122results about How to "Improved prognosis" patented technology

The invention provides a tumor area double-view detection method and system based on image modalities and views, and relates to the field of medical image analys.The method comprises the steps that multi-modal image data are collected from the body of a patient, and image data of different view angles at the same position are obtained according to time frames; extracting multi-modal features from the image data of different modalities and different view angles, and performing weighted fusion on the extracted multi-modal features to form a fused feature map; inputting the fused feature map to train and predict the 3D-CNN network so as to identify and position a tumor region, and marking the tumor region by using a mask output by the segmentation model; calculating the pixel number of the tumor area in each layer of image according to the marked mask, and multiplying the pixel number by the volume of each pixel to obtain the volume of the tumor area; and the segmentation results of each layer of image are superposed, and a three-dimensional model of a tumor region is generated by using 3D reconstruction, so that the limitation of single-mode and single-view image data in tumor detection is overcome.

The invention discloses a personalized hypertensive nephropathy risk assessment method and system based on a graph convolutional network, and the method comprises the steps: collecting modal data related to hypertensive nephropathy, and carrying out the preprocessing; constructing a patient similarity graph; performing multi-source information fusion and domain knowledge integration; sparse processing is carried out on the graph structure, and standardization processing is carried out on an adjacent matrix; modeling through a time sequence diagram convolutional network and a long-short term memory network, and capturing the evolution trend of patient characteristics along with time; through a self-attention mechanism and a graph regularization item, the transmission of important features is enhanced; a multi-head attention mechanism is adopted, and different types of relation modes are captured; optimizing model parameters by using an Adam optimization algorithm and a regularization method; and a risk assessment result is optimized by adopting weighted stacking and a self-adaptive attention mechanism. According to the risk assessment method, accurate assessment of the risk of hypertensive nephropathy is realized by constructing the multi-dimensional and dynamically changing patient similarity graph.

The invention discloses an acute kidney injury risk early warning system, and relates to the technical field of clinical decision support systems. In order to solve the problems that in the prior art, due to the fact that a large amount of data preprocessing and model training need long-time data processing and model operation, the early warning opportunity is not accurate, the real-time performance is low, personalized early warning prompting cannot be carried out for patient groups, and early warning fatigue and early warning desensitization are likely to be caused. Through data preprocessing, model construction and risk analysis, real-time monitoring and accurate prediction of the AKI risk of a patient are realized, the early recognition rate is improved, the early warning decision unit generates specific early warning information according to risk scores and kidney function change rules and provides targeted treatment suggestions, and meanwhile, through an early warning threshold adjustment and approach matching module, the early warning decision unit can perform early warning on the AKI risk of the patient. The early warning strategy is optimized, the response speed of medical staff and the compliance of patients are improved, and the user interaction unit continuously optimizes the early warning system through a feedback mechanism.

The invention provides a risk early warning method and system for stomach cancer postoperative malnutrition, and relates to the technical field of medical treatment, and the method comprises the steps: obtaining gene expression data and clinical indexes of a stomach cancer patient based on a cancer genome map database; gastric cancer methylation data is collected, and a methylation risk scoring model is constructed to determine a methylation risk score; performing quantitative evaluation on the nutritional status of the gastric cancer patient based on a nutritional risk screening tool to obtain a nutritional risk level; determining risk characteristics related to stomach cancer postoperative dystrophy according to the gene expression data, the clinical indexes, the methylation risk score and the nutrition risk grade, and establishing a risk early warning model based on a support vector machine; and acquiring current risk data of the patient side, inputting the current risk data into the risk early warning model, outputting a risk score and a risk level, generating a risk intervention measure according to the risk level, and feeding back the risk intervention measure to the medical care side, so that accurate and comprehensive early warning can be performed on the risk of postoperative malnutrition of the gastric cancer patient, and a timely and effective nutrition intervention scheme is formulated.

The invention discloses an application of a biomarker in preparation of a kit for a prognosis risk early warning method of an acute ST segment elevation type myocardial infarction patient. The biomarker comprises an HBP (Hepatitis Binding Protein). By monitoring the change of the HBP protein level, whether a patient suffering from the acute ST segment elevation type myocardial infarction has poor prognosis within 30 days after a PCI operation can be effectively evaluated, so that early recognition and timely clinical intervention on high-risk patients are realized, the treatment response speed and effect are improved, the occurrence rate of adverse cardiovascular events is reduced, and the treatment effect of the patient suffering from the acute ST segment elevation type myocardial infarction is improved. And the prognosis of the patient is finally improved.

The invention discloses a sugar net recognition system based on a block chain and federal learning, and the system comprises a data collection module which is used for collecting fundus image data and related medical data; the federal learning module is connected with the data acquisition module, the federal learning module comprises a plurality of participant nodes, and each participant node performs model training based on local data; the block chain module is connected with the federated learning module and used for storing model parameters, training data abstracts and data access record key information in the federated learning process; the sugar network identification module is used for receiving the global sugar network identification model trained by the federal learning module; and the result output and feedback module is connected with the sugar net identification module. According to the method, the data collaborative training model is integrated through federal learning, so that the sugar net recognition accuracy is improved, misdiagnosis and missed diagnosis are reduced, the block chain ensures the data to be safe and credible, the innovative formula assists optimization, the system application is wide, clinical and remote medical treatment is facilitated, and the sugar net diagnosis service quality is improved.

The invention relates to the field of acute lung injury caused by sepsis, in particular to application of lactobacillus rhamnosus exosome in preparation of medicine for treating and / or preventing acute lung injury caused by sepsis of subjects, and the acute lung injury caused by sepsis is acute complication of sepsis. The sepsis is caused by bacterial infection, and the particle size of the lactobacillus rhamnosus exosome ranges from 50 nm to 120 nm. The lactobacillus rhamnosus exosome provided by the invention can prevent and / or timely and effectively prevent the development of the disease course of a subject at the initial stage of sepsis acute lung injury, and finally, the treatment success rate of the subject is increased, and the prognosis of the subject is improved.

The shock wave mesh basket electrode catheter comprises an inner tube and an outer tube, the inner tube is arranged in the outer tube and extends out of the far end of the outer tube, the far end of the inner tube is provided with a tip, the near end of the outer tube is connected with a handle, the handle is connected with a plug through a cable, and the plug is used for being connected with an external shock wave device. A mesh basket part is arranged on the inner tube, a balloon and a shock wave generator are arranged on the mesh basket part, and the mesh basket part has self-expansion performance so that a cage-shaped structure can be formed after expansion. According to the embodiment, the risks that the artificial valve is difficult to position and fix in the operation process, the artificial valve is not suitable to release and difficult to remove and the like can be effectively avoided, the operation time is shortened, and the operation operation and prognosis effects are greatly improved.

The invention provides a traditional Chinese medicine compound for treating sicca syndrome and a preparation method and application thereof, and belongs to the technical field of traditional Chinese medicine compounds. The traditional Chinese medicine compound provided by the invention has the effects of eliminating dampness and heat, removing blood stasis and promoting salivation, can safely and effectively treat sicca syndrome by improving functions of exocrine glands and regulating immunity, belongs to a pure traditional Chinese medicine preparation, and has no toxic or side effect. The traditional Chinese medicine compound is proved to be capable of remarkably relieving the sicca syndrome, relieving dry mouth and eye symptoms of a patient, relieving fatigue, regulating and controlling a plurality of signals taking RAGE / TLR4 as a core, inhibiting excessive activation of an HMGB1-RAGE / TLR4-NF-kappa B pro-inflammatory pathway from gene and protein levels, inhibiting generation of pro-inflammatory cytokines, reducing inflammatory response and improving the immunity of the patient. The effect of treating the sicca syndrome is achieved. By acting on STAT3 phosphorylation, Tfh proliferation is inhibited, IL-21 secretion is reduced, humoral immune disorder is relieved, and the sicca syndrome is treated, so that the condition of the sicca syndrome is relieved, and the prognosis of the sicca syndrome is improved.

The invention belongs to the field of tumor drugs, and discloses a radioactive hydrogel based on crosslinking of sodium alginate and metal ions and a preparation method and application thereof.The preparation method of the radioactive hydrogel comprises the following steps that lutetium chloride and metal ions are mixed, and a metal ion mixed solution is obtained; doping 177Lu radioactive isotope into the obtained metal ion mixed solution to obtain a metal ion cross-linking agent; and injecting a metal ion cross-linking agent into the sodium alginate solution under a vortex condition, centrifuging, and discarding the supernatant to obtain the radioactive hydrogel. The radioactive hydrogel (177Lu-RH) provided by the invention has good in-tumor colonization capability, can be directly injected into a tumor to realize local radiotherapy, has good radioactive stability, and can be stably retained at a tumor part for more than 120 hours, so that the stability of radioactive labeling in a treatment process is ensured.

The present disclosure relates to a method, device, equipment and medium for intelligent fusion of CTA and DSA images, the method comprising: obtaining a two-dimensional image and a three-dimensional image of a patient's coronary artery, the two-dimensional image being a digital subtraction angiography image, and the three-dimensional image being a computed tomography angiography reconstruction image; determining the projection angle of the two-dimensional image when the patient is in a preset position; performing position correction processing on the three-dimensional image to obtain a first image of the coronary artery when the patient is in the preset position; performing registration and fusion based on the two-dimensional image, the projection angle and the first image to obtain a two-dimensional fused image; and displaying the fused image. The present disclosure can display information on completely occluded lesions and plaque properties through fused images by registering and fusing the two-dimensional and three-dimensional images of the patient's coronary artery, assisting doctors in diagnosing coronary artery lesions and planning interventional pathways, improving the success rate of treatment, and improving patient prognosis.

The invention discloses a method and a system for automatically analyzing chest respiratory muscle volume based on a deep learning network, and belongs to the field of medical images. The method for automatically analyzing the chest respiratory muscle volume based on the deep learning network comprises the steps that a CT image and a chest respiratory muscle image manually marked by a doctor are collected, and the CT image and the image manually marked by the doctor are preprocessed to obtain a standard sketching graph; performing data enhancement operation on the standard sketching picture; constructing a U-Net model, and training the constructed U-Net model by using the standard sketching graph after data enhancement; and automatically sketching the chest respiratory muscle in the medical image by using the trained U-Net model to obtain the contour of the chest respiratory muscle. A U-Net network model is constructed, an efficient, reliable and easy-to-implement solution is provided for three-dimensional medical image segmentation, the method has wide application prospects and clinical values, time consumed in clinical work is greatly shortened, respiratory muscle related information is helped to be obtained clinically and rapidly, treatment of a patient is guided, and prognosis of the patient is improved.

The invention provides a bionic MOF nano platform capable of double targeting cervical cancer tumor cells and cancer-related fibroblasts and co-delivering an FAK inhibitor and bismuth as well as a preparation method and application thereof, the bionic MOF nano platform comprises an MOF material loaded with the FAK inhibitor (IN10018) and bismuth (Bi), and a hybrid membrane coating the outer part of the MOF material loaded with the FAK inhibitor and the bismuth, the hybrid membrane is obtained by mixing and physically extruding a cervical cancer tumor cell (HeLa and SiHa) membrane and a cancer-related fibroblast (CAFs) membrane. According to the bionic MOF nano platform, in an acid environment, the ZIF-8 nano particles loaded with the IN10018 and the Bi disintegrate, the IN10018 is released, CAFs infiltration in tumors is reduced, meanwhile, due to addition of the Bi, the radiation absorption efficiency is improved, and the sensitivity of the tumors to radiotherapy is further enhanced through a double-targeting mechanism.

The invention discloses injectable and degradable composite drug-loading hydrogel as well as a preparation method and application thereof. The injectable and degradable composite drug-loading hydrogel comprises sodium alginate hydrogel, piezoelectric nanofibers and triamcinolone acetonide and / or ropivacaine, wherein the piezoelectric nanofibers and the triamcinolone acetonide and / or the ropivacaine are loaded on the sodium alginate hydrogel; the piezoelectric nanofibers are poly-L-lactic acid nanofibers. Through the synergistic effect of controllable release of the medicine and piezoelectric stimulation, the dual effects of continuous analgesia and neural restoration are achieved in the PHN treatment process, more effective treatment selection is provided for a PHN patient, complications caused by a traditional implantable electrode can be avoided, a more minimally invasive, convenient and safe treatment mode can be provided for the patient, and the treatment effect is good. And a theoretical basis is provided for future clinical practice.

The invention relates to a ventilation detection device for a myasthenia gravis patient, and the device comprises a muscle strength monitoring module which is configured to monitor the swallowing muscle of the myasthenia gravis patient and the muscle activity of the near end of the limb, and obtains the muscle strength data of the myasthenia gravis patient; the respiration monitoring module is configured to detect the respiration frequency, the tidal volume of each respiration cycle and the inspiration time of each respiration cycle under the condition that mechanical assisted ventilation is carried out on the myasthenia gravis patient, and the change trend along with time is obtained; the control module is in signal connection with the muscle strength monitoring module and the respiration monitoring module, and is configured to control the respiration monitoring module when the muscle strength data of the serious myasthenia patient is lower than a preset muscle strength threshold value and the change trend of the respiration frequency, the tidal volume of each respiration cycle and the inspiration time along with the time is inconsistent with the change trend of pre-stored corresponding parameters; and determining that man-machine resistance exists in the mechanical assisted ventilation process of the myasthenia gravis patient.

The invention relates to the technical field of data processing, in particular to an intelligent data processing method and system based on surgical nursing, and the method comprises the steps: firstly obtaining food intake and physiological indexes of a patient within a preset time, comparing the food intake and physiological indexes with a standard food intake set, and generating a food intake standard score; in conjunction with the physiological metric, the system determines a real-time feeding score and a total feeding score. By comparing the real-time and total feeding scores at different time points, the system finally generates a feeding balance score of the patient. According to the method, food intake and physiological data are effectively integrated, a scientific and quantitative food intake evaluation tool is provided for surgical nursing, nutrition management of a patient is optimized, nursing quality is improved, the absolute value of the food intake is considered in the evaluation, the relevance between time distribution of food intake and physiological indexes is concerned, and the evaluation accuracy is improved. Therefore, more comprehensive and in-depth patient state information is provided for nursing personnel. Especially, due to the introduction of a feeding balance degree score, an important basis is provided for formulating a more reasonable nutrition intervention scheme.

The invention relates to the technical field of digital medical treatment, in particular to a method and a device for constructing a colorectal cancer multi-mode recurrence risk model. The construction method comprises the following steps: acquiring a panoramic digital scanning image of a pathological tissue section of a colorectal cancer patient; constructing a data set and selecting a region of interest by using the panoramic digital scanning image; constructing a pathological omics feature scoring model, a collagen feature scoring model and an immune feature scoring model through the region of interest; and according to the pathological omics feature scoring model, the collagen feature scoring model and the immune feature scoring model, constructing a multi-modal recurrence risk model. On the basis of an image analysis technology, the pathological omics feature scoring model, the collagen feature scoring model and the immune feature scoring model are constructed and integrated into the multi-mode recurrence risk model, and accurate prediction of the recurrence risk of the colorectal cancer patient is achieved.

The invention discloses a thyroid disease course development time sequence analysis method based on an LSTM network, and the method comprises the following steps: 1, data collection and preprocessing: collecting time sequence data related to a thyroid disease course of a patient, and carrying out the standardization processing of the time sequence data; 2, constructing an LSTM network model: designing the LSTM network model, training the LSTM network model by using the time sequence data standardized in the step 1, and capturing a time dependency relationship in a thyroid disease course; and through cross validation and hyper-parameter tuning, the performance of the LSTM network model is optimized. According to the thyroid disease course development time sequence analysis method based on the LSTM network, time sequence analysis is carried out on the disease course data of a thyroid disease patient, the disease development trend is predicted, a scientific basis is provided for clinical decision making, doctors can better master the disease condition change trend of the patient, a treatment scheme is optimized, and the patient experience is improved. The prognosis of the patient is improved.

The invention provides a prognosis-guided intensity modulated radiation therapy plan optimization method based on gradient enhanced particle swarm solution. The method comprises the following steps: S10, constructing a prognosis-based radiation field flux intensity distribution optimization model; s20, based on the radiation field flux intensity distribution optimization model, randomly generating a group of flux distribution initialization particle swarm in a solution space; step S30, carrying out iterative updating on particles in the flux distribution initialization particle swarm by randomly comparing interaction information and gradient information so as to find a global optimal flux; and S40, judging whether a preset termination condition is met or not, if the preset termination condition is not met, turning to the step S30 to continue iteration, and if the preset termination condition is met, outputting the currently searched global optimal flux to obtain an intensity modulated radiotherapy plan. According to the method, the prognosis-guided personalized intensity modulated radiotherapy plan can be efficiently and quickly generated for the patient, and a technical foundation is laid for wide clinical application of prognosis-guided intensity modulated radiotherapy plan design.

The invention relates to a finger-pressing type nucleic acid detection micro-fluidic chip, which comprises a bottom layer, a flow channel layer, a finger-pressing layer and a thin film layer, the flow channel layer comprises an LAMP reaction chamber, a CRISPR reaction chamber, a water storage chamber, a Tesla valve, a finger-pressing chamber and a test paper reaction chamber, the LAMP reaction chamber comprises a nucleic acid extraction-free reaction system based on LAMP, the CRISPR reaction chamber comprises a CRISPR-based cas12b reaction system, and the test paper reaction chamber comprises a Tesla valve, a finger-pressing chamber and a test paper reaction system. The water storage chamber is mainly used for diluting a mixed system, and the Tesla valve is used for preventing crosstalk of the two reaction systems; the finger pressing layer comprises an LAMP reaction chamber button and a CRISPR reaction chamber button, when the LAMP reaction chamber button is pressed, liquid in the LAMP reaction chamber is pumped into the CRISPR reaction chamber, when the two buttons are pressed at the same time, a reaction mixing system is pumped into the water storage chamber to be mixed, and then the reaction mixing system is further pumped into the test paper reaction chamber. The chip can be widely applied to the field of rapid diagnosis of nucleic acid molecules, the detection cost is reduced, manual operation is simplified, and the detection efficiency is improved.

The invention belongs to the field of pesticide poisoning prognosis, and particularly discloses a method for establishing an acute diquat pesticide poisoning prediction death risk index, which comprises the following steps: collecting data; establishing a death risk index model based on demographic characteristics and blood routine test results; and carrying out model training, internal verification and external verification. The death risk index provided by the invention comprehensively considers age, diquat blood concentration, leukocyte count and glutamic oxalacetic transaminase concentration, and aims to accurately evaluate the death risk of acute diquat pesticide poisoning patients in an index form. Through deep analysis of large-scale clinical data, the death risk index of the invention not only has scientificity and accuracy on the data level, but also can play an important role in clinical practice, can be applied to construction of acute diquat pesticide poisoning death risk prediction terminal equipment, helps medical teams to distribute medical resources more reasonably, and has a good application prospect. High-risk patients are preferentially processed, so that the overall treatment effect and the survival opportunity of the patients are improved.

The invention relates to the technical field of intelligent medical treatment, and discloses a pancreatic cancer evolution simulation and dynamic intervention system based on multi-model driving, and the system comprises a multi-source data fusion module which is used for accessing and processing patient data, and forming a multi-dimensional feature set; the model fusion construction module is integrated with a model coupler and can construct a patient-specific integrated calculation model; the twinborn calibration generation module is used for generating pancreatic cancer digital twinborn matched with the initial state of the patient; and the evolution simulation and intervention module is used for running the pancreatic cancer digital twins, simulating the natural evolution trajectory of the tumor and carrying out quantitative simulation on the input virtual treatment scheme effect. According to the method, by constructing the patient-specific digital twins, normal form transformation from static diagnosis to dynamic prediction is achieved, and a quantitative evaluation basis can be provided for selection of clinical treatment schemes.

The invention relates to the field of medical diagnosis, in particular to a preoperative evaluation and R0 excision prediction model and prediction method for ovarian cancer initial tumor cell deduction. The preoperative evaluation and R0 resection prediction model comprises a data acquisition module, a preoperative evaluation module and an R0 resection prediction module. The preoperative evaluation module is used for assigning and calculating tumor diameter data according to tumor lesion sizes to obtain lesion scores, the R0 resection prediction module is used for calculating R0 resection prediction scores, and the R0 resection prediction scores are obtained by multiplying six factors by corresponding assignments and adding the six factors. Through individualized evaluation, the operation R0 excision rate is improved, so that the overall ovarian cancer treatment effect is improved, and the living quality and prognosis of a patient are improved.

The invention relates to a method for simulating expansion of a valve component and a valve component release evaluation system. The method for simulating expansion of the valve component comprises the following steps: S1, establishing a valve bracket model and a blood vessel model based on a valve bracket of the valve component and an image of a blood vessel of a patient; s2, a first coordinate of a stent control point of the valve stent model in the unfolded state is obtained, a second coordinate of the stent control point of the valve stent model in the compressed state is obtained based on the first coordinate and the nominal size of the valve stent after compression, and the stent control point is an intersection point of metal wires of the valve stent model; s3, based on the second coordinates, adjusting the valve stent model to a compressed state; s4, putting the valve stent model in a compressed state into a release position of the blood vessel model; and S5, based on the first coordinate, the second coordinate and the blood vessel model, obtaining a third coordinate of the stent control point expanded in the blood vessel model, and expanding the valve stent model in the compressed state at the release position according to the third coordinate.

The invention relates to the technical field of medical systems, in particular to a cardiovascular operation nursing intelligent shift change system and an implementation method thereof, comprising a receiving end, an information sending end, an output end, an information acquisition end, an electronic signature end and a management end; the identity information and the state of a patient are confirmed through the output end, the two-dimensional code generator, the second recognition device and the first recognition device, so that the first patient information and the second patient information are confirmed, and the behaviors that the first patient information and the second patient information are manually filled in to be inconsistent and manually modified when a doctor receives the patient are avoided; the output end confirms the information of the medical instruments, omission of the instruments is avoided, omission of the instruments in an operation is avoided, influence on the operation quality is avoided, and economic loss is avoided; the state data of the second patient is acquired through the information acquisition end, so that the second patient is confirmed and matched with the actual illness state, the state of the patient during receiving is ensured, and the safety of the patient is ensured.

The application discloses a kind of biomarkers for evaluating systemic lupus erythematosus to lupus nephritis progression, prediction model and application, belong to lupus nephritis prediction technical field.The application provides a kind of for evaluating systemic lupus erythematosus to lupus nephritis progression prediction model, the prediction model is according to the ratio of biomarker CD8 / CD4 and the κ / λ ratio of naive B cell, carries out binary Logistic regression analysis, obtains LogitP value, by comparing the high and low of the LogitP value and critical value 0.66938, predicts systemic lupus erythematosus to lupus nephritis progression situation.The prediction model constructed in the application aims to identify the individuals in lupus patients who may develop into lupus nephritis.This innovative model not only provides important guidance in the diagnosis, prognosis prediction and efficacy evaluation of the disease, but also provides a new perspective for the clinical management of lupus nephritis.

The invention discloses a method for screening a B-cell lymphoma biomarker, and belongs to the technical field of bioinformatics. The invention aims to provide a more accurate and simple method for screening the B-cell lymphoma biomarker. The invention provides a method for screening a B cell lymphoma biomarker. The relation between the infiltration ratio of all cell subgroups of T / NK and myeloid cells and the lifetime of a patient is screened out by utilizing scRNA-seq data of Burki lymphoma, diffuse large B cell lymphoma, follicular lymphoma and spleen marginal region lymphoma and bulk RNA-seq data of a Burki lymphoma and diffuse large B cell lymphoma database. And a theoretical basis is provided for screening survival analysis of lymphoma diseases.

The present invention relates to a method for removing a large-volume tumor in a body through a single hole, comprising an operation kit, the operation kit comprising an isolation protection bag, the isolation protection bag being configured with an internal accommodating cavity and a bag opening, and the isolation protection bag being configured to be resistant to cutting; the method comprising the steps of: 1, delivering the isolation protection bag into a body through an incision, placing the tumor to be removed from the body into the isolation protection bag, and tightening the bag opening; 2, pulling the bag opening of the isolation protection bag out of the body through the incision; 3, pulling the isolation protection bag outward, and pulling the tumor to a position corresponding to the incision; 4, extending a cutting tool into the isolation protection bag through the bag opening, cutting the tumor into a long strip structure or a small block structure by using the cutting tool, and removing the tumor through the bag opening; and 5, pulling the isolation protection bag outward, and pulling the entire isolation protection bag outward through the incision; the method can strictly follow the tumor-free principle to remove a large-volume tumor in a body through a small incision, and is particularly suitable for single-hole laparoscopic surgery.

Use of an active ingredient in repairing heart tissue injury. Specifically, disclosed is an active ingredient capable of being used for repairing heart tissue injury and treating diseases related to lymphatic abnormalities, comprising: a TBX1 protein, a coding gene thereof, or an accelerator thereof, or a combination thereof. The TBX1 protein can promote the proliferation of heart lymphatic endothelium cells, play an immunoregulatory role, promote the establishment of an immunosuppressive microenvironment in the myocardium after heart tissue injury, inhibit autoimmune responses after the heart tissue injury, relieve concurrent inflammation of the heart tissue, and promote the repair and regeneration of the injured heart tissue.

A neurosurgery postoperative near-infrared drainage device comprises a transparent tube body and a near-infrared controller, a drainage tube body is arranged in an inner cavity of the transparent tube body, a drainage hole is formed in the front end of the transparent tube body, and the drainage hole is communicated with the inner cavity of the drainage tube body; a near-infrared lamp bead is arranged at the front end of an inner cavity of the transparent tube body and is connected with a near-infrared controller through a first conductive wire; a plurality of near-infrared light probes are uniformly arranged on the front half section of the transparent tube body along the axial direction; each near-infrared light probe is connected with the near-infrared controller through a second conductive wire; the near-infrared controller is connected with an external power source through a plug, and the near-infrared light probe and the near-infrared lamp beads are located on the same side of the inner wall of the transparent tube body. According to the utility model, the defects in the prior art are overcome, and the situation that the treatment efficiency is reduced due to the fact that traditional near-infrared treatment penetrates through the skull is avoided. The treatment purpose required by a patient can be achieved only by low-dose illumination intensity, heat production is reduced, and side effects of near-infrared treatment are further reduced.