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.

Bio-Inspired Screwed Conduits from the Microfluidic Rope-Coiling Effect for Microvessels and Bronchioles

Tubular microfibers have recently attracted extensive interest for applications in tissue engineering.However,the fabrication of tubular fibers with intricate hierarchical structures remains a major challenge.Here,we present a novel one-step microfluidic spinning method to generate bio-inspired screwed conduits(BSCs).Based on the microfluidic rope-coiling effect,a viscous hydrogel precursor is first curved into a helix stream in the channel,and then consecutively packed as a hollow structured stream and gelated into a screwed conduit(SC)via ionic and covalent crosslinking.By taking advantage of the excellent fluid-controlling ability of microfluidics,various tubes with diverse structures are fabricated via simple control over fluid velocities and multiple microfluidic device designs.The perfusability and permeability results,as well as the encapsulation and culture of human umbilical vein endothelial cells(HUVECs),human pulmonary alveolar epithelial cells(HPAs),and myogenic cells(C2C12),demonstrate that these SCs have good perfusability and permeability and the ability to induce the formation of functional biostructures.These features support the uniqueness and potential applications of these BSCs as biomimetic blood vessels and bronchiole tissues in combination with tissue microstructures,with likely application possibilities in biomedical engineering.

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.

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.

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.

A Deformable Network with Attention Mechanism for Retinal Vessel Segmentation

The intensive application of deep learning in medical image processing has facilitated the advancement of automatic retinal vessel segmentation research.To overcome the limitation that traditional U-shaped vessel segmentation networks fail to extract features in fundus image sufficiently,we propose a novel network(DSeU-net)based on deformable convolution and squeeze excitation residual module.The deformable convolution is utilized to dynamically adjust the receptive field for the feature extraction of retinal vessel.And the squeeze excitation residual module is used to scale the weights of the low-level features so that the network learns the complex relationships of the different feature layers efficiently.We validate the DSeU-net on three public retinal vessel segmentation datasets including DRIVE,CHASEDB1,and STARE,and the experimental results demonstrate the satisfactory segmentation performance of the network.

Repeatability,interocular correlation and agreement of optic nerve head vessel density in healthy eyes:a sweptsource optical coherence tomographic angiography study

AIM:To assess the repeatability,interocular correlation,and agreement of quantitative swept-source optical coherence tomography angiography(OCTA)optic nerve head(ONH)parameters in healthy subjects.METHODS:Thir ty-three healthy subjects were enrolled.The ONH of both eyes were imaged four times by a swept-source-OCTA using a 3 mm×3 mm scanning protocol.Images of the radial peripapillary capillary were analyzed by a customized Matlab program,and the vessel density,fractal dimension,and vessel diameter index were measured.The repeatability of the four scans was determined by the intraclass correlation coefficient(ICC).The most well-centered optic disc from the four repeated scans was then selected for the interocular correlation and agreement analysis using the Pearson correlation coefficient,ICC and Bland-Altman plots.RESULTS:All swept-source-OCTA ONH parameters exhibited certain repeatability,with ICC>0.760 and coefficient of variation(CoV)≤7.301%.The obvious interocular correlation was observed for papillary vessel density(ICC=0.857),vessel diameter index(ICC=0.857)and fractal dimension(ICC=0.906),while circumpapillary vessel density exhibited moderate interocular correlation(ICC=0.687).Bland-Altman plots revealed an agreement range of-5.26%to 6.21%for circumpapillary vessel density.CONCLUSION:OCTA ONH parameters demonstrate good repeatability in healthy subjects.The interocular correlations of papillary vessel density,fractal dimension and vessel diameter index are high,but the correlation for circumpapillary vessel density is moderate.

Clinical Value of the Quantitative Flow Ratio to Predict Long-term Target Vessel Failure in Patients with In-stent Restenosis after Drug-coated Balloon Angioplasty

Objective The study sought to investigate the clinical predictive value of quantitative flow ratio(QFR)for the long-term target vessel failure(TVF)outcome in patients with in-stent restenosis(ISR)by using drug-coated balloon(DCB)treatment after a long-term follow-up.Methods This was a retrospective study.A total of 186 patients who underwent DCB angioplasty for ISR in two hospitals from March 2014 to September 2019 were enrolled.The QFR of the entire target vessel was measured offline.The primary endpoint was TVF,including target vessel-cardiac death(TV-CD),target vessel-myocardial infarction(TV-MI),and clinically driven-target vessel revascularization(CD-TVR).Results The follow-up time was 3.09±1.53 years,and 50 patients had TVF.The QFR immediately after percutaneous coronary intervention(PCI)was significantly lower in the TVF group than in the no-TVF group.Multivariable Cox regression analysis indicated that the QFR immediately after PCI was an excellent predictor for TVF after the long-term follow-up[hazard ratio(HR):5.15×10−5(6.13×10−8−0.043);P<0.01].Receiver-operating characteristic(ROC)curve analysis demonstrated that the optimal cut-off value of the QFR immediately after PCI for predicting the long-term TVF was 0.925(area under the curve:0.886,95%confidence interval:0.834–0.938;sensitivity:83.40%,specificity:88.00;P<0.01).In addition,QFR≤0.925 post-PCI was strongly correlated with the TVF,including TV-MI and CD-TVR(P<0.01).Conclusion The QFR immediately after PCI showed a high predictive value of TVF after a long-term follow-up in ISR patients who underwent DCB angioplasty.A lower QFR immediately after PCI was associated with a worse TVF outcome.

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.

Investigating the relationship between intracranial atherosclerotic plaque remodelling and diabetes using high-resolution vessel wall imaging

BACKGROUND Intracranial atherosclerosis,a leading cause of stroke,involves arterial plaque formation.This study explores the link between plaque remodelling patterns and diabetes using high-resolution vessel wall imaging(HR-VWI).AIM To investigate the factors of intracranial atherosclerotic remodelling patterns and the relationship between intracranial atherosclerotic remodelling and diabetes mellitus using HR-VWI.METHODS Ninety-four patients diagnosed with middle cerebral artery or basilar artery INTRODUCTION Intracranial atherosclerotic disease is one of the main causes of ischaemic stroke in the world,accounting for approx-imately 10%of transient ischaemic attacks and 30%-50%of ischaemic strokes[1].It is the most common factor among Asian people[2].The adaptive changes in the structure and function of blood vessels that can adapt to changes in the internal and external environment are called vascular remodelling,which is a common and important pathological mechanism in atherosclerotic diseases,and the remodelling mode of atherosclerotic plaques is closely related to the occurrence of stroke.Positive remodelling(PR)is an outwards compensatory remodelling where the arterial wall grows outwards in an attempt to maintain a constant lumen diameter.For a long time,it was believed that the degree of stenosis can accurately reflect the risk of ischaemic stroke[3-5].Previous studies have revealed that lesions without significant luminal stenosis can also lead to acute events[6,7],as summarized in a recent meta-analysis study in which approximately 50%of acute/subacute ischaemic events were due to this type of lesion[6].Research[8,9]has pointed out that the PR of plaques is more dangerous and more likely to cause acute ischaemic stroke.Previous studies[10-13]have found that there are specific vascular remodelling phenomena in the coronary and carotid arteries of diabetic patients.However,due to the deep location and small lumen of intracranial arteries and limitations of imaging techniques,the relationship between intracranial arterial remodelling and diabetes is still unclear.In recent years,with the development of magnetic resonance technology and the emergence of high-resolution(HR)vascular wall imaging,a clear and multidimensional display of the intracranial vascular wall has been achieved.Therefore,in this study,HR wall imaging(HR-VWI)was used to display the remodelling characteristics of bilateral middle cerebral arteries and basilar arteries and to explore the factors of intracranial vascular remodelling and its relationship with diabetes.

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.

Quantifying peripapillary vessel density and retinal nerve fibre layer in type 1 diabetic children without clinically detectable retinopathy using OCTA

AIM:To quantify changes in radial peripapillary capillary vessel density(ppVD)and the peripapillary retinal nerve fiber layer(pRNFL)in children with type 1 diabetes without clinical diabetic retinopathy by optical coherence tomography angiography(OCTA),providing a basis for early retinopathy in children with type 1 diabetes.METHODS:This was a retrospective study.A total of 30 patients(3–14y)with type 1 diabetes without clinical diabetic retinopathy(NDR group)were included.A total of 30 age-matched healthy subjects were included as the normal control group(CON group).The HbA1c level in the last 3mo was measured once in the NDR group.The pRNFL thickness and ppVD were automatically measured,and the mean pRNFL and ppVD were calculated in the nasal,inferior,temporal,and superior quadrants.The changes in ppVD and pRNFL in the two groups were analyzed.RESULTS:Compared with CON group,the nasal and superior ppVDs decreased in the NDR group(all P<0.01).The thickness of the nasal pRNFL decreased significantly(P<0.01),while the inferior,temporal and superior pRNFLs slightly decreased but not significant in the NDR group(all P>0.05).Person and Spearman correlation analysis of ppVD and pRNFL thickness in each quadrant of the NDR group showed a positive correlation between nasal and superior(all P<0.01),while inferior and temporal had no significant correlation(all P>0.05).There was no significant correlation between the HbA1c level and ppVD and pRNFL in any quadrant(all P>0.05).There was no significant correlation between the course of diabetes mellitus and ppVD and pRNFL in any quadrant(all P>0.05).CONCLUSION:ppVD and pRNFL decrease in eyes of children with type 1 diabetes before clinically detectable retinopathy and OCTA is helpful for early monitoring.

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.

A prediction model for large vessel occlusion in suspected stroke patients based on available prehospital information

Objective:Early and accurate identification of large vessel occlusion(LVO)acute ischemic stroke(AIS)patients is critically important for stroke management.Practicable scales with simple items can facilitate prehospital paramedics distinguishing LVO-AIS patients with high efficiency and help to avoid unnecessary and costly delays.The current study aims to develop a screening tool to predict AIS-LVO patients based on prehospital available data.Method:A total of 251 suspected stroke patients who were transported to the emergency department of our hospital via emergency medical services were consecutively enrolled from August,2020 to January,2022.Data including demographic information,medical history,clinical manifestations,and vital signs were collected.A multivariate logistic regression model was developed based on statistically significant variables selected from univariate analysis.Result:Forty-two patients(16.7%)were diagnosed as LVO-AIS based on imaging validation at admission.A comprehensive model was developed with past medical history factors such as atrial fibrillation and coronary heart disease,vital signs such as systolic blood pressure,and prominent symptoms and signs such as gaze palsy,facial paralysis,and dysarthria.The model showed better diagnostic performance in terms of area under the receiver operating characteristic curves(0.884,95%CI,0.830-0.939),which was higher than other common prehospital prediction scales such as the Face,Arm,Speech,Time test(FAST),the Field Assessment Stroke Triage for Emergency Destination(FAST-ED)scale,and the Gaze-Face-Arm-Speech-Time test(G-FAST).Calibration curve analysis,decision curve analysis,and clinical impact curve analysis further validated the reliability,net benefit,and potential clinical impact of the prediction model,respectively.Conclusion:We conducted a prediction model based on prehospital accessible factors including past history of atrial fibrillation and coronary heart disease,systolic blood pressure,and signs such as gaze palsy,facial palsy,and dysarthria.The prediction model showed good diagnostic power and accuracy for identification of the high-risk patients with LVO and may become an effective tool for the LVO recognition in prehospital settings.Future studies are warranted to refine and validate the model further in order to enhance the accuracy and objectivity of clinical judgments.

Accuracy and Utility of Vessel Analysis Using Non-Contrast CT for Planning Endovascular Aortic Repair

Objectives: This study aimed to determine whether errors in vascular measurements would affect device selection in endovascular aortic repair (EVAR) by comparing measurements obtained using non-contrast computed tomography (NCT) with those obtained using contrast-enhanced CT (CECT). Materials and Methods: This single-center, retrospective study included 25 patients who underwent EVAR for abdominal aortic aneurysm at our institution. A 1-mm horizontal cross-sectional slice of NCT and CECT from each patient was retrospectively reviewed. The area from the abdominal aorta to the common iliac artery was divided into four zones. A centerline was created using the NCT by manually plotting the center points. Subsequently, the centerlines were automatically extracted and manually corrected during the arterial phase of CECT. The diameter and length of each zone were measured for each modality. The mean diameters and lengths of the target vessels were compared between NCT and CECT. Results: The measurements obtained using both methods were reproducible and demonstrated good agreement. The mean differences in vessel length and diameter measurements for each segment between NCT and CECT were not statistically significant, indicating good consistency. Conclusion: NCT may be useful for preoperative EVAR evaluation in patients with renal dysfunction or allergies to contrast agents.

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.