curative effect evaluation sequence is formed, and a time sequence evolution rule of the drug curative effect can be intuitively reflected according to a curative effect change trend identified by the dynamic curative effect evaluation sequence; the comprehensive curative effect stability index is calculated by combining the duration and the alternating frequency of the curative effect change trend in the medication cycle, and a scientific basis is provided for determining the drug curative effect grade.

The invention provides a multi-module collaborative clinical blood coagulation function intelligent evaluation and drug recommendation system, and relates to the technical field of medical information processing. Comprising a data acquisition and fusion module, a state recognition module, a drug intervention effect evaluation module, a decision recommendation module and a system visualization module. According to the system, continuous integration of clinical scattered data is realized by constructing a unified time sequence structure of multi-source detection indexes and medication records; generating a blood coagulation state vector containing the bleeding risk and the thrombus risk through a state recognition mechanism combining rule judgment and data calculation, outputting a confidence score and an index contribution degree, and forming a state track evolving along with time; performing causal evaluation on the difference of the state change before and after intervention to obtain a drug average treatment effect; and individualized drug suggestion or early warning information is generated based on the state track and the intervention effect. And dynamic evaluation and drug intervention measurement and calculation of the blood coagulation risk are realized.

The invention relates to the technical field of medical monitoring and intelligent decision making, and particularly discloses an intraoperative noninvasive real-time blood flow monitoring and medication intervention analysis system. Pulse wave oscillation harmonic component characteristics and diastolic attenuation characteristic characteristics are extracted by using variational mode decomposition and a polynomial fitting algorithm; the multi-dimensional features are fused and then input into a deep learning classification model, and accurate recognition of insufficient heart pump efficiency, abnormal peripheral vascular tension and circulation capacity imbalance states is achieved; time sequence prediction and grading early warning are carried out based on the hidden Markov model and the individualized baseline safety interval, and finally a targeted medication scheme is output through the intervention strategy knowledge base.

The invention relates to a recurrent abortion early-warning method based on maternal and fetal immune interaction characteristics, which comprises the following steps: by taking decidua immune cells and trophoblasts as a unit, defining the regulation intensity of a key path of a path in an immune receptivity state; evaluating the coordination degree of signals among different cells by utilizing an information theory method; introducing a maternal and fetal immune receptivity steady-state index UISI; through continuous time sampling analysis, an immune signal offset track is identified; establishing an interactive imbalance index (IEI), and quantifying the imbalance intensity; designing a disturbance and response test; fitting the response trend of the IEI change to the disturbance into a system response curve IRC, and quantifying the recovery capability of the immune system; the IRC and individual clinical features are fused, and a dynamic risk thermodynamic relation is established; intervention window weight factors are constructed, wherein the intervention window weight factors comprise the fluctuation amplitude, the recovery period and the UISI critical value proximity; outputting a dynamic intervention suggestion map, and prompting a doctor to observe a period and a drug intervention starting point; the early warning capability is strong, and the limitation of traditional passive diagnosis is broken through.

The invention discloses a microfluidic multi-organ tumor chip targeted drug test AIGC system, and relates to the technical field of medical drug test information processing. The microfluidic multi-organ tumor chip targeted drug test AIGC system comprises a multi-omics data acquisition module for acquiring and preprocessing disturbance response data and dynamic expression data; the disturbance response pre-screening module is used for carrying out strength evaluation on drug action strength and reconstructing channel mapping; the characteristic space reconstruction module is used for performing action analysis on the whole medicine action state and dynamically adjusting a liquid medicine blending rule; the drug effect prediction module is used for predicting and evaluating the response degree of the organoid under the intervention of the specific drug and deducing the individualized drug effect intensity; and the feature augmentation self-closed loop module constructs a negative supervision signal and dynamically corrects a disturbance perception and feature embedding path. The problems that current multi-omics data is high in dimension, large in redundancy and large in noise, key features are difficult to extract under limited samples, and model generalization is difficult to maintain are solved.

The invention relates to the technical field of critical index monitoring methods, in particular to an intelligent critical index monitoring method and system based on clinical data. According to the method, a standardized data packet is constructed by collecting vital sign data of a patient, an inspection index group, drug intervention parameters and individual characteristics of the patient; calculating an individualized drug metabolism correction coefficient based on the liver and kidney function state and a real-time creatinine value, and dynamically generating a drug influence factor in combination with the flow rate of an analgesia pump; scene classification is carried out according to the medicine influence factor value and the blood pressure change trend, and the alarm weight of each monitoring index is dynamically adjusted; and finally, accurate risk assessment and graded early warning are realized through multi-index fusion analysis. The system comprises a data acquisition function module, a dynamic analysis function module, a weight adjustment function module and an early warning decision function module. The clinical problem that a traditional monitoring system is insufficient in sensitivity to progressive deterioration in a drug interference environment is effectively solved, and a more reliable safety monitoring scheme is provided for postoperative high-risk patients.

This invention discloses a method and system for evaluating the effectiveness of cardiac rehabilitation, relating to the field of medical and health technology. The method includes: acquiring physiological monitoring data, individualized parameter data, comorbidity data, multidrug therapy data, pharmacokinetic parameters, and pharmacodynamic interaction parameters of the target patient; generating baseline physiological index data without drug intervention based on the individualized parameter data and comorbidity data through a pre-set individualized cardiac response baseline model; calculating drug concentration based on multidrug therapy data and pharmacokinetic parameters; calculating comprehensive pharmacodynamic data by combining pharmacodynamic interaction parameters; generating predicted physiological data under multidrug intervention; subsequently obtaining purified physiological data through adaptive filtering and frequency domain decomposition; and finally generating a rehabilitation effect score through a pre-trained long short-term memory network model. Its beneficial effects include: distinguishing between drug interference and real cardiac function improvement, and improving the accuracy of rehabilitation assessment for patients undergoing multidrug therapy.

The invention discloses a dynamic intelligent monitoring and early warning system based on endocrine gland functions, and relates to the technical field of endocrine monitoring, and the dynamic intelligent monitoring and early warning system comprises the following steps: obtaining hypothalamus, pituitary and target gland three-layer hormone concentration data, and carrying out timestamp alignment; after wavelet denoising, the deviation degree of each parameter relative to the health baseline is quantified; establishing an original differential equation set to simulate a hormone axis regulation and control relationship, and calculating a hierarchical weight; a fourth-order Runge-Kutta method is adopted to discretely solve a dynamic weight value; fusing the weight and the abnormality to generate a risk index, and dynamically adjusting an early warning line in combination with a hyperbolic threshold function; according to the threshold breakthrough duration and trend, three-level response of data review, targeted monitoring and drug intervention is triggered. According to the method, a hierarchical coupling differential equation is constructed by simulating a multi-stage regulation mechanism of an endocrine system, so that the recognition sensitivity of early signals of endocrine disorder is improved.

The application relates to application of semaglutide in preparation of a medicine for treating or delaying ovarian aging, and through a natural aging mouse model, a cell aging model and transcriptome analysis, it is first proved that semaglutide can significantly increase the number of follicles and reduce the level of aging markers, and from a molecular level, it is revealed that the mechanism of realizing multi-target point delay of ovarian aging is that semaglutide realizes multi-target point delay of ovarian aging through regulating an adipocyte cytokine signal pathway, inhibiting excessive cell division and regulating an NF-kappa B signal pathway. As a marketed drug, semaglutide has clear safety, a long half-life and high patient compliance, and has a significant clinical conversion prospect. The application breaks through the limitation that existing hormone replacement therapy and assisted reproductive technology can only treat symptoms or solve the problem of fertility, provides a first drug intervention strategy which can fundamentally delay the process of follicle depletion, and fills the blank in the field of ovarian aging treatment.

The invention provides a non-drug intervention strategy making method and system for an insomnia patient, and the method comprises the steps: obtaining a traditional Chinese medicine physiological reference parameter of the patient, mapping the traditional Chinese medicine physiological reference parameter to a continuous physiological waveform, removing a static component matched with a traditional Chinese medicine physiological reference from the continuous physiological waveform, and obtaining a non-drug intervention strategy of the patient; obtaining a pure stress shock waveform triggered by external disturbance, and calculating a permeation gain of the environment characteristics to the pure stress shock waveform in the environment path; calculating the interference intensity of the traditional Chinese medicine syndrome characteristic data on the pure stress shock wave form in the syndrome path; performing state object division on the current sleep state of the patient based on the ratio relationship between the permeation gain and the interference intensity; and dynamically adjusting the output weights of the physical environment adjustment instruction, the traditional Chinese medicine syndrome adjustment instruction and the cognitive intervention instruction in a preset non-drug intervention library based on the recognition result of the state object and the recovery characteristic time parameter of the physiological steady state in the corresponding state. And a dynamic self-adaptive household non-drug intervention scheme is provided.

The invention discloses a real-time monitoring-based implant operation pain self-adaptive regulation and control method and system, and belongs to the field of biomedical engineering. The method comprises the following steps: establishing a tooth position-myoelectricity mapping relation according to an implant tooth position, and deploying bilateral myoelectricity electrodes to establish an individualized myoelectricity baseline; event-related myoelectricity response and skin conductance response are calculated, and pain side positioning is carried out; evaluating the anxiety level, and quantifying and correcting the pain intensity; based on the corrected pain intensity index and anxiety level index, performing state comprehensive judgment by adopting fuzzy logic; self-adaptive regulation and control including cognitive intervention, physical intervention, drug intervention and joint regulation and control are executed according to the state judgment result, and hierarchical upgrading is carried out according to the regulation and control effect. According to the invention, scientific distinguishing between pain and anxiety, accurate positioning of pain side identification and closed-loop self-adaptive regulation and control are realized.

The invention relates to the technical field of model construction, in particular to a modeling system and modeling method suitable for a rat epileptic status model.The modeling method comprises the steps that electrical stimulation is applied to a rat according to preset stimulation parameters, and the stimulation parameters are output; monitoring physiological signals of the rats in real time, performing feature extraction on the physiological signals, and outputting epilepsy feature parameters; comparing the epilepsy characteristic parameters according to a preset threshold value to confirm whether an epilepsy persistent state is reached, and generating a final modeling result based on a state confirmation result; when the model is successfully established, the medicine intervention module is automatically triggered, the anti-epileptic effect of the candidate medicine is evaluated in real time based on the change of epileptic characteristic parameters obtained in real time, and a medicine effect evaluation report is output; according to the method, the process of automatically constructing the rat epileptic status model is realized, and the establishment of the model can be dynamically adjusted and confirmed according to the change of the epileptic characteristic parameters by accurately controlling the preset stimulation parameters and monitoring the physiological signals of the rat in real time.

The invention relates to the technical field of biomedical experiment models, in particular to a construction method and system applied to an animal experiment evaluation model. The method comprises the following steps: performing grouping and baseline determination on male SD rats to obtain a grouped baseline data table; performing space-time separation type stress implementation according to the grouped baseline data table, and performing stress sensitivity evaluation to obtain a stress sensitivity index; performing functional flora specific sequencing on the male SD rat according to the stress sensitivity index to obtain a functional flora sequencing data packet; performing micro-ecological disorder degree calculation on the functional flora sequencing data packet to obtain an intestinal micro-ecological disorder index; and performing drug intervention and behavior testing according to the intestinal microecological disorder index to obtain a multi-dimensional behavior parameter set. Through the biomedical experiment model technology, standardization, objectiveness and comprehensiveness of construction of the animal experiment evaluation model and intervention effect evaluation are achieved.

The invention relates to the technical field of learning and memory ability evaluation, and provides a mouse hippocampus learning and memory ability comprehensive evaluation method and system based on a Morris water maze, the method is different from a traditional method for evaluating learning and memory only through an incubation period, a mouse behavior character stability and swimming skill dual evaluation mechanism is innovatively introduced, and the method is suitable for comprehensive evaluation of learning and memory ability of a mouse hippocampus. And in combination with a training adaptation period, behavior path analysis and weighted scoring of multi-dimensional behavior indexes, precise quantification of the hippocampus dependency space learning and memory ability is realized. The experimental indexes comprise swimming speed, path length, target quadrant residence time and incubation period, and performing standardized calculation after weight assignment to generate a memory ability evaluation score. According to the invention, the scientificity, stability and experimental repeatability of an evaluation result are improved, and the method is suitable for mouse cognitive function evaluation under various research situations such as drug intervention, neurodegenerative disease models and the like.

The invention discloses a motion intervention heart failure repair method based on Lgmn signal regulation and control, and relates to the technical field of heart failure treatment. According to the method, through aerobic exercise training (AET) with specific parameters, expression of Legumain (Lgmn) genes in macrophages is regulated in a targeted mode, the interburial effect of the macrophages is enhanced, then cell communication between the macrophages and cardiac muscle cells is enhanced, removal of the vertical death cardiac muscle cells is promoted, myocardial fibrosis and inflammatory response are relieved, and the effect of treating myocardial fibrosis is achieved. Finally, ventricular remodeling and heart functions of chronic heart failure (CHF) mice are improved. Experimental verification shows that the exercise intervention method can significantly improve the left ventricular ejection fraction (LVEF) and shortening fraction (FS) of CHF model animals, reduce the left ventricular end-of-systole inner diameter (LVESD), reduce myocardial cell apoptosis and necrosis, and promote inflammation regression. Drug intervention is not needed, safety is high, operation is easy and convenient, and a new effective way is provided for clinical rehabilitation treatment of heart failure.

The application discloses application of an inhibitor targeting CCL28 in treatment of visceral pain. The application firstly proves that CCL28 is significantly up-regulated in spinal cord dorsal horn neurons of a mouse model of visceral pain, and establishes CCL28 as a new target for treatment of visceral pain. On this basis, the application designs and screens a high-efficiency and specific siRNA sequence targeting CCL28, the siRNA can be delivered to the spinal cord locally through intrathecal injection, specifically silences CCL28 gene expression, inhibits activation of a downstream ERK signal pathway, thereby significantly alleviating visceral pain, and has no obvious off-target effect. The application provides a complete technical scheme from target discovery to drug intervention, provides a new strategy and a drug candidate molecule for treatment of visceral pain, and has a good clinical application prospect.

The present invention discloses a method and system for dynamic risk assessment of medication for elderly patients, relating to the technical field of medication risk assessment. The method comprises collecting static factor data and dynamic factor data of elderly patients, pre-processing the collected static factor data and dynamic factor data, and generating a feature vector for risk assessment; calculating a comprehensive risk score based on the feature vector using preset assessment rules; comparing the comprehensive risk score with a preset risk grading threshold to determine the medication compliance risk level of the elderly patients. The system comprises data collection, pre-processing, risk assessment, and grading modules. The present application realizes multi-dimensional risk assessment by integrating static and dynamic data, thereby improving the comprehensiveness and timeliness of medication compliance risk assessment for elderly patients and providing technical support for medication intervention.

The invention belongs to the field of analytical chemistry, and provides a method for simultaneously determining 10 tryptophan metabolites through liquid chromatography-mass spectrometry, differentiated pretreatment schemes are designed aiming at different biological matrixes such as excrement, serum, colon tissue and NCM460 inflammatory cells through a liquid chromatography-tandem mass spectrometry technology, matrix interference is effectively eliminated, and the method for simultaneously determining 10 tryptophan metabolites through liquid chromatography-mass spectrometry is provided. A quantitative analysis method with high sensitivity and high selectivity is established; the method is successfully applied to an ulcerative colitis (UC) rat model and a lipopolysaccharide (LPS)-induced NCM460 inflammation model, and a technical means is provided for revealing a metabolic regulation mechanism of medicine intervention on UC; the method solves the technical problem that various metabolites in a tryptophan metabolic pathway are difficult to detect in the prior art, is suitable for metabolic mechanism research, drug intervention effect evaluation and large-scale detection of clinical samples of inflammatory bowel diseases such as UC, and provides a technical basis for systematic research of a tryptophan metabolic network.

The invention discloses an endocrine disease intelligent nursing monitoring system based on multi-modal physiological signals, and relates to the technical field of disease intelligent nursing, the system synchronously collects blood glucose, heart rate, heart rate variability, skin electrical activity, core body temperature and body movement signals through a wearable device and a household terminal, and multi-dimensional features are extracted after filtering and time alignment processing. The fusion module adopts an attention mechanism to perform weighted analysis on multi-source features, and the risk assessment module calculates individual health risk indexes and generates diet, exercise and drug intervention parameters according to dynamic weights output by the model. The system is provided with an interpretability analysis unit which is used for calculating the contribution value of each modal feature to a risk prediction result and supporting traceability and verification of a clinical end. The cloud platform is used for data storage and trend analysis, long-term tracking of patient states and model self-updating are achieved, and the precision and stability of monitoring and nursing are improved.

This application discloses the use of NUAK2 inhibitors in the preparation of drugs for the prevention and / or treatment of pulmonary fibrosis, belonging to the field of medical preparation technology. The technical problem this application aims to solve is: to find and validate a novel drug target that plays a key role in pulmonary fibrosis, and to provide an intervention strategy based on this novel target with a clear therapeutic effect; specifically, to provide an effective therapeutic drug for pulmonary fibrosis. To solve this technical problem, this application provides the application of NUAK2 inhibitors in the preparation of drugs for the prevention and / or treatment of pulmonary fibrosis. This application is the first in the world to reveal that NUAK2 is a key pathogenic factor and drug intervention target for pulmonary fibrosis, and the first to propose and validate a novel use of NUAK2 inhibitors (represented by WZ4003) for the treatment of pulmonary fibrosis, filling a technological gap in this field.

The invention belongs to the technical field of neurobiology, and particularly relates to application of a dopamine D2 receptor G protein antagonist in preparation of a drug for treating drug addiction. Researches show that the dopamine D2 receptor G protein antagonist can inhibit recurrence after drug addiction fading induced by ignition of small-dose drugs. A mouse cocaine self-administration addiction model is adopted, a small dose of cocaine is given after model mice are subjected to regression training, and the recurrence behavior of the mouse cocaine addiction after regression is induced. A signal channel dependent on dopamine D2 receptor downstream G protein is inhibited before addiction recurrence is induced by a small dose of cocaine, and recurrence after drug-induced cocaine fading can be inhibited; however, the signal pathway for inhibiting the dependence of beta-arretin on the downstream of the dopamine D2 receptor cannot inhibit the recurrence after drug-induced cocaine fading. The invention discloses the effect of the G protein biased antagonist of the dopamine D2 receptor in treatment of drug addiction, and provides a new thought and a drug intervention target for treatment of drug addiction of cocaine and the like.

The present application relates to the technical field of intelligent control system data analysis and monitoring, in particular to a model target verification data dynamic analysis system, which comprises a data acquisition control module that collects model construction data, drug intervention data, behavior and imaging data and generates state values according to a preset time sequence. According to the present application, modeling data, intervention data, behavior score, imaging lesion area, physiological indicators, molecular detection data and omics detection data are linked according to the sampling time sequence, and the collected state values, model state determination values, target variable quantity values and verification deviation values are sequentially transmitted. Expression difference values, protein gray values and positive cell rates are jointly used to select targets together with threshold values. The deviation of fasting blood glucose, body weight change rate, pathological staining integral and immunofluorescence average fluorescence intensity after intervention is used as a basis. Sampling time sequence, detection nodes and target review instructions are hierarchically output, and the continuity of the monitoring link is increased.

The invention relates to the technical field of biological medicine, in particular to application of glibenclamide and halofuginone in preparation of a preparation for preventing and / or treating radiation-induced lung injury. The glibenclamide and the halofuginone are combined for use, so that the radiation-induced lung injury can be effectively prevented and / or treated; the two drugs break through the limitation of single drug intervention through mechanism synergy, the onset risk of radiation-induced lung injury is effectively reduced, the pathological injury degree is reduced, the disease prognosis is improved, a new technical path is provided for prevention and treatment of radiation-induced lung injury, and the pharmaceutical composition has important clinical transformation value and application prospect.

The invention discloses application of idarubicin in preparation of a medicine for treating benign prostatic hyperplasia, and relates to the technical field of biological medicine. The invention discloses application of idarubicin in preparation of a medicine for treating benign prostatic hyperplasia. The application of idarubicin in BPH treatment is found and confirmed for the first time: (1) the specificity effectiveness of BPH, preferably gland proliferation type BPH, is verified, and the intervention effect of idarubicin on a core target TP63 and gland proliferation is clear; (2) the regulation and control effect on prostate volume and gland hyperplasia is supported through in-vivo experimental data; and (3) curative effect verification at a clinical level is carried out, and a clinical application path of subtype screening-drug intervention-curative effect evaluation is established, so that transformation in BPH precise treatment is facilitated. According to the research, through a complete evidence chain of cell, animal and multi-center clinical retrospective research, the treatment value of idarubicin on BPH, especially gland proliferation type BPH, is verified, and the blank in the field is filled.

The application discloses a mental disorder-oriented multi-modal large model identification and intelligent intervention method and system, belongs to the technical field of mental disorder intelligent identification and intervention, and comprises a multi-modal data acquisition stage, a data preprocessing stage, a feature extraction stage, a cross-modal feature fusion stage, a mental disorder identification stage and a personalized non-drug intervention stage.The multi-modal data acquisition stage acquires skin electricity, electrocardiogram, electroencephalogram and facial expression multi-modal data in real time, combines cognitive behavior therapy theory, and constructs a dialogue-feedback-adjustment closed loop mechanism.The application adopts the mental disorder-oriented multi-modal large model identification and intelligent intervention method and system, integrates electroencephalogram, electrocardiogram, skin electricity, expression analysis and text data multi-modal physiological and behavioral data, combines a large language model and a cross-modal attention mechanism, and realizes accurate identification and personalized intervention on mental disorders.

The invention relates to application of a near-infrared light source or a blue light source in preparation of equipment for treating diabetes, and belongs to the technical field of photomedicine. The invention provides application of a near-infrared light source or a blue light source in preparation of equipment for treating diabetes. According to the invention, a diabetic rat model is established, near-infrared light and blue light are adopted to carry out phototherapy on diabetic rats, and blood sugar and blood fat related indexes of the diabetic rats and changes of different tissue forms and behaviors of the rats are measured; results show that the near-infrared light and the blue light can effectively improve blood sugar and blood fat related indexes of the rats after phototherapy of the rats, and can also improve tissue morphology and cognitive behaviors of the diabetic rats, which indicates that the phototherapy of the near-infrared light or the blue light has the effects of treating diabetic blood sugar and cognition, can reduce dependence of patients on medicines, and can improve the curative effect of the patients on diabetes mellitus. And new experimental basis and theoretical support are provided for clinical non-drug intervention of diabetes.

The invention discloses a targeted periprosthetic infection detection, drug delivery and drug intervention system as well as a method and application thereof, and belongs to the field of biological medicine. The detection and drug intervention system comprises a micrococcus nuclease sensitive biological probe, a functional silicon plastid for bearing the micrococcus nuclease sensitive biological probe, light-cured hydrogel and an implant, wherein medicines are carried in the functional silica plastid; a micrococcus nuclease sensitive biological probe is connected to the surface of a functional silicon plastid through electrostatic interaction force to obtain a nuclease probe functional silicon plastid, and the nuclease probe functional silicon plastid is connected to the surface of an implant through photocuring hydrogel. According to the system provided by the invention, the detection is realized, the delivery of the medicine is also realized, and the release of the medicine can also be realized when the occurrence of infection around the prosthesis is judged, so that the intervention treatment of the medicine is carried out.