Experimental and numerical study of hypervelocity impact damage on composite overwrapped pressure vessels

Ground-based tests are important for studying hypervelocity impact(HVI)damage to spacecraft pressure vessels in the orbital debris environment.We analyzed the damage to composite overwrapped pressure vessels(COPVs)in the HVI tests and classified the damage into non-catastrophic damage and catastrophic damage.We proposed a numerical simulation method to further study non-catastrophic damage and revealed the characteristics and mechanisms of non-catastrophic damage affected by impact conditions and internal pressures.The fragments of the catastrophically damaged COPVs were collected after the tests.The crack distribution and propagation process of the catastrophic ruptures of the COPVs were analyzed.Our findings contribute to understanding the damage characteristics and mechanisms of COPVs by HVIs.

Predictive visual field outcomes after optic chiasm decompressive surgery by retinal vessels parameters using optical coherence tomography angiography

AIM:To evaluate the predictive value of superficial retinal capillary plexus(SRCP)and radial peripapillary capillary(RPC)for visual field recovery after optic cross decompression and compare them with peripapillary nerve fiber layer(pRNFL)and ganglion cell complex(GCC).METHODS:This prospective longitudinal observational study included patients with chiasmal compression due to sellar region mass scheduled for decompressive surgery.Generalized estimating equations were used to compare retinal vessel density and retinal layer thickness preand post-operatively and with healthy controls.Logistic regression models were used to assess the relationship between preoperative GCC,pRNFL,SRCP,and RPC parameters and visual field recovery after surgery.RESULTS:The study included 43 eyes of 24 patients and 48 eyes of 24 healthy controls.Preoperative RPC and SRCP vessel density and pRNFL and GCC thickness were lower than healthy controls and higher than postoperative values.The best predictive GCC and pRNFL models were based on the superior GCC[area under the curve(AUC)=0.866]and the tempo-inferior pRNFL(AUC=0.824),and the best predictive SRCP and RPC models were based on the nasal SRCP(AUC=0.718)and tempo-inferior RPC(AUC=0.825).There was no statistical difference in the predictive value of the superior GCC,tempo-inferior pRNFL,and tempo-inferior RPC(all P>0.05).CONCLUSION:Compression of the optic chiasm by tumors in the saddle area can reduce retinal thickness and blood perfusion.This reduction persists despite the recovery of the visual field after decompression surgery.GCC,pRNFL,and RPC can be used as sensitive predictors of visual field recovery after decompression surgery.

Nomogram prediction of vessels encapsulating tumor clusters in small hepatocellular carcinoma≤3 cm based on enhanced magnetic resonance imaging

BACKGROUND Vessels encapsulating tumor clusters(VETC)represent a recently discovered vascular pattern associated with novel metastasis mechanisms in hepatocellular carcinoma(HCC).However,it seems that no one have focused on predicting VETC status in small HCC(sHCC).This study aimed to develop a new nomogram for predicting VETC positivity using preoperative clinical data and image features in sHCC(≤3 cm)patients.AIM To construct a nomogram that combines preoperative clinical parameters and image features to predict patterns of VETC and evaluate the prognosis of sHCC patients.METHODS A total of 309 patients with sHCC,who underwent segmental resection and had their VETC status confirmed,were included in the study.These patients were recruited from three different hospitals:Hospital 1 contributed 177 patients for the training set,Hospital 2 provided 78 patients for the test set,and Hospital 3 provided 54 patients for the validation set.Independent predictors of VETC were identified through univariate and multivariate logistic analyses.These independent predictors were then used to construct a VETC prediction model for sHCC.The model’s performance was evaluated using the area under the curve(AUC),calibration curve,and clinical decision curve.Additionally,Kaplan-Meier survival analysis was performed to confirm whether the predicted VETC status by the model is associated with early recurrence,just as it is with the actual VETC status and early recurrence.RESULTS Alpha-fetoprotein_lg10,carbohydrate antigen 199,irregular shape,non-smooth margin,and arterial peritumoral enhancement were identified as independent predictors of VETC.The model incorporating these predictors demonstrated strong predictive performance.The AUC was 0.811 for the training set,0.800 for the test set,and 0.791 for the validation set.The calibration curve indicated that the predicted probability was consistent with the actual VETC status in all three sets.Furthermore,the decision curve analysis demonstrated the clinical benefits of our model for patients with sHCC.Finally,early recurrence was more likely to occur in the VETC-positive group compared to the VETC-negative group,regardless of whether considering the actual or predicted VETC status.CONCLUSION Our novel prediction model demonstrates strong performance in predicting VETC positivity in sHCC(≤3 cm)patients,and it holds potential for predicting early recurrence.This model equips clinicians with valuable information to make informed clinical treatment decisions.

Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma:Machine learning model based on contrast-enhanced computed tomography

BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner,and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma(HCC).AIM To develop and validate a preoperative nomogram using contrast-enhanced computed tomography(CECT)to predict the presence of VETC+in HCC.METHODS We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers.Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase.Radiomics features,essential for identifying VETC+HCC,were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set.The model’s performance was validated on two separate test sets.Receiver operating characteristic(ROC)analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets.The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features.ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features,the radiomics features and the radiomics nomogram.RESULTS The study included 190 individuals from two independent centers,with the majority being male(81%)and a median age of 57 years(interquartile range:51-66).The area under the curve(AUC)for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825,0.788,and 0.680 in the training set and the two test sets.A total of 13 features were selected to construct the Rad-score.The nomogram,combining clinicalradiological and combined radiomics features could accurately predict VETC+in all three sets,with AUC values of 0.859,0.848 and 0.757.Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.CONCLUSION This study demonstrates the potential utility of a CECT-based radiomics nomogram,incorporating clinicalradiological features and combined radiomics features,in the identification of VETC+HCC.

Reduction of photodynamic damage of blood vessels in the protected region by(–)-epigallocatechin gallate

Photodynamic therapy(PDT)has been increasingly used in the clinical treatment of neoplastic,inflammatory and infectious skin diseases.However,the generation of reactive oxygen species(ROS)may induce undesired side effects in normal tissue surrounding the treatment lesion,which is a big challenge for the clinical application of PDT.To date,(–)-Epigallocatechin gallate(EGCG)has been widely proposed as an antiangiogenic and antitumor agent for the protection of normal tissue from ROS-mediated oxidative damage.This study evaluates the regulation ability of EGCG for photodynamic damage of blood vessels during hematoporphyrin monomethyl ether(Hemoporfin)-mediated PDT.The quenching rate constants of EGCG for the triplet-state Hemoporfin and photosensitized 1O2 generation are determined to be 6.8×10^(8)M^(−1)S^(−1),respectively.The vasoconstriction of blood vessels in the protected region treated with EGCG hydrogel after PDT is lower than that of the control region treated with pure hydrogel,suggesting an efficiently reduced photodamage of Hemoporfin for blood vessels treated with EGCG.This study indicates that EGCG is an efficient quencher for triplet-state Hemoporfin and 1O2,and EGCG could be potentially used to reduce the undesired photodamage of normal tissue in clinical PDT.

Exploration on the Optimization Strategy for the Layup of Composite Material Pressure Vessels Based on Advanced Algorithms

This study aims to explore the influence of the laying angle on the pressure shell structure made of composite materials under the condition of a fixed shape. By using a composite material composed of a mixture of T800 carbon fiber and AG80 epoxy resin to design pressure vessels, this material combination can significantly improve the interlaminar shear strength and heat resistance. The article elaborates on the basic concepts and failure criteria of composite materials, such as the maximum stress criterion, the maximum strain criterion, the Tsai-Hill criterion, etc. With the help of the APDL parametric modeling language, the arc-shaped, parabolic, elliptical, and fitting curve-shaped pressure vessel models are accurately constructed, and the material property settings and mesh division are completed. Subsequently, APDL is used for static analysis, and the genetic algorithm toolbox built into Matlab is combined to carry out optimization calculations to determine the optimal laying angle. The research results show that the equivalent stress corresponding to the optimal laying angle of the arc-shaped pressure vessel is 5.3685e+08 Pa, the elliptical one is 5.1969e+08 Pa, the parabolic one is 5.8692e+08 Pa, and the fitting curve-shaped one is 5.36862e+08 Pa. Among them, the stress distribution of the fitting curve-shaped pressure vessel is relatively more uniform, with a deformation of 0.568E−03 m, a minimum equivalent stress value of 0.261E+09 Pa, a maximum equivalent stress value of 0.537E+09 Pa, and a ratio of 0.48, which conforms to the equivalent stress criterion. In addition, the fitting curve of this model can adapt to various models and has higher practical value. However, the stress distribution of the elliptical and parabolic pressure vessels is uneven, and their applicability is poor. In the future, further exploration can be conducted on the application of the fitting curve model in composite materials to optimize the design of pressure vessels. This study provides important theoretical support and practical guidance for the design of composite material pressure vessels.

Automated Segmentation of the Brainstem,Cranial Nerves and Vessels for Trigeminal Neuralgia and Hemifacial Spasm

Accurate localization of cranial nerves and responsible blood vessels is important for diagnosing trigeminal neuralgia(TN)and hemifacial spasm(HFS).Manual delineation of the nerves and vessels on medical images is time-consuming and labor-intensive.Due to the development of convolutional neural networks(CNNs),the performance of medical image segmentation has been improved.In this work,we investigate the plans for automated segmentation of cranial nerves and responsible vessels for TN and HFS,which has not been comprehensively studied before.Different inputs are given to the CNN to find the best training configuration of segmenting trigeminal nerves,facial nerves,responsible vessels and brainstem,including the image modality and the number of segmentation targets.According to multiple experiments with seven training plans,we suggest training with the combination of three-dimensional fast imaging employing steady-state acquisition(3D-FIESTA)and three-dimensional time-of-flight magnetic resonance angiography(3DTOF-MRA),and separate segmentation of cranial nerves and vessels.

Evaluation of optic nerve head vessels density changes after phacoemulsification cataract surgery using optical coherence tomography angiography

·AIM:To evaluate optic nerve head(ONH)vessel density(VD)changes after cataract surgery using optical coherence tomography angiography(OCTA).·METHODS:This was a prospective observational study.Thirty-four eyes with mild/moderate cataracts were included.ONH scans were obtained before and 3mo after cataract surgery using OCTA.Radial peripapillary capillary(RPC)density,all VD,large VD and retinal nerve fiber layer thickness(RNFLT)in total disc,inside disc,and different peripapillary sectors were assessed and analyzed.Image quality score(QS),fundus photography grading and bestcorrected visual acuity(BCVA)were also collected,and correlation analyses were performed between VD change and these parameters.·RESULTS:Compared with baseline,both RPC and all VD increased in inside disc area 3mo postoperatively(from 47.5%±5.3%to 50.2%±3.7%,and from 57.87%±4.30%to 60.47%±3.10%,all P<0.001),but no differences were observed in peripapillary area.However,large VD increased from 5.63%±0.77%to 6.47%±0.72%in peripapillary ONH region(P<0.001).RPC decreased in inferior and superior peripapillary ONH parts(P=0.019,<0.001 respectively).There were obvious negative correlations between RPC change and large VD change in inside disc,superior-hemi,and inferior-hemi(r=-0.419,-0.370,and-0.439,P=0.017,0.044,and 0.015,respectively).No correlations were found between VD change and other parameters including QS change,fundus photography grading,postoperative BCVA,and postoperative peripapillary RNFLT.·CONCLUSION:RPC density and all VD in the inside disc ONH region increase 3mo after surgery in patients with mild to moderate cataract.No obvious VD changes are found in peripapillary area postoperatively.

“Parenchyma transection-first”strategy is superior to“tunnel-first”strategy in robotic spleen-preserving distal pancreatectomy with conservation of splenic vessels

Background: Creating a tunnel between the pancreas and splenic vessels followed by pancreatic parenchyma transection(“tunnel-first” strategy) has long been used in spleen-preserving distal pancreatectomy(SPDP) with splenic vessel preservation(Kimura’s procedure). However, the operation space is limited in the tunnel, leading to the risks of bleeding and difficulties in suturing. We adopted the pancreatic “parenchyma transection-first” strategy to optimize Kimura’s procedure. Methods: The clinical data of consecutive patients who underwent robotic SPDP with Kimura’s procedure between January 2017 and September 2022 at our center were retrieved. The cohort was classified into a “parenchyma transection-first” strategy(P-F) group and a “tunnel-first” strategy(T-F) group and analyzed. Results: A total of 91 patients were enrolled in this cohort, with 49 in the T-F group and 42 in the P-F group. Compared with the T-F group, the P-F group had significantly shorter operative time(146.1 ± 39.2 min vs. 174.9 ± 46.6 min, P < 0.01) and lower estimated blood loss [40.0(20.0–55.0) m L vs. 50.0(20.0–100.0) m L, P = 0.03]. Failure of splenic vessel preservation occurred in 10.2% patients in the TF group and 2.4% in the P-F group( P = 0.14). The grade 3/4 complications were similar between the two groups( P = 0.57). No differences in postoperative pancreatic fistula, abdominal infection or hemorrhage were observed between the two groups. Conclusions: The pancreatic “parenchyma transection-first” strategy is safe and feasible compared with traditional “tunnel-first strategy” in SPDP with Kimura’s procedure.

Construction of Oriented Structure in Inner Surface of Small-Diameter Artificial Blood Vessels:A Review

There is an urgent need for small-diameter artificial blood vessels in clinic.Physical,chemical and biological factors should be integrated to avoid thrombosis and intimal hyperplasia after implantation and to promote successful fabrication of small-diameter artificial blood vessels.From a physical perspective,the internal oriented structures of natural blood vessels plays an important role in guiding the directional growth of cells,improving the blood flow environment,and promoting the regeneration of vascular tissue.In this review,the effects of the oriented structures on cells,including endothelial cells(ECs),smooth muscle cells(SMCs)and stem cells,as well as the effect of the oriented structures on hemodynamics and vascular tissue remodeling and regeneration are introduced.Various forms of oriented structures(fibers,grooves,channels,etc.)and their construction methods are also reviewed.Conclusions and future perspectives are given.It is expected to give some references to relevant researches.

Blood-brain barrier pathology in cerebral small vessel disease

Cerebral small vessel disease is a neurological disease that affects the brain microvasculature and which is commonly observed among the elderly.Although at first it was considered innocuous,small vessel disease is nowadays regarded as one of the major vascular causes of dementia.Radiological signs of small vessel disease include small subcortical infarcts,white matter magnetic resonance imaging hyperintensities,lacunes,enlarged perivascular spaces,cerebral microbleeds,and brain atrophy;however,great heterogeneity in clinical symptoms is observed in small vessel disease patients.The pathophysiology of these lesions has been linked to multiple processes,such as hypoperfusion,defective cerebrovascular reactivity,and blood-brain barrier dysfunction.Notably,studies on small vessel disease suggest that blood-brain barrier dysfunction is among the earliest mechanisms in small vessel disease and might contribute to the development of the hallmarks of small vessel disease.Therefore,the purpose of this review is to provide a new foundation in the study of small vessel disease pathology.First,we discuss the main structural domains and functions of the blood-brain barrier.Secondly,we review the most recent evidence on blood-brain barrier dysfunction linked to small vessel disease.Finally,we conclude with a discussion on future perspectives and propose potential treatment targets and interventions.

Cognitive impairment in cerebral small vessel disease induced by hypertension

Hypertension is a primary risk factor for the progression of cognitive impairment caused by cerebral small vessel disease,the most common cerebrovascular disease.Howeve r,the causal relationship between hypertension and cerebral small vessel disease remains unclear.Hypertension has substantial negative impacts on brain health and is recognized as a risk factor for cerebrovascular disease.Chronic hypertension and lifestyle factors are associated with risks for stro ke and dementia,and cerebral small vessel disease can cause dementia and stroke.Hypertension is the main driver of cerebral small vessel disease,which changes the structure and function of cerebral vessels via various mechanisms and leads to lacunar infarction,leukoaraiosis,white matter lesions,and intracerebral hemorrhage,ultimately res ulting in cognitive decline and demonstrating that the brain is the to rget organ of hypertension.This review updates our understanding of the pathogenesis of hypertensioninduced cerebral small vessel disease and the res ulting changes in brain structure and function and declines in cognitive ability.We also discuss drugs to treat cerebral small vessel disease and cognitive impairment.

Three-dimensional structure of liver vessels and spatial distribution of hepatic immune cells

As the largest internal organ of the human body,the liver has an extremely complex vascularnetwork and multiple types of immune cells.It plays an important role in blood circulation,material metabolism,and immune response.Optical imaging is an effective tool for studying finevascular structure and immunocyte distribution of the liver.Here,we provide an overview of thestructure and composition of liver vessels,the threedimensional(3D)imaging of the liver,andthe spatial distribution and immune function of various cell components of the liver.Especially,we emphasize the 3D imaging methods for visualizing fine structure in the liver.Finally,wesummarize and prospect the development of 3D imaging of liver vesels and immune cells.

Event-triggered model-free adaptive control for a class of surface vessels with time-delay and external disturbance via state observer

This paper provides an improved model-free adaptive control(IMFAC)strategy for solving the surface vessel trajectory tracking issue with time delay and restricted disturbance.Firstly,the original nonlinear time-delay system is transformed into a structure consisting of an unknown residual term and a parameter term with control inputs using a local compact form dynamic linearization(local-CFDL).To take advantage of the resulting structure,use a discrete-time extended state observer(DESO)to estimate the unknown residual factor.Then,according to the study,the inclusion of a time delay has no effect on the linearization structure,and an improved control approach is provided,in which DESO is used to adjust for uncertainties.Furthermore,a DESO-based event-triggered model-free adaptive control(ET-DESO-MFAC)is established by designing event-triggered conditions to assure Lyapunov stability.Only when the system’s indicator fulfills the provided event-triggered condition will the control input signal be updated;otherwise,the control input will stay the same as it is at the last trigger moment.A coordinate compensation approach is developed to reduce the steady-state inaccuracy of trajectory tracking.Finally,simulation experiments are used to assess the effectiveness of the proposed technique for trajectory tracking.

Drug-coated balloons for treating de novo lesions in large coronary vessels:A case report

BACKGROUND Percutaneous transluminal coronary angioplasty,while an effective intervention,can frequently lead to acute occlusion with severe consequences.Although clinical trials have demonstrated the efficacy of drug-coated balloons(DCB)in treating acute coronary artery occlusion and in preventing restenosis,there has been limited exploration on the use of DCB in treating de novo lesions in large vessels.Currently,DCB are only recommended for patients with small vessel lesions and in-stent restenosis lesions,those at high risk of bleeding,and other special groups of patients.CASE SUMMARY This report presents a case of successful drug-coated balloon treatment of de novo lesions in large coronary vessels.Postoperatively,the patient demonstrated favorable recovery,with subsequent examination results revealing no significant differences from the previous examination.CONCLUSION The successful treatment of the patient in our case highlights the potential of DCB in the treatment of de novo lesions in large coronary vessels.

An Efficient Long Short-Term Memory and Gated Recurrent Unit Based Smart Vessel Trajectory Prediction Using Automatic Identification System Data

Maritime transportation,a cornerstone of global trade,faces increasing safety challenges due to growing sea traffic volumes.This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System(AIS)data and advanced deep learning models,including Long Short-Term Memory(LSTM),Gated Recurrent Unit(GRU),Bidirectional LSTM(DBLSTM),Simple Recurrent Neural Network(SimpleRNN),and Kalman Filtering.The research implemented rigorous AIS data preprocessing,encompassing record deduplication,noise elimination,stationary simplification,and removal of insignificant trajectories.Models were trained using key navigational parameters:latitude,longitude,speed,and heading.Spatiotemporal aware processing through trajectory segmentation and topological data analysis(TDA)was employed to capture dynamic patterns.Validation using a three-month AIS dataset demonstrated significant improvements in prediction accuracy.The GRU model exhibited superior performance,achieving training losses of 0.0020(Mean Squared Error,MSE)and 0.0334(Mean Absolute Error,MAE),with validation losses of 0.0708(MSE)and 0.1720(MAE).The LSTM model showed comparable efficacy,with training losses of 0.0011(MSE)and 0.0258(MAE),and validation losses of 0.2290(MSE)and 0.2652(MAE).Both models demonstrated reductions in training and validation losses,measured by MAE,MSE,Average Displacement Error(ADE),and Final Displacement Error(FDE).This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions,contributing significantly to the development of robust,intelligent navigation systems for the maritime industry.

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

Vulnerability and Conservation of Nearshore Cetaceans to Increasing Vessel Traffic:The Indo-Pacific Humpback Dolphin in the South China Sea

A comprehensive risk assessment to evaluate the vulnerability of the nearshore cetaceans to increasing marine traffic is lacking.In this study,the risk to Indo-Pacific humpback dolphins(Sousa chinensis)in the main habitats in China was assessed based on a semiquantitative spatial vulnerability analysis.85%of the(sub)population which overlapped with the lanes of ferries and/or cargo vessels,with exposure scores of 1.23±0.31(calculated based on the proportion of sea routes that overlap the dolphin’s range).A combination of high exposure to the sea routes and sensitivity to marine traffic would render the(sub)populations to be highly vulnerable(EPRE:5.21 and XM:4.47).A low frequency of vessels and an awareness of the ecology assures a low vulnerability(SH:2.43,EZ:2.73).Uncertainty scores were commonly lower for the higher vulnerable populations,and higher for the lower vulnerable populations,suggesting additional field data and more monitoring are necessary.Six years of field data have been used to analyze the influences of various types of marine traffic on humpback dolphin behavior.Fishing and non-fishing vessels were significantly different(χ^(2)=65.19,p<0.01).The humpback dolphins were attracted by fishing vessels(83.1%)but avoided non-fishing vessels(95.2%).We recommend a management with seasonal and geographical constraints,to balance economic development and environmental conservation.

Meningeal lymphatic vessel crosstalk with central nervous system immune cells in aging and neurodegenerative diseases

Meningeal lymphatic vessels form a relationship between the nervous system and periphery, which is relevant in both health and disease. Meningeal lymphatic vessels not only play a key role in the drainage of brain metabolites but also contribute to antigen delivery and immune cell activation. The advent of novel genomic technologies has enabled rapid progress in the characterization of myeloid and lymphoid cells and their interactions with meningeal lymphatic vessels within the central nervous system. In this review, we provide an overview of the multifaceted roles of meningeal lymphatic vessels within the context of the central nervous system immune network, highlighting recent discoveries on the immunological niche provided by meningeal lymphatic vessels. Furthermore, we delve into the mechanisms of crosstalk between meningeal lymphatic vessels and immune cells in the central nervous system under both homeostatic conditions and neurodegenerative diseases, discussing how these interactions shape the pathological outcomes. Regulation of meningeal lymphatic vessel function and structure can influence lymphatic drainage, cerebrospinal fluid-borne immune modulators, and immune cell populations in aging and neurodegenerative disorders, thereby playing a key role in shaping meningeal and brain parenchyma immunity.

Protocol to study the effects of AMPK-mTOR/PINK-Parkin dual signaling pathways on the formation of coronary heart disease showing blood stasis symptom pattern based on traditional Chinese medicine theory of“heart governing blood and vessels”

In this study,we aim to combine gene transfection techniques with the modeling methods previously employed by the research group to deeply investigate the corresponding theories of traditional Chinese medicine regarding“myocardial energy metabolism”and“aortic thrombosis”.Our goal is to elucidate the biological mechanism underlying the occurrence and development of coronary heart disease with blood stasis syndrome from the perspectives of“heart and vessels”and“Qi(in traditional Chinese medicine,it refers to the most fundamental and subtle substances that constitute the human body and maintain life activities.At the same time,it also has the meaning of physiological function.In terms of traditional Chinese medicine,Qi and different words are used together to express different meanings)and blood”.The research content is divided into four modules as follows:1.establishment of an animal model of coronary heart disease with blood stasis syndrome through fibrinogen overexpression.2.Investigation of the mitochondrial quality control system in coronary heart disease with blood stasis syndrome under fibrinogen overexpression.3.Study of platelet autophagy in coronary heart disease with blood stasis syndrome under fibrinogen overexpression.4.Examination of the relationship between the AMPK-mTOR pathway and metabolism in platelet autophagy of coronary heart disease with blood stasis syndrome under fibrinogen overexpression.Ninety-six Sprague Dawley rats will be randomly assigned to the following groups:control group,model group,fibrinogen group and adeno-associated virus group.All rats will undergo a 14-week model construction process,and modern molecular biology methods will be employed to evaluate the model and examine relevant research indicators.The obtained data will be analyzed according to a predefined statistical analysis plan.