304 results about "Brain tissue" patented technology

The invention relates to the technical field of medical monitoring and early warning, and discloses a postoperative care risk early warning system for neurosurgical patients. According to the system, real-time monitoring flows of electroencephalogram, intracranial pressure and body surface myoelectricity of a patient are continuously received, and a dynamic interaction network of neuroelectrophysiology and intracranial mechanical states is constructed so as to represent the coupling relation among electroencephalogram rhythm, pressure conduction and postoperative skull windowing area tissue compliance. The system analyzes three types of core parameters of cerebral cortex excitability, cerebrospinal fluid circulation load and cranial cavity compensation space from the network, further calculates a brain tissue perfusion risk and a neural structure compression risk, and generates a corresponding nursing early warning signal and a physiological regulation path. According to the scheme, deep coupling and mechanism risk early warning of multiple physiological signals are achieved, and the postoperative complication risk can be recognized earlier and more accurately.

A neurosurgery system for probing brain tissue of a patient for tumorous tissue. The system including a suction tool, an excitation source, an optical instrument, and a controller. The suction tool including a suction cannula defining a lumen, an optical fiber configured to transmit fluorescence emitted by the brain tissue; and an indicator configured to selectively emit visible light. An excitation source is configured to emit an excitation light having a wavelength to induce the fluorescence in the tumorous tissue. The optical instrument is coupled to the optical fiber. The optical instrument configured to convert the fluorescence emitted by the brain tissue and transmitted by the optical and configured to determine that the brain tissue is tumorous based on the electrical signal and activate the indicator based on the determination.

The invention discloses a brain-computer interface signal enhancement and evaluation method fusing physical information. The method comprises the following steps: firstly, based on an individual structure magnetic resonance image, constructing a personalized six-layer brain tissue anatomical model comprising a cortex, a white matter, cerebrospinal fluid, a dura mater, a skull and a scalp, and endowing differentiated conductivity parameters; secondly, neuroelectrophysiology priori knowledge such as neurodynamics and white matter anisotropic conduction is converted into a representation rule which can be learned by a neural network; then, the rules are systematically embedded into a physical information neural network in a differentiable physical constraint form, including a cortical neurodynamic equation residual error, a volume conduction equation residual error of each layer and an interlayer interface continuity constraint; and finally, training a network by using the scalp electroencephalogram signals, and jointly outputting high-fidelity intracranial electroencephalogram signals and multi-modal neurophysiological information by minimizing a loss function containing reconstruction and physical constraints. According to the method, the fidelity, the physical rationality and the clinical interpretability of signal enhancement are effectively improved.

The invention provides a multi-modal image fusion system and method for neurosurgery, and the method comprises the steps: carrying out the rigid transformation of a multi-modal magnetic resonance image and an ultrasonic image, and obtaining a preoperative magnetic resonance image and an intraoperative ultrasonic image after preliminary alignment; inputting the preoperative magnetic resonance image and the intraoperative ultrasonic image into a pre-trained lightweight deformation registration network for deformation modeling to obtain a voxel-level dense deformation field, and determining a confidence map of deformation field region registration based on the dense deformation field; according to the confidence map, multi-scale feature fusion based on confidence weighting is carried out on the deformed preoperative multi-modal labeling information and the corresponding features of the intra-operative ultrasonic image, and a three-dimensional anatomical structure chart for real-time navigation in the neurosurgery operation is obtained. Based on the scheme, brain tissue drift can be dynamically compensated in real time in a neurosurgery operation, and multi-modal image fusion is guided based on a compensation result.

The present disclosure proposes a method for monitoring simultaneously vascular activity in at least one region of a brain, of a human or animal, and the temporal evolution of physiological parameters, the method including generating a sequence of Doppler or Ultrasound Localization Microscopy "ULM" images of said brain with an ultrasound probe and simultaneously computing physiological information based on a temporal series of brain tissue motion data in a selected region of interest of the brain.

The invention relates to the technical field of brain science image processing, and discloses a brain tissue neuronal morphology three-dimensional reconstruction and connection group analysis method and system, and the method comprises the steps: carrying out the feature point extraction and matching and optical flow registration of continuous ultrathin section electron microscope images, and obtaining three-dimensional image volume data; carrying out semantic segmentation on cell bodies, dendrites, axons and dendritic spines through a three-dimensional deep convolutional neural network, and driving secondary registration through confidence feedback; detecting synapses and classifying the synapses as excitatory or inhibitory types; executing topology perception skeletonized reconstruction and performing segmentation correction through topology anomaly feedback constraint; and constructing a synaptic connection matrix and executing graph theory analysis.

The invention relates to the technical field of neurotrauma prognosis image analysis, and discloses a craniocerebral trauma prognosis prediction analysis system based on a three-dimensional model. According to the system, multi-scale segmentation and topology construction are carried out on a craniocerebral three-dimensional image of a patient, the morphological evolution rate of a trauma area is tracked, and key signal events in the trauma evolution process are accurately recognized in combination with an edema signal change curve. The system further quantitatively analyzes dynamic deviations associated with the integrity of normal brain tissue fiber bundles when a signal event occurs, thereby generating a lesion propagation path and mapping it to functional network nodes of a standard brain map, ultimately identifying a prognostic key brain network. According to the technical scheme, key event capture and path foresight prediction in the dynamic propagation process of the secondary injury after the craniocerebral trauma are realized, and the accuracy of prognosis evaluation is improved.

The invention provides a pharmaceutical composition containing polypeptide and application of the pharmaceutical composition to preparation of a medicine for preventing and treating Parkinson's disease, and belongs to the technical field of polypeptide and biology. The amino acid sequence of the polypeptide is PCVLYDLREKM, the damage of 6-OHDA induced BZ555 nematode dopaminergic neurons can be obviously relieved, mouse dyskinesia caused by a Parkinson's disease model can be obviously improved, the spontaneous standing frequency can be improved, the movement speed in an open field can be increased, and meanwhile the IL-1beta and IL-18 levels caused by the mouse Parkinson's disease model can be reduced; the polypeptide provided by the invention can significantly reduce MAO-B level while significantly increasing DA level in nigra of brain tissues of rats with Parkinson's disease, which prompts that the polypeptide provided by the invention has a significant therapeutic effect on Parkinson's disease, and has a wide market prospect in many fields such as health food and medicine.

The disclosure relates to compositions, methods, and processes for the preparation, use, and / or formulation of adeno-associated virus capsid proteins, wherein the capsid proteins comprise targeting peptide inserts for enhanced tropism to a target tissue.

The invention discloses application of an NR1D1 protein phosphorylation site in preparation of cerebral hemorrhage treatment drugs, and belongs to the technical field of molecular biology. According to the invention, the specific phosphorylation site and phosphorylation modification level of the NR1D1 protein are determined for the first time, and the NR1D1 protein can be used as a key marker for evaluating the secondary nerve injury degree of the hemorrhagic cerebral apoplexy and developing treatment and / or alleviation of the hemorrhagic cerebral apoplexy; a specific antigen peptide and an antibody for accurately detecting the NR1D1 protein phosphorylation site are further constructed, and an efficient tool is provided for molecular evaluation of hemorrhagic stroke secondary nerve injury; meanwhile, polypeptide molecules capable of inhibiting NR1D1 protein phosphorylation are researched and developed, through the dual effects of specifically blocking the phosphorylation process and reducing protein degradation, necrosis of brain tissues around hematoma after hemorrhagic cerebral apoplexy is relieved, secondary dyskinesia is improved, and the effect of inhibiting NR1D1 protein phosphorylation is achieved. And a brand new scheme is provided for molecular evaluation and targeted intervention of hemorrhagic stroke secondary nerve injury.

The invention discloses a brain age prediction method, system and device and a medium, and relates to the technical field of biomedical image analys.The method comprises the steps that firstly, precise local detail features representing the cerebral cortex and brain tissue are precisely captured, then the dependency relationship between local areas of different images is obtained based on a windowed multi-head self-attention mechanism, and the brain age prediction result is obtained; a channel attention mechanism is introduced, importance weights of different feature channels are learned, and the importance weights are applied to feature fusion, so that long-distance dependency relationships and fine structure features are accurately captured; and then based on a cross attention mechanism, guiding global detail features to focus on a region with rich local features and guiding the local detail features to focus on a most relevant local region so as to mine deeper detail features, and finally dynamically adjusting the contribution proportion of the local detail features and global context detail features in a final decision. And the features are fused into final features so as to perceive local detail features and global detail features in a deeper level.

This utility model relates to an innovation of a carotid artery vasodilator that can be used at home and in the emergency room as a supplement to drug treatment for conditions such as carotid artery obstruction in the neck region. It increases the production of nitric oxide mediated by endothelial nitric oxide synthase in the intact endothelial layer of the carotid artery, which is located on the inner surface of the neck brace. It can be applied for a certain period of time for each patient. The intermittent or continuous operation function can be selected through an adjustable power circuit. It only affects the lesion area and does not affect the patient's peripheral blood vessels. It can be used in situations where nitrates may be prohibited. It prevents the reduction of blood flow to the brain tissue that may occur due to jugular venous constriction. The flexible structure of the applicator neck brace (9) can be maintained in the application area for a long time and includes a pulsed magnetic field (PMF).

The present application relates to the technical field of medical auxiliary equipment, in particular to a neurosurgery operation retractor device, which comprises a central adjusting seat, the side wall of the central adjusting seat is symmetrically hinged with retraction arms, the end of the retraction arms away from the central adjusting seat is hinged with a retraction plate, the side wall of the central adjusting seat is hinged with a plurality of rhombic telescopic frames, the end of the rhombic telescopic frames away from the central adjusting seat is hinged with the retraction arms, the central adjusting seat is further provided with an adapter disc, and a multi-modal fixed base is detachably connected to the adapter disc; a transmission mechanism is installed in the central adjusting seat, a pressure sensor for collecting the tension of brain tissue is installed on the transmission mechanism, a control module is signal-connected with the pressure sensor, the control module is signal-connected with the rhombic telescopic frames, the adapter disc and the transmission mechanism, and the control module is signal-connected with an electromagnetic locker for locking the rhombic telescopic frames and the transmission mechanism. The present application effectively reduces the risk of brain tissue pulling injury, frees the hands of medical staff, and simplifies the operation process.

The invention belongs to the technical field of biological medicines, and discloses a cationic polymer targeted nano material modified siRNA (small interfering ribonucleic acid) nano-drug and application thereof. The siRNA nano-drug disclosed by the invention has the capability of effectively penetrating through the blood brain barrier and improving the brain tissue distribution of the siRNA drug.

Embodiments of the present application provide a whole brain and whole spinal cord automatic delineation method and device, electronic equipment and medium, the method comprises: acquiring a CT image, segmenting the CT image according to a first adaptive threshold to obtain a human body contour region of interest, segmenting the human body contour region of interest according to a second adaptive threshold to obtain a human body skeleton contour region of interest, performing inflation operation and corrosion operation on the human body skeleton contour region of interest to obtain a brain tissue region of interest, performing inflation translation superposition subtraction processing and corrosion operation on the human body skeleton contour region of interest to obtain a spinal cord target contour, and combining the brain tissue region of interest and the spinal cord target contour to obtain a whole brain and whole spinal cord region of interest. By using the method, the whole brain and whole spinal cord region of interest can be automatically, quickly and accurately delineated, which greatly helps image analysis, accurate treatment and reduction of the workload of clinicians for patients.

The invention provides a depression detection method, system and equipment based on a multi-modal brain image and a medium. The method comprises the following steps: acquiring a functional magnetic resonance image and a structural magnetic resonance image of the brain of a subject; performing collaborative analysis on the time sequence change information of the functional magnetic resonance image and the spatial relationship of the brain region, and extracting brain function characteristics representing brain function activity characteristics from the functional magnetic resonance image; carrying out collaborative analysis on voxel distribution and regional hierarchical relationship in the structural magnetic resonance image, and extracting brain structure features representing brain tissue morphology from the structural magnetic resonance image; inputting the brain function features and the brain structure features into a cross-modal interaction module, and performing cross-modal feature fusion on the brain function features and the brain structure features to generate cross-modal brain features; and inputting the cross-modal brain features into a classification module to obtain a depression detection result of the subject. According to the invention, the depression identification precision can be greatly improved.

The invention relates to the technical field of traditional Chinese medicine compositions, in particular to a traditional Chinese medicine composition and application of the traditional Chinese medicine composition in preparation of drugs for improving sleep disorder and treating mood disorder or cognitive disorder. The invention provides a traditional Chinese medicine composition. The traditional Chinese medicine composition comprises the following components in parts by mass: 20-30 parts of lycium ruthenicum, 30-40 parts of nitraria fruit, 15-25 parts of gastrodia elata, 13-25 parts of hyperforin perforatum and 2-6 parts of lycopene. The traditional Chinese medicine composition provided by the invention is prepared from lycium ruthenicum, nitraria fruit, gastrodia elata, hyperforin perforatum and lycopene according to a specific ratio, and the composition can effectively relieve anxiety behaviors of chronic stress bound anxiety model mice through ways of resisting oxidation and inflammation, regulating expression of neurotransmitters and the like, prolong sleep time and improve sleep quality. The learning ability and the memory ability of cognitive impairment mice induced by scopolamine are improved, and the neuron density of brain tissues is increased, so that the neuroprotective effect is achieved.

The invention belongs to the technical field of drug detection, and particularly relates to a method for detecting lycium barbarum glycopeptide metabolites in rat plasma and tissues based on non-targeted metabonomics. According to the method, after rat lycium barbarum glycopeptides are administered through intragastric administration, blood, liver, intestine, lung and brain tissue samples after administration are collected. A UPLC-Q-TOF-MS (Ultra Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry) analysis method is combined with a statistical analysis method comprising principal component analysis (PCA) and orthogonal-partial least squares discriminant analysis (OPLS-DA) to carry out in-vivo metabonomics analysis on the wolfberry glycopeptide. Then, based on a human metabolome database (HMDB), lycium barbarum glycopeptide differential metabolite is searched, so that the pharmacological action mechanism of the lycium barbarum glycopeptide is clarified from the perspective of metabolism, and a foundation is laid for deep research and development of the medicinal value of the lycium barbarum glycopeptide in future.

Disclosed is a marking composition comprising a marker and a hydrogel. Disclosed is a process of forming a marking composition comprising mixing a marker and a hydrogel. Disclosed is an article comprising a marker, a hydrogel, and an implement. Disclosed is a kit comprising a marker, a hydrogel, and an implement, wherein the marker and hydrogel are combined. Disclosed is a method for marking a portion of the brain in a mammal comprising: (a) removing a portion of a mammal's skull to expose a portion of the brain matter; and (b) contacting the exposed portion of the brain with a marking composition. Disclosed is a method for recording electrical activity in a brain, comprising: (a) removing a portion of the skull, thereby exposing a portion of a brain; (b) inserting an electrode into the brain; and (c) recording electrical activity via the electrode, wherein the electrode is at least partially coated with a marking composition.

The invention provides an intelligent delirium evaluation system for an intensive care unit, which solves the subjective limitation of a traditional delirium evaluation dependency scale through multi-modal data acquisition and mathematical model quantitative calculation, and specifically, acquires key data such as a brain tissue oxygenation index, a serum albumin concentration and a total plasma concentration in real time to obtain a delirium evaluation result. Through models such as a blood-brain barrier penetration coefficient and a free drug score, accurately calculating a core index of effective brain concentration, and dynamically adjusting an early warning threshold and a limb movement frequency in combination with ambient light intensity to divide risk levels; in the whole evaluation process, quantitative logic is constructed based on a pathophysiological mechanism, subjective judgment deviation of medical staff is avoided, and the problem of delirium intervention lag caused by missed judgment and misjudgment is effectively reduced.

The invention discloses a method for training a detection model for cerebrovascular occlusion detection and a related product. The method comprises the following steps: performing deboning operation based on CT perfusion imaging data to obtain target image data containing brain tissues and blood vessels; performing vascular occlusion region labeling on the target image data to obtain a three-dimensional occlusion region label; extracting a blood flow arrival time graph based on the CT perfusion imaging data; based on the target image data and the blood flow arrival time graph, extracting a blood vessel region feature volume after weighted fusion under blood flow arrival time gating; inputting the blood vessel region characteristic volume into the detection model to carry out cerebrovascular occlusion detection; and calculating a loss function based on the three-dimensional occlusion region label so as to train the detection model for cerebrovascular occlusion detection. By using the scheme of the invention, the accuracy, robustness and clinical applicability of occlusion detection can be improved.

A probe for insertion into a brain tissue includes a tubular body having an inner lumen and at least two carbon fiber electrode threads (CFETs) extending through the inner lumen of the tubular body. Each CFET includes a carbon fiber having a proximal portion and a distal portion. The proximal portion of the carbon fiber is coated with a polymer. The distal portion of the carbon fiber is exposed to allow direct contact with the brain tissue. The carbon fiber of each CFET has an aspect ratio between 100 and 1500.

The present application provides a kind of potassium channel regulator, its preparation method, pharmaceutical composition and application. Specifically provided are compounds as shown in formula V or pharmaceutically acceptable salts thereof. The potassium channel regulator compound of the present application has one or more of the following effect advantages: (1) novel structure; (2) good KCNQ2 / 3 channel opening activity; (3) weak KCNQ4, KCNQ5 opening activity, high KCNQ2 / 3 selectivity; (4) good in vivo efficacy, good protection effect on seizures; (5) low neuro-motor toxicity; (6) high brain-blood ratio; (7) high plasma, brain tissue concentration.

A stimulation electric field display method, an apparatus, an electronic device, and a storage medium. The method comprises: in response to a model display operation, determining a target object and a brain tissue image model corresponding to the target object, wherein the brain tissue image model comprises at least one electrode model for deep brain stimulation (S110); in response to an electrode configuration operation, determining electrode configuration information and stimulation parameter application information of each electrode model (S120); and in response to an electric field display operation, determining program-controlled electric field information of the at least one electrode model under the electrode configuration information and the stimulation parameter application information, and displaying the program-controlled electric field information on the displayed brain tissue image model (S130).

A method for separately quantifying N-acetylcysteine and glutathione in brain tissue includes administering N-acetylcysteine to a subject, acquiring a first magnetic resonance spectroscopy signal from a region of brain tissue of the subject, the first magnetic resonance spectroscopy signal comprising a cysteine β-proton signal, acquiring a second magnetic resonance spectroscopy signal from the region of brain tissue, the second magnetic resonance spectroscopy signal comprising an N-acetyl proton signal, and determining a concentration of N-acetylcysteine in the region of brain tissue based on the N-acetyl proton signal and determining a concentration of glutathione in the region of brain tissue based on a difference between the cysteine β-proton signal and the N-acetyl proton signal.

This invention discloses a conductive hydrogel neural probe and its preparation method. The conductive hydrogel neural probe includes: a light guide core, which is a hydrogel formed by a photoinitiator, a water-soluble double-bonded olefin monomer, and a first crosslinking agent; a light guide shell, which wraps around the surface of the light guide core; the light guide shell is a transparent plastic tube or silicone tube; a conductive layer, which is solidified on the surface of the light guide shell; the conductive layer is a hydrogel formed by a photoinitiator, a conductive polymer, and a second crosslinking agent; and an insulating layer, which is solidified on the surface of the conductive layer. It features excellent light guiding performance (light transmission loss <0.5dB / cm); good conductivity based on the conductive polymer hydrogel, and long-term stability of conductivity; and matched tissue mechanical properties (flexural stiffness <10N / m within the physiological activity frequency range of 0.1-10Hz) ensuring long-term stability of light guiding and conductivity after implantation into brain tissue.

The application belongs to the field of food processing and biomedical technology, and discloses a preparation method of a salty taste enhancing peptide-naringenin compound and application of the compound in improving cognitive decline. The compound is prepared by compounding salty taste enhancing peptides from soft-shelled turtle eggs and naringenin at a ratio of 20-150:1 (w:w). The preparation process comprises the following steps: soft-shelled turtle egg enzymolysis, ultrafiltration, freeze-drying to obtain salty taste enhancing peptides, mixing the salty taste enhancing peptides with a naringenin solution, concentration, and freeze-drying. The compound has good stability, salty taste enhancing and antioxidant activities, can reduce the use of salt and maintain salty taste. The compound can improve cognitive decline and anxiety caused by aging and diabetes, improve autonomous activity, memory and social skills, strengthen physical fitness, protect nerve cells and skeletal muscles, maintain brain tissue health, and can be applied to the preparation of related preparations for improving cognitive decline.

This invention discloses a method and system for evaluating the effectiveness of photostimulation based on multimodal feature fusion, belonging to the field of big data analysis technology. The method and system include the following steps: S1, acquiring raw observation data and performing time axis relocation, dynamic denoising, normalization, and sliding time window segmentation; S2, evaluating the state of the stimulation process and selecting effective windows; S3, extracting neural activity response features and hemodynamic response features, and performing physiological response reliability assessment; S4, performing consistency fusion to evaluate the effectiveness of photostimulation. This invention effectively improves the stability and reliability of effectiveness evaluation during head-mounted photostimulation, solving the problems of difficulty in distinguishing between abnormal stimulation pathways and true brain tissue responses, as well as insufficient consistency of results across batches of experiments.

The invention discloses a three-dimensional surgical risk model reconstruction method based on brain anatomy and a functional atlas, and the method comprises the steps: S1, carrying out the image processing and fine segmentation of a brain MRI image or a DICOM sequence image of a patient, and recognizing a plurality of anatomical structures; s2, establishing a multi-dimensional risk assessment model, and performing quantitative scoring on each brain region from four dimensions of functional importance, structural vulnerability, recovery potential and clinical significance; s3, constructing a continuous three-dimensional risk field based on the risk score, and realizing the propagation of the risk value in the brain tissue based on a Gaussian diffusion model; and S4, based on an improved path planning algorithm, searching an optimal operation path in the three-dimensional risk field to realize risk minimization. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium.

The application discloses a kind of based on brain structure image's hepatic encephalopathy evaluation method and system, the method includes: obtaining the brain structure image data of subject brain;Based on brain structure image data, the feature parameter of characterizing brain tissue morphology is extracted;The characteristic parameter is handled by pre-training disease progression evaluation model, and the space-time progression trajectory of brain structure abnormality is inferred;Based on space-time progression trajectory, the disease subtype and disease progression stage to which the subject belongs are determined;Based on disease subtype and disease progression stage, evaluation information for characterizing the disease state of hepatic encephalopathy is generated.The space-time progression trajectory of brain structure abnormality is inferred based on cross-sectional image data, which overcomes the dependence on massive longitudinal tracking data, realizes the objective typing and staging of hepatic encephalopathy based on neurobiology, thereby effectively solving the technical problems of difficult to track disease evolution and individualized evaluation.